dlnd_face_generation.html

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

<title>dlnd_face_generation</title>

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


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

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

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

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

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

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

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

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

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

    </style>


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

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

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

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

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

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

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

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


<div class="output_area">

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


<div class="output_subarea output_stream output_stdout output_text">
<pre>Archive:  processed_celeba_small.zip
replace processed_celeba_small/.DS_Store? [y]es, [n]o, [A]ll, [N]one, [r]ename: </pre>
</div>
</div>

</div>
</div>

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

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

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[2]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">data_dir</span> <span class="o">=</span> <span class="s1">&#39;processed_celeba_small/&#39;</span>

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

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

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

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[3]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># necessary imports</span>
<span class="kn">import</span> <span class="nn">os</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">from</span> <span class="nn">torchvision</span> <span class="k">import</span> <span class="n">datasets</span>
<span class="kn">from</span> <span class="nn">torch.utils.data</span> <span class="k">import</span> <span class="n">DataLoader</span>
<span class="kn">from</span> <span class="nn">torchvision</span> <span class="k">import</span> <span class="n">transforms</span>
</pre></div>

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

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[4]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">get_dataloader</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">image_size</span><span class="p">,</span> <span class="n">data_dir</span><span class="o">=</span><span class="s1">&#39;processed_celeba_small/&#39;</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Batch the neural network data using DataLoader</span>
<span class="sd">    :param batch_size: The size of each batch; the number of images in a batch</span>
<span class="sd">    :param img_size: The square size of the image data (x, y)</span>
<span class="sd">    :param data_dir: Directory where image data is located</span>
<span class="sd">    :return: DataLoader with batched data</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1"># TODO: Implement function and return a dataloader</span>
    <span class="n">transform</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span><span class="n">transforms</span><span class="o">.</span><span class="n">Resize</span><span class="p">(</span><span class="n">image_size</span><span class="p">),</span>
                                    <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">()])</span>
    
    <span class="n">data_path</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="s1">&#39;./&#39;</span> <span class="o">+</span> <span class="n">data_dir</span><span class="p">)</span>
    <span class="n">dataset</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">data_path</span><span class="p">,</span> <span class="n">transform</span><span class="p">)</span>
    <span class="n">data_loader</span> <span class="o">=</span> <span class="n">DataLoader</span><span class="p">(</span><span class="n">dataset</span><span class="o">=</span><span class="n">dataset</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">data_loader</span>
</pre></div>

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

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[5]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Define function hyperparameters</span>
<span class="n">batch_size</span> <span class="o">=</span> <span class="mi">64</span>
<span class="n">img_size</span> <span class="o">=</span> <span class="mi">32</span>

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

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

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[6]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># helper display function</span>
<span class="k">def</span> <span class="nf">imshow</span><span class="p">(</span><span class="n">img</span><span class="p">):</span>
    <span class="n">npimg</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">npimg</span><span class="p">,</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">)))</span>

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

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

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

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


<div class="output_area">

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


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

</div>

</div>
</div>

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[7]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Complete the scale function</span>
<span class="k">def</span> <span class="nf">scale</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">feature_range</span><span class="o">=</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">)):</span>
    <span class="sd">&#39;&#39;&#39; Scale takes in an image x and returns that image, scaled</span>
<span class="sd">       with a feature_range of pixel values from -1 to 1. </span>
<span class="sd">       This function assumes that the input x is already scaled from 0-1.&#39;&#39;&#39;</span>
    <span class="c1"># assume x is scaled to (0, 1)</span>
    <span class="c1"># scale to feature_range and return scaled x</span>
    <span class="nb">min</span><span class="p">,</span> <span class="nb">max</span> <span class="o">=</span> <span class="n">feature_range</span>
    <span class="n">x</span> <span class="o">=</span> <span class="n">x</span> <span class="o">*</span> <span class="p">(</span><span class="nb">max</span> <span class="o">-</span> <span class="nb">min</span><span class="p">)</span> <span class="o">+</span> <span class="nb">min</span>
    <span class="k">return</span> <span class="n">x</span>
</pre></div>

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

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[8]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="c1"># check scaled range</span>
<span class="c1"># should be close to -1 to 1</span>
<span class="n">img</span> <span class="o">=</span> <span class="n">images</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="n">scaled_img</span> <span class="o">=</span> <span class="n">scale</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>

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

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

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


<div class="output_area">

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


<div class="output_subarea output_stream output_stdout output_text">
<pre>Min:  tensor(-0.9529)
Max:  tensor(0.8745)
</pre>
</div>
</div>

</div>
</div>

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[9]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">torch.nn</span> <span class="k">as</span> <span class="nn">nn</span>
<span class="kn">import</span> <span class="nn">torch.nn.functional</span> <span class="k">as</span> <span class="nn">F</span>

<span class="c1"># helper conv function</span>
<span class="k">def</span> <span class="nf">conv</span><span class="p">(</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;Creates a convolutional layer, with optional batch normalization.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">conv_layer</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Conv2d</span><span class="p">(</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="p">,</span> 
                           <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">padding</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
    
    <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">conv_layer</span><span class="p">)</span>

    <span class="k">if</span> <span class="n">batch_norm</span><span class="p">:</span>
        <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">BatchNorm2d</span><span class="p">(</span><span class="n">out_channels</span><span class="p">))</span>
    <span class="k">return</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="o">*</span><span class="n">layers</span><span class="p">)</span>
</pre></div>

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

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[10]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">class</span> <span class="nc">Discriminator</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Initialize the Discriminator Module</span>
<span class="sd">        :param conv_dim: The depth of the first convolutional layer</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">Discriminator</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
        <span class="c1"># complete init function</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span> <span class="o">=</span> <span class="n">conv_dim</span>
        
        <span class="bp">self</span><span class="o">.</span><span class="n">conv1</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="n">batch_norm</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv2</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv3</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        
        <span class="bp">self</span><span class="o">.</span><span class="n">fc</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>

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


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

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

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


<div class="output_area">

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


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

</div>
</div>

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[11]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">torch.nn</span> <span class="k">as</span> <span class="nn">nn</span>
<span class="kn">import</span> <span class="nn">torch.nn.functional</span> <span class="k">as</span> <span class="nn">F</span>
<span class="c1"># helper deconv function</span>
<span class="k">def</span> <span class="nf">deconv</span><span class="p">(</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;Creates a transpose convolutional layer, with optional batch normalization.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="c1"># append transpose conv layer</span>
    <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">ConvTranspose2d</span><span class="p">(</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">padding</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">False</span><span class="p">))</span>
    <span class="c1"># optional batch norm layer</span>
    <span class="k">if</span> <span class="n">batch_norm</span><span class="p">:</span>
        <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">BatchNorm2d</span><span class="p">(</span><span class="n">out_channels</span><span class="p">))</span>
    <span class="k">return</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="o">*</span><span class="n">layers</span><span class="p">)</span>
</pre></div>

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

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[12]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">class</span> <span class="nc">Generator</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
    
    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Initialize the Generator Module</span>
<span class="sd">        :param z_size: The length of the input latent vector, z</span>
<span class="sd">        :param conv_dim: The depth of the inputs to the *last* transpose convolutional layer</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">Generator</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>

        <span class="c1"># complete init function</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span> <span class="o">=</span> <span class="n">conv_dim</span>
        
        <span class="bp">self</span><span class="o">.</span><span class="n">fc</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="p">)</span>
        
        <span class="bp">self</span><span class="o">.</span><span class="n">t_conv1</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">t_conv2</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">t_conv3</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>

    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Forward propagation of the neural network</span>
<span class="sd">        :param x: The input to the neural network     </span>
<span class="sd">        :return: A 32x32x3 Tensor image as output</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="c1"># define feedforward behavior</span>
        <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>

        <span class="n">x</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">t_conv1</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">t_conv2</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">tanh</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">t_conv3</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
    
        <span class="k">return</span> <span class="n">x</span>

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

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

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


<div class="output_area">

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


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

</div>
</div>

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[13]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">weights_init_normal</span><span class="p">(</span><span class="n">m</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Applies initial weights to certain layers in a model .</span>
<span class="sd">    The weights are taken from a normal distribution </span>
<span class="sd">    with mean = 0, std dev = 0.02.</span>
<span class="sd">    :param m: A module or layer in a network    </span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1"># classname will be something like:</span>
    <span class="c1"># `Conv`, `BatchNorm2d`, `Linear`, etc.</span>
    <span class="n">classname</span> <span class="o">=</span> <span class="n">m</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span>
    <span class="c1"># TODO: Apply initial weights to convolutional and linear layers</span>
    <span class="n">classname</span> <span class="o">=</span> <span class="n">m</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span>
    <span class="k">if</span> <span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;Conv&#39;</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="p">:</span>
        <span class="n">m</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">normal_</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">)</span>
    <span class="k">elif</span> <span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;BatchNorm&#39;</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="p">:</span>
        <span class="n">m</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">normal_</span><span class="p">(</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">)</span>
        <span class="n">m</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">fill_</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
</pre></div>

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

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[14]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">build_network</span><span class="p">(</span><span class="n">d_conv_dim</span><span class="p">,</span> <span class="n">g_conv_dim</span><span class="p">,</span> <span class="n">z_size</span><span class="p">):</span>
    <span class="c1"># define discriminator and generator</span>
    <span class="n">D</span> <span class="o">=</span> <span class="n">Discriminator</span><span class="p">(</span><span class="n">d_conv_dim</span><span class="p">)</span>
    <span class="n">G</span> <span class="o">=</span> <span class="n">Generator</span><span class="p">(</span><span class="n">z_size</span><span class="o">=</span><span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">=</span><span class="n">g_conv_dim</span><span class="p">)</span>

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

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

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

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h4 id="Exercise:-Define-model-hyperparameters">Exercise: Define model hyperparameters<a class="anchor-link" href="#Exercise:-Define-model-hyperparameters">&#182;</a></h4>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[15]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Define model hyperparams</span>
<span class="n">d_conv_dim</span> <span class="o">=</span> <span class="mi">32</span>
<span class="n">g_conv_dim</span> <span class="o">=</span> <span class="mi">32</span>
<span class="n">z_size</span> <span class="o">=</span> <span class="mi">100</span>

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

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

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


<div class="output_area">

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


<div class="output_subarea output_stream output_stdout output_text">
<pre>Discriminator(
  (conv1): Sequential(
    (0): Conv2d(3, 32, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
  )
  (conv2): Sequential(
    (0): Conv2d(32, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (conv3): Sequential(
    (0): Conv2d(64, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (fc): Linear(in_features=2048, out_features=1, bias=True)
)

Generator(
  (fc): Linear(in_features=100, out_features=2048, bias=True)
  (t_conv1): Sequential(
    (0): ConvTranspose2d(128, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (t_conv2): Sequential(
    (0): ConvTranspose2d(64, 32, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (t_conv3): Sequential(
    (0): ConvTranspose2d(32, 3, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
  )
)
</pre>
</div>
</div>

</div>
</div>

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[16]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">torch</span>

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

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

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


<div class="output_area">

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


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

</div>
</div>

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[17]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">real_loss</span><span class="p">(</span><span class="n">D_out</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39;Calculates how close discriminator outputs are to being real.</span>
<span class="sd">       param, D_out: discriminator logits</span>
<span class="sd">       return: real loss&#39;&#39;&#39;</span>
    <span class="n">batch_size</span> <span class="o">=</span> <span class="n">D_out</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">labels</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">batch_size</span><span class="p">)</span>
    
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
        
    <span class="n">criterion</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">BCEWithLogitsLoss</span><span class="p">()</span>
    <span class="n">loss</span> <span class="o">=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">D_out</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(),</span> <span class="n">labels</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">loss</span>

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

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

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[18]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">torch.optim</span> <span class="k">as</span> <span class="nn">optim</span>

<span class="c1"># hyperparams for Adam optimizers</span>
<span class="n">lr</span><span class="o">=</span><span class="mf">0.0002</span>
<span class="n">beta1</span><span class="o">=</span><span class="mf">0.5</span>
<span class="n">beta2</span><span class="o">=</span><span class="mf">0.999</span>

<span class="c1"># Create optimizers for the discriminator D and generator G</span>
<span class="n">d_optimizer</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">(</span><span class="n">D</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span><span class="p">,</span> <span class="p">[</span><span class="n">beta1</span><span class="p">,</span> <span class="n">beta2</span><span class="p">])</span>
<span class="n">g_optimizer</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span><span class="p">,</span> <span class="p">[</span><span class="n">beta1</span><span class="p">,</span> <span class="n">beta2</span><span class="p">])</span>
</pre></div>

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

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

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[19]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="n">D</span><span class="p">,</span> <span class="n">G</span><span class="p">,</span> <span class="n">n_epochs</span><span class="p">,</span> <span class="n">print_every</span><span class="o">=</span><span class="mi">50</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39;Trains adversarial networks for some number of epochs</span>
<span class="sd">       param, D: the discriminator network</span>
<span class="sd">       param, G: the generator network</span>
<span class="sd">       param, n_epochs: number of epochs to train for</span>
<span class="sd">       param, print_every: when to print and record the models&#39; losses</span>
<span class="sd">       return: D and G losses&#39;&#39;&#39;</span>
    
    <span class="c1"># move models to GPU</span>
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">D</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
        <span class="n">G</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>

    <span class="c1"># keep track of loss and generated, &quot;fake&quot; samples</span>
    <span class="n">samples</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">losses</span> <span class="o">=</span> <span class="p">[]</span>

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

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

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

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

            <span class="c1"># ===============================================</span>
            <span class="c1">#         YOUR CODE HERE: TRAIN THE NETWORKS</span>
            <span class="c1"># ===============================================</span>
            
            <span class="c1"># 1. Train the discriminator on real and fake images</span>
            <span class="n">d_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
            
            <span class="c1"># 1. Train with real images</span>
            
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">real_images</span> <span class="o">=</span> <span class="n">real_images</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
            
            <span class="n">D_real</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">real_images</span><span class="p">)</span>
            <span class="n">d_real_loss</span> <span class="o">=</span> <span class="n">real_loss</span><span class="p">(</span><span class="n">D_real</span><span class="p">)</span>
            
            <span class="c1"># 2. Train with fake images</span>
            
            <span class="c1"># Generate fake images</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
            <span class="c1"># move x to GPU, if available</span>
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">z</span> <span class="o">=</span> <span class="n">z</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
            <span class="n">fake_images</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">z</span><span class="p">)</span>
            
            <span class="c1"># Compute the discriminator losses on fake images            </span>
            <span class="n">D_fake</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">fake_images</span><span class="p">)</span>
            <span class="n">d_fake_loss</span> <span class="o">=</span> <span class="n">fake_loss</span><span class="p">(</span><span class="n">D_fake</span><span class="p">)</span>

            <span class="c1"># add up loss and perform backprop</span>
            <span class="n">d_loss</span> <span class="o">=</span> <span class="n">d_real_loss</span> <span class="o">+</span> <span class="n">d_fake_loss</span>
            <span class="n">d_loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
            <span class="n">d_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
        
            <span class="c1"># 2. Train the generator with an adversarial loss</span>
            
            <span class="n">g_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
            
            <span class="c1"># 1. Train with fake images and flipped labels</span>
            
            <span class="c1"># Generate fake images</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">z</span> <span class="o">=</span> <span class="n">z</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
            <span class="n">fake_images</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">z</span><span class="p">)</span>
            
            <span class="c1"># Compute the discriminator losses on fake images </span>
            <span class="n">D_fake</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">fake_images</span><span class="p">)</span>
            <span class="n">g_loss</span> <span class="o">=</span> <span class="n">real_loss</span><span class="p">(</span><span class="n">D_fake</span><span class="p">)</span>
            
            <span class="n">g_loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
            <span class="n">g_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
          
            <span class="c1"># ===============================================</span>
            <span class="c1">#              END OF YOUR CODE</span>
            <span class="c1"># ===============================================</span>

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


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

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

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

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[20]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># set number of epochs </span>
<span class="n">n_epochs</span> <span class="o">=</span> <span class="mi">50</span>


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

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

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


<div class="output_area">

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


<div class="output_subarea output_stream output_stdout output_text">
<pre>Epoch [    1/   50] | d_loss: 1.4493 | g_loss: 0.8554
Epoch [    1/   50] | d_loss: 0.2038 | g_loss: 3.1657
Epoch [    1/   50] | d_loss: 0.1878 | g_loss: 3.8401
Epoch [    1/   50] | d_loss: 0.3278 | g_loss: 4.3263
Epoch [    1/   50] | d_loss: 0.4562 | g_loss: 4.5669
Epoch [    1/   50] | d_loss: 0.5355 | g_loss: 2.0585
Epoch [    1/   50] | d_loss: 0.3382 | g_loss: 3.0642
Epoch [    1/   50] | d_loss: 0.3995 | g_loss: 2.3096
Epoch [    1/   50] | d_loss: 0.5071 | g_loss: 1.8999
Epoch [    1/   50] | d_loss: 0.4230 | g_loss: 2.1354
Epoch [    1/   50] | d_loss: 0.4876 | g_loss: 2.6678
Epoch [    1/   50] | d_loss: 0.7054 | g_loss: 1.3544
Epoch [    1/   50] | d_loss: 1.0130 | g_loss: 0.8131
Epoch [    1/   50] | d_loss: 0.6984 | g_loss: 1.9403
Epoch [    1/   50] | d_loss: 0.7826 | g_loss: 1.9240
Epoch [    1/   50] | d_loss: 0.7082 | g_loss: 1.5543
Epoch [    1/   50] | d_loss: 0.8455 | g_loss: 1.1676
Epoch [    1/   50] | d_loss: 0.8590 | g_loss: 1.1068
Epoch [    1/   50] | d_loss: 0.9952 | g_loss: 1.5851
Epoch [    1/   50] | d_loss: 0.8633 | g_loss: 1.1019
Epoch [    1/   50] | d_loss: 1.1431 | g_loss: 0.7410
Epoch [    1/   50] | d_loss: 0.8265 | g_loss: 1.2690
Epoch [    1/   50] | d_loss: 1.1193 | g_loss: 1.8990
Epoch [    1/   50] | d_loss: 0.8533 | g_loss: 1.0779
Epoch [    1/   50] | d_loss: 1.0417 | g_loss: 1.7973
Epoch [    1/   50] | d_loss: 0.8805 | g_loss: 1.7766
Epoch [    1/   50] | d_loss: 0.8564 | g_loss: 1.0889
Epoch [    1/   50] | d_loss: 1.0622 | g_loss: 0.7960
Epoch [    1/   50] | d_loss: 0.8377 | g_loss: 1.3551
Epoch [    2/   50] | d_loss: 1.1708 | g_loss: 1.7497
Epoch [    2/   50] | d_loss: 0.9235 | g_loss: 1.1214
Epoch [    2/   50] | d_loss: 1.3255 | g_loss: 0.7592
Epoch [    2/   50] | d_loss: 0.8843 | g_loss: 1.7240
Epoch [    2/   50] | d_loss: 0.9741 | g_loss: 1.1383
Epoch [    2/   50] | d_loss: 1.1104 | g_loss: 1.6806
Epoch [    2/   50] | d_loss: 0.9815 | g_loss: 1.5370
Epoch [    2/   50] | d_loss: 0.8910 | g_loss: 1.1181
Epoch [    2/   50] | d_loss: 1.0860 | g_loss: 1.8158
Epoch [    2/   50] | d_loss: 0.7082 | g_loss: 1.2442
Epoch [    2/   50] | d_loss: 1.2276 | g_loss: 1.8808
Epoch [    2/   50] | d_loss: 0.8997 | g_loss: 0.7227
Epoch [    2/   50] | d_loss: 0.9951 | g_loss: 1.2688
Epoch [    2/   50] | d_loss: 1.1565 | g_loss: 0.7728
Epoch [    2/   50] | d_loss: 0.8473 | g_loss: 1.8425
Epoch [    2/   50] | d_loss: 0.9728 | g_loss: 2.1953
Epoch [    2/   50] | d_loss: 0.7113 | g_loss: 1.4473
Epoch [    2/   50] | d_loss: 0.9885 | g_loss: 1.6267
Epoch [    2/   50] | d_loss: 0.7464 | g_loss: 1.2325
Epoch [    2/   50] | d_loss: 1.0070 | g_loss: 1.2138
Epoch [    2/   50] | d_loss: 0.8898 | g_loss: 1.8701
Epoch [    2/   50] | d_loss: 1.1594 | g_loss: 1.4068
Epoch [    2/   50] | d_loss: 0.8059 | g_loss: 1.1948
Epoch [    2/   50] | d_loss: 1.2355 | g_loss: 1.4392
Epoch [    2/   50] | d_loss: 0.9458 | g_loss: 1.6766
Epoch [    2/   50] | d_loss: 0.8598 | g_loss: 1.7755
Epoch [    2/   50] | d_loss: 0.9054 | g_loss: 1.7107
Epoch [    2/   50] | d_loss: 0.8151 | g_loss: 1.1728
Epoch [    2/   50] | d_loss: 1.0107 | g_loss: 1.0253
Epoch [    3/   50] | d_loss: 0.9574 | g_loss: 1.0521
Epoch [    3/   50] | d_loss: 0.9095 | g_loss: 0.9779
Epoch [    3/   50] | d_loss: 0.9428 | g_loss: 0.8931
Epoch [    3/   50] | d_loss: 1.3095 | g_loss: 1.0039
Epoch [    3/   50] | d_loss: 0.7457 | g_loss: 2.1630
Epoch [    3/   50] | d_loss: 0.7995 | g_loss: 2.2491
Epoch [    3/   50] | d_loss: 1.0450 | g_loss: 0.9366
Epoch [    3/   50] | d_loss: 0.7954 | g_loss: 1.5067
Epoch [    3/   50] | d_loss: 0.7921 | g_loss: 1.8161
Epoch [    3/   50] | d_loss: 0.7873 | g_loss: 1.9017
Epoch [    3/   50] | d_loss: 0.8040 | g_loss: 1.1556
Epoch [    3/   50] | d_loss: 0.8280 | g_loss: 1.3529
Epoch [    3/   50] | d_loss: 0.8470 | g_loss: 1.3769
Epoch [    3/   50] | d_loss: 0.7981 | g_loss: 2.2127
Epoch [    3/   50] | d_loss: 0.8077 | g_loss: 1.5625
Epoch [    3/   50] | d_loss: 0.8056 | g_loss: 1.0982
Epoch [    3/   50] | d_loss: 0.9175 | g_loss: 2.0386
Epoch [    3/   50] | d_loss: 0.9915 | g_loss: 1.0529
Epoch [    3/   50] | d_loss: 0.7468 | g_loss: 1.6726
Epoch [    3/   50] | d_loss: 0.8899 | g_loss: 1.5559
Epoch [    3/   50] | d_loss: 0.7525 | g_loss: 1.8423
Epoch [    3/   50] | d_loss: 1.3089 | g_loss: 0.7096
Epoch [    3/   50] | d_loss: 1.1672 | g_loss: 0.6995
Epoch [    3/   50] | d_loss: 0.9250 | g_loss: 1.2964
Epoch [    3/   50] | d_loss: 0.9190 | g_loss: 1.4230
Epoch [    3/   50] | d_loss: 0.8436 | g_loss: 1.5014
Epoch [    3/   50] | d_loss: 1.0539 | g_loss: 1.0139
Epoch [    3/   50] | d_loss: 0.9606 | g_loss: 1.2165
Epoch [    3/   50] | d_loss: 0.6573 | g_loss: 1.7567
Epoch [    4/   50] | d_loss: 0.9954 | g_loss: 1.4240
Epoch [    4/   50] | d_loss: 0.8969 | g_loss: 1.1164
Epoch [    4/   50] | d_loss: 0.8169 | g_loss: 1.3557
Epoch [    4/   50] | d_loss: 0.7772 | g_loss: 1.4340
Epoch [    4/   50] | d_loss: 0.7952 | g_loss: 2.5426
Epoch [    4/   50] | d_loss: 0.7851 | g_loss: 1.4326
Epoch [    4/   50] | d_loss: 0.6867 | g_loss: 1.7119
Epoch [    4/   50] | d_loss: 0.7155 | g_loss: 0.8967
Epoch [    4/   50] | d_loss: 0.7126 | g_loss: 1.2863
Epoch [    4/   50] | d_loss: 0.8553 | g_loss: 1.6371
Epoch [    4/   50] | d_loss: 0.6809 | g_loss: 1.8268
Epoch [    4/   50] | d_loss: 0.9171 | g_loss: 1.9222
Epoch [    4/   50] | d_loss: 0.7246 | g_loss: 1.1938
Epoch [    4/   50] | d_loss: 0.8674 | g_loss: 0.8043
Epoch [    4/   50] | d_loss: 0.9442 | g_loss: 1.1064
Epoch [    4/   50] | d_loss: 0.7546 | g_loss: 1.7406
Epoch [    4/   50] | d_loss: 1.1525 | g_loss: 2.5625
Epoch [    4/   50] | d_loss: 0.8744 | g_loss: 2.0826
Epoch [    4/   50] | d_loss: 0.9172 | g_loss: 1.6675
Epoch [    4/   50] | d_loss: 0.6307 | g_loss: 2.6566
Epoch [    4/   50] | d_loss: 0.7704 | g_loss: 1.1635
Epoch [    4/   50] | d_loss: 0.7514 | g_loss: 1.7660
Epoch [    4/   50] | d_loss: 0.7390 | g_loss: 1.5096
Epoch [    4/   50] | d_loss: 0.9284 | g_loss: 1.6564
Epoch [    4/   50] | d_loss: 0.6438 | g_loss: 1.4081
Epoch [    4/   50] | d_loss: 0.6447 | g_loss: 2.1682
Epoch [    4/   50] | d_loss: 0.7137 | g_loss: 1.3560
Epoch [    4/   50] | d_loss: 0.6392 | g_loss: 1.2605
Epoch [    4/   50] | d_loss: 1.2764 | g_loss: 0.6337
Epoch [    5/   50] | d_loss: 0.7280 | g_loss: 1.3268
Epoch [    5/   50] | d_loss: 0.7078 | g_loss: 1.5891
Epoch [    5/   50] | d_loss: 0.6255 | g_loss: 2.3841
Epoch [    5/   50] | d_loss: 0.6243 | g_loss: 1.1290
Epoch [    5/   50] | d_loss: 0.9254 | g_loss: 2.0023
Epoch [    5/   50] | d_loss: 0.8875 | g_loss: 2.0334
Epoch [    5/   50] | d_loss: 0.6303 | g_loss: 1.3013
Epoch [    5/   50] | d_loss: 0.8587 | g_loss: 2.8026
Epoch [    5/   50] | d_loss: 0.8100 | g_loss: 1.2976
Epoch [    5/   50] | d_loss: 0.7571 | g_loss: 1.7409
Epoch [    5/   50] | d_loss: 0.8078 | g_loss: 1.5424
Epoch [    5/   50] | d_loss: 2.0386 | g_loss: 3.3256
Epoch [    5/   50] | d_loss: 0.6808 | g_loss: 1.2147
Epoch [    5/   50] | d_loss: 0.7812 | g_loss: 2.4095
Epoch [    5/   50] | d_loss: 0.5196 | g_loss: 2.0947
Epoch [    5/   50] | d_loss: 0.6709 | g_loss: 1.5079
Epoch [    5/   50] | d_loss: 0.6828 | g_loss: 1.3245
Epoch [    5/   50] | d_loss: 0.5165 | g_loss: 1.9672
Epoch [    5/   50] | d_loss: 0.4696 | g_loss: 1.7964
Epoch [    5/   50] | d_loss: 0.9559 | g_loss: 2.0880
Epoch [    5/   50] | d_loss: 1.1415 | g_loss: 0.7512
Epoch [    5/   50] | d_loss: 0.7020 | g_loss: 1.6701
Epoch [    5/   50] | d_loss: 0.8863 | g_loss: 2.3849
Epoch [    5/   50] | d_loss: 0.8522 | g_loss: 0.9161
Epoch [    5/   50] | d_loss: 0.6810 | g_loss: 1.8581
Epoch [    5/   50] | d_loss: 0.7876 | g_loss: 1.3247
Epoch [    5/   50] | d_loss: 0.4855 | g_loss: 1.5134
Epoch [    5/   50] | d_loss: 0.7519 | g_loss: 2.3164
Epoch [    5/   50] | d_loss: 0.8639 | g_loss: 1.0013
Epoch [    6/   50] | d_loss: 0.6805 | g_loss: 1.5231
Epoch [    6/   50] | d_loss: 0.6421 | g_loss: 2.3572
Epoch [    6/   50] | d_loss: 0.7516 | g_loss: 1.4419
Epoch [    6/   50] | d_loss: 0.7426 | g_loss: 2.0758
Epoch [    6/   50] | d_loss: 0.9187 | g_loss: 0.9234
Epoch [    6/   50] | d_loss: 0.5694 | g_loss: 1.1585
Epoch [    6/   50] | d_loss: 0.8271 | g_loss: 0.6133
Epoch [    6/   50] | d_loss: 0.7222 | g_loss: 1.0380
Epoch [    6/   50] | d_loss: 0.6588 | g_loss: 1.7922
Epoch [    6/   50] | d_loss: 0.8493 | g_loss: 0.8889
Epoch [    6/   50] | d_loss: 0.6421 | g_loss: 1.7770
Epoch [    6/   50] | d_loss: 0.8424 | g_loss: 1.1958
Epoch [    6/   50] | d_loss: 0.7280 | g_loss: 1.4373
Epoch [    6/   50] | d_loss: 0.8133 | g_loss: 1.4613
Epoch [    6/   50] | d_loss: 1.3805 | g_loss: 1.0490
Epoch [    6/   50] | d_loss: 0.7099 | g_loss: 1.8955
Epoch [    6/   50] | d_loss: 0.5329 | g_loss: 1.4937
Epoch [    6/   50] | d_loss: 0.7573 | g_loss: 1.3735
Epoch [    6/   50] | d_loss: 0.6727 | g_loss: 1.5115
Epoch [    6/   50] | d_loss: 0.7689 | g_loss: 1.7084
Epoch [    6/   50] | d_loss: 1.0659 | g_loss: 1.3995
Epoch [    6/   50] | d_loss: 0.6476 | g_loss: 2.6661
Epoch [    6/   50] | d_loss: 0.6921 | g_loss: 1.4733
Epoch [    6/   50] | d_loss: 0.6337 | g_loss: 1.4775
Epoch [    6/   50] | d_loss: 0.7952 | g_loss: 1.8276
Epoch [    6/   50] | d_loss: 2.8216 | g_loss: 0.0552
Epoch [    6/   50] | d_loss: 0.6087 | g_loss: 2.2936
Epoch [    6/   50] | d_loss: 0.5497 | g_loss: 1.9558
Epoch [    6/   50] | d_loss: 0.7711 | g_loss: 1.9064
Epoch [    7/   50] | d_loss: 0.5226 | g_loss: 2.1529
Epoch [    7/   50] | d_loss: 1.2161 | g_loss: 0.6866
Epoch [    7/   50] | d_loss: 0.5750 | g_loss: 2.2607
Epoch [    7/   50] | d_loss: 0.6029 | g_loss: 2.1613
Epoch [    7/   50] | d_loss: 0.6022 | g_loss: 1.0661
Epoch [    7/   50] | d_loss: 0.7155 | g_loss: 1.3739
Epoch [    7/   50] | d_loss: 0.7139 | g_loss: 2.1382
Epoch [    7/   50] | d_loss: 0.6699 | g_loss: 1.6068
Epoch [    7/   50] | d_loss: 0.6999 | g_loss: 2.0521
Epoch [    7/   50] | d_loss: 0.6286 | g_loss: 1.6986
Epoch [    7/   50] | d_loss: 0.6865 | g_loss: 2.2048
Epoch [    7/   50] | d_loss: 0.6228 | g_loss: 1.8169
Epoch [    7/   50] | d_loss: 1.4987 | g_loss: 5.2435
Epoch [    7/   50] | d_loss: 0.4960 | g_loss: 1.8085
Epoch [    7/   50] | d_loss: 1.0721 | g_loss: 0.8719
Epoch [    7/   50] | d_loss: 0.8503 | g_loss: 2.6052
Epoch [    7/   50] | d_loss: 0.7207 | g_loss: 2.4143
Epoch [    7/   50] | d_loss: 0.6725 | g_loss: 2.2843
Epoch [    7/   50] | d_loss: 0.9861 | g_loss: 2.3571
Epoch [    7/   50] | d_loss: 0.6425 | g_loss: 2.5147
Epoch [    7/   50] | d_loss: 0.6195 | g_loss: 2.0067
Epoch [    7/   50] | d_loss: 0.6518 | g_loss: 1.7496
Epoch [    7/   50] | d_loss: 0.5555 | g_loss: 1.8360
Epoch [    7/   50] | d_loss: 1.6443 | g_loss: 3.2078
Epoch [    7/   50] | d_loss: 0.4726 | g_loss: 2.4337
Epoch [    7/   50] | d_loss: 0.4760 | g_loss: 2.2214
Epoch [    7/   50] | d_loss: 0.4229 | g_loss: 2.5028
Epoch [    7/   50] | d_loss: 0.4511 | g_loss: 1.7936
Epoch [    7/   50] | d_loss: 0.6790 | g_loss: 1.7447
Epoch [    8/   50] | d_loss: 0.5509 | g_loss: 2.0884
Epoch [    8/   50] | d_loss: 0.4703 | g_loss: 1.8701
Epoch [    8/   50] | d_loss: 0.6320 | g_loss: 1.5746
Epoch [    8/   50] | d_loss: 0.6392 | g_loss: 1.5229
Epoch [    8/   50] | d_loss: 0.6312 | g_loss: 1.5730
Epoch [    8/   50] | d_loss: 0.5094 | g_loss: 1.7486
Epoch [    8/   50] | d_loss: 0.5307 | g_loss: 2.1206
Epoch [    8/   50] | d_loss: 0.7379 | g_loss: 1.4201
Epoch [    8/   50] | d_loss: 0.5222 | g_loss: 1.9429
Epoch [    8/   50] | d_loss: 0.5667 | g_loss: 1.1047
Epoch [    8/   50] | d_loss: 0.7090 | g_loss: 2.0479
Epoch [    8/   50] | d_loss: 0.4571 | g_loss: 2.1197
Epoch [    8/   50] | d_loss: 0.7491 | g_loss: 1.7877
Epoch [    8/   50] | d_loss: 0.8419 | g_loss: 1.1191
Epoch [    8/   50] | d_loss: 0.8561 | g_loss: 1.1542
Epoch [    8/   50] | d_loss: 0.6410 | g_loss: 2.5311
Epoch [    8/   50] | d_loss: 0.5385 | g_loss: 2.3890
Epoch [    8/   50] | d_loss: 1.1516 | g_loss: 0.8789
Epoch [    8/   50] | d_loss: 0.9606 | g_loss: 2.5610
Epoch [    8/   50] | d_loss: 0.5389 | g_loss: 2.3453
Epoch [    8/   50] | d_loss: 0.5898 | g_loss: 1.3747
Epoch [    8/   50] | d_loss: 0.5071 | g_loss: 2.6670
Epoch [    8/   50] | d_loss: 0.8253 | g_loss: 0.9608
Epoch [    8/   50] | d_loss: 0.5981 | g_loss: 1.7466
Epoch [    8/   50] | d_loss: 0.6245 | g_loss: 1.8404
Epoch [    8/   50] | d_loss: 0.4519 | g_loss: 2.9037
Epoch [    8/   50] | d_loss: 0.9261 | g_loss: 4.1308
Epoch [    8/   50] | d_loss: 0.6055 | g_loss: 2.4369
Epoch [    8/   50] | d_loss: 0.4757 | g_loss: 1.9401
Epoch [    9/   50] | d_loss: 0.8105 | g_loss: 1.7630
Epoch [    9/   50] | d_loss: 0.8534 | g_loss: 1.3888
Epoch [    9/   50] | d_loss: 0.6951 | g_loss: 2.1505
Epoch [    9/   50] | d_loss: 0.4732 | g_loss: 2.0102
Epoch [    9/   50] | d_loss: 1.3926 | g_loss: 4.3908
Epoch [    9/   50] | d_loss: 0.8063 | g_loss: 2.3494
Epoch [    9/   50] | d_loss: 0.5377 | g_loss: 1.6423
Epoch [    9/   50] | d_loss: 0.4345 | g_loss: 2.8190
Epoch [    9/   50] | d_loss: 0.2668 | g_loss: 2.7905
Epoch [    9/   50] | d_loss: 0.5503 | g_loss: 2.2131
Epoch [    9/   50] | d_loss: 0.5344 | g_loss: 2.6226
Epoch [    9/   50] | d_loss: 0.3622 | g_loss: 1.8539
Epoch [    9/   50] | d_loss: 0.6473 | g_loss: 2.4823
Epoch [    9/   50] | d_loss: 0.3823 | g_loss: 2.8589
Epoch [    9/   50] | d_loss: 0.6128 | g_loss: 1.3637
Epoch [    9/   50] | d_loss: 0.5288 | g_loss: 2.4746
Epoch [    9/   50] | d_loss: 0.4868 | g_loss: 1.7445
Epoch [    9/   50] | d_loss: 0.5307 | g_loss: 1.6962
Epoch [    9/   50] | d_loss: 0.5147 | g_loss: 1.5949
Epoch [    9/   50] | d_loss: 0.7129 | g_loss: 1.6979
Epoch [    9/   50] | d_loss: 0.6534 | g_loss: 1.6312
Epoch [    9/   50] | d_loss: 0.5704 | g_loss: 1.4164
Epoch [    9/   50] | d_loss: 0.8483 | g_loss: 1.2438
Epoch [    9/   50] | d_loss: 0.5571 | g_loss: 1.6218
Epoch [    9/   50] | d_loss: 0.5497 | g_loss: 2.2697
Epoch [    9/   50] | d_loss: 0.5443 | g_loss: 3.6614
Epoch [    9/   50] | d_loss: 0.4666 | g_loss: 2.1053
Epoch [    9/   50] | d_loss: 0.8412 | g_loss: 3.1336
Epoch [    9/   50] | d_loss: 0.7236 | g_loss: 0.9930
Epoch [   10/   50] | d_loss: 0.5736 | g_loss: 2.2502
Epoch [   10/   50] | d_loss: 0.5055 | g_loss: 1.6445
Epoch [   10/   50] | d_loss: 0.3959 | g_loss: 2.4343
Epoch [   10/   50] | d_loss: 0.4335 | g_loss: 1.8655
Epoch [   10/   50] | d_loss: 0.7641 | g_loss: 3.0149
Epoch [   10/   50] | d_loss: 0.8598 | g_loss: 0.7968
Epoch [   10/   50] | d_loss: 0.6478 | g_loss: 1.6803
Epoch [   10/   50] | d_loss: 0.6865 | g_loss: 1.8925
Epoch [   10/   50] | d_loss: 0.6476 | g_loss: 2.4441
Epoch [   10/   50] | d_loss: 1.1211 | g_loss: 3.7819
Epoch [   10/   50] | d_loss: 0.6236 | g_loss: 2.0298
Epoch [   10/   50] | d_loss: 0.4874 | g_loss: 2.2304
Epoch [   10/   50] | d_loss: 0.6369 | g_loss: 2.1677
Epoch [   10/   50] | d_loss: 0.6493 | g_loss: 2.8795
Epoch [   10/   50] | d_loss: 0.5133 | g_loss: 2.4550
Epoch [   10/   50] | d_loss: 0.2561 | g_loss: 3.3387
Epoch [   10/   50] | d_loss: 0.3397 | g_loss: 1.7746
Epoch [   10/   50] | d_loss: 0.4381 | g_loss: 2.3294
Epoch [   10/   50] | d_loss: 0.9989 | g_loss: 3.0391
Epoch [   10/   50] | d_loss: 0.6590 | g_loss: 2.7007
Epoch [   10/   50] | d_loss: 0.3881 | g_loss: 2.7904
Epoch [   10/   50] | d_loss: 0.4066 | g_loss: 2.1551
Epoch [   10/   50] | d_loss: 1.1067 | g_loss: 0.5329
Epoch [   10/   50] | d_loss: 0.3713 | g_loss: 2.5564
Epoch [   10/   50] | d_loss: 0.5455 | g_loss: 3.0986
Epoch [   10/   50] | d_loss: 0.5120 | g_loss: 2.5345
Epoch [   10/   50] | d_loss: 0.7796 | g_loss: 0.7951
Epoch [   10/   50] | d_loss: 0.7702 | g_loss: 1.1857
Epoch [   10/   50] | d_loss: 0.5578 | g_loss: 1.5337
Epoch [   11/   50] | d_loss: 1.0598 | g_loss: 3.5293
Epoch [   11/   50] | d_loss: 0.3852 | g_loss: 2.1552
Epoch [   11/   50] | d_loss: 0.3974 | g_loss: 2.5906
Epoch [   11/   50] | d_loss: 0.6664 | g_loss: 2.8836
Epoch [   11/   50] | d_loss: 0.5858 | g_loss: 2.5756
Epoch [   11/   50] | d_loss: 0.4583 | g_loss: 2.6324
Epoch [   11/   50] | d_loss: 0.3956 | g_loss: 2.4606
Epoch [   11/   50] | d_loss: 0.5204 | g_loss: 3.1473
Epoch [   11/   50] | d_loss: 0.4194 | g_loss: 2.5414
Epoch [   11/   50] | d_loss: 0.3518 | g_loss: 1.7822
Epoch [   11/   50] | d_loss: 0.5352 | g_loss: 2.6270
Epoch [   11/   50] | d_loss: 0.4171 | g_loss: 2.3847
Epoch [   11/   50] | d_loss: 0.4815 | g_loss: 2.7579
Epoch [   11/   50] | d_loss: 0.2632 | g_loss: 3.5718
Epoch [   11/   50] | d_loss: 0.6130 | g_loss: 2.6042
Epoch [   11/   50] | d_loss: 0.4802 | g_loss: 2.5288
Epoch [   11/   50] | d_loss: 0.5563 | g_loss: 2.3512
Epoch [   11/   50] | d_loss: 0.5489 | g_loss: 1.5307
Epoch [   11/   50] | d_loss: 2.7326 | g_loss: 3.9447
Epoch [   11/   50] | d_loss: 0.5733 | g_loss: 2.0752
Epoch [   11/   50] | d_loss: 1.0779 | g_loss: 3.6746
Epoch [   11/   50] | d_loss: 0.7801 | g_loss: 3.6957
Epoch [   11/   50] | d_loss: 0.3118 | g_loss: 2.1183
Epoch [   11/   50] | d_loss: 0.8755 | g_loss: 3.0772
Epoch [   11/   50] | d_loss: 0.5016 | g_loss: 2.0459
Epoch [   11/   50] | d_loss: 1.0877 | g_loss: 0.8096
Epoch [   11/   50] | d_loss: 0.4421 | g_loss: 2.5471
Epoch [   11/   50] | d_loss: 0.5335 | g_loss: 2.4396
Epoch [   11/   50] | d_loss: 0.4354 | g_loss: 1.6646
Epoch [   12/   50] | d_loss: 0.9333 | g_loss: 4.9048
Epoch [   12/   50] | d_loss: 0.5282 | g_loss: 1.8448
Epoch [   12/   50] | d_loss: 0.3844 | g_loss: 2.6420
Epoch [   12/   50] | d_loss: 0.4126 | g_loss: 2.6725
Epoch [   12/   50] | d_loss: 0.4521 | g_loss: 2.3267
Epoch [   12/   50] | d_loss: 0.4765 | g_loss: 2.1947
Epoch [   12/   50] | d_loss: 0.4810 | g_loss: 2.0587
Epoch [   12/   50] | d_loss: 0.4119 | g_loss: 2.8537
Epoch [   12/   50] | d_loss: 0.3836 | g_loss: 2.6729
Epoch [   12/   50] | d_loss: 0.5934 | g_loss: 3.3539
Epoch [   12/   50] | d_loss: 0.2685 | g_loss: 1.8605
Epoch [   12/   50] | d_loss: 0.3337 | g_loss: 1.6302
Epoch [   12/   50] | d_loss: 0.2969 | g_loss: 3.0267
Epoch [   12/   50] | d_loss: 0.4192 | g_loss: 2.7937
Epoch [   12/   50] | d_loss: 0.2809 | g_loss: 3.3160
Epoch [   12/   50] | d_loss: 0.5181 | g_loss: 1.8950
Epoch [   12/   50] | d_loss: 0.5498 | g_loss: 3.0817
Epoch [   12/   50] | d_loss: 0.4287 | g_loss: 1.8704
Epoch [   12/   50] | d_loss: 0.6679 | g_loss: 1.6539
Epoch [   12/   50] | d_loss: 0.6801 | g_loss: 1.4626
Epoch [   12/   50] | d_loss: 0.3333 | g_loss: 2.6542
Epoch [   12/   50] | d_loss: 0.4457 | g_loss: 1.9641
Epoch [   12/   50] | d_loss: 0.4080 | g_loss: 1.7605
Epoch [   12/   50] | d_loss: 0.6703 | g_loss: 3.1101
Epoch [   12/   50] | d_loss: 0.3410 | g_loss: 2.5104
Epoch [   12/   50] | d_loss: 0.8165 | g_loss: 1.7599
Epoch [   12/   50] | d_loss: 0.4548 | g_loss: 2.3665
Epoch [   12/   50] | d_loss: 0.6475 | g_loss: 2.5716
Epoch [   12/   50] | d_loss: 0.4444 | g_loss: 2.9062
Epoch [   13/   50] | d_loss: 0.4375 | g_loss: 2.4114
Epoch [   13/   50] | d_loss: 0.4086 | g_loss: 2.5658
Epoch [   13/   50] | d_loss: 0.3937 | g_loss: 2.2228
Epoch [   13/   50] | d_loss: 0.4659 | g_loss: 2.0593
Epoch [   13/   50] | d_loss: 0.6658 | g_loss: 1.3244
Epoch [   13/   50] | d_loss: 0.2737 | g_loss: 2.7203
Epoch [   13/   50] | d_loss: 0.4592 | g_loss: 2.8137
Epoch [   13/   50] | d_loss: 0.2609 | g_loss: 2.1630
Epoch [   13/   50] | d_loss: 0.4902 | g_loss: 2.1122
Epoch [   13/   50] | d_loss: 0.8589 | g_loss: 1.0607
Epoch [   13/   50] | d_loss: 0.4635 | g_loss: 1.9631
Epoch [   13/   50] | d_loss: 0.4806 | g_loss: 2.4835
Epoch [   13/   50] | d_loss: 0.7042 | g_loss: 3.0730
Epoch [   13/   50] | d_loss: 0.4901 | g_loss: 2.5469
Epoch [   13/   50] | d_loss: 0.2584 | g_loss: 2.9080
Epoch [   13/   50] | d_loss: 0.2449 | g_loss: 2.1053
Epoch [   13/   50] | d_loss: 0.4238 | g_loss: 2.0157
Epoch [   13/   50] | d_loss: 0.3933 | g_loss: 3.6095
Epoch [   13/   50] | d_loss: 0.4216 | g_loss: 2.6829
Epoch [   13/   50] | d_loss: 0.4830 | g_loss: 1.9760
Epoch [   13/   50] | d_loss: 0.4298 | g_loss: 2.3595
Epoch [   13/   50] | d_loss: 0.3240 | g_loss: 2.0483
Epoch [   13/   50] | d_loss: 0.3156 | g_loss: 3.4341
Epoch [   13/   50] | d_loss: 0.4045 | g_loss: 2.1980
Epoch [   13/   50] | d_loss: 0.1898 | g_loss: 3.6740
Epoch [   13/   50] | d_loss: 0.5753 | g_loss: 1.9812
Epoch [   13/   50] | d_loss: 0.3860 | g_loss: 2.2264
Epoch [   13/   50] | d_loss: 1.0127 | g_loss: 1.6442
Epoch [   13/   50] | d_loss: 0.3579 | g_loss: 3.0601
Epoch [   14/   50] | d_loss: 0.3838 | g_loss: 2.6851
Epoch [   14/   50] | d_loss: 0.5925 | g_loss: 3.9143
Epoch [   14/   50] | d_loss: 0.5831 | g_loss: 2.4547
Epoch [   14/   50] | d_loss: 0.6929 | g_loss: 2.1416
Epoch [   14/   50] | d_loss: 0.4755 | g_loss: 0.9801
Epoch [   14/   50] | d_loss: 0.3493 | g_loss: 1.7417
Epoch [   14/   50] | d_loss: 0.3037 | g_loss: 2.3314
Epoch [   14/   50] | d_loss: 0.2695 | g_loss: 2.9803
Epoch [   14/   50] | d_loss: 0.5457 | g_loss: 2.1126
Epoch [   14/   50] | d_loss: 0.5314 | g_loss: 4.7589
Epoch [   14/   50] | d_loss: 0.3885 | g_loss: 3.0951
Epoch [   14/   50] | d_loss: 0.4870 | g_loss: 1.5935
Epoch [   14/   50] | d_loss: 0.4396 | g_loss: 3.4987
Epoch [   14/   50] | d_loss: 0.2668 | g_loss: 3.0551
Epoch [   14/   50] | d_loss: 0.3709 | g_loss: 2.5026
Epoch [   14/   50] | d_loss: 0.3273 | g_loss: 2.7941
Epoch [   14/   50] | d_loss: 0.4762 | g_loss: 2.4491
Epoch [   14/   50] | d_loss: 0.3652 | g_loss: 2.7735
Epoch [   14/   50] | d_loss: 0.4272 | g_loss: 1.4544
Epoch [   14/   50] | d_loss: 0.3335 | g_loss: 3.9197
Epoch [   14/   50] | d_loss: 0.6724 | g_loss: 2.3205
Epoch [   14/   50] | d_loss: 0.4621 | g_loss: 2.5945
Epoch [   14/   50] | d_loss: 0.3723 | g_loss: 1.7414
Epoch [   14/   50] | d_loss: 0.1927 | g_loss: 3.2176
Epoch [   14/   50] | d_loss: 0.9862 | g_loss: 3.6711
Epoch [   14/   50] | d_loss: 0.5513 | g_loss: 2.5406
Epoch [   14/   50] | d_loss: 0.3558 | g_loss: 2.9333
Epoch [   14/   50] | d_loss: 0.2887 | g_loss: 2.0304
Epoch [   14/   50] | d_loss: 0.2788 | g_loss: 2.9652
Epoch [   15/   50] | d_loss: 0.3927 | g_loss: 2.4920
Epoch [   15/   50] | d_loss: 0.2903 | g_loss: 2.8845
Epoch [   15/   50] | d_loss: 0.3066 | g_loss: 2.1154
Epoch [   15/   50] | d_loss: 0.4809 | g_loss: 2.9517
Epoch [   15/   50] | d_loss: 0.4651 | g_loss: 3.9021
Epoch [   15/   50] | d_loss: 0.2504 | g_loss: 1.7160
Epoch [   15/   50] | d_loss: 0.7863 | g_loss: 1.2953
Epoch [   15/   50] | d_loss: 0.4671 | g_loss: 3.3389
Epoch [   15/   50] | d_loss: 0.5134 | g_loss: 2.6014
Epoch [   15/   50] | d_loss: 0.2785 | g_loss: 3.0081
Epoch [   15/   50] | d_loss: 0.3977 | g_loss: 2.3906
Epoch [   15/   50] | d_loss: 0.2580 | g_loss: 2.7063
Epoch [   15/   50] | d_loss: 0.3490 | g_loss: 2.1889
Epoch [   15/   50] | d_loss: 0.2489 | g_loss: 2.3951
Epoch [   15/   50] | d_loss: 0.7934 | g_loss: 5.2171
Epoch [   15/   50] | d_loss: 0.3037 | g_loss: 2.9956
Epoch [   15/   50] | d_loss: 0.4108 | g_loss: 2.5211
Epoch [   15/   50] | d_loss: 0.5851 | g_loss: 1.3231
Epoch [   15/   50] | d_loss: 0.3011 | g_loss: 2.5951
Epoch [   15/   50] | d_loss: 0.5542 | g_loss: 3.4568
Epoch [   15/   50] | d_loss: 0.3179 | g_loss: 3.7874
Epoch [   15/   50] | d_loss: 0.5453 | g_loss: 0.8988
Epoch [   15/   50] | d_loss: 0.4157 | g_loss: 3.5845
Epoch [   15/   50] | d_loss: 0.6787 | g_loss: 1.3036
Epoch [   15/   50] | d_loss: 0.8584 | g_loss: 2.4152
Epoch [   15/   50] | d_loss: 0.2713 | g_loss: 2.1334
Epoch [   15/   50] | d_loss: 0.5029 | g_loss: 2.3935
Epoch [   15/   50] | d_loss: 0.9162 | g_loss: 4.4381
Epoch [   15/   50] | d_loss: 1.9982 | g_loss: 6.7354
Epoch [   16/   50] | d_loss: 0.8653 | g_loss: 4.2433
Epoch [   16/   50] | d_loss: 0.5019 | g_loss: 3.0694
Epoch [   16/   50] | d_loss: 0.2151 | g_loss: 2.8346
Epoch [   16/   50] | d_loss: 0.2022 | g_loss: 2.9298
Epoch [   16/   50] | d_loss: 0.3944 | g_loss: 1.6224
Epoch [   16/   50] | d_loss: 0.3783 | g_loss: 1.9100
Epoch [   16/   50] | d_loss: 0.4406 | g_loss: 2.6213
Epoch [   16/   50] | d_loss: 0.4356 | g_loss: 3.9142
Epoch [   16/   50] | d_loss: 0.3611 | g_loss: 2.3667
Epoch [   16/   50] | d_loss: 0.2301 | g_loss: 2.6953
Epoch [   16/   50] | d_loss: 0.2957 | g_loss: 2.7391
Epoch [   16/   50] | d_loss: 0.2555 | g_loss: 1.8057
Epoch [   16/   50] | d_loss: 0.2507 | g_loss: 3.0178
Epoch [   16/   50] | d_loss: 0.2730 | g_loss: 2.3476
Epoch [   16/   50] | d_loss: 0.2730 | g_loss: 2.8934
Epoch [   16/   50] | d_loss: 0.3665 | g_loss: 3.8048
Epoch [   16/   50] | d_loss: 0.4753 | g_loss: 2.6511
Epoch [   16/   50] | d_loss: 0.4834 | g_loss: 3.3366
Epoch [   16/   50] | d_loss: 0.3701 | g_loss: 2.3042
Epoch [   16/   50] | d_loss: 0.2968 | g_loss: 2.5064
Epoch [   16/   50] | d_loss: 0.2665 | g_loss: 3.5380
Epoch [   16/   50] | d_loss: 2.2373 | g_loss: 0.8063
Epoch [   16/   50] | d_loss: 0.3178 | g_loss: 2.5732
Epoch [   16/   50] | d_loss: 0.3630 | g_loss: 1.9837
Epoch [   16/   50] | d_loss: 0.3462 | g_loss: 2.2282
Epoch [   16/   50] | d_loss: 0.2414 | g_loss: 3.3203
Epoch [   16/   50] | d_loss: 1.1833 | g_loss: 2.0066
Epoch [   16/   50] | d_loss: 0.5602 | g_loss: 3.3893
Epoch [   16/   50] | d_loss: 0.2210 | g_loss: 2.5085
Epoch [   17/   50] | d_loss: 0.3358 | g_loss: 2.0342
Epoch [   17/   50] | d_loss: 0.2200 | g_loss: 3.3819
Epoch [   17/   50] | d_loss: 0.2431 | g_loss: 3.1132
Epoch [   17/   50] | d_loss: 0.6072 | g_loss: 2.7903
Epoch [   17/   50] | d_loss: 0.3376 | g_loss: 2.3527
Epoch [   17/   50] | d_loss: 0.1634 | g_loss: 3.8581
Epoch [   17/   50] | d_loss: 0.3044 | g_loss: 1.1169
Epoch [   17/   50] | d_loss: 0.2111 | g_loss: 3.1802
Epoch [   17/   50] | d_loss: 0.2057 | g_loss: 3.5061
Epoch [   17/   50] | d_loss: 0.4496 | g_loss: 2.0001
Epoch [   17/   50] | d_loss: 0.4453 | g_loss: 4.2434
Epoch [   17/   50] | d_loss: 1.0343 | g_loss: 2.0580
Epoch [   17/   50] | d_loss: 0.4120 | g_loss: 3.1245
Epoch [   17/   50] | d_loss: 0.2757 | g_loss: 2.7198
Epoch [   17/   50] | d_loss: 0.3494 | g_loss: 3.0482
Epoch [   17/   50] | d_loss: 0.3084 | g_loss: 3.0840
Epoch [   17/   50] | d_loss: 0.4429 | g_loss: 1.9222
Epoch [   17/   50] | d_loss: 0.3309 | g_loss: 2.9658
Epoch [   17/   50] | d_loss: 0.3656 | g_loss: 2.3896
Epoch [   17/   50] | d_loss: 0.5068 | g_loss: 1.4396
Epoch [   17/   50] | d_loss: 0.1924 | g_loss: 2.4603
Epoch [   17/   50] | d_loss: 0.2483 | g_loss: 3.5895
Epoch [   17/   50] | d_loss: 0.2470 | g_loss: 2.3592
Epoch [   17/   50] | d_loss: 0.2625 | g_loss: 3.6652
Epoch [   17/   50] | d_loss: 0.8996 | g_loss: 0.7121
Epoch [   17/   50] | d_loss: 0.5746 | g_loss: 1.5740
Epoch [   17/   50] | d_loss: 0.3435 | g_loss: 2.2370
Epoch [   17/   50] | d_loss: 0.3214 | g_loss: 3.0610
Epoch [   17/   50] | d_loss: 0.2461 | g_loss: 2.9959
Epoch [   18/   50] | d_loss: 2.7199 | g_loss: 8.4094
Epoch [   18/   50] | d_loss: 0.3727 | g_loss: 2.9660
Epoch [   18/   50] | d_loss: 0.2383 | g_loss: 2.7195
Epoch [   18/   50] | d_loss: 0.5365 | g_loss: 1.9078
Epoch [   18/   50] | d_loss: 0.7207 | g_loss: 1.9580
Epoch [   18/   50] | d_loss: 0.2164 | g_loss: 3.3431
Epoch [   18/   50] | d_loss: 0.2652 | g_loss: 3.5826
Epoch [   18/   50] | d_loss: 0.2468 | g_loss: 2.9701
Epoch [   18/   50] | d_loss: 0.2847 | g_loss: 3.0216
Epoch [   18/   50] | d_loss: 0.3699 | g_loss: 2.1945
Epoch [   18/   50] | d_loss: 0.4379 | g_loss: 1.8257
Epoch [   18/   50] | d_loss: 0.2681 | g_loss: 3.1094
Epoch [   18/   50] | d_loss: 0.3058 | g_loss: 2.3562
Epoch [   18/   50] | d_loss: 0.5860 | g_loss: 5.3582
Epoch [   18/   50] | d_loss: 0.3214 | g_loss: 3.3453
Epoch [   18/   50] | d_loss: 0.3376 | g_loss: 2.1944
Epoch [   18/   50] | d_loss: 0.3379 | g_loss: 3.9636
Epoch [   18/   50] | d_loss: 0.2536 | g_loss: 3.9753
Epoch [   18/   50] | d_loss: 0.5080 | g_loss: 3.0618
Epoch [   18/   50] | d_loss: 0.3572 | g_loss: 4.3923
Epoch [   18/   50] | d_loss: 0.4340 | g_loss: 2.9601
Epoch [   18/   50] | d_loss: 0.3007 | g_loss: 2.8331
Epoch [   18/   50] | d_loss: 0.3858 | g_loss: 3.4185
Epoch [   18/   50] | d_loss: 0.5401 | g_loss: 2.4685
Epoch [   18/   50] | d_loss: 0.2179 | g_loss: 2.6822
Epoch [   18/   50] | d_loss: 0.1931 | g_loss: 3.0724
Epoch [   18/   50] | d_loss: 0.2999 | g_loss: 2.6019
Epoch [   18/   50] | d_loss: 2.6353 | g_loss: 7.3300
Epoch [   18/   50] | d_loss: 0.4468 | g_loss: 3.9849
Epoch [   19/   50] | d_loss: 2.1774 | g_loss: 2.5643
Epoch [   19/   50] | d_loss: 0.3415 | g_loss: 3.1969
Epoch [   19/   50] | d_loss: 0.3742 | g_loss: 3.1270
Epoch [   19/   50] | d_loss: 0.3014 | g_loss: 3.2964
Epoch [   19/   50] | d_loss: 0.1318 | g_loss: 4.9278
Epoch [   19/   50] | d_loss: 0.2907 | g_loss: 1.8712
Epoch [   19/   50] | d_loss: 0.2136 | g_loss: 1.9750
Epoch [   19/   50] | d_loss: 0.3258 | g_loss: 2.4361
Epoch [   19/   50] | d_loss: 0.3514 | g_loss: 3.2841
Epoch [   19/   50] | d_loss: 0.2778 | g_loss: 4.0981
Epoch [   19/   50] | d_loss: 0.3094 | g_loss: 1.8382
Epoch [   19/   50] | d_loss: 0.1633 | g_loss: 3.3196
Epoch [   19/   50] | d_loss: 0.1918 | g_loss: 3.9640
Epoch [   19/   50] | d_loss: 0.5510 | g_loss: 2.9061
Epoch [   19/   50] | d_loss: 0.4397 | g_loss: 3.1534
Epoch [   19/   50] | d_loss: 0.2808 | g_loss: 3.5923
Epoch [   19/   50] | d_loss: 0.1931 | g_loss: 3.4387
Epoch [   19/   50] | d_loss: 0.3014 | g_loss: 3.2796
Epoch [   19/   50] | d_loss: 0.2223 | g_loss: 2.7967
Epoch [   19/   50] | d_loss: 0.3306 | g_loss: 3.9542
Epoch [   19/   50] | d_loss: 0.3995 | g_loss: 3.2424
Epoch [   19/   50] | d_loss: 0.2324 | g_loss: 3.7110
Epoch [   19/   50] | d_loss: 0.3754 | g_loss: 3.4457
Epoch [   19/   50] | d_loss: 0.7834 | g_loss: 0.7704
Epoch [   19/   50] | d_loss: 0.2822 | g_loss: 1.6881
Epoch [   19/   50] | d_loss: 0.2199 | g_loss: 3.4602
Epoch [   19/   50] | d_loss: 0.3595 | g_loss: 3.8219
Epoch [   19/   50] | d_loss: 0.4130 | g_loss: 3.2340
Epoch [   19/   50] | d_loss: 0.3571 | g_loss: 2.8583
Epoch [   20/   50] | d_loss: 0.5087 | g_loss: 3.3192
Epoch [   20/   50] | d_loss: 0.2692 | g_loss: 2.2463
Epoch [   20/   50] | d_loss: 0.2510 | g_loss: 3.9652
Epoch [   20/   50] | d_loss: 0.1773 | g_loss: 2.7168
Epoch [   20/   50] | d_loss: 0.1875 | g_loss: 3.1826
Epoch [   20/   50] | d_loss: 0.3193 | g_loss: 2.7987
Epoch [   20/   50] | d_loss: 0.3920 | g_loss: 2.1816
Epoch [   20/   50] | d_loss: 0.2158 | g_loss: 3.2468
Epoch [   20/   50] | d_loss: 0.3790 | g_loss: 2.8333
Epoch [   20/   50] | d_loss: 0.6003 | g_loss: 1.9827
Epoch [   20/   50] | d_loss: 0.1351 | g_loss: 4.1402
Epoch [   20/   50] | d_loss: 0.3032 | g_loss: 1.5459
Epoch [   20/   50] | d_loss: 0.2888 | g_loss: 2.0329
Epoch [   20/   50] | d_loss: 0.3077 | g_loss: 2.9474
Epoch [   20/   50] | d_loss: 0.2317 | g_loss: 3.8227
Epoch [   20/   50] | d_loss: 0.2678 | g_loss: 3.3283
Epoch [   20/   50] | d_loss: 0.1495 | g_loss: 2.7553
Epoch [   20/   50] | d_loss: 0.2880 | g_loss: 4.2242
Epoch [   20/   50] | d_loss: 0.2067 | g_loss: 2.8803
Epoch [   20/   50] | d_loss: 0.2855 | g_loss: 2.4399
Epoch [   20/   50] | d_loss: 0.2338 | g_loss: 3.2738
Epoch [   20/   50] | d_loss: 0.1933 | g_loss: 3.1024
Epoch [   20/   50] | d_loss: 0.2062 | g_loss: 2.6047
Epoch [   20/   50] | d_loss: 0.4806 | g_loss: 4.5887
Epoch [   20/   50] | d_loss: 0.6101 | g_loss: 1.9660
Epoch [   20/   50] | d_loss: 0.3858 | g_loss: 2.4570
Epoch [   20/   50] | d_loss: 0.2319 | g_loss: 2.3502
Epoch [   20/   50] | d_loss: 0.4555 | g_loss: 2.0022
Epoch [   20/   50] | d_loss: 0.2409 | g_loss: 3.7583
Epoch [   21/   50] | d_loss: 0.3135 | g_loss: 2.8434
Epoch [   21/   50] | d_loss: 0.1092 | g_loss: 3.8789
Epoch [   21/   50] | d_loss: 0.2120 | g_loss: 2.0218
Epoch [   21/   50] | d_loss: 0.2009 | g_loss: 2.4590
Epoch [   21/   50] | d_loss: 0.3629 | g_loss: 4.1434
Epoch [   21/   50] | d_loss: 0.3349 | g_loss: 3.3979
Epoch [   21/   50] | d_loss: 0.3359 | g_loss: 2.8431
Epoch [   21/   50] | d_loss: 0.2907 | g_loss: 3.4708
Epoch [   21/   50] | d_loss: 0.2407 | g_loss: 3.3318
Epoch [   21/   50] | d_loss: 0.2271 | g_loss: 3.2016
Epoch [   21/   50] | d_loss: 0.1795 | g_loss: 2.9729
Epoch [   21/   50] | d_loss: 0.1503 | g_loss: 4.0019
Epoch [   21/   50] | d_loss: 0.4728 | g_loss: 1.6822
Epoch [   21/   50] | d_loss: 0.3060 | g_loss: 3.5433
Epoch [   21/   50] | d_loss: 0.2091 | g_loss: 3.9611
Epoch [   21/   50] | d_loss: 0.3526 | g_loss: 3.5518
Epoch [   21/   50] | d_loss: 0.3332 | g_loss: 2.8264
Epoch [   21/   50] | d_loss: 0.2193 | g_loss: 4.8405
Epoch [   21/   50] | d_loss: 0.1922 | g_loss: 3.1533
Epoch [   21/   50] | d_loss: 0.1461 | g_loss: 3.0791
Epoch [   21/   50] | d_loss: 0.1915 | g_loss: 2.7129
Epoch [   21/   50] | d_loss: 0.3370 | g_loss: 3.3126
Epoch [   21/   50] | d_loss: 0.3120 | g_loss: 2.8562
Epoch [   21/   50] | d_loss: 0.3569 | g_loss: 2.2674
Epoch [   21/   50] | d_loss: 0.1629 | g_loss: 2.4801
Epoch [   21/   50] | d_loss: 0.2355 | g_loss: 3.4521
Epoch [   21/   50] | d_loss: 0.5107 | g_loss: 3.6775
Epoch [   21/   50] | d_loss: 0.3789 | g_loss: 2.5933
Epoch [   21/   50] | d_loss: 0.2395 | g_loss: 3.3368
Epoch [   22/   50] | d_loss: 0.3488 | g_loss: 4.0370
Epoch [   22/   50] | d_loss: 0.2655 | g_loss: 4.1779
Epoch [   22/   50] | d_loss: 0.3004 | g_loss: 2.5548
Epoch [   22/   50] | d_loss: 0.1284 | g_loss: 4.6805
Epoch [   22/   50] | d_loss: 0.1252 | g_loss: 4.3740
Epoch [   22/   50] | d_loss: 1.4555 | g_loss: 1.4776
Epoch [   22/   50] | d_loss: 0.3108 | g_loss: 3.5731
Epoch [   22/   50] | d_loss: 0.2397 | g_loss: 3.5991
Epoch [   22/   50] | d_loss: 0.2555 | g_loss: 4.1664
Epoch [   22/   50] | d_loss: 0.2093 | g_loss: 2.3681
Epoch [   22/   50] | d_loss: 0.1447 | g_loss: 3.7433
Epoch [   22/   50] | d_loss: 0.1583 | g_loss: 3.5054
Epoch [   22/   50] | d_loss: 0.2525 | g_loss: 1.5903
Epoch [   22/   50] | d_loss: 4.4422 | g_loss: 4.8116
Epoch [   22/   50] | d_loss: 0.3459 | g_loss: 3.3846
Epoch [   22/   50] | d_loss: 0.2918 | g_loss: 3.0086
Epoch [   22/   50] | d_loss: 0.1942 | g_loss: 3.7696
Epoch [   22/   50] | d_loss: 0.3021 | g_loss: 2.5774
Epoch [   22/   50] | d_loss: 0.3401 | g_loss: 2.9163
Epoch [   22/   50] | d_loss: 0.4126 | g_loss: 4.6336
Epoch [   22/   50] | d_loss: 0.7014 | g_loss: 1.8449
Epoch [   22/   50] | d_loss: 0.4302 | g_loss: 1.7121
Epoch [   22/   50] | d_loss: 0.2262 | g_loss: 3.2082
Epoch [   22/   50] | d_loss: 0.2865 | g_loss: 3.8560
Epoch [   22/   50] | d_loss: 0.2283 | g_loss: 2.9344
Epoch [   22/   50] | d_loss: 1.3463 | g_loss: 4.3769
Epoch [   22/   50] | d_loss: 0.1833 | g_loss: 3.6771
Epoch [   22/   50] | d_loss: 0.1467 | g_loss: 3.9485
Epoch [   22/   50] | d_loss: 0.4204 | g_loss: 2.3290
Epoch [   23/   50] | d_loss: 0.6072 | g_loss: 3.8381
Epoch [   23/   50] | d_loss: 0.7290 | g_loss: 1.5779
Epoch [   23/   50] | d_loss: 0.1103 | g_loss: 3.5459
Epoch [   23/   50] | d_loss: 0.2554 | g_loss: 3.3710
Epoch [   23/   50] | d_loss: 0.2148 | g_loss: 3.4980
Epoch [   23/   50] | d_loss: 0.5881 | g_loss: 2.9838
Epoch [   23/   50] | d_loss: 0.4235 | g_loss: 2.5925
Epoch [   23/   50] | d_loss: 0.3539 | g_loss: 4.3984
Epoch [   23/   50] | d_loss: 0.1564 | g_loss: 4.5497
Epoch [   23/   50] | d_loss: 0.2234 | g_loss: 3.2990
Epoch [   23/   50] | d_loss: 0.1748 | g_loss: 2.2836
Epoch [   23/   50] | d_loss: 0.2571 | g_loss: 2.8809
Epoch [   23/   50] | d_loss: 0.3822 | g_loss: 2.9619
Epoch [   23/   50] | d_loss: 0.3773 | g_loss: 2.0859
Epoch [   23/   50] | d_loss: 0.2376 | g_loss: 3.6865
Epoch [   23/   50] | d_loss: 0.3625 | g_loss: 2.5148
Epoch [   23/   50] | d_loss: 0.1464 | g_loss: 2.3283
Epoch [   23/   50] | d_loss: 0.3127 | g_loss: 5.4442
Epoch [   23/   50] | d_loss: 0.4082 | g_loss: 2.4335
Epoch [   23/   50] | d_loss: 0.2670 | g_loss: 3.2486
Epoch [   23/   50] | d_loss: 0.3585 | g_loss: 2.8471
Epoch [   23/   50] | d_loss: 0.2010 | g_loss: 3.1184
Epoch [   23/   50] | d_loss: 0.1178 | g_loss: 3.5447
Epoch [   23/   50] | d_loss: 0.0890 | g_loss: 3.5544
Epoch [   23/   50] | d_loss: 0.8208 | g_loss: 5.7640
Epoch [   23/   50] | d_loss: 0.3368 | g_loss: 2.8055
Epoch [   23/   50] | d_loss: 0.2567 | g_loss: 2.9652
Epoch [   23/   50] | d_loss: 0.1834 | g_loss: 4.0620
Epoch [   23/   50] | d_loss: 0.3509 | g_loss: 2.3996
Epoch [   24/   50] | d_loss: 0.6398 | g_loss: 0.5109
Epoch [   24/   50] | d_loss: 0.2561 | g_loss: 3.0979
Epoch [   24/   50] | d_loss: 0.2002 | g_loss: 3.2347
Epoch [   24/   50] | d_loss: 0.3096 | g_loss: 3.8715
Epoch [   24/   50] | d_loss: 0.4398 | g_loss: 2.1442
Epoch [   24/   50] | d_loss: 0.3875 | g_loss: 2.2558
Epoch [   24/   50] | d_loss: 0.2043 | g_loss: 2.9538
Epoch [   24/   50] | d_loss: 0.1502 | g_loss: 3.4082
Epoch [   24/   50] | d_loss: 0.2013 | g_loss: 3.5330
Epoch [   24/   50] | d_loss: 0.3653 | g_loss: 4.4064
Epoch [   24/   50] | d_loss: 0.2964 | g_loss: 3.8719
Epoch [   24/   50] | d_loss: 0.1927 | g_loss: 3.6995
Epoch [   24/   50] | d_loss: 0.2957 | g_loss: 2.7902
Epoch [   24/   50] | d_loss: 0.1997 | g_loss: 4.2204
Epoch [   24/   50] | d_loss: 0.0798 | g_loss: 3.9832
Epoch [   24/   50] | d_loss: 0.3277 | g_loss: 2.0684
Epoch [   24/   50] | d_loss: 0.2171 | g_loss: 4.3394
Epoch [   24/   50] | d_loss: 0.2505 | g_loss: 2.5530
Epoch [   24/   50] | d_loss: 0.7943 | g_loss: 1.8043
Epoch [   24/   50] | d_loss: 0.1448 | g_loss: 3.8665
Epoch [   24/   50] | d_loss: 0.1796 | g_loss: 3.0476
Epoch [   24/   50] | d_loss: 0.2121 | g_loss: 3.9830
Epoch [   24/   50] | d_loss: 0.2334 | g_loss: 2.4813
Epoch [   24/   50] | d_loss: 0.2588 | g_loss: 3.3991
Epoch [   24/   50] | d_loss: 0.1569 | g_loss: 4.4351
Epoch [   24/   50] | d_loss: 1.7628 | g_loss: 3.3176
Epoch [   24/   50] | d_loss: 0.1969 | g_loss: 3.6263
Epoch [   24/   50] | d_loss: 0.2212 | g_loss: 3.1939
Epoch [   24/   50] | d_loss: 0.2872 | g_loss: 2.4813
Epoch [   25/   50] | d_loss: 0.1591 | g_loss: 3.8471
Epoch [   25/   50] | d_loss: 0.2231 | g_loss: 3.5077
Epoch [   25/   50] | d_loss: 0.2108 | g_loss: 2.4800
Epoch [   25/   50] | d_loss: 0.0691 | g_loss: 4.0337
Epoch [   25/   50] | d_loss: 0.8924 | g_loss: 4.7609
Epoch [   25/   50] | d_loss: 0.3412 | g_loss: 5.1314
Epoch [   25/   50] | d_loss: 0.1934 | g_loss: 3.0214
Epoch [   25/   50] | d_loss: 0.2359 | g_loss: 3.2365
Epoch [   25/   50] | d_loss: 0.3178 | g_loss: 2.7612
Epoch [   25/   50] | d_loss: 0.1149 | g_loss: 3.7753
Epoch [   25/   50] | d_loss: 0.3114 | g_loss: 2.5155
Epoch [   25/   50] | d_loss: 0.5199 | g_loss: 2.6753
Epoch [   25/   50] | d_loss: 0.2449 | g_loss: 4.4014
Epoch [   25/   50] | d_loss: 0.1076 | g_loss: 3.4275
Epoch [   25/   50] | d_loss: 0.1661 | g_loss: 4.0880
Epoch [   25/   50] | d_loss: 0.2559 | g_loss: 3.3757
Epoch [   25/   50] | d_loss: 0.3130 | g_loss: 2.7164
Epoch [   25/   50] | d_loss: 0.3087 | g_loss: 3.1121
Epoch [   25/   50] | d_loss: 0.2317 | g_loss: 2.4511
Epoch [   25/   50] | d_loss: 0.1467 | g_loss: 2.5765
Epoch [   25/   50] | d_loss: 0.5051 | g_loss: 2.9269
Epoch [   25/   50] | d_loss: 0.2523 | g_loss: 3.7539
Epoch [   25/   50] | d_loss: 0.1182 | g_loss: 3.3261
Epoch [   25/   50] | d_loss: 0.3140 | g_loss: 2.3513
Epoch [   25/   50] | d_loss: 0.3291 | g_loss: 2.8910
Epoch [   25/   50] | d_loss: 0.2812 | g_loss: 1.8699
Epoch [   25/   50] | d_loss: 0.1908 | g_loss: 3.2132
Epoch [   25/   50] | d_loss: 0.1410 | g_loss: 3.4760
Epoch [   25/   50] | d_loss: 0.3277 | g_loss: 2.6662
Epoch [   26/   50] | d_loss: 0.8764 | g_loss: 4.3354
Epoch [   26/   50] | d_loss: 0.1485 | g_loss: 4.2036
Epoch [   26/   50] | d_loss: 0.2496 | g_loss: 3.0701
Epoch [   26/   50] | d_loss: 0.3391 | g_loss: 1.8340
Epoch [   26/   50] | d_loss: 0.3142 | g_loss: 5.1513
Epoch [   26/   50] | d_loss: 0.1910 | g_loss: 4.2351
Epoch [   26/   50] | d_loss: 0.2979 | g_loss: 4.8482
Epoch [   26/   50] | d_loss: 0.1854 | g_loss: 3.8020
Epoch [   26/   50] | d_loss: 0.1030 | g_loss: 3.7197
Epoch [   26/   50] | d_loss: 0.4470 | g_loss: 2.7799
Epoch [   26/   50] | d_loss: 0.1879 | g_loss: 2.8158
Epoch [   26/   50] | d_loss: 0.1900 | g_loss: 3.2239
Epoch [   26/   50] | d_loss: 0.2665 | g_loss: 3.1655
Epoch [   26/   50] | d_loss: 0.1891 | g_loss: 3.0678
Epoch [   26/   50] | d_loss: 0.1757 | g_loss: 4.3595
Epoch [   26/   50] | d_loss: 0.1377 | g_loss: 3.9753
Epoch [   26/   50] | d_loss: 0.2787 | g_loss: 2.6549
Epoch [   26/   50] | d_loss: 0.3485 | g_loss: 3.9959
Epoch [   26/   50] | d_loss: 0.0816 | g_loss: 4.0981
Epoch [   26/   50] | d_loss: 1.4390 | g_loss: 3.2687
Epoch [   26/   50] | d_loss: 0.2055 | g_loss: 3.3326
Epoch [   26/   50] | d_loss: 0.2114 | g_loss: 3.9982
Epoch [   26/   50] | d_loss: 0.1761 | g_loss: 3.3397
Epoch [   26/   50] | d_loss: 0.9502 | g_loss: 6.6548
Epoch [   26/   50] | d_loss: 0.3149 | g_loss: 3.9008
Epoch [   26/   50] | d_loss: 0.1764 | g_loss: 3.9049
Epoch [   26/   50] | d_loss: 0.1530 | g_loss: 2.9448
Epoch [   26/   50] | d_loss: 0.2751 | g_loss: 4.3497
Epoch [   26/   50] | d_loss: 0.4628 | g_loss: 4.7733
Epoch [   27/   50] | d_loss: 1.7579 | g_loss: 0.2146
Epoch [   27/   50] | d_loss: 0.2468 | g_loss: 1.8800
Epoch [   27/   50] | d_loss: 0.2982 | g_loss: 2.4557
Epoch [   27/   50] | d_loss: 0.1888 | g_loss: 1.5252
Epoch [   27/   50] | d_loss: 0.4601 | g_loss: 1.1761
Epoch [   27/   50] | d_loss: 0.1000 | g_loss: 2.9496
Epoch [   27/   50] | d_loss: 0.1610 | g_loss: 3.9901
Epoch [   27/   50] | d_loss: 0.1214 | g_loss: 2.9317
Epoch [   27/   50] | d_loss: 0.1154 | g_loss: 2.8861
Epoch [   27/   50] | d_loss: 0.4926 | g_loss: 2.3126
Epoch [   27/   50] | d_loss: 0.1532 | g_loss: 3.4367
Epoch [   27/   50] | d_loss: 0.1799 | g_loss: 3.3503
Epoch [   27/   50] | d_loss: 0.5514 | g_loss: 3.2130
Epoch [   27/   50] | d_loss: 0.3459 | g_loss: 2.8957
Epoch [   27/   50] | d_loss: 0.3579 | g_loss: 2.4185
Epoch [   27/   50] | d_loss: 1.1901 | g_loss: 4.4986
Epoch [   27/   50] | d_loss: 0.1351 | g_loss: 3.4458
Epoch [   27/   50] | d_loss: 0.3993 | g_loss: 2.1000
Epoch [   27/   50] | d_loss: 0.3488 | g_loss: 2.9483
Epoch [   27/   50] | d_loss: 0.5808 | g_loss: 3.3039
Epoch [   27/   50] | d_loss: 0.2039 | g_loss: 3.5242
Epoch [   27/   50] | d_loss: 0.1219 | g_loss: 4.2908
Epoch [   27/   50] | d_loss: 0.0874 | g_loss: 4.6102
Epoch [   27/   50] | d_loss: 0.2661 | g_loss: 4.2546
Epoch [   27/   50] | d_loss: 0.2704 | g_loss: 3.6625
Epoch [   27/   50] | d_loss: 0.2680 | g_loss: 3.0951
Epoch [   27/   50] | d_loss: 0.1811 | g_loss: 2.7239
Epoch [   27/   50] | d_loss: 0.4690 | g_loss: 1.6821
Epoch [   27/   50] | d_loss: 0.2329 | g_loss: 3.1506
Epoch [   28/   50] | d_loss: 0.3026 | g_loss: 2.1392
Epoch [   28/   50] | d_loss: 0.2228 | g_loss: 4.2997
Epoch [   28/   50] | d_loss: 0.0798 | g_loss: 2.9467
Epoch [   28/   50] | d_loss: 0.1962 | g_loss: 4.9084
Epoch [   28/   50] | d_loss: 0.4608 | g_loss: 3.7235
Epoch [   28/   50] | d_loss: 0.2144 | g_loss: 3.3944
Epoch [   28/   50] | d_loss: 0.0718 | g_loss: 4.6199
Epoch [   28/   50] | d_loss: 0.2885 | g_loss: 2.3931
Epoch [   28/   50] | d_loss: 0.0883 | g_loss: 3.8769
Epoch [   28/   50] | d_loss: 0.2169 | g_loss: 1.7018
Epoch [   28/   50] | d_loss: 0.1049 | g_loss: 2.5188
Epoch [   28/   50] | d_loss: 0.2043 | g_loss: 3.0835
Epoch [   28/   50] | d_loss: 0.3138 | g_loss: 3.8068
Epoch [   28/   50] | d_loss: 0.3110 | g_loss: 1.9614
Epoch [   28/   50] | d_loss: 0.1729 | g_loss: 3.9032
Epoch [   28/   50] | d_loss: 0.1141 | g_loss: 3.6229
Epoch [   28/   50] | d_loss: 0.1570 | g_loss: 3.4492
Epoch [   28/   50] | d_loss: 0.2834 | g_loss: 2.9984
Epoch [   28/   50] | d_loss: 0.1161 | g_loss: 3.4688
Epoch [   28/   50] | d_loss: 0.1456 | g_loss: 4.5928
Epoch [   28/   50] | d_loss: 0.9131 | g_loss: 1.7538
Epoch [   28/   50] | d_loss: 0.1128 | g_loss: 3.4652
Epoch [   28/   50] | d_loss: 0.1666 | g_loss: 3.7991
Epoch [   28/   50] | d_loss: 0.1700 | g_loss: 2.1016
Epoch [   28/   50] | d_loss: 0.1814 | g_loss: 3.4795
Epoch [   28/   50] | d_loss: 0.7010 | g_loss: 0.5997
Epoch [   28/   50] | d_loss: 0.2702 | g_loss: 4.3054
Epoch [   28/   50] | d_loss: 0.2972 | g_loss: 3.0312
Epoch [   28/   50] | d_loss: 0.2604 | g_loss: 4.2827
Epoch [   29/   50] | d_loss: 0.1250 | g_loss: 3.2828
Epoch [   29/   50] | d_loss: 0.0797 | g_loss: 3.2511
Epoch [   29/   50] | d_loss: 0.3019 | g_loss: 3.5935
Epoch [   29/   50] | d_loss: 0.1423 | g_loss: 4.0651
Epoch [   29/   50] | d_loss: 0.1659 | g_loss: 4.5218
Epoch [   29/   50] | d_loss: 0.3665 | g_loss: 2.0609
Epoch [   29/   50] | d_loss: 0.0767 | g_loss: 4.4802
Epoch [   29/   50] | d_loss: 0.2494 | g_loss: 2.9951
Epoch [   29/   50] | d_loss: 0.1655 | g_loss: 4.4052
Epoch [   29/   50] | d_loss: 0.5037 | g_loss: 1.1445
Epoch [   29/   50] | d_loss: 0.1778 | g_loss: 2.6803
Epoch [   29/   50] | d_loss: 0.0803 | g_loss: 4.0868
Epoch [   29/   50] | d_loss: 0.1838 | g_loss: 4.6628
Epoch [   29/   50] | d_loss: 0.2852 | g_loss: 2.3394
Epoch [   29/   50] | d_loss: 0.3765 | g_loss: 1.7296
Epoch [   29/   50] | d_loss: 0.2681 | g_loss: 1.5593
Epoch [   29/   50] | d_loss: 0.0932 | g_loss: 3.2892
Epoch [   29/   50] | d_loss: 0.1889 | g_loss: 2.9322
Epoch [   29/   50] | d_loss: 0.0841 | g_loss: 4.3249
Epoch [   29/   50] | d_loss: 0.1196 | g_loss: 3.5084
Epoch [   29/   50] | d_loss: 0.0847 | g_loss: 3.9248
Epoch [   29/   50] | d_loss: 1.1676 | g_loss: 2.2273
Epoch [   29/   50] | d_loss: 0.2631 | g_loss: 4.0591
Epoch [   29/   50] | d_loss: 0.1858 | g_loss: 2.6732
Epoch [   29/   50] | d_loss: 0.0904 | g_loss: 4.1537
Epoch [   29/   50] | d_loss: 0.1014 | g_loss: 4.1431
Epoch [   29/   50] | d_loss: 1.5950 | g_loss: 2.5394
Epoch [   29/   50] | d_loss: 0.7399 | g_loss: 0.5918
Epoch [   29/   50] | d_loss: 0.2049 | g_loss: 3.6703
Epoch [   30/   50] | d_loss: 0.8369 | g_loss: 5.7745
Epoch [   30/   50] | d_loss: 0.1896 | g_loss: 3.9934
Epoch [   30/   50] | d_loss: 0.2266 | g_loss: 3.9252
Epoch [   30/   50] | d_loss: 0.2063 | g_loss: 3.5212
Epoch [   30/   50] | d_loss: 0.1980 | g_loss: 3.9120
Epoch [   30/   50] | d_loss: 0.1767 | g_loss: 3.4698
Epoch [   30/   50] | d_loss: 0.1918 | g_loss: 3.0264
Epoch [   30/   50] | d_loss: 0.1125 | g_loss: 3.3795
Epoch [   30/   50] | d_loss: 0.0960 | g_loss: 3.1559
Epoch [   30/   50] | d_loss: 0.0890 | g_loss: 3.5043
Epoch [   30/   50] | d_loss: 0.0790 | g_loss: 5.6941
Epoch [   30/   50] | d_loss: 0.4679 | g_loss: 4.8293
Epoch [   30/   50] | d_loss: 0.1495 | g_loss: 3.7103
Epoch [   30/   50] | d_loss: 0.0780 | g_loss: 4.3672
Epoch [   30/   50] | d_loss: 0.2388 | g_loss: 3.4370
Epoch [   30/   50] | d_loss: 0.1659 | g_loss: 3.6446
Epoch [   30/   50] | d_loss: 0.1073 | g_loss: 4.3440
Epoch [   30/   50] | d_loss: 0.3649 | g_loss: 3.5418
Epoch [   30/   50] | d_loss: 0.3101 | g_loss: 3.6664
Epoch [   30/   50] | d_loss: 0.1749 | g_loss: 3.5178
Epoch [   30/   50] | d_loss: 0.3532 | g_loss: 2.2596
Epoch [   30/   50] | d_loss: 0.2337 | g_loss: 3.1172
Epoch [   30/   50] | d_loss: 0.0857 | g_loss: 3.9781
Epoch [   30/   50] | d_loss: 0.3282 | g_loss: 3.0564
Epoch [   30/   50] | d_loss: 0.0903 | g_loss: 3.7714
Epoch [   30/   50] | d_loss: 0.1379 | g_loss: 3.8573
Epoch [   30/   50] | d_loss: 0.1461 | g_loss: 4.0902
Epoch [   30/   50] | d_loss: 4.5128 | g_loss: 0.0864
Epoch [   30/   50] | d_loss: 0.5365 | g_loss: 1.6275
Epoch [   31/   50] | d_loss: 0.5518 | g_loss: 3.6072
Epoch [   31/   50] | d_loss: 0.3794 | g_loss: 2.7146
Epoch [   31/   50] | d_loss: 0.2168 | g_loss: 3.0093
Epoch [   31/   50] | d_loss: 0.0732 | g_loss: 4.3410
Epoch [   31/   50] | d_loss: 0.1430 | g_loss: 3.8690
Epoch [   31/   50] | d_loss: 0.2702 | g_loss: 3.4587
Epoch [   31/   50] | d_loss: 0.1562 | g_loss: 3.9529
Epoch [   31/   50] | d_loss: 0.1270 | g_loss: 3.2695
Epoch [   31/   50] | d_loss: 0.1209 | g_loss: 4.8068
Epoch [   31/   50] | d_loss: 0.1675 | g_loss: 3.2134
Epoch [   31/   50] | d_loss: 0.1159 | g_loss: 3.7261
Epoch [   31/   50] | d_loss: 0.2213 | g_loss: 3.2473
Epoch [   31/   50] | d_loss: 0.0612 | g_loss: 3.5750
Epoch [   31/   50] | d_loss: 0.1325 | g_loss: 4.2732
Epoch [   31/   50] | d_loss: 0.1906 | g_loss: 4.5606
Epoch [   31/   50] | d_loss: 0.1581 | g_loss: 4.3732
Epoch [   31/   50] | d_loss: 0.6826 | g_loss: 2.5314
Epoch [   31/   50] | d_loss: 0.3155 | g_loss: 2.4046
Epoch [   31/   50] | d_loss: 0.4426 | g_loss: 2.4056
Epoch [   31/   50] | d_loss: 0.2174 | g_loss: 4.1280
Epoch [   31/   50] | d_loss: 0.1603 | g_loss: 4.2596
Epoch [   31/   50] | d_loss: 0.3241 | g_loss: 4.9577
Epoch [   31/   50] | d_loss: 0.1471 | g_loss: 3.8671
Epoch [   31/   50] | d_loss: 0.1493 | g_loss: 2.9250
Epoch [   31/   50] | d_loss: 0.1460 | g_loss: 4.4944
Epoch [   31/   50] | d_loss: 0.1052 | g_loss: 4.1205
Epoch [   31/   50] | d_loss: 0.1976 | g_loss: 2.4313
Epoch [   31/   50] | d_loss: 0.5462 | g_loss: 1.7965
Epoch [   31/   50] | d_loss: 0.1792 | g_loss: 3.7120
Epoch [   32/   50] | d_loss: 1.1208 | g_loss: 4.7535
Epoch [   32/   50] | d_loss: 0.1421 | g_loss: 3.6971
Epoch [   32/   50] | d_loss: 0.4034 | g_loss: 3.9978
Epoch [   32/   50] | d_loss: 0.1615 | g_loss: 4.7493
Epoch [   32/   50] | d_loss: 0.1682 | g_loss: 5.4970
Epoch [   32/   50] | d_loss: 0.1281 | g_loss: 3.7720
Epoch [   32/   50] | d_loss: 0.1397 | g_loss: 3.8557
Epoch [   32/   50] | d_loss: 0.1021 | g_loss: 5.1246
Epoch [   32/   50] | d_loss: 0.2245 | g_loss: 3.1084
Epoch [   32/   50] | d_loss: 0.1905 | g_loss: 2.9216
Epoch [   32/   50] | d_loss: 0.1891 | g_loss: 2.4471
Epoch [   32/   50] | d_loss: 2.8861 | g_loss: 5.0820
Epoch [   32/   50] | d_loss: 0.0725 | g_loss: 4.3307
Epoch [   32/   50] | d_loss: 0.4444 | g_loss: 1.9693
Epoch [   32/   50] | d_loss: 0.1875 | g_loss: 2.1530
Epoch [   32/   50] | d_loss: 0.2905 | g_loss: 4.0938
Epoch [   32/   50] | d_loss: 0.4244 | g_loss: 4.1185
Epoch [   32/   50] | d_loss: 0.1726 | g_loss: 3.7235
Epoch [   32/   50] | d_loss: 0.2372 | g_loss: 3.9680
Epoch [   32/   50] | d_loss: 0.1185 | g_loss: 3.6783
Epoch [   32/   50] | d_loss: 0.2588 | g_loss: 3.9457
Epoch [   32/   50] | d_loss: 0.1111 | g_loss: 3.7601
Epoch [   32/   50] | d_loss: 0.0907 | g_loss: 3.7909
Epoch [   32/   50] | d_loss: 0.2680 | g_loss: 3.3457
Epoch [   32/   50] | d_loss: 0.0800 | g_loss: 4.3091
Epoch [   32/   50] | d_loss: 0.1418 | g_loss: 4.2397
Epoch [   32/   50] | d_loss: 0.1304 | g_loss: 3.8700
Epoch [   32/   50] | d_loss: 0.0694 | g_loss: 5.6751
Epoch [   32/   50] | d_loss: 0.5056 | g_loss: 1.8459
Epoch [   33/   50] | d_loss: 0.7254 | g_loss: 3.1484
Epoch [   33/   50] | d_loss: 0.2048 | g_loss: 3.8749
Epoch [   33/   50] | d_loss: 2.0558 | g_loss: 2.4538
Epoch [   33/   50] | d_loss: 0.1442 | g_loss: 3.3416
Epoch [   33/   50] | d_loss: 0.1899 | g_loss: 4.0741
Epoch [   33/   50] | d_loss: 0.1346 | g_loss: 4.0803
Epoch [   33/   50] | d_loss: 0.1097 | g_loss: 4.0552
Epoch [   33/   50] | d_loss: 0.2695 | g_loss: 4.3185
Epoch [   33/   50] | d_loss: 0.1300 | g_loss: 2.5827
Epoch [   33/   50] | d_loss: 0.2013 | g_loss: 2.7485
Epoch [   33/   50] | d_loss: 0.0713 | g_loss: 4.5476
Epoch [   33/   50] | d_loss: 0.0995 | g_loss: 2.8264
Epoch [   33/   50] | d_loss: 0.1498 | g_loss: 3.6900
Epoch [   33/   50] | d_loss: 0.1680 | g_loss: 3.1260
Epoch [   33/   50] | d_loss: 0.1559 | g_loss: 4.0202
Epoch [   33/   50] | d_loss: 0.1059 | g_loss: 3.0804
Epoch [   33/   50] | d_loss: 0.1759 | g_loss: 3.0800
Epoch [   33/   50] | d_loss: 0.2070 | g_loss: 4.1970
Epoch [   33/   50] | d_loss: 5.8043 | g_loss: 0.1681
Epoch [   33/   50] | d_loss: 0.3044 | g_loss: 3.9118
Epoch [   33/   50] | d_loss: 0.1536 | g_loss: 4.0817
Epoch [   33/   50] | d_loss: 0.0859 | g_loss: 5.1472
Epoch [   33/   50] | d_loss: 0.1878 | g_loss: 4.1673
Epoch [   33/   50] | d_loss: 0.1069 | g_loss: 3.8845
Epoch [   33/   50] | d_loss: 0.2296 | g_loss: 3.1158
Epoch [   33/   50] | d_loss: 0.2279 | g_loss: 3.7392
Epoch [   33/   50] | d_loss: 0.2654 | g_loss: 3.1886
Epoch [   33/   50] | d_loss: 0.1506 | g_loss: 3.8293
Epoch [   33/   50] | d_loss: 0.0626 | g_loss: 4.3133
Epoch [   34/   50] | d_loss: 0.3774 | g_loss: 5.0740
Epoch [   34/   50] | d_loss: 0.2576 | g_loss: 3.4058
Epoch [   34/   50] | d_loss: 0.1405 | g_loss: 3.9492
Epoch [   34/   50] | d_loss: 0.1205 | g_loss: 3.3370
Epoch [   34/   50] | d_loss: 0.1280 | g_loss: 4.2791
Epoch [   34/   50] | d_loss: 0.1617 | g_loss: 4.0158
Epoch [   34/   50] | d_loss: 0.1553 | g_loss: 4.4720
Epoch [   34/   50] | d_loss: 0.2543 | g_loss: 3.3578
Epoch [   34/   50] | d_loss: 0.0749 | g_loss: 3.5853
Epoch [   34/   50] | d_loss: 0.1070 | g_loss: 3.9585
Epoch [   34/   50] | d_loss: 0.1009 | g_loss: 3.9403
Epoch [   34/   50] | d_loss: 0.1763 | g_loss: 3.4397
Epoch [   34/   50] | d_loss: 0.4041 | g_loss: 3.1800
Epoch [   34/   50] | d_loss: 0.1100 | g_loss: 3.7008
Epoch [   34/   50] | d_loss: 0.2691 | g_loss: 2.5745
Epoch [   34/   50] | d_loss: 0.1126 | g_loss: 4.4740
Epoch [   34/   50] | d_loss: 0.1084 | g_loss: 2.8314
Epoch [   34/   50] | d_loss: 0.0714 | g_loss: 4.1045
Epoch [   34/   50] | d_loss: 0.0727 | g_loss: 4.4260
Epoch [   34/   50] | d_loss: 0.1556 | g_loss: 4.3101
Epoch [   34/   50] | d_loss: 0.2839 | g_loss: 4.8603
Epoch [   34/   50] | d_loss: 3.2001 | g_loss: 0.1071
Epoch [   34/   50] | d_loss: 0.2261 | g_loss: 3.3611
Epoch [   34/   50] | d_loss: 0.1166 | g_loss: 4.5528
Epoch [   34/   50] | d_loss: 0.5216 | g_loss: 5.3005
Epoch [   34/   50] | d_loss: 0.0588 | g_loss: 4.7836
Epoch [   34/   50] | d_loss: 0.2595 | g_loss: 3.1120
Epoch [   34/   50] | d_loss: 0.0394 | g_loss: 5.9238
Epoch [   34/   50] | d_loss: 0.1051 | g_loss: 3.7351
Epoch [   35/   50] | d_loss: 3.3620 | g_loss: 5.3040
Epoch [   35/   50] | d_loss: 0.1178 | g_loss: 5.0375
Epoch [   35/   50] | d_loss: 0.1944 | g_loss: 3.6706
Epoch [   35/   50] | d_loss: 0.1335 | g_loss: 3.9466
Epoch [   35/   50] | d_loss: 0.1321 | g_loss: 5.3051
Epoch [   35/   50] | d_loss: 0.1431 | g_loss: 5.0263
Epoch [   35/   50] | d_loss: 0.1150 | g_loss: 4.4349
Epoch [   35/   50] | d_loss: 0.1288 | g_loss: 4.4967
Epoch [   35/   50] | d_loss: 0.0881 | g_loss: 2.9270
Epoch [   35/   50] | d_loss: 0.1358 | g_loss: 3.9462
Epoch [   35/   50] | d_loss: 0.8454 | g_loss: 1.7790
Epoch [   35/   50] | d_loss: 0.6659 | g_loss: 2.7370
Epoch [   35/   50] | d_loss: 0.2990 | g_loss: 3.2909
Epoch [   35/   50] | d_loss: 0.0644 | g_loss: 3.6973
Epoch [   35/   50] | d_loss: 0.1311 | g_loss: 2.0411
Epoch [   35/   50] | d_loss: 0.1515 | g_loss: 3.9375
Epoch [   35/   50] | d_loss: 0.1769 | g_loss: 5.0672
Epoch [   35/   50] | d_loss: 0.1243 | g_loss: 3.1454
Epoch [   35/   50] | d_loss: 0.1474 | g_loss: 3.7494
Epoch [   35/   50] | d_loss: 0.2099 | g_loss: 4.2877
Epoch [   35/   50] | d_loss: 0.1694 | g_loss: 4.7716
Epoch [   35/   50] | d_loss: 0.3571 | g_loss: 2.2721
Epoch [   35/   50] | d_loss: 0.0739 | g_loss: 4.1145
Epoch [   35/   50] | d_loss: 0.0934 | g_loss: 4.0992
Epoch [   35/   50] | d_loss: 0.1564 | g_loss: 4.4880
Epoch [   35/   50] | d_loss: 0.1292 | g_loss: 4.0271
Epoch [   35/   50] | d_loss: 0.2323 | g_loss: 5.0700
Epoch [   35/   50] | d_loss: 0.1167 | g_loss: 3.3250
Epoch [   35/   50] | d_loss: 0.1187 | g_loss: 4.2220
Epoch [   36/   50] | d_loss: 0.0568 | g_loss: 3.2954
Epoch [   36/   50] | d_loss: 0.8067 | g_loss: 3.1532
Epoch [   36/   50] | d_loss: 0.3492 | g_loss: 2.6962
Epoch [   36/   50] | d_loss: 0.1664 | g_loss: 3.2215
Epoch [   36/   50] | d_loss: 0.2089 | g_loss: 2.8341
Epoch [   36/   50] | d_loss: 0.7823 | g_loss: 5.7399
Epoch [   36/   50] | d_loss: 0.0789 | g_loss: 4.2651
Epoch [   36/   50] | d_loss: 0.0568 | g_loss: 3.8339
Epoch [   36/   50] | d_loss: 0.1182 | g_loss: 3.5886
Epoch [   36/   50] | d_loss: 0.1171 | g_loss: 4.3936
Epoch [   36/   50] | d_loss: 0.1454 | g_loss: 3.8496
Epoch [   36/   50] | d_loss: 0.0617 | g_loss: 3.3366
Epoch [   36/   50] | d_loss: 0.1451 | g_loss: 4.2671
Epoch [   36/   50] | d_loss: 0.1659 | g_loss: 2.3871
Epoch [   36/   50] | d_loss: 0.1315 | g_loss: 3.1265
Epoch [   36/   50] | d_loss: 0.1042 | g_loss: 4.0606
Epoch [   36/   50] | d_loss: 0.1547 | g_loss: 4.2729
Epoch [   36/   50] | d_loss: 0.1188 | g_loss: 4.5346
Epoch [   36/   50] | d_loss: 1.4770 | g_loss: 6.3819
Epoch [   36/   50] | d_loss: 0.3068 | g_loss: 4.0981
Epoch [   36/   50] | d_loss: 0.2268 | g_loss: 3.0341
Epoch [   36/   50] | d_loss: 0.9610 | g_loss: 2.2924
Epoch [   36/   50] | d_loss: 0.1425 | g_loss: 2.8674
Epoch [   36/   50] | d_loss: 0.1151 | g_loss: 4.1260
Epoch [   36/   50] | d_loss: 0.2394 | g_loss: 3.0422
Epoch [   36/   50] | d_loss: 0.1039 | g_loss: 3.2440
Epoch [   36/   50] | d_loss: 0.0818 | g_loss: 4.6907
Epoch [   36/   50] | d_loss: 0.1351 | g_loss: 3.5825
Epoch [   36/   50] | d_loss: 0.1510 | g_loss: 3.6596
Epoch [   37/   50] | d_loss: 0.1702 | g_loss: 4.4806
Epoch [   37/   50] | d_loss: 0.1567 | g_loss: 3.3258
Epoch [   37/   50] | d_loss: 0.1887 | g_loss: 3.9223
Epoch [   37/   50] | d_loss: 0.1441 | g_loss: 3.2914
Epoch [   37/   50] | d_loss: 0.4097 | g_loss: 1.6116
Epoch [   37/   50] | d_loss: 0.3393 | g_loss: 3.7654
Epoch [   37/   50] | d_loss: 0.3001 | g_loss: 3.6413
Epoch [   37/   50] | d_loss: 0.1431 | g_loss: 4.2021
Epoch [   37/   50] | d_loss: 0.1108 | g_loss: 3.4636
Epoch [   37/   50] | d_loss: 0.1154 | g_loss: 3.5602
Epoch [   37/   50] | d_loss: 0.2230 | g_loss: 3.5416
Epoch [   37/   50] | d_loss: 0.1286 | g_loss: 5.0677
Epoch [   37/   50] | d_loss: 0.0798 | g_loss: 4.6251
Epoch [   37/   50] | d_loss: 0.1263 | g_loss: 3.8188
Epoch [   37/   50] | d_loss: 0.1753 | g_loss: 4.2476
Epoch [   37/   50] | d_loss: 0.1178 | g_loss: 4.3008
Epoch [   37/   50] | d_loss: 0.0982 | g_loss: 5.2994
Epoch [   37/   50] | d_loss: 0.2820 | g_loss: 3.0822
Epoch [   37/   50] | d_loss: 1.4516 | g_loss: 5.9054
Epoch [   37/   50] | d_loss: 0.3008 | g_loss: 3.0802
Epoch [   37/   50] | d_loss: 0.1395 | g_loss: 4.4319
Epoch [   37/   50] | d_loss: 0.1077 | g_loss: 3.7256
Epoch [   37/   50] | d_loss: 0.0963 | g_loss: 4.3900
Epoch [   37/   50] | d_loss: 0.1182 | g_loss: 4.1891
Epoch [   37/   50] | d_loss: 0.3591 | g_loss: 1.7159
Epoch [   37/   50] | d_loss: 0.1619 | g_loss: 4.1855
Epoch [   37/   50] | d_loss: 0.1647 | g_loss: 3.9770
Epoch [   37/   50] | d_loss: 0.2610 | g_loss: 3.4725
Epoch [   37/   50] | d_loss: 0.3724 | g_loss: 3.2975
Epoch [   38/   50] | d_loss: 0.4029 | g_loss: 5.9293
Epoch [   38/   50] | d_loss: 0.0429 | g_loss: 4.6072
Epoch [   38/   50] | d_loss: 0.0783 | g_loss: 4.4956
Epoch [   38/   50] | d_loss: 0.0994 | g_loss: 4.6375
Epoch [   38/   50] | d_loss: 0.1528 | g_loss: 4.0255
Epoch [   38/   50] | d_loss: 0.1071 | g_loss: 3.3212
Epoch [   38/   50] | d_loss: 0.1647 | g_loss: 4.1217
Epoch [   38/   50] | d_loss: 0.8656 | g_loss: 1.9046
Epoch [   38/   50] | d_loss: 0.1036 | g_loss: 4.4557
Epoch [   38/   50] | d_loss: 0.0998 | g_loss: 4.0970
Epoch [   38/   50] | d_loss: 0.0775 | g_loss: 4.4741
Epoch [   38/   50] | d_loss: 0.1293 | g_loss: 3.9774
Epoch [   38/   50] | d_loss: 0.1159 | g_loss: 4.5240
Epoch [   38/   50] | d_loss: 0.0927 | g_loss: 4.3063
Epoch [   38/   50] | d_loss: 0.0915 | g_loss: 4.4994
Epoch [   38/   50] | d_loss: 5.7177 | g_loss: 7.7247
Epoch [   38/   50] | d_loss: 0.3223 | g_loss: 3.8752
Epoch [   38/   50] | d_loss: 0.4418 | g_loss: 3.9713
Epoch [   38/   50] | d_loss: 0.6572 | g_loss: 0.3106
Epoch [   38/   50] | d_loss: 0.1853 | g_loss: 3.9179
Epoch [   38/   50] | d_loss: 0.1789 | g_loss: 4.0372
Epoch [   38/   50] | d_loss: 0.1036 | g_loss: 4.1620
Epoch [   38/   50] | d_loss: 0.1188 | g_loss: 3.8351
Epoch [   38/   50] | d_loss: 0.1408 | g_loss: 3.7018
Epoch [   38/   50] | d_loss: 0.1295 | g_loss: 5.0912
Epoch [   38/   50] | d_loss: 0.0784 | g_loss: 3.6574
Epoch [   38/   50] | d_loss: 0.3020 | g_loss: 2.2678
Epoch [   38/   50] | d_loss: 0.1122 | g_loss: 4.3915
Epoch [   38/   50] | d_loss: 0.5623 | g_loss: 6.0136
Epoch [   39/   50] | d_loss: 1.1749 | g_loss: 4.5393
Epoch [   39/   50] | d_loss: 0.1922 | g_loss: 3.0920
Epoch [   39/   50] | d_loss: 0.3642 | g_loss: 2.0506
Epoch [   39/   50] | d_loss: 0.1173 | g_loss: 3.3903
Epoch [   39/   50] | d_loss: 0.1679 | g_loss: 4.4261
Epoch [   39/   50] | d_loss: 0.4195 | g_loss: 1.7917
Epoch [   39/   50] | d_loss: 0.0867 | g_loss: 3.7745
Epoch [   39/   50] | d_loss: 0.0825 | g_loss: 3.9601
Epoch [   39/   50] | d_loss: 0.1264 | g_loss: 5.9830
Epoch [   39/   50] | d_loss: 0.0821 | g_loss: 4.2037
Epoch [   39/   50] | d_loss: 0.0850 | g_loss: 4.1294
Epoch [   39/   50] | d_loss: 0.1177 | g_loss: 3.1792
Epoch [   39/   50] | d_loss: 0.0774 | g_loss: 4.3840
Epoch [   39/   50] | d_loss: 0.2151 | g_loss: 2.1477
Epoch [   39/   50] | d_loss: 0.0945 | g_loss: 5.5267
Epoch [   39/   50] | d_loss: 0.0757 | g_loss: 4.7358
Epoch [   39/   50] | d_loss: 0.1239 | g_loss: 3.6436
Epoch [   39/   50] | d_loss: 0.2974 | g_loss: 4.3452
Epoch [   39/   50] | d_loss: 0.4028 | g_loss: 3.9694
Epoch [   39/   50] | d_loss: 0.3411 | g_loss: 2.0375
Epoch [   39/   50] | d_loss: 0.0910 | g_loss: 3.6835
Epoch [   39/   50] | d_loss: 0.1120 | g_loss: 4.5253
Epoch [   39/   50] | d_loss: 0.0923 | g_loss: 4.2558
Epoch [   39/   50] | d_loss: 0.1201 | g_loss: 5.1906
Epoch [   39/   50] | d_loss: 0.1228 | g_loss: 3.9840
Epoch [   39/   50] | d_loss: 0.2312 | g_loss: 2.8331
Epoch [   39/   50] | d_loss: 0.0727 | g_loss: 4.7705
Epoch [   39/   50] | d_loss: 0.0933 | g_loss: 5.3792
Epoch [   39/   50] | d_loss: 0.2617 | g_loss: 6.2107
Epoch [   40/   50] | d_loss: 0.1479 | g_loss: 3.4635
Epoch [   40/   50] | d_loss: 0.1388 | g_loss: 4.3800
Epoch [   40/   50] | d_loss: 0.1277 | g_loss: 3.6925
Epoch [   40/   50] | d_loss: 0.0643 | g_loss: 3.8233
Epoch [   40/   50] | d_loss: 1.3891 | g_loss: 3.6209
Epoch [   40/   50] | d_loss: 0.7455 | g_loss: 3.4261
Epoch [   40/   50] | d_loss: 0.2280 | g_loss: 4.4065
Epoch [   40/   50] | d_loss: 0.1268 | g_loss: 3.7944
Epoch [   40/   50] | d_loss: 0.2278 | g_loss: 4.1580
Epoch [   40/   50] | d_loss: 0.1153 | g_loss: 4.1524
Epoch [   40/   50] | d_loss: 0.0840 | g_loss: 4.4660
Epoch [   40/   50] | d_loss: 0.1968 | g_loss: 4.7426
Epoch [   40/   50] | d_loss: 0.0829 | g_loss: 4.7641
Epoch [   40/   50] | d_loss: 0.2679 | g_loss: 4.2485
Epoch [   40/   50] | d_loss: 0.2144 | g_loss: 2.6208
Epoch [   40/   50] | d_loss: 0.0987 | g_loss: 4.1465
Epoch [   40/   50] | d_loss: 0.1614 | g_loss: 4.1576
Epoch [   40/   50] | d_loss: 0.0381 | g_loss: 2.5070
Epoch [   40/   50] | d_loss: 1.1601 | g_loss: 7.8991
Epoch [   40/   50] | d_loss: 0.5003 | g_loss: 5.0378
Epoch [   40/   50] | d_loss: 0.1593 | g_loss: 5.0566
Epoch [   40/   50] | d_loss: 0.1415 | g_loss: 3.6497
Epoch [   40/   50] | d_loss: 0.0869 | g_loss: 4.4531
Epoch [   40/   50] | d_loss: 0.1067 | g_loss: 4.3807
Epoch [   40/   50] | d_loss: 0.1345 | g_loss: 4.3183
Epoch [   40/   50] | d_loss: 0.3166 | g_loss: 3.6180
Epoch [   40/   50] | d_loss: 0.0713 | g_loss: 4.6913
Epoch [   40/   50] | d_loss: 0.0806 | g_loss: 3.4991
Epoch [   40/   50] | d_loss: 0.0709 | g_loss: 4.7657
Epoch [   41/   50] | d_loss: 0.0754 | g_loss: 5.6380
Epoch [   41/   50] | d_loss: 0.1596 | g_loss: 5.4991
Epoch [   41/   50] | d_loss: 0.0984 | g_loss: 4.6434
Epoch [   41/   50] | d_loss: 0.0806 | g_loss: 4.3032
Epoch [   41/   50] | d_loss: 0.1546 | g_loss: 4.1394
Epoch [   41/   50] | d_loss: 0.2501 | g_loss: 5.4649
Epoch [   41/   50] | d_loss: 0.1237 | g_loss: 4.7271
Epoch [   41/   50] | d_loss: 0.0749 | g_loss: 5.0679
Epoch [   41/   50] | d_loss: 0.1103 | g_loss: 6.5772
Epoch [   41/   50] | d_loss: 0.1319 | g_loss: 3.8918
Epoch [   41/   50] | d_loss: 0.1221 | g_loss: 3.5850
Epoch [   41/   50] | d_loss: 0.6375 | g_loss: 3.7728
Epoch [   41/   50] | d_loss: 0.2983 | g_loss: 3.8870
Epoch [   41/   50] | d_loss: 0.1762 | g_loss: 4.2250
Epoch [   41/   50] | d_loss: 0.1030 | g_loss: 4.5922
Epoch [   41/   50] | d_loss: 0.2763 | g_loss: 3.0362
Epoch [   41/   50] | d_loss: 0.1881 | g_loss: 2.9717
Epoch [   41/   50] | d_loss: 0.0606 | g_loss: 4.6928
Epoch [   41/   50] | d_loss: 0.1254 | g_loss: 3.5869
Epoch [   41/   50] | d_loss: 0.1714 | g_loss: 2.2193
Epoch [   41/   50] | d_loss: 0.1123 | g_loss: 3.8777
Epoch [   41/   50] | d_loss: 0.1084 | g_loss: 3.4990
Epoch [   41/   50] | d_loss: 0.1173 | g_loss: 5.4345
Epoch [   41/   50] | d_loss: 0.1822 | g_loss: 3.3649
Epoch [   41/   50] | d_loss: 0.0910 | g_loss: 4.2909
Epoch [   41/   50] | d_loss: 0.2980 | g_loss: 2.3455
Epoch [   41/   50] | d_loss: 0.4722 | g_loss: 1.7285
Epoch [   41/   50] | d_loss: 0.2220 | g_loss: 4.5383
Epoch [   41/   50] | d_loss: 0.0932 | g_loss: 4.0199
Epoch [   42/   50] | d_loss: 0.2213 | g_loss: 4.8365
Epoch [   42/   50] | d_loss: 0.1020 | g_loss: 4.7816
Epoch [   42/   50] | d_loss: 0.0808 | g_loss: 4.3321
Epoch [   42/   50] | d_loss: 0.1103 | g_loss: 4.4729
Epoch [   42/   50] | d_loss: 0.1527 | g_loss: 3.8369
Epoch [   42/   50] | d_loss: 0.1856 | g_loss: 4.6624
Epoch [   42/   50] | d_loss: 1.0765 | g_loss: 0.8799
Epoch [   42/   50] | d_loss: 0.1669 | g_loss: 4.3851
Epoch [   42/   50] | d_loss: 0.1045 | g_loss: 4.4395
Epoch [   42/   50] | d_loss: 0.1035 | g_loss: 4.6131
Epoch [   42/   50] | d_loss: 0.1618 | g_loss: 4.3945
Epoch [   42/   50] | d_loss: 1.1068 | g_loss: 3.0112
Epoch [   42/   50] | d_loss: 0.3055 | g_loss: 2.5686
Epoch [   42/   50] | d_loss: 0.1480 | g_loss: 4.0801
Epoch [   42/   50] | d_loss: 0.1451 | g_loss: 4.9782
Epoch [   42/   50] | d_loss: 0.0746 | g_loss: 4.2523
Epoch [   42/   50] | d_loss: 0.2339 | g_loss: 2.6433
Epoch [   42/   50] | d_loss: 0.0865 | g_loss: 4.1840
Epoch [   42/   50] | d_loss: 0.0693 | g_loss: 3.8409
Epoch [   42/   50] | d_loss: 0.1296 | g_loss: 4.0492
Epoch [   42/   50] | d_loss: 0.0665 | g_loss: 3.3414
Epoch [   42/   50] | d_loss: 0.0535 | g_loss: 5.1437
Epoch [   42/   50] | d_loss: 0.0476 | g_loss: 5.0452
Epoch [   42/   50] | d_loss: 0.1537 | g_loss: 4.0004
Epoch [   42/   50] | d_loss: 0.0530 | g_loss: 4.9425
Epoch [   42/   50] | d_loss: 0.1193 | g_loss: 4.2655
Epoch [   42/   50] | d_loss: 0.7154 | g_loss: 7.7167
Epoch [   42/   50] | d_loss: 0.1649 | g_loss: 5.1361
Epoch [   42/   50] | d_loss: 0.0802 | g_loss: 5.2339
Epoch [   43/   50] | d_loss: 0.0903 | g_loss: 3.7953
Epoch [   43/   50] | d_loss: 0.8330 | g_loss: 1.1899
Epoch [   43/   50] | d_loss: 0.1759 | g_loss: 3.2150
Epoch [   43/   50] | d_loss: 0.0702 | g_loss: 5.1486
Epoch [   43/   50] | d_loss: 0.1140 | g_loss: 4.3190
Epoch [   43/   50] | d_loss: 0.0945 | g_loss: 3.8527
Epoch [   43/   50] | d_loss: 0.1330 | g_loss: 4.5230
Epoch [   43/   50] | d_loss: 0.0897 | g_loss: 3.6691
Epoch [   43/   50] | d_loss: 0.1655 | g_loss: 4.2065
Epoch [   43/   50] | d_loss: 0.0717 | g_loss: 5.3244
Epoch [   43/   50] | d_loss: 0.0393 | g_loss: 4.1786
Epoch [   43/   50] | d_loss: 0.1479 | g_loss: 6.0158
Epoch [   43/   50] | d_loss: 0.1084 | g_loss: 6.0116
Epoch [   43/   50] | d_loss: 0.0875 | g_loss: 4.4864
Epoch [   43/   50] | d_loss: 0.1235 | g_loss: 4.1038
Epoch [   43/   50] | d_loss: 0.1010 | g_loss: 4.1151
Epoch [   43/   50] | d_loss: 0.0497 | g_loss: 5.0445
Epoch [   43/   50] | d_loss: 0.1081 | g_loss: 4.3859
Epoch [   43/   50] | d_loss: 1.2384 | g_loss: 3.8418
Epoch [   43/   50] | d_loss: 0.2801 | g_loss: 4.2661
Epoch [   43/   50] | d_loss: 0.1117 | g_loss: 4.0626
Epoch [   43/   50] | d_loss: 0.1867 | g_loss: 3.7572
Epoch [   43/   50] | d_loss: 0.1128 | g_loss: 3.7450
Epoch [   43/   50] | d_loss: 0.0570 | g_loss: 4.8557
Epoch [   43/   50] | d_loss: 0.2060 | g_loss: 5.6561
Epoch [   43/   50] | d_loss: 0.0948 | g_loss: 3.2095
Epoch [   43/   50] | d_loss: 0.1083 | g_loss: 4.8037
Epoch [   43/   50] | d_loss: 0.0597 | g_loss: 3.3752
Epoch [   43/   50] | d_loss: 0.3616 | g_loss: 5.6284
Epoch [   44/   50] | d_loss: 0.2644 | g_loss: 4.6966
Epoch [   44/   50] | d_loss: 0.0820 | g_loss: 3.6488
Epoch [   44/   50] | d_loss: 0.0701 | g_loss: 3.7143
Epoch [   44/   50] | d_loss: 0.2609 | g_loss: 3.9694
Epoch [   44/   50] | d_loss: 0.1751 | g_loss: 3.6588
Epoch [   44/   50] | d_loss: 0.2778 | g_loss: 4.1256
Epoch [   44/   50] | d_loss: 0.1582 | g_loss: 3.6287
Epoch [   44/   50] | d_loss: 0.1408 | g_loss: 4.4637
Epoch [   44/   50] | d_loss: 0.0982 | g_loss: 4.4199
Epoch [   44/   50] | d_loss: 0.1441 | g_loss: 3.4842
Epoch [   44/   50] | d_loss: 0.1119 | g_loss: 4.5765
Epoch [   44/   50] | d_loss: 0.0814 | g_loss: 3.6361
Epoch [   44/   50] | d_loss: 0.1525 | g_loss: 4.1501
Epoch [   44/   50] | d_loss: 0.0292 | g_loss: 5.1175
Epoch [   44/   50] | d_loss: 0.2586 | g_loss: 4.3476
Epoch [   44/   50] | d_loss: 0.1372 | g_loss: 3.3186
Epoch [   44/   50] | d_loss: 0.1359 | g_loss: 4.3126
Epoch [   44/   50] | d_loss: 0.0647 | g_loss: 5.1822
Epoch [   44/   50] | d_loss: 0.0841 | g_loss: 4.3596
Epoch [   44/   50] | d_loss: 0.0411 | g_loss: 6.4373
Epoch [   44/   50] | d_loss: 0.0294 | g_loss: 5.2820
Epoch [   44/   50] | d_loss: 0.0922 | g_loss: 3.5050
Epoch [   44/   50] | d_loss: 0.5293 | g_loss: 2.2601
Epoch [   44/   50] | d_loss: 0.1538 | g_loss: 2.6152
Epoch [   44/   50] | d_loss: 0.1211 | g_loss: 3.7420
Epoch [   44/   50] | d_loss: 0.1616 | g_loss: 4.0436
Epoch [   44/   50] | d_loss: 0.2210 | g_loss: 3.2498
Epoch [   44/   50] | d_loss: 0.0808 | g_loss: 4.2692
Epoch [   44/   50] | d_loss: 0.0576 | g_loss: 4.2033
Epoch [   45/   50] | d_loss: 0.0685 | g_loss: 4.4872
Epoch [   45/   50] | d_loss: 0.1454 | g_loss: 3.9466
Epoch [   45/   50] | d_loss: 0.0659 | g_loss: 5.3875
Epoch [   45/   50] | d_loss: 0.2626 | g_loss: 3.7716
Epoch [   45/   50] | d_loss: 0.0752 | g_loss: 3.7872
Epoch [   45/   50] | d_loss: 0.1965 | g_loss: 3.3091
Epoch [   45/   50] | d_loss: 0.1336 | g_loss: 5.3160
Epoch [   45/   50] | d_loss: 0.0699 | g_loss: 3.6015
Epoch [   45/   50] | d_loss: 0.1873 | g_loss: 1.8803
Epoch [   45/   50] | d_loss: 0.0752 | g_loss: 4.0390
Epoch [   45/   50] | d_loss: 0.1222 | g_loss: 4.4230
Epoch [   45/   50] | d_loss: 0.0888 | g_loss: 5.4127
Epoch [   45/   50] | d_loss: 1.3588 | g_loss: 0.5972
Epoch [   45/   50] | d_loss: 0.3029 | g_loss: 3.5264
Epoch [   45/   50] | d_loss: 0.0826 | g_loss: 3.5214
Epoch [   45/   50] | d_loss: 0.1836 | g_loss: 4.2044
Epoch [   45/   50] | d_loss: 0.0360 | g_loss: 4.0462
Epoch [   45/   50] | d_loss: 0.0646 | g_loss: 4.7615
Epoch [   45/   50] | d_loss: 0.1810 | g_loss: 3.7954
Epoch [   45/   50] | d_loss: 0.0885 | g_loss: 4.5897
Epoch [   45/   50] | d_loss: 0.0338 | g_loss: 4.2292
Epoch [   45/   50] | d_loss: 0.1896 | g_loss: 2.9545
Epoch [   45/   50] | d_loss: 0.1290 | g_loss: 4.8492
Epoch [   45/   50] | d_loss: 0.1756 | g_loss: 3.1820
Epoch [   45/   50] | d_loss: 0.0841 | g_loss: 5.4079
Epoch [   45/   50] | d_loss: 0.4822 | g_loss: 3.4079
Epoch [   45/   50] | d_loss: 0.7611 | g_loss: 3.4461
Epoch [   45/   50] | d_loss: 0.1178 | g_loss: 4.5050
Epoch [   45/   50] | d_loss: 0.1308 | g_loss: 4.1557
Epoch [   46/   50] | d_loss: 0.0681 | g_loss: 4.6355
Epoch [   46/   50] | d_loss: 0.0577 | g_loss: 4.4700
Epoch [   46/   50] | d_loss: 0.0575 | g_loss: 3.9994
Epoch [   46/   50] | d_loss: 0.0899 | g_loss: 4.3491
Epoch [   46/   50] | d_loss: 0.0999 | g_loss: 4.4966
Epoch [   46/   50] | d_loss: 0.1763 | g_loss: 3.5720
Epoch [   46/   50] | d_loss: 0.1015 | g_loss: 4.4649
Epoch [   46/   50] | d_loss: 0.1496 | g_loss: 4.3827
Epoch [   46/   50] | d_loss: 0.0464 | g_loss: 4.2196
Epoch [   46/   50] | d_loss: 0.1169 | g_loss: 4.0196
Epoch [   46/   50] | d_loss: 0.0901 | g_loss: 3.8211
Epoch [   46/   50] | d_loss: 1.1188 | g_loss: 6.1235
Epoch [   46/   50] | d_loss: 0.2352 | g_loss: 5.2655
Epoch [   46/   50] | d_loss: 0.2427 | g_loss: 3.6442
Epoch [   46/   50] | d_loss: 0.0581 | g_loss: 4.2736
Epoch [   46/   50] | d_loss: 0.0966 | g_loss: 4.9750
Epoch [   46/   50] | d_loss: 0.1402 | g_loss: 5.1091
Epoch [   46/   50] | d_loss: 0.1463 | g_loss: 4.3344
Epoch [   46/   50] | d_loss: 0.0903 | g_loss: 4.6002
Epoch [   46/   50] | d_loss: 0.0799 | g_loss: 4.5543
Epoch [   46/   50] | d_loss: 0.1388 | g_loss: 4.6572
Epoch [   46/   50] | d_loss: 0.0717 | g_loss: 4.6613
Epoch [   46/   50] | d_loss: 0.0998 | g_loss: 5.1562
Epoch [   46/   50] | d_loss: 0.1959 | g_loss: 5.5698
Epoch [   46/   50] | d_loss: 0.0544 | g_loss: 3.9535
Epoch [   46/   50] | d_loss: 0.0668 | g_loss: 4.9874
Epoch [   46/   50] | d_loss: 0.0853 | g_loss: 3.4357
Epoch [   46/   50] | d_loss: 2.9050 | g_loss: 4.2922
Epoch [   46/   50] | d_loss: 0.2764 | g_loss: 3.3983
Epoch [   47/   50] | d_loss: 0.5277 | g_loss: 3.2999
Epoch [   47/   50] | d_loss: 0.1357 | g_loss: 4.9281
Epoch [   47/   50] | d_loss: 0.1870 | g_loss: 4.6110
Epoch [   47/   50] | d_loss: 0.1076 | g_loss: 4.6527
Epoch [   47/   50] | d_loss: 0.0706 | g_loss: 4.2627
Epoch [   47/   50] | d_loss: 0.1513 | g_loss: 3.7149
Epoch [   47/   50] | d_loss: 0.1110 | g_loss: 4.9349
Epoch [   47/   50] | d_loss: 0.0745 | g_loss: 2.9642
Epoch [   47/   50] | d_loss: 0.1384 | g_loss: 4.2184
Epoch [   47/   50] | d_loss: 0.0960 | g_loss: 3.4239
Epoch [   47/   50] | d_loss: 0.1333 | g_loss: 3.1674
Epoch [   47/   50] | d_loss: 0.1913 | g_loss: 3.8142
Epoch [   47/   50] | d_loss: 0.1526 | g_loss: 3.6809
Epoch [   47/   50] | d_loss: 0.0721 | g_loss: 5.3092
Epoch [   47/   50] | d_loss: 0.5730 | g_loss: 6.6690
Epoch [   47/   50] | d_loss: 0.1882 | g_loss: 2.2736
Epoch [   47/   50] | d_loss: 0.1620 | g_loss: 4.6395
Epoch [   47/   50] | d_loss: 0.3428 | g_loss: 4.3533
Epoch [   47/   50] | d_loss: 0.2789 | g_loss: 2.4139
Epoch [   47/   50] | d_loss: 0.1212 | g_loss: 6.3169
Epoch [   47/   50] | d_loss: 0.1959 | g_loss: 4.7311
Epoch [   47/   50] | d_loss: 0.0422 | g_loss: 5.1659
Epoch [   47/   50] | d_loss: 0.0664 | g_loss: 4.3943
Epoch [   47/   50] | d_loss: 0.0745 | g_loss: 4.1903
Epoch [   47/   50] | d_loss: 0.4749 | g_loss: 5.7317
Epoch [   47/   50] | d_loss: 0.0688 | g_loss: 5.2100
Epoch [   47/   50] | d_loss: 0.0780 | g_loss: 3.5651
Epoch [   47/   50] | d_loss: 0.0363 | g_loss: 5.0803
Epoch [   47/   50] | d_loss: 0.0988 | g_loss: 4.4375
Epoch [   48/   50] | d_loss: 0.3355 | g_loss: 6.7253
Epoch [   48/   50] | d_loss: 0.1475 | g_loss: 3.6661
Epoch [   48/   50] | d_loss: 0.0613 | g_loss: 3.8503
Epoch [   48/   50] | d_loss: 0.0851 | g_loss: 3.8505
Epoch [   48/   50] | d_loss: 0.0733 | g_loss: 4.6413
Epoch [   48/   50] | d_loss: 0.0655 | g_loss: 3.9879
Epoch [   48/   50] | d_loss: 0.0675 | g_loss: 4.3206
Epoch [   48/   50] | d_loss: 1.3020 | g_loss: 1.5231
Epoch [   48/   50] | d_loss: 0.2245 | g_loss: 3.9649
Epoch [   48/   50] | d_loss: 0.0933 | g_loss: 3.0418
Epoch [   48/   50] | d_loss: 0.3562 | g_loss: 2.2587
Epoch [   48/   50] | d_loss: 0.2548 | g_loss: 4.2278
Epoch [   48/   50] | d_loss: 0.1879 | g_loss: 4.6772
Epoch [   48/   50] | d_loss: 0.0409 | g_loss: 5.6489
Epoch [   48/   50] | d_loss: 0.1305 | g_loss: 3.1933
Epoch [   48/   50] | d_loss: 0.0701 | g_loss: 4.5130
Epoch [   48/   50] | d_loss: 0.0698 | g_loss: 6.1310
Epoch [   48/   50] | d_loss: 0.1334 | g_loss: 5.2819
Epoch [   48/   50] | d_loss: 0.0799 | g_loss: 4.2066
Epoch [   48/   50] | d_loss: 0.0717 | g_loss: 5.1338
Epoch [   48/   50] | d_loss: 0.1512 | g_loss: 5.0013
Epoch [   48/   50] | d_loss: 0.0373 | g_loss: 6.9149
Epoch [   48/   50] | d_loss: 0.0766 | g_loss: 3.8491
Epoch [   48/   50] | d_loss: 0.2738 | g_loss: 4.6834
Epoch [   48/   50] | d_loss: 0.4985 | g_loss: 6.4132
Epoch [   48/   50] | d_loss: 0.0798 | g_loss: 5.7779
Epoch [   48/   50] | d_loss: 0.0930 | g_loss: 4.4151
Epoch [   48/   50] | d_loss: 0.2382 | g_loss: 4.3179
Epoch [   48/   50] | d_loss: 0.0533 | g_loss: 5.1958
Epoch [   49/   50] | d_loss: 0.9544 | g_loss: 7.4562
Epoch [   49/   50] | d_loss: 0.1753 | g_loss: 3.2155
Epoch [   49/   50] | d_loss: 0.1875 | g_loss: 4.3462
Epoch [   49/   50] | d_loss: 0.1391 | g_loss: 4.4478
Epoch [   49/   50] | d_loss: 0.1012 | g_loss: 3.4626
Epoch [   49/   50] | d_loss: 0.3435 | g_loss: 3.8632
Epoch [   49/   50] | d_loss: 0.1372 | g_loss: 5.9410
Epoch [   49/   50] | d_loss: 0.1491 | g_loss: 4.2807
Epoch [   49/   50] | d_loss: 0.8471 | g_loss: 7.1810
Epoch [   49/   50] | d_loss: 0.8378 | g_loss: 2.0506
Epoch [   49/   50] | d_loss: 0.2087 | g_loss: 3.5548
Epoch [   49/   50] | d_loss: 0.1716 | g_loss: 4.5572
Epoch [   49/   50] | d_loss: 0.1107 | g_loss: 2.6330
Epoch [   49/   50] | d_loss: 0.0440 | g_loss: 5.5762
Epoch [   49/   50] | d_loss: 0.1217 | g_loss: 3.6759
Epoch [   49/   50] | d_loss: 0.0670 | g_loss: 5.0191
Epoch [   49/   50] | d_loss: 0.1067 | g_loss: 3.9131
Epoch [   49/   50] | d_loss: 0.0588 | g_loss: 3.8135
Epoch [   49/   50] | d_loss: 0.1041 | g_loss: 3.9281
Epoch [   49/   50] | d_loss: 0.0913 | g_loss: 4.8812
Epoch [   49/   50] | d_loss: 0.0896 | g_loss: 4.7989
Epoch [   49/   50] | d_loss: 0.0491 | g_loss: 4.4067
Epoch [   49/   50] | d_loss: 0.0336 | g_loss: 5.3123
Epoch [   49/   50] | d_loss: 0.0825 | g_loss: 3.7903
Epoch [   49/   50] | d_loss: 0.0672 | g_loss: 4.5439
Epoch [   49/   50] | d_loss: 0.0778 | g_loss: 3.8784
Epoch [   49/   50] | d_loss: 0.0418 | g_loss: 3.5568
Epoch [   49/   50] | d_loss: 1.3792 | g_loss: 6.4400
Epoch [   49/   50] | d_loss: 0.1150 | g_loss: 3.7705
Epoch [   50/   50] | d_loss: 2.8969 | g_loss: 6.3862
Epoch [   50/   50] | d_loss: 0.1795 | g_loss: 5.7774
Epoch [   50/   50] | d_loss: 0.0687 | g_loss: 4.7025
Epoch [   50/   50] | d_loss: 0.1187 | g_loss: 3.8357
Epoch [   50/   50] | d_loss: 0.0923 | g_loss: 4.6037
Epoch [   50/   50] | d_loss: 0.2166 | g_loss: 4.8406
Epoch [   50/   50] | d_loss: 0.0777 | g_loss: 4.2687
Epoch [   50/   50] | d_loss: 0.1284 | g_loss: 3.7247
Epoch [   50/   50] | d_loss: 0.1169 | g_loss: 4.7595
Epoch [   50/   50] | d_loss: 0.0321 | g_loss: 4.4068
Epoch [   50/   50] | d_loss: 0.0781 | g_loss: 4.9921
Epoch [   50/   50] | d_loss: 0.0814 | g_loss: 4.1419
Epoch [   50/   50] | d_loss: 0.1279 | g_loss: 4.5959
Epoch [   50/   50] | d_loss: 0.1015 | g_loss: 5.4072
Epoch [   50/   50] | d_loss: 0.0408 | g_loss: 4.2776
Epoch [   50/   50] | d_loss: 1.2542 | g_loss: 0.6863
Epoch [   50/   50] | d_loss: 0.2076 | g_loss: 5.3562
Epoch [   50/   50] | d_loss: 0.1098 | g_loss: 3.9932
Epoch [   50/   50] | d_loss: 0.1083 | g_loss: 5.0240
Epoch [   50/   50] | d_loss: 0.0593 | g_loss: 5.4517
Epoch [   50/   50] | d_loss: 0.0983 | g_loss: 3.3805
Epoch [   50/   50] | d_loss: 0.0906 | g_loss: 4.3546
Epoch [   50/   50] | d_loss: 0.1040 | g_loss: 4.6428
Epoch [   50/   50] | d_loss: 0.1731 | g_loss: 4.9695
Epoch [   50/   50] | d_loss: 0.1501 | g_loss: 6.0645
Epoch [   50/   50] | d_loss: 0.1703 | g_loss: 3.6817
Epoch [   50/   50] | d_loss: 0.0996 | g_loss: 4.0668
Epoch [   50/   50] | d_loss: 0.0525 | g_loss: 4.4544
Epoch [   50/   50] | d_loss: 0.0416 | g_loss: 4.1590
</pre>
</div>
</div>

</div>
</div>

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[21]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
<span class="n">losses</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">losses</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">losses</span><span class="o">.</span><span class="n">T</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Discriminator&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">losses</span><span class="o">.</span><span class="n">T</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Generator&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Training Losses&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[21]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>&lt;matplotlib.legend.Legend at 0x7f4cc82aeeb8&gt;</pre>
</div>

</div>

<div class="output_area">

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


<div class="output_png output_subarea ">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAW4AAAEICAYAAAB/Dx7IAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAIABJREFUeJzsvXeYHNWV9/893ZOzJmlGcZRzHkkIiWQyJq0XDAsmOCzmtY1t8NqG3ffdH+vf+6zXXmwMtpdgE7wYL2ARjDE4ECSSUBbKcTQ559jT6b5/VFVPdXVVdVV1VXfNzP3o0TPd1bfuPZXOPXXuuecSYwwcDofDGT94Ui0Ah8PhcMzBFTeHw+GMM7ji5nA4nHEGV9wcDoczzuCKm8PhcMYZXHFzOBzOOIMrbk7KISIvEQ0S0Sw7y3I4ExXicdwcsxDRoOxrDoBRACHx+1cZY88nX6rEIaL/C2AGY+zOVMvC4eiRlmoBOOMPxlie9JmIagF8hTH2tlZ5IkpjjAWTIRuHMxngrhKO7RDR/yWiF4nof4hoAMAXiGgTEX1CRL1E1EJEjxJRulg+jYgYEVWJ338r/v4WEQ0Q0Q4immO2rPj7lUR0koj6iOjnRPQREd1p4ZiWEdF2Uf5DRPRZ2W9XE9Exsf1GIrpX3F5ORG+K+3QT0fuyfWYQ0atE1EFEZ4no67LfziGifUTUT0RtRPSfZuXlTGy44uY4xd8B+B2AQgAvAggC+BaAUgCbAVwB4Ks6+98C4P8AKAZQD+D/N1uWiMoBvATgu2K7ZwFsMHsgRJQB4A0AfwJQBuBeAC8S0XyxyDMAvswYywewEsB2cft3AdSI+1SIMoKIvGJ9uwFMB3ApgO8S0cXifj8H8J+MsQIA8wFsNSszZ2LDFTfHKT5kjP2RMRZmjI0wxnYzxnYyxoKMsRoATwK4QGf/rYyxPYyxAIDnAay2UPZqAAcYY38Qf3sYQKeFY9kMIAOCMg2IbqG3ANws/h4AsJSI8hlj3YyxfbLt0wDMYoz5GWOSQj8HQAFj7N/F7acBPKWobwERlTDGBhhjOy3IzJnAcMXNcYoG+RciWkxEfyKiViLqB/ADCFawFq2yz8MA8rQK6pSdJpeDCSPxjQZkVzINQD2LHsmvg2AtA8LbxbUA6oloGxFtFLf/h1juHSI6Q0TfFbfPBjBLdKH0ElEvgO9BsMoB4IsAlgI4QUS7iOgqCzJzJjBccXOcQhmu9ASAwwDmiy6AfwVADsvQAmCG9IWICGPK1gzNAGaK+0vMAtAEAOKbxLUAyiG4QF4Qt/czxu5ljFUBuB7A94noAgidySnGWJHsfz5j7BpxvxOMsZvF+n4C4GUiyrIgN2eCwhU3J1nkA+gDMERES6Dv37aLNwCsJaJriCgNgo+9LM4+XiLKkv3PBPAxBB/9d4gonYg+A+AqAC8RUTYR3UJEBaI7ZgBiaKTY7jxR4feJ20MAdgDwE9F3xDa8RLSCiNaJ+91GRKWMsbC4HwMQtvnccMYxXHFzksV3ANwBQbE9AWHA0lEYY20AbgLwUwBdAOYB2A8h7lyLLwAYkf0/wRgbBXANgOsg+MgfBXALY+ykuM8dAOpEF9CXAdwmbl8E4F0AgwA+AvAIY+xDMTTyKggDpbVinU8AKBD3uwrAMTEi5yEANzHG/NbPBGeiwSfgcCYNYjRHM4AbGGMfpFoeDscq3OLmTGiI6AoiKhRdHv8HgstjV4rF4nASgituzkRnC4RY6k4IsePXi64PDmfcwl0lHA6HM87gFjeHw+GMMxxJMlVaWsqqqqqcqJrD4XAmJHv37u1kjMULVwXgkOKuqqrCnj17nKiaw+FwJiREVGe0LHeVcDgczjiDK24Oh8MZZ3DFzeFwOOOMpK2AEwgE0NjYCJ/Pl6wmOQbIysrCjBkzkJ6enmpROByOQZKmuBsbG5Gfn4+qqipEJ1njpArGGLq6utDY2Ig5c+bE34HD4biCpLlKfD4fSkpKuNJ2EUSEkpIS/hbE4Ywzkurj5krbffBrwuGMP/jgJMcYAR/QdjTVUnA4HEwyxe31erF69WosW7YMq1atwk9/+lOEw0J++j179uCb3/xmwm08/vjj+O///m9T+5x77rmW23v22WfR3NxseX/DHH8DOPoHYKjL+bY4HI4uSRucdAPZ2dk4cOAAAKC9vR233HIL+vr68G//9m+orq5GdXV1QvUHg0Hcfffdpvf7+OOPLbf57LPPYvny5Zg2bZrhfUKhELxer7mGfH3C33DA3H4cDsd2JpXFLae8vBxPPvkkfvGLX4Axhm3btuHqq68GAGzfvh2rV6/G6tWrsWbNGgwMDAAAfvzjH2PFihVYtWoV7r//fgDAhRdeiH/+53/GBRdcgEceeQQPPvggHnroochv9957L84//3wsWbIEu3fvxuc+9zksWLAA//t//++ILHl5wtq227Ztw4UXXogbbrgBixcvxq233gope+MPfvADrF+/HsuXL8ddd90Fxhi2bt2KPXv24NZbb8Xq1asxMjKCd955B2vWrMGKFSvwpS99CaOjQgbTqqoq/OAHP8CWLVvw+9//PjknmcPhOEJKLO5tJ9rRMWBvSuSy/ExcuKjc1D5z585FOBxGe3t71PaHHnoIv/zlL7F582YMDg4iKysLb731Fl577TXs3LkTOTk56O7ujpTv7e3F9u3bAQAPPvhgVF0ZGRl4//338cgjj+C6667D3r17UVxcjHnz5uHee+9FSUlJVPn9+/fjyJEjmDZtGjZv3oyPPvoIW7ZswTe+8Q3867/+KwDgtttuwxtvvIEbbrgBv/jFL/DQQw+huroaPp8Pd955J9555x0sXLgQt99+Ox577DF8+9vfBiDEbH/44YemzhGHw3Efk9billDLR75582bcd999ePTRR9Hb24u0tDS8/fbb+OIXv4icnBwAQHFxcaT8TTfdpFn/tddeCwBYsWIFli1bhsrKSmRmZmLu3LloaGiIKb9hwwbMmDEDHo8Hq1evRm1tLQDgvffew8aNG7FixQq8++67OHLkSMy+J06cwJw5c7Bw4UIAwB133IH333/fkJwcDmf8kBKL26xl7BQ1NTXwer0oLy/HsWPHItvvv/9+fPazn8Wbb76Jc845B2+//TYYY5qhc7m5uZptZGZmAgA8Hk/ks/Q9GAxqlgeEwdRgMAifz4evfe1r2LNnD2bOnIkHH3xQNfY63qIYenJyOJzxw6S1uDs6OnD33XfjG9/4RoxCPnPmDFasWIHvf//7qK6uxvHjx3HZZZfh6aefxvDwMABEuUqcRlLSpaWlGBwcxNatWyO/5efnR3zwixcvRm1tLU6fPg0AeO6553DBBRckTU4Oh5McDFncRHQvgK8AYAAOAfgiY2zcTbcbGRnB6tWrEQgEkJaWhttuuw333XdfTLmf/exneO+99+D1erF06VJceeWVyMzMxIEDB1BdXY2MjAxcddVV+Pd///ekyF1UVIR//Md/xIoVK1BVVYX169dHfrvzzjtx9913Izs7Gzt27MAzzzyDG2+8EcFgEOvXr7cU5cLhcNxN3DUniWg6gA8BLGWMjRDRSwDeZIw9q7VPdXU1Uy6kcOzYMSxZsiRxiTm2Y+ja7H4KGGwHqr8I5FckRzAOZxJBRHsZY4Ziko26StIAZBNRGoAcAEmY8cHhcDgcNeIqbsZYE4CHANQDaAHQxxj7q7IcEd1FRHuIaE9HR4f9knI4HA4HgAHFTURTAFwHYA6AaQByiegLynKMsScZY9WMseqyMkPrXXI4nInGSA/QGxvmyrEXI66SSwCcZYx1MMYCAF4BYD25BofDmbh88jiw/7eplmLCY0Rx1wM4h4hySIibuxjAsTj7cDgcDschjPi4dwLYCmAfhFBAD4AnHZaLw+FwOBoYiiphjP1/jLHFjLHljLHbGGP2JhpJEm1tbbjlllswd+5crFu3Dps2bcKrr76aElm2bduWUFZADsdxQkGgvyV5bYViZxJz1Jk0MycZY7j++utx/vnno6amBnv37sULL7yAxsZGx9pUm9IuYUVx69XH4djOybeAvc8CowPOt/XRw8CHDzvfzgRh0ijud999FxkZGVEzCWfPno177rkHoVAI3/3ud7F+/XqsXLkSTzzxBAD9NKt79+7FBRdcgHXr1uHyyy9HS4tgmSjTvP7xj3/Exo0bsWbNGlxyySVoa2tDbW0tHn/8cTz88MNYvXo1PvjgA9TV1eHiiy/GypUrcfHFF6O+vh6AMDPyvvvuw0UXXYTvf//7ST5rnElNvzhdI+h3vq1QEAhzw8QoqVlI4dTbwGCbvXXmTQUWXKL585EjR7B27VrV35566ikUFhZi9+7dGB0dxebNm3HZZZcBUE+zunHjRtxzzz34wx/+gLKyMrz44ov4l3/5Fzz99NMAotO89vT04JNPPgER4de//jV+/OMf4yc/+Qnuvvtu5OXl4Z/+6Z8AANdccw1uv/123HHHHXj66afxzW9+E6+99hoA4OTJk3j77bfNL37A4XAmJJNqBRw5X//61/Hhhx8iIyMDs2fPxsGDByPJm/r6+nDq1ClkZGRE0qwCiKRZLSoqwuHDh3HppZcCEFaUqaysjNQtT5/a2NiIm266CS0tLfD7/ZgzZ46qPDt27MArr7wCQMi3/b3vfS/y24033siVNofDiZAaxa1jGTvFsmXL8PLLL0e+//KXv0RnZyeqq6sxa9Ys/PznP8fll18etc+2bdtU06wyxrBs2TLs2LFDtS15+tR77rkH9913H6699lps27YtZqEFLeQZC3k6Vg6HI2fS+Lg/85nPwOfz4bHHHotsk1K0Xn755XjssccQCAjrKZ48eRJDQ0OadS1atAgdHR0RxR0IBFQXNgAE63369OkAgN/85jeR7fJ0rICwYPALL7wAAHj++eexZcsWK4fJ4XAmAZNGcRMRXnvtNWzfvh1z5szBhg0bcMcdd+BHP/oRvvKVr2Dp0qVYu3Ytli9fjq9+9au6ERwZGRnYunUrvv/972PVqlVYvXq1ZoTIgw8+iBtvvBHnnXceSktLI9uvueYavPrqq5HByUcffRTPPPMMVq5cieeeew6PPPKI7eeAw+GY4PTbwLb/SLUUqsRN62oFntZ1fMHTunJU2fkEMNwNbPwqkFMcvzwAvPdD4e9FD5hry+p+TpJkmZxI68rhcDgcl8AVNycx9j4L7PpVqqXgcCYVSY0q0Vtwl5MaEnaVJWtKNIfDiZA0izsrKwtdXV2JKwqObTDG0NXVhaysrFSLwnEj/Fl1LUmzuGfMmIHGxkbw1XHcRVZWVmSCEYfDUaG7BsgsBHJLUi1JhKQp7vT0dM1ZgxwOx4Vwt6bApy8Kf10U8cIHJzkcjjrcVeJauOLmcDiccQZX3BwOhzPO4Iqbw+FwxhlccXM4HI6SkZ5US6DLpM3HzeFwOKp0ngIObU21FLpwi5vD4XDkDLSmWoK4cMXN4XA44wyuuDkcDicK98evc8U9Wdn1q7EZYRzOZKbtKFCnvhCKW+GDk5OVoU7h/2QnHBamdvPp3ZOLgVbAky7kHzn6B2Hb7HNTK5MJuMXNmdxs/xGw7zfxy3EmFnueAXY9mWopLMMVN4fDc4o7R8AH+PpTLcWEgytuDofjHLt/Dez4ZaqlMMc4SK7FFTeHw3GO0YFUSzAh4Yqbw+Fo4H7Lc7LCFTeHwxk/hEPAez8EmvalTob3fggcfT117YMrbg5nclG/ExhoS7UU1gn5hb8121IqBtqOpNQXzhU3hzOZOPMusOdpc/tYUVCOKTUp3t6m+sMhlY0G65Y6kRTAFTeHw5m8fPyo9X1Z2D45TMIVN4fDGT9IM1ztsugDPuv7clcJh8NxLzoKqr8ZaDmossskiEhJocXNc5VwOBzr7BXTBVSuTE57kQ7BDR0Dt7g5HI7TJNUKdoFiHe4GWg+b28c/BNTtMFbW7a4SIioioq1EdJyIjhHRJqcF43A4nFhMKMvdTwHH/miu+rPvmxBF5ioJh4HAiLm2EsCoxf0IgD8zxhYDWAXgmHMicTgcR7BqIbrJX21GlnDQQgNm0vvKZDm7DfjwZ4kNdpogruImogIA5wN4CgAYY37GWK/TgnE4HBdx5FUh/ts/ZMyyTETZH3lNSLuqW7/16m1Dfoztx4W/QZcobgBzAXQAeIaI9hPRr4koV1mIiO4ioj1EtKejo8N2QTkcTqIkoO3ajwszLj96VLAsnaT9mM6CvQ5PBjKzoEZUVElyexIjijsNwFoAjzHG1gAYAnC/shBj7EnGWDVjrLqsrMxmMTkcjiYjPcAnj8XPe62nwPqbAV8fcPod4P2HlDtaEMppRWaifqdcPXLFLbWRpJWUjIQDNgJoZIztFL9vhYri5nA4KaJ5PzDSK+TPmG0xbmDvOFkFyJISToLiTjJxLW7GWCuABiJaJG66GMBRR6XicDgmMGrlucExbBNmFLgpBZuoqyQ5FrfRqJJ7ADxPRAcBrAbw786JxOEYgDF3RTsAgjx9jbZX29rnw8N/O4nWvgQHvpIZVeLYtXGRLG62uAGAMXZA9F+vZIxdzxjrcVowjktxi7Lc9h/A4ZdTLUU0jbuBfc8B3TW2VlvTOQgAONs5ZK2C/hagt978fm651qqYkS0Jg5NJ9nHzmZOc8UvnqVRLEM2QGE3l6xeiMMKps8ii2PsssP95mLVWW/pHsKOmC/6QleNwysq1YnG75DrYCFfcHI5tiNZWxwkh7rne4NRpJU37hFVWQmYnkNirLBu6hgEAQ6NWJrLAgvwqNB8QYscTwYyyHzSxyITLwwE5HI4ZAoLCw2ic8Dwtaj8U/gZtnkJt2fVhYb+u08D7/2mxPZGRHuDEW0Ls+HB3tCxGjoUsLLrQ22C8rJoMSXIvccXNMYmb/Z4uwTY/p93+0iReu566xOuQr07T8qnw15RilHJ3hwXXVaIrznefVWyQyZLk8QCuuDkcp0imhZtsus7o/56WkXgbUecvgXMSDgmuqwO/S0yeT1+I/m6XfBbgipvDsYsYS9vAw+zrFxSKWv4PuyMU7LQKD76k/7vXBsUtx0oebun8SZZ7vJmliZDkPOFccXPGFwEf0LQ31VLEwYTCbdgpuBXajjgnTiogb+y20UFhhqdhElWCkuIWB0lt7wjFwcmBViA4am/dceAr4HDGFyfeFKI2xgNGLNxIGVLZZjcpzu/x8c+Fvxc9YEEGlUHJcEjIxtd1RogGWXAp0LgXyC0FpsweO6URxW2zncqYcC8efkVDZufgiptjDsaELHHBEWBKVfLblyI2Jgw2POhGLUlT08RTN/BmmKOvAR0nx74vuBQ49Vfh80UPYGxwUnSV2K24waKVdhLhrhKOefY8DRz4n1RLMQ4wYXFH6V6TeS9CAeHvYLs9sdNGcUKhB/3yBlQ/RpArbTVI6SqxQd3JZ6CqHj/3cXM44xNTvlQbkhM17hH+th8TrNC4bSmQFgEwUtZpWg7IRLAxqgQYU9xaHY6Rjmj/8/bIlCBccRvlxFtAy8FUS5EYQb/CouE4g/SKbsbitmngTC8NgJY83SqhfYZk15tKblGpyWO31eqwEsdt1OI2+wbBJ+CMA5oPAMf/lGopEuPDh4EPfpJqKSYwFsIB1fZNtk857iu/hjwDLfbL0lMra1YliVPIQvRGxOKO16GaVdwuzw7ImSDYcqO5dKBKSSg45vuV03Y0WjmkHGMWd46/C1n9iWYdNKGwjHQe+55LSJoI/bIOIEpxq3QeR/9gvF7SGpxMwFUSvYPJ8vbBFTdnYrLj5ypLcEF48J0eWI1r2cmQyhx/U7fYytaXUXr29QQFM8OY7GRptXQT7H1WQwSFoTHcbTIOXKTuY+FvPB+3aYubK24Ox14CyVltOworMyflZQ5tVWxT2f/o68IgpB5DnUD9J4KSO/lXWVMq9Y0OAq2HVcQaK5tx/FX99tRQe9sxC5P5uxkDGnZZq0dS9vHGEUy/kabOx83juDmcVCJ/0I3kF287IvwvX6JdZv9zQsfVflSIuR9rLLbsqb/GbouUFcpTcBRIV5kJqYfyWKwotE9fVMiT4ACu3a4SbnFzOBMJE64SJ/ykkrWbcGSIBSTlmJEbv2woaN2KtoLUidnlKlFdVYhb3Bw3onXT9zcDBdOSK4tbMZIH+oOfAtlFQHaxdpmELTrF/mr1abkPmEULNz1bXPjAgOyNu4Ca7cbqZcxCyKRK+c5TgH9Quw0zpDC/DLe43cqRV+P7Mt3E3t/Y49d0Gwf+B6jZZn+9wVGFG0NGMl/BNWObx1wl5uqT5cCOqk6lLlOJmWw6J4e2Aif+7FwbPI57ktN+HDiiNwvOhURNnjBIcFS2uokL6akF6iwuQZYMV0mjSqZEqV1Dq8RoqIBE/b16Lhhfn7m6jZLodH+35mRRgStujn1Ymf23/zlg5xPR24Kjwiu06mK7Ns0wdKSzIMVfBSO9JgftDCgSzcFFterUXCV6FrcVNCxueX07/kuY0GZqRXUDrpKzBt0umm2Mn3kOXHFPNAbbE1+iSRebb8zBjthtNduF2Nt2B32IyreDZLil9jwtC/kTGVHrQGw6x0Od8cvYZXEDQnpV6d6LpwTbj8JcJ2xAHnmeE0twi5uTKnY/Bez4ZYoat8kaliZ8qE78sOnhUlpvTrillMpPzaer1nE5hoMWd8gfvSpOjOuExZa3G2UeHrNvgHa4SriPm2OZceSri8I/PLYo7HghHIo934kmjHLq8snlPLRV7Ehs6myDiglPSmu//uPo7+GgeVeJ44yf54Yrbo57OP6GMPV7WHzoe2pVZkC6bAX17T+OXYTWrvUHnVxsuPMU0HZY2+I2OwYQb2Cw9qPo74MdQt4Yw5g8F0Nd5soD9qxMz33cHMdI1dJYoSDQ26D9u7S6jfQa3X4cOPyyPaIpiWft7f9ttPXffVaYHq62urk0EUMZv+26Nx8TrhLliubxsJLPZKTH/D5G2fUkTHfOJ95yRBQncJfiDvqBXb8C+ppSLQlHi0SU0em3BYWoZQ1JC8zKo0kk6zscFi20JCnD3oboxE/dNYJlffClxBVyXAUhq7+/BZ7AUGLt6TVj1wuM04moGAOa9jnbhh1MylwlA82Cb6xmG7Dm1lRLM3Fx6uaKV++gOOEkOKL+u0dU3FERCaJmadwNnHk3IfGi0JI1HAZGVeKMiYBhWYfTeUrd+o6qW/jb1u/DgC+I+dLvzUajHxiw91lUDDDYkvna5HXPCA5C40rF4rTittJhpzBfttO4S3FLfjJvemrl4KQGj3g7qj1wqmFziaChCE6/DTSpTGqJ2pXFhvUBGDNfo+v+3U7BlXKvxafNq9bRdZzQnvCk2SkplOuZd4Dp66K3ZeZbCyd1WnGPakxT1yNguNuxDyeiZVRwl6tEuvgek5nIOCZJte9V4/1c9LcOjIxi59kujAZlisnoA9G411hMtuYyXlqLFViIgLD6ZmNkv8OvmFtUAIhVrmqKP7/CXJ1addtNX6Oz9duFcqDaIVymuMVcF55xbHH7+gSrzXUDUw5w8i+KDQkes9hht/QMIsyAvpGAkLBopFd/rcz3fjgmy6m/Rsdkv/dDjVhpDVltWftRrDucYO4Wu++hNpW828rj7dMZPNbj8CvW9uNYwmWKW7K43eXBMcXR14GG3UC/iwdYE1IIsn1NDxbptMtYZHCSlK6STx6L769s2qedz7pdDDuTr55y+GVzK+FEKTiV41BLsNXXFOk0sgIWVm6xG9XFrhWKOxULUHBM4zLFLb66jWfFnXI3xPiHqVm9RixhVb8zELkmnzw2tmmkV2PtSQPtqOXEkC+TJu8Yd/8aALC65SUYIhwe66ScyEqoxK7V5ZNNVmGqJUgp7lLc0g2rOQ2XYw9GEuwzwNdvstoEOq3x5Fqq3xmnQALHIs8VnfK0vi5W6mYyDGbkOCdHinCXhpQeXhffL5OGs+8LOU/sSsHZdiR6Ne8YHBzIs6VTSNJNmWyjRXfx3XHUmepBEy/YwWWKm1vcScGIIpOiK/w2Tf44amCFcnFFEW9ILcG+3kotNpKI60Aao0nozSPJsccpt+qTwHh1B+ngMg0p3fDj9ER3ngIGWlMthbOYzR8dCgIHfx+9baRHyMksj811Mi+HHZajkYe/eX/i7dnVUXJkjFN9ooNhxU1EXiLaT0RvOCbNeLe4D221tgqMEsf9vbL67Wzr0NbYxQ8GmoGu09HbmvYILpiO4+oyqaG5NqIBC1XXReMAinNaMqwxw1KNvc/aK0uqccNkumRa3Emag2JGQ34LgLPvVREf98TrIV2LnYq7v9ngDEczq6DHwUgWO9XVuM1i/Z5c0PmODe2nAhuew7kXJl5HwiRRnxTOTEozhhQ3Ec0A8FkAv3ZUmvFucctxc5SEo7IZeEik69srS6Npdapw50lr+6lh23JmLr72Scei0py61EYRJq/F/TMA3wOg+V5KRHcR0R4i2tPRYXFVj4mkuK3iH06y0jfbVpzy3TVjyZfajqonYpIeJPmEGcuDcjaeq51PGFvuKx52uMs4NpJExZ0k3RW3FSK6GkA7Y0w38w5j7EnGWDVjrLqsrMyiOON8cDJROk8DHz0C9Naa39fXHz2hpOvMWGL4oF+R6F6m7DpO6E8nN8vpt4XUp901Qi6N+k9UCqlc33iKW8saTlYnZ6ZjcfOq9aawY1DXatM2XtdkWtxJUtxGpihuBnAtEV0FIAtAARH9ljH2Bdulmew+bilPRH+z+X13/ypaAUvr/130APDBT4DsKer7Hf2D8Fq69LqxbYwlnjRILzpCzeccz0rVykndbmYVlQSo+zh+GY6N2NwhF1QmZ5DaLRY3Y+wBxtgMxlgVgJsBvOuI0hYaE/5OZleJVeJZzfLVRpTWjHKSzdn3E3cZmE0NGs/C0sqhoTuBhJMIzI43X8uTX2w03iagxe0yDTnBB3UYE9JTxlNSTr/+K8Pz+poE/65k9bYeSryNGpV8HnpM4KT345VAWl7ilVjNOzT/ksTbjkAw3REs/iwwZbb5plw2OAkAYIxtY4xd7ZQwkYfXzREZidB+FNj3nHp6TSB2zUKnOP6n2G3D3cColJskThY/J3BacZ9+29n6JyJ2WI9W68i0odOIyEDmre7KlUCGBRkmpcU9URW2hOSuiDd4NRlf/5nDkRi4YoGiAAAgAElEQVQNu52tfwJiz9OYQC1zL7RFggRGSGM3rfy88DcjV6MpF1rcjhOxuiaYAu88bS5Zk5izwzBn39f+TTUHsxYaN3hfEzDYbkok05z9wNn6Oeaxw3pM5E1q9qbE2wdEa9uC8lYzJKVzklsKrLhRGPSUY+ebgg7uUtwTSmHLjuXQ74WpzHZHzTAmDCLWfqRdRs0tYqReOfv+23wdZtFcMmwSMKXKnnpsnl5uy9NoRXHPOseOlsfILbfvmZMUNwsDpfOj3SnZRcDMjfa0Ewd3Ke6J7OP2D+v/Hg5rJPbXofUgsOtXlkUyhDJMr5ZbxrZj14DWoivtqUeEieqBJTvP+ryLYrflllprf/UtwILL4pcrnK6yUSG7Nz1acSupXOXOwUnHmYgKOx59jUBwFKjfYT7OdKDNXlka98ReA2XukWQnbJoUuHTegh1WavlSe9wHVizZ3FIhMsSbhrjnOKckdpvyWSAC0rKEz1lF5uWxEXetETbZQsICPiHKpHiutVU67I5Pbdwt5oiYhB1oKnHthDMb5ErLAJZ9LjnuNjnnfUdoO4LOPb3xq8Kkt5jxIJV98sqAFTcARWqhgsm7ju5S3JETNYEUR1SvrZjSL0VSDLYKytsNTLbO0w24VHEzIuuqaP7FY4nD7Dg+rZm/WphpM6fY4Gxlsc7SBYm3mSAuc5VMYqVhyU3kxI3iTiUysUnxOV/8WY0fElAPMzcAVVvELzYcX1YhcN59xssrw/IKpplvU81V4hJcprhZ9F+34PTgjF4ZX592Hg8n7qN9/x1/IJVjjLkXGitng0IYHA1iwGcxv0yu1aRwIjM3AAsvdz4ULi3TeFmPQrXNudBWUdTbTN6iEe5U3E4TCgpZ65SrtSSCpuwq22s/ND6tfMd/Aft/KwxgcsYXeeXGysnjpS2uSH6oqQ+v7m+ytG/CeDOA6Wu1fzfSMcULZczMNy6P2nlXKnIjxDzTOseRPxWYttp8GxZxl+JOlo+77iPgzHtA66fOtgNoK/RjJlaA628GDr+s8kMSXt3c9vYzIZFdx5kbgYrl+sVnn2u+iaxC8/sYJt49YuA+XXNbnCpc4KbQk2H2lqSFAgJuU9zJ8nFLgyZGE94n5O7Q29dEbpJ+FWvKDTczRxuj10ducZMHKF2oX37uBcZnNUrui2wT4WtzLzRe1i6MWtQXPSDkEZEoXxJbRuu8r7sDKDKztJh7jRaXKe4k+7ittNN+HDj5F7XK4reR0HFxJe0IjvpljSpueTlzyn7YH0Rbv0/cU+X+CgWEv9KiGnHbB1A4I+pr3Ls23n1tpAOzYoRkFwFZBcbLF0wD8ivjl5OISTKlJ2NylbzLFPc4iCo58irQtC92uyWlLO4T8AGDcSbTqN7YXJknTHq2c3WrXbMFl6oVNF+3qFwPNvahplNn0QorYyO2v8klUN+Sa4A1ivT/0rM2c4P6PoWzrLcHjL2dzL8EWCJLhuqiN1x3KW7XxnEbkceCq0S+2EC8hQvIIySfkj+IybiR7FyM15U4eQ5V6p5RrVJM7ioxmBBp4eUAlHeXyr1mc/4SSyRyn1Ys13FvaNSrNmU+goFnef1XhL9pGUDFivjtpQCXKW6RIYuLDZvFTsWntLiNuH32PGO8/oAPOPo6cPLP4vcRoG6HORmtoLbY70TCqc7PjCVvJgvf8s8Jf1UUMlN7nI0oblesOGXhOmhdO0uDhPLn1D0KWgs3XLExJCXXMR6tPAMWt3z5MKv4xMUOTv0t8bo4zmEmeX/U1Gxt+ss3AGWLpAaifvu08kb19ozkh84t00iyZBQbokos4X4F6xTuUtzJwqw/2lJUiYrF3X7MXLvqDQl/QjauzM6xF48XmHsRDCsWr4mJJRJGOwWtpcMiHYBY19rbzctglPSs+GVMvfk4vKi4i3zZWrhMcbvNt22GJEfCjIOba3zgwHm84HtCyJrNFnc00XVrLuyr5TYomWe47rjEM2zSrU0qio+FBRIyjUShuP/ZcpniHsdo+bjtVuj9zfGXPuMYR2552o5RizsDwXAYobCJe0alUxj1Jmf1FdMQAUXxIj1sUJYLLtVcZDgcZvjgVAdGytcAy//eYgPCdRnxh3BWL5InCbhLcbt2lp6KXFquEQlfr5Am0oljUp1FybFERi5QMt+Zug27M9Kxu7YH++rFMRCteyZOvPdg5lTjsjlxX+rVaWe8vNZbZ24ZMHO96i5nOgaxp7YH2091AmVxJjjFuW6v7m/Ca/ubEAilLnzZXYo7WRhY/9EfDOO94+3wBzUujjLmXHnTnvizsGyYE7Hpw13mV8vhpACjiltwZwTDTNzHwGSuRCNB7HS1ORkLbxPSy4wdurZn2C/WmTpD02WKOwknYrgb6DotftG+effV9+BAQy/212tEgsSzuONuTwDGgCAfnHQ9Vqa82163WC5mHUcTilvvFp61EZihbuWawk1jNm6SRQOXKe4kIJ/0onNHSr1pmEH9FTCexa1VTocwY2jqHUlpT65FmDGMBAzkdildkJxkO2amOqcMcxZ3hJg80GqPqUnlYnYhAqNMW5PU5EoCigVJJFKhcFOk5N2luF2osLQxaHGbOKbm3hHUdw9Hck+4ibruYRxo6MVoMI7yTs82ns40ERLJfZxXFj0jLllhZVopW2NiraPvmTCphPSRwagSo7JZJsX1JFNxukg/uUtxyzn4kn11Ne0DzqqtTq5x0QM+zPz0EZQNntCuU2lJ7/gvjXLGL7bkhwu75/6IMDAiJCsKhqKF84fC8CfqOIw3WKRGIg8sY6mxlJbfoL49jsXNvGK4oJVkVAsuEzqpmOW2bDp+w+fRofMdda7c7+KwC5cpbtlFsHOq9cm/CIsXGEUcvKwckBY7MBJVooULtbCN7K3rwd66BGeE5lqw0BMdnJt7oZD4vnxZYvWYwasRrx3H4mZqbxdGFWZmvpAoSWsijgH072CZHFbdV1OXjQu/sm70UZKtcZcpbhsJh50dxJNb3Hpx1eMh42GqsfLQJqq4M3KBRVcCXgfXyzb6MMfxEQfTDeSqNnsODZU3GU+u9UYRj6XXmisvPVPkSa7CFxN7uQF3KW47e63tPxLWT6zZZl+dcqQV2oOjwM4ndMpNNsVt5UGyMcGQm9GSWdkJyZ+DFTfCn6eSR4QIWHiZmcbjfLcBK7Haqmlu4yBX3HKcvieSPgirjbsUt930NwMhG/IRq3Uo0iSY3nr9ugITf+HdE6VmFIgK0vnWW7cwdqf4Rbxp6kt2Je211uCahTFvD7L9SnVez6evMy6KY0pNpV61QVit9iNpbk3IJ60Vm2JFmsqxSgffE92CQzfsgLjwgZbfUuLwK86072YsJ/Eyca30XCVpmcKb0KZ7hARH7/1Q2WD0VwMTshwlXjigtNnQMngGsUuRK+vZcq/zaWK1LO5JhMsUdxK6sL6Gsc+n/goUVAJZRZZX146ruKWloyYiVVuwM1CKopGG+GWBMYWqRHI7mVmJe+YGoK8xdnvRLGDNrdHblv2dsHKRFoPtxttNBEnJKc9DTHZA8TnIKbGjUbFKEyuWW6lfwkgmQNVqzEwIMq+4NavPKTberouY+F2W/Ir11MWGBe79DbD7V8L0dBUlK+yu06GMR1+rFVRXTiMwZUSE3vlYeZP69nBQ+Gsm8qFQa1UUlWtVvlhRJMVrmi7/e6Bq89h3IrTlLRU/y/ZTrPxCiSjbBKJKdEnF/S919HZY3NLq8i6K0TaCuxS3IydPdmP5B9WL+IeFhFAtB6M2Z4SGjK8EP4lhRh9erYFayWdpJOm/hFabhu6hFD+kU2YDc86XbVAei8J1ZOCY4k7A8XiEFdKleO6kT8CJU86KxW3Cx615Cq2+aacYdyluKwT9+iF/8hvCZMeQFh5FxfFnAL9OCsdx1lPbiuaxm5z+H3GVGLQKFauQG2rbKLM2JrZ/FMqp66ma3SijQIxQySqyp91UWNxhucWdujfeVD76419xf/QI8OFPBT+lqj9ZfmHNn+k0/yCw91mdEhNDcY8Wzsau2m4MjgYt7G10Rp/GuZqxXvDnKl0aSqQZlgWV2u1YWq1IRtV58fc3Soxy1IoqUUYxqRfTH5xUYfra2KiaWecAG+4C8k2kgAUEv7wqKVCcUjRNIvlXVv8DMP9ie+RJAeNPcZ/4c/RAUzgoPIi7nwKOvR5bXv5QWF3zUa1DkGaJTRCLu2twFKEwQ0vfiPGdZAOzqkolyh0AbYs7pxjYeBeQnqvfXoGepW0XVnNmqDxKGTmCe8JQm/LzZyHKRo2Fl8d2CkRArrlBTwYGVH9J/UejFnflSlNtxq3rogdU0slqyxIj5pQqYYBbScXyRKVLCu5S3EaUYPN+oP24+m+9atENsitW+5ElsVQpmC5EBkzWtR+L58hicIGeIdl5kK5jfkX0PvGubzwlIP3O9Mom6OO2+uq/9Lr4ZTQn4GjMG1BsT2hw0hJGzqVBmYpmGezExg+CseLS7IBENJOI3iOiY0R0hIi+lQzBbMMpH1zHceCDnwKfvpB4XcnIpgcICYe0MPvmMHNDZHCIgcRFAFSQJ5BKeBaphktm7W2yNhJ0lVjF0H2mXcYT5ec3b3Gbzg5oGtk5m3uBw22lkvERJWbE4g4C+A5jbAmAcwB8nYiWOiNOgg9UQO01X/1CqKYnPfVXUYwkP/zJUtx2dmKy4yf5ddNrI67ijiNfwTTh75TZ0dujBisTvC7kEdahXGEx74alNgleJrrjRPfT4GgQdd0unXVbtnjMNTRZwmFVcPXgJGOshTG2T/w8AOAYAJXkCS5hVBHyp3JfdQ6OYl99L/pGtCbHsCSPOSbp5pc9ZIFQGMFwAhawLEyStBQyEaKOLVGLu3A6cN53hJA2pcKQEgAlGg5IBCz/HDBljn4VlauUO8ZvVkfJecIyxc0YDjX1xWRdNDU4KXVydsAAZCjykERWiU+x4jbYcSSkZCuWmx/MdRhTUflEVAVgDYCdKr/dBeAuAJg1K96KzhrY0YUFRhTJbmIv7IAYOTHsD6IwWyVlZrK7UietFo9XET4lsEdUCpvmSgNVTH0fLWRKmDQVCkUPIMkV97LrgSOvxRFehTRpQFRxziJWt01vS/Emd2TmCbKYyj6pfZ29TD4JSZDPlPtDeQ+tvlW9nFW86UIUhzTAv/Q6YTUpM7NdxwUq98aSa5IvRhwMn3UiygPwMoBvM8b6lb8zxp5kjFUzxqrLysrska6vKfE6OnQWQ9Ak2e9ACSju+RfrhGpBZhnpt0OiMgt5M4E5og8zWyfWV6aEPUz55iI7f/M+M/ZZmu24+h+A8iUqQiTSgRmfrGKsOgOyMIMuIqm4zn1VX7geo948IL9Sc3DSFE6mqwUERT6Opos7YRsxnW9OY0hxE1E6BKX9PGPMwaxJioM/8Dyw7UdjE2D6m8d+05sUI8dsAqHBdmEafDJJ5K6auUE/9tjkyuAjObJX7AIdj5hMcaeH5GMLsmMhiu5UsgqEyIIpVXHliItamJthTOaZlpBF0ajsYKBd7TIDWZXYP/0W8Y0ixSGmaUK+kdF0Zcc9MUJfJwJGokoIwFMAjjHGfuq4RPJJGOGQoCCkMD+5Qv3oUfX9248k1v7Z9xPb3xIJmgNmV/w2imI6cENhNUKFohtMprhH0rUmQpg9LjPllWXjWNwxS3fZgbOKTOkq0QsHtDWqJKcYWHUTGsrGQfRI6aKxz7aY1SYieVI4OmnE4t4M4DYAnyGiA+L/qxyRhjHBx6fMQTDcZdxyrtuRmAypSPGZ8A1nR74ItZswurwvrQCBEjG8TzYjrzd7FnoXfV74MjWJS4HJiZxDjYdp6fXAOXcLn6eZyfttI4Ynq6xCf2YlWvOjJ4OYnjmZCMVzI0umudrOzp8aO19gEhDXEcYY+xCpHjrWsoK1rG5Lfm2RZKX4lJOpsVZf+RKg/Vj8/RO9OlOXwcemAmek86bxqBIhOHU1MG2+sFK6jED+jNgJFk4OuirrzioCypegqWAVWut6sG624i3AmyYMrqlMAhnyBzHsD6EsT2esAIjjPzeQCIopbOY55wMNMeP8QEYujk5134AYpq0FzrwrLPs2TrGz80tlh+ayIWGdmUhqylvLz+32xQvW3Rn9PX+qxpRilVtD1T+soyDlfmotRbr0WvUFaWOkIaGOPJsGn5Ukoug9HmDZ9XjpeADvn+wwtevBxj6cbtfIHClHOR06apa6hVDHqs3AefeZ308V8dxt/Krw3wlmbRQ6Pr3BcE5ScJniHgecczdwwfes7+/xikmS5BCQPxVMb+1BQHBPLLoitk49hTfrHJMC6vlRPcaMeysr2qgwXL5WO342mRM/pOtVMA2YozEQHDaQnCsZMucUW4/2mH9x9ExXJ1hxI7DuDmfb0EF7nMDVDqEY3LUCDmPJubkTuEb76/twpKcfX7BagVpkR+SYFcdevjTa7RMOqO8fs4KKom7yiBahhcx9iRDvWq75AjDcqVl+cOaFwPRClaXHksTCy4VZrXkVwrmPQXbODOSsSXQA0fFcJTM3qCdeshO9NTQTJrkeXVfPnOREs6OmCx0DBhYgLtaYeWemYypfLFh4ktUZDkL15ixfEpuJT47GJAlfWqH6Yroassa8EWgRiUOOU75oJjBtjbE6U8H0tcLEHm9abCY65VMbCqChexi9I84lHdPzz44ve5GTKC5T3KKP28WpUg1ZTRk5QE6piVqFOlVXkqnaAqy8WfgcCmpb7HJLSakMNRTogWk3AZu+ZlhKpjNHUh3rFlBPtmz2bUaOMOHDbUTdp4TG3hEcaxnQLu+2vB7n3A2ce0+qpUgqtkbm6GapdBaXKW730jcSgC9gcBkzFoa2DaRyocWLP1Kg8Rop5b1mYZ0bRbZdytsR+cmmhECG91fM/CueCyy41FRTJ8pkvvxN9wBb7BrEc4CqLYJ1HpckRtkYIXuKIj3EeMUGZSzlYtF7A3URrlLcnQM+9PrcuSr60ZZ+7G/oHdugN3Kv98ag9oCJay12zbgE+6bdEvu7PK5dy/0grzdmVqGZy6w/ycNYDifF4OSqm+LMOhyjd8SPYY8i3MzjcWlODPE4Z240tP5hKidsSPz8nVPYXdsds71zcBRDllY/miAUzxUGTmdvjl9WjSRfW1cNTp5oHUBh+giK3PiMikRcJXoj97qhYSqKUXroPV7401QsICJh5t/UZer7a9U7+1zxJwMnVOvGy68ABlq121CvTCxu3gp8NXguhk2u0GKVF3bVo2NgFMa6FB2cmrnqAMEww4enOrG+Kvr+fW5HHdI8hHsudmKGqXvQHOAlMj1wmtQJUQpcpSKJNPy8SWTAF0Cz3vJdceTrHhrFtrOD8Kvl+9as08Bq1StuEAYhja6ictEDYwnvpfqNxhrLlfiqmyOKn5HH2M1qdHBShd7s2eqdlwO09Pm0F4AwhR0zV5MlgzZa5yKeMflpQy9+t7M+4fatwpiQpjhZ+IPJa0sLVyluAKp3STAcRn+SXCiHm/tR12Uwgb1K9rw9WefgaPnV6M3QmIarpngNvGbHRa9DkRRovFStsTsK0RTilGLjKs5aHLeaK+EvR1qx3eSEGmeRHZPJ1+PUO0qc4d3j7Wjr96Ws/ZrOQeyp68GwP76rx9aZkzwcUIKNzc6Tcbp9EEea+2N6VX8ojB01XegW1zvsHvZjR00X/Bq9r3LxANJRdv1l6oNN8aJKeguXYTStAIGSRcBmtVXe1HzcJi6Dx4J3S6rf8kCUlB/aY+5mteHt6WhzP/bVWVzk2RFUTsA4cZW4wcfuBFJ47kjA+vGN+EN4bkdtRJe4HVcpblL5BABDo4KlGGYs0mP6AiEMiFZ4+4DQ27eLvf6gT73n3VPXE7OqiLYwRnzJakpY+MMYi8mup1mvGYvb4wXO/67x8gCw9FphOa7CWZFBwu7sKtWiqq4qszMhLSqI8atXUu8qcX7NyeQSDjM09+q4LG3mTMcgOgf9qgO3WjAAo8EwajoHEUryzes6xS1Y3MpfhJOyr74XB+p7EWIM+xt6cUaRX8LrEXbUO4nGXZpCXQ09I8bDAOUSS+3ETDDRjioxjFnXSn6FsByXxxOx2AczletcGkigREbjuK35uN2gt8NhFueVWzuc0+04rVvstOh31Xbjxd0NSVXeVjja0o+2/lHUdRtcH8AmXKW4BcYSTTHxnz80dkP4gmGMioo0FNEnQnmv+Dcs084MDIMqYU5NBasRysjXlUJCuHkoarv8JvWHwhH3TMwjvOiK+PkfREVs+PlPSFHoP1wtvSOo7VIkXBIHNU0/liblTPWrPAPDh6c78cT2GgOddbSsewxYaqm2ihM5uzUdg3hpT4PuNQozoGfIj3qjY0RqiNFanYOC+yNZIYqWH6kU3bKuUtyk8HHvqe3BJzWxD8QHHdk4MvXa2P1VLO6WPh8ONfWhB9H+3YaiDagfzsCOmi7VEWnl/RlxIahc4b0yF4yq31ysLMwY6ntGEAyFEWZszBdv1uJ2EAZCTYfCepC5SgwpV4tJplJucS/7HM50CJ2WobcsaZ1LInxwqlO/rAqMMeyv7zHxRqd3PuOf60Q6xj8dbEFTzwhCOq+sYcbw7Me1eHlfo6E6/aFwdITGpq/FZs40gXLgsW8kgNPt0TNZ7cz34vaFFJIGQXrmhZOrHapFwvp8sv0A2cHIdhsWe+yWRWMZyZrn3QgA6BdXeVcL7xnwjQ1SMMRaS4wBmDJb81jUrmlrvw81nUPY39CLk20D2FvXI/jtFS6F+u5htKZwlH4gt0r4ULY4artxi9FaHHeqfdxsylxzO6z8PLD+y5Yf4NZ+H7ad6MBfj7ZZ2j+ZGHExhk2ch+4hP/bW9eCF3bIwwqzCSMpYOxTs8zvr8MdPW6K2pTL22k5cpbi1okpiIELQM5YRr2vID8w+N2Lt1nUPYzhraqQsEH1TjeZIoXpMXiSKlj6l4ozO4McAYMFlMTMopVJqN4jkwgkEw+gZFjqNnWe78dGZ2LeKs50GfGYOrfzhyywGu/B+fNqXLbyNyBav1Xo2ox40i3HcqX6omOz4DCmOtEwhe6DR+hXHFwyNDbQng0TOriS7ngI303+daBMs4a5B/SgOUzIrHuTRgLPx1qm8W12luImEG6S5bxQ7aro0yzEQwhQdFheedS4afGPK/FCHYGmrPX7xHsrTJRdGfR8sjJ1NxhgTfNOKGZTxjUzCkD/6QT3aYmG5tA3/CKwWpsf3Dvvx8N9Oom8kOta9d9hvIrxJNi7AhFH2d4+34+MzXZHfTFvc4y7SwZq8Tr4pRFvzOtkBDYhuh5x6nasZi9utWD6EJB+6qxQ3ICiHhp54I8mCVT4iW4X6UPMgGrOEQcCR9CKcCQqWkGTNyC+IdPONWcfRdOZGDyaGPBmxrpJ4xyEvIFvMgIFwuMmYog7rmTe5pZHXykbxfHUMjgrJ/kWe+agWv/m41lBbUe0yIcwJEOJbTd/NMgvdym52YMV9wZhMLZkQfbyoK7nSNTv7TzqdeqfVlkmoFogX62TVldXW78PBxt74BVOAqxQ3AeJToP/USJch4BnLkdw9EgCJF0iIUWbwBULoF2O63z425kf8tKEvqibGhFjwhm710XC166627fXAusisy6ifC2foJqXSegN483CL6nYtahd9OWKF66HvkqDYV/pwGEOjIQtREamzuEeDYd2BNDXipVvwBULY39AbY1k6OUgVXXVi51NeV73GvZ4IKbe4NZq3KtbvdtbjnWPaa9DymZMiksqIfz6EG7gvS1hP8VjZleJA49gr+nBGCQ43G7Ns3+ufjl1DFWiUxYxGKykme2Ykt4HwV64czlDV2B5SJEmYISj6iQVXhvGH71Sb9jqILX0jgjUsI5RmIG910WyMBsMYyNBYEgyxN+RxyZWj4+NW1BApb4aYSJ4EHozHtp3Bq/uborYdauzDR6e1oz+Y3N+g0vbOs9041TaAdsVCGkbFtHI8xncxd67jXZqDjb2qvne9Y5Cnwkl1aKccI5LouU8DoXD845nM2QEljFp2TQVr0J0zByPpU9DXMYTpMl/sQGYFPqm4Feuafhu3ntac+cgfbUPJ8Bn0Zc2IlYcBx8quwtTBYwhRRmQbALx5qAUdZVeqHIPAK/ub0NA9jOxAD1b5gmDpsccmPUTxrn3fcADBcBgleZl4YVcDinMzcMe5VXGPL4qSeXgi/HcIZ0UreJI1rhRjMJInxuzMSbPhgMZv/vquYZQHQshK1w6lVL5BSW9dm+fHX+RCb3BZ+RArr9uwP4icDOOPlp3vJc9+dBYhBnx5yxwAouEQZshIM56uoGNgVNPSNOrjDjPAq3FgjDGcLrkIQxnR1+GDUx2oLMzC/PJ8W+c0JdqJvLCrHl6PB7dsnBW1nUUZdMnFVYr71Iy/R3FhAQKDARSP7gMA5GZ6UZKbiZLcDFk+7DGLbiR9SmR/5TkMeIUp57409eTocmUl7TuUHpuuNQxgMHMqBjNjrdSajiGEs2fG7iM+5JLyCIsvN3L3jlme/ugsAODblwiDpUYHHvuGAzjc3AeCEOMeVlnRPZRRAAAYyiiJ0kRE0oxWoUM0olxHAkH0DfpgNuZF+XzpPbwv72vEOQ292DRXSAEbCjP8bmedyRYV7dPYQ679rMcKpTwnNR1DWD7dnoT8gjzGFY8UrSTxp0MtON0+iOvXTEdFQZZOG2MoXUzy41PzPhEJ50v+U5gxeDW0GmNAZ27sgP+eWmEuxL2X5keVNYN0LPL5FIn63jvjRL4AyR/ncJXiHs0sQTA9E2fyqnEmeyXWNz6LldOFAUj5zdWdI8Tb3vOZ+fj5u6cBANOLsoHe2Ff0QxWfi4r5lhMSFRiDF7qv9xo+7rquIU2/njIGfTS9EDXF56M7e3bU9hOll8U8KHum367rbzV7I/7pUEvc7G3B/Ok4NPXvMJRRimIW/cCQ7E3GSBrU9/sqUNBzGCWMYGbBMb2a+30BFGRp19Y/EjD0gOm2HzWAbbywG7wCWm+pp3q7bsYAABfFSURBVMW0EK/tb8JXLzAZp67WjsrBktihR1vc2ifFqdPFAOw404WdZ7vxTVle8VSHmTqBu3zcYs8dYkIkR0v+CmDWRmDLvaDVN0derdpzF+H2TbOR5vVg45xifG7tdHx+/UxMK8pEZWEWwrKZiEMZpQh61S2N0yUXoaFwPYYySqOsbyUtKvm5/cEwXtnXpFJaIBRm6FNYP+15ixH0RlvcPdmzY2ZuBr1ZCHmiV26X+xvlij4o2/dk64BqtIBe7hb5gziUWSb6sRUWWLrw5sLIg9cPNGvWJXGiYBN2z7gTLMEZoUdkYxRPfXBWt6zdj6be63Vd1zACIeuKe8QfirpOyt3l94Odx6Ulpxn51YqKE5ajFbdO0IrauX1pd4NxIRREDAuGyFu5/Bkxd330CzNTvbtzuMriFl7JGcoLMtHeP4p5m64DZoohf8VzUXbeF1HgDeBybwFK8gTFdq7MX7n5vEuAYz78uXmWSu2xBLw5aCqMv8p4r4rfW3JbaNE15I9kLYwrR0gYwNSyDEb8ITy+/Uzk++/3jt3ktV1jE3WCYYYPTnXg4iVTowbh9NxwoTBDmsIZqZSidtpnEeo4E9PpaEIehDwZpqMMlA90c2/88xcKC+9LdqMnOQNwsn0AyxZK380d5+PbzyAvMw1XLFd3JgUtdQoGpryb3C7RNxwACrXlURujiZrwFgwh3eOBxyNNhouto8mGZFJhJhuHUByVU29Fw3lV8OAIgllmFgdPHFcpbilqITPNi+lF2Vg1M3qhglVV2pEQAIQps2tuxZyMVkwvysbskhyEGfD0h/pKVo7ylbO5YFXENWMGwzmkxbu+fWA04uOTEwjFLiLR3j8aU05Cmtyz6+zYbEyPjtslGGZIU2i+3uFA1GQelp6HjrxF2segAWOCMu4c9KMsPxOMMRxq6sOSygKke2Nf9qw8W5829sLIMr1GiDKm4ggTjoqgMN+WPPGZ8urEdnj2jIBpvUXEDLYqrkRzny+iuNUukuBP1naV/Nd7Z7CkMh9XLK9Urd8uGMY6Ba1OJOE2FAb3QNFinJxRhktyymxrwwiucpUAwskIhcORFK1WuHxZBZZPL0R+VjoKs9Nx26bZ+Pz6mZhz5bfgr74L1VVTYvbpyF0AvzcXs5cL6zTmi/7UEJnx0lpHy+L4xbun8WGcBEby6AmvipLWG+TTuqmjFX/0b28fbVN9tZVCH6UqQ4xhb10PfvtJHVr7hDwt7xyTZmPGEu/5eudYbE4PaaKQHeFnDCziAvnzkVbVMoOZwgM6mlsh289g/QYLyl1bRgNklahN3pJvIY3t8dCPKpG3L5YXj+VYy1iyJyPnQS91hJLBHOGNOJyWFSkfrxM+2TaAOtnbqtEoFjVpQp4MYzvbiKsUNwE40z6I5l5fzOt7IpTmZWJ6UTYqps3EBasW4rwFsb2jPy0Pp+bdgeJSYcZlTuaYGbplgfOvQXrKOd5kieOtYw/FybYB7K+Pttz1zmQwHHujK1Fa7Iea+tDUO4JPZaveMzD86VBLZLAYEMYBpA5pcDQY8esOq6TqDCozxalwsFE7Ll9L/MYe4xNN/MFwZCyhc0D9raYvawb2Tv8CRgrG3sIk5bR/2s04UPl5zfqVYyUfn1G/5qGQhU5IcY3MrKVpps/TiioBojsLySBQK59oHzs4GsTu2u7IeW8pPRf7p92McHpepO5wVOc31gE0dAvX4E8HW3THqLSQGwipHJR2latEfu/FSz6TKDOmZEemigPAzOIc3LBuBoKhMJZU5mONdwq6B7LRwIAV0wsjivX8haV4/6T5FJ5KjpZfjZLhM/ELxuGMMgUrgG0notdojE2YNUYoxMAY05zae7S5X3Pfd4+PxfoyNhbBID008un2Xg9BGl+V7ndfIAR/KIyCrHQ8v7Pe0rJR0huR1pvD7/c0YkllfpTFp8UhRSoCXyCENA8hTeHWCXhzwBiws6YLH5/pwpfPE2KmR9MKImWUfl1hW3THpOXDD9mgHNTOh+bgpAmbWyuqRFm/1L4yYmpwNIiAien2ajK/dagFjT0jqCrJRVl+JkCeqHMvb1/5WTmpaHA0qDrDVmslHLWjF7YnV4u7SnHLe2xlwiS7ubF6Jh7+20mkewlZ6V5smifEA6d5PYIvruYk8opzMGvODCDdixvWzcCwYqaipPwLstNx/oJSvHEwdor6qpmFsin2QgfR0D2M/qxp6M+aFlPeLHqK1Qh763qwqCLf0EBgIniJIh3zidYBXLWiEv+zqx69wwHce+lCU0pbUh77pt2CEKVh9WhQV8EplfaJ1gFVV5xyjOGxbULHWpidji+JE1rkSC4fNbeE4NctwBXLK+D1EEJhFjXoGHU8ss/BkPmp+mqoWtwGo0p0Z0eqbFONKlGxfAHgV+/XaFduECmPvVS3escx9lkYa1GvS5JHOVAczz2ZalyluOUWyewSlfUabeau8+fC6yHd2XcSM4sFeeQP1d+vnYHjrQOYPiUbBVlp2DCnGAvK8/D8zrEcw1vml2Hd7OLIAOmlS6bGjUhJJoea+mKmcDsBUaz11TtsvnMe9gfx3nHhjcKfJsTnv7S7AVeuMD7d581D5nLAqBkRUcpWOWFF/HqspR9XLK9Amqi4/SH19K1Nsje/n797Gjetj53QpSbTEXFSlRpq7halVbjrbDdyMryYXz42z0FIrKTtknpuRx2+ftF8tPSNYDQYxsKpY7Mc1azcZLoT5MfnVNhedLWp85W4SnHLX2OuXpm4NRqP3Ezzh+/1EG7ZOAsFWenweAhLp429oqlNpU7zEAqz07GksgB9I37DvnspJDIZdA8l3o7cbaJGmEVbnH+RDf5Jy1QZ4YntsRZb30ggseWyDCJ/UPtlyvy5HdEzNuWujlf3N2K2+FnpKtFCLwb54b+dxOpZRWjuHUF7/yjOgTr9vgAaFP59pS6TQkbnlY0p7t/JjA4tRvyhiH944aX5EYs3anAy4uNOTLkFQwzbT3bgnLnFyBTDn7TyimgNSJqR4VTbIK5Yrv27WybzuEpxyyc1ZKS5atw0iqkaU4eVbJpXEvFxSq9i8s5p07wSLJ1WAF8ghOc/iX5gLl0yFZlp3hjrvCgn3ZKlqkfAymCYgniv92c6BqNmPspdPErFZwWtSBW7ON7aH+VOOt2unQBMfi5qO4dRISpso6lU453LA/W9KMrRj3Z6bX9T7JuA/LPBWY6qyPRmOMxkcdxj9ew6243LllZEDxKaaEeq80hzH1r6fPAQYoIKYlw8ss8xg5Nxmv7zYcGQCIaZrpxmQkadxJXa8ZpVzlvbcbEhy805Yh4NOfL45XPmlqAgKx3l+VlYXCHkZ5BcREU5GShUPJxXr6zEP2zQnlw0vch6HhSn+bShz9K6jG7hrUOt6DDoUtJShPvrew0pb/kg6dnOocit6JOt6KLlL4/8Hkf5y0VUjt3IGUkvimThlJD79If8QQyIqZO7ZOMUNR1DeO9Ee5QVPmBh4V8pomlPbQ/a+n3o9wXGMnMyhpa+EQ1XzVgdZkNF/Spr0GrVY2cyLDO4UnFXFhqzaN3KmllFmr9JAznTp0Qr2Xmin/G8BWW499KFkTeOwmxBed+6cRYWTM3X9cdLA6yAfga8y5cZ9wdL7XOMo6fgX9sfPwRNbs3/5UhrJDZfvpzdoAUlKFc8+2QhozUd2m8Pn1Z+HsfKPxu1bUT21vhrWSqCHYq3nsae4ajJb385rB4br5YHX1LY8kHk3+2sx1MfnI24EP92pBUv7GpAqxg1FT3jdOxzS5/PlItDmS55rM7oDk8+MS7Z1rerXCUSRgYL3cyFi8px4SL1tQiJCHecW4U8hX994dR8VF2UG+MiUotm+PYlCzASCKFjYBShMMMfxPwhM4tzcO+lY6v3SD7ML22Zg2F/EO39o5hTlouCrHRMK8rCMx/VijIBd18wD4whamp9upewuCIfO892Y0pOeiTz3BXLKzC1IAuHm/oiq9uPZ0bSi5AdsG+lkxOt2qGHVqZ2tw/4bHlQ5bpF7vYx62Z60WBekaHRaAXYqLGy1da9savCS2+menMYlJkQ35ItPCItoAIIFvQnsqUQe+JEMGm9gQTC0Wkp3jrUirlluZE2eob8mJKbnMk4rlLcFy0ux9nOwYRmTdqOA11pscbFNerXJyLkZKRhdolw+ZZPL0RBVuylXDmjEHNKc1GYLcwgrSwcs/ILs9Nx8ZJyTCvKRmneWEKrb128AM/vrEPnoB/XrJqGkrxMdAyO4rKlFchK96B/JBhx4WyYU4x+XyBmwYfr10zHtKIsfFLTHTP1/4JFZdiuiDPX4vyFpTjQ0Bc1EOgEh6deD2/Y2XkDiVA3lIF5gGaWS6PYMZaQDB7+28m4Pnw15I/qHz8dS4amvN+ejbOcn1YMd+egH1MUckljVttPdGA7OnBj9QzMmOJ8RJwhxU1EVwB4BIAXwK8ZY//hhDCrZxZh9UxtNwNHnUuXqudwuXiJdm4XIsLKGbHn2uMh3LBuJhp7hjG7RLAmrls95uOU+92z0r24euU0/OVIK4429+PKFRWYXpQdSRewZX4plk0rwHM76uAhwiVLy7FsWmHkQTpnbgky0z043iKEVIYZw4F6wfI9f2Ep1s0uRkVhdmR6/ZLKAhRmp0espzWzirB8eiE+Ot2JGnEiUkF2OhhjEb+rERZOLzE0QccIFy8p113uSiIjzWN4sLIjdyH8abnoy5wev/AEwe4BeDPUqExqA4Sw041zo/P1K+c/tPX73KG4icgL4JcALgXQCGA3Eb3OGDvqtHCc1JCd4cWCqfnxC4pcsmQqzp1XElHYEl4PoTQvE//rwnnITPNEkttvnFOMyqJszCkVOoa1s4TcMcFQGDOn5GBuaW4kGmd6UTZuWj8TZzuHIn77uWW5+N3OehTlZKA0LxPXrZ6Oh/92EhlpHnx5yxyc7RyK+JKLctJx6dKp6BgYxZLKAmSmefCbj2uxfk4x/nqkDR4iXLG8EuUFWdh+ogO3bJyF/Kw0PLG9BhWFWRH/KSC8KQXDDEsrC6JeveUUZqejqjQHtZ1jr/ghT0aMRf+1C+fhjYMtWFJZgP31PapuhI1zi7GzphsgUl2ZCRDyuZcOn1b9TQspffLfr52BT2q6otw3uZneKBdHupdsiTpSI81jLL97qplXnocz4rjDzhp1a1yif8T82IMVKN6IKxFtAvAgY+xy8fsDAMAY+6HWPtXV1WzPnj12ypl8+puBvb8B1t0RtXI6xx30DQeQn5UWUfAN3cMoEF1CoTDD+yc7sK5qiu7iC239PmRneFXL9A0HkJ3hRW3XEI63DuCiRWWRjokxhhNtAxjxC0unleRloKXXhyrRLRUMhbHzbDfK8zMxrSgbff19SGNBtAey0O8LoH8kEMmUJ9HSN4LuIT+WVBRg+6kOhMMMn1lcjv0NvZhakIXinAz0+wL465FWXLq0AvXdw5hfnod9dT2RKJRLl05FeUEmPj7dhY1zi1HbOYzT7QPo9wl5YrIzvPjH84QcK2c7ByPx2yfbBjG3LBdeIuyr78EHpzpx5YoKjAbCWFSRD6+HcKJ1AMumFeBwUz9OdwygICsdq2cW4WTbILqH/KgozAQRRd6mFkzNQ+fAKOaW5WFuWS5qOobgC4Rw7vxS9Az5kZ3hRUluBt451h6RvzA7HcW5GVGDsBKb55eisWc4shi3Hosr8qPy90hvN6X5mVhQnoemnhHMmJINXzAc5cpTC7UtycvA7Zuq8PDfTuq2mZnuQWluJnqG/fji5jmWwpmJaC9jrNpQWQOK+wYAVzDGviJ+vw3ARsbYN7T2mRCKm8MZJzDGUNM5hLmluVFLdlkhFGboGBhFhcXIrrZ+HzK8HlODdIFQGCOBUKQDbegeRmFOOrLTvVHhs75ACLvOdiMvKw1TcjIib2wA0Dvsx5HmfswqzonMcu4d9qMwOx0kWxxEfn5CYYbWfh8GfUHMLslBVroX7f0+5Gamob57GIum5kcMg76RANK9hLOdQ2AMWFSRj55hP5p6RlBZmI2Kwix0DY6iZ9iP+eXG31bl2K24bwRwuUJxb2CM3aModxeAuwBg1qxZ6+rqxsdACIfD4bgBM4rbiD3fCECePGEGgJj1qxhjTzLGqhlj1WVlyU0qzuFwOJMJI4p7N4AFRDSHiDIA3AzgdWfF4nA4HI4WcaNKGGNBIvoGgL9ACAd8mjF2xHHJOBwOh6OKoThuxtibAN50WBYOh8PhGMCVuUo4HA6How1X3BwOhzPO4Iqbw+FwxhlccXM4HM44I+4EHEuVEnUAsDoDpxTAeMi4z+W0Fy6nvXA57SUZcs5mjBmaBOOI4k4EItpjdPZQKuFy2guX0164nPbiNjm5q4TD4XDGGVxxczgczjjDjYr7yVQLYBAup71wOe2Fy2kvrpLTdT5uDofD4ejjRoubw+FwODpwxc3hcDjjDNcobiK6gohOENFpIro/xbLMJKL3iOgYER0hom+J24uJ6G9EdEr8O0XcTkT0qCj7QSJam2R5vUS0n4jeEL/PIaKdopwviul4QUSZ4vfT4u9VSZSxiIi2EtFx8bxucuP5JKJ7xWt+mIj+h4iy3HA+iehpImonosOybabPHxHdIZY/RUR3JEnO/xSv+0EiepWIimS/PSDKeYKILpdtd1QfqMkp++2fiIgRUan4PWXnUxPGWMr/Q0gXewbAXAAZAD4FsDSF8lQCWCt+zgdwEsBSAD8GcL+4/X4APxI/XwXgLQAE4BwAO5Ms730AfgfgDfH7SwBuFj8/DuB/iZ+/BuBx8fPNAF5Mooy/AfAV8XMGgCK3nU8A0wGcBZAtO493uuF8AjgfwFoAh2XbTJ0/AMUAasS/U8TPU5Ig52UA0sTPP5LJuVR81jMBzBF1gDcZ+kBNTnH7TAgprOsAlKb6fGrKn4xGDJzETQD+Ivv+AIAHUi2XTJ4/QFjl/gSASnFbJYAT4ucnAPyDrHykXBJkmwHgHQCfAfCGeHN1yh6UyLkVb8hN4uc0sRwlQcYCUSGSYrurzicExd0gPohp4vm83C3nE0CVQiGaOn8A/gHAE7LtUeWcklPx298BeF78HPWcS+czWfpATU4AWwGsAlCLMcWd0vOp9t8trhLpgZFoFLelHPH1dw2AnQCmMsZaAED8Wy4WS6X8PwPwPQBh8XsJgF7GWFBFloic4u99YnmnmQugA8Azokvn10SUC5edT8ZYE4CHANQDaIFwfvbCfedTwuz5c8Nz9iUI1it05EmJnER0LYAmxtinip9cJSfgHh+32tLUKY9TJKI8AC8D+DZjrF+vqMo2x+UnoqsBtDPG9hqUJVXnOQ3Ca+ljjLE1AIYgvNprkarzOQXAdRBe26cByAVwpY4srrxvoS1XSuUlon8BEATwvLRJQ56ky0lEOQD+BcC/qv2sIU/KzqdbFLehBYmTCRGlQ1DazzPGXhE3txFRpfh7JYB2cXuq5N8M4FoiqgXwAgR3yc8AFBGRtLqRXJaInOLvhQC6kyBnI4BGxthO8ftWCIrcbefzEgBnGWMdjLEAgFcAnAv3nU8Js+cvZc+ZOHB3NYBbmehXcJmc8yB02J+Kz9MMAPuIqMJlcgJwj+J21YLEREQAngJwjDH2U9lPrwOQRo7vgOD7lrbfLo4+nwOgT3qFdRLG2AOMsRmMsSoI5+xdxtitAN4DcIOGnJL8N4jlHbcQ/l/79q/SQBDEcfw7lWKnhbUGxNbCwsJCEIJaWNuKD2GRyocQ7C0sbGwtfAGxECPinysELfIENhZjMRMSgoIKyd3C7wPLkb0rhuF24GY37t4D3sxsOac2gQcalk+iRbJmZjP5DvTjbFQ+h/w1f5dA28xm8+uinXNjZWZbwCGw6+4fI/Hv5emcRWAJuKaGeuDuXXefd/eFXE/vxAGFHg3LZz/gRgxi5/aZ2E3u1BzLOvHJcwfc5tgh+pdXwEte5/J5A44z9i6wWkPMGwxOlbSIBVAB58BUzk/n7yrvtyYY3wpwkzm9IHbhG5dP4Ah4BO6BU+LEQ+35BM6IvvsnUVQO/pM/osdc5difUJwV0Qvur6WToec7GecTsD00P9Z68F2cI/dfGWxO1pbPn4b+8i4iUpimtEpEROSXVLhFRAqjwi0iUhgVbhGRwqhwi4gURoVbRKQwKtwiIoX5AiDMV+DJNeiFAAAAAElFTkSuQmCC
"
>
</div>

</div>

</div>
</div>

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[22]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># helper function for viewing a list of passed in sample images</span>
<span class="k">def</span> <span class="nf">view_samples</span><span class="p">(</span><span class="n">epoch</span><span class="p">,</span> <span class="n">samples</span><span class="p">):</span>
    <span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">16</span><span class="p">,</span><span class="mi">4</span><span class="p">),</span> <span class="n">nrows</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">ncols</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">sharey</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">sharex</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    <span class="k">for</span> <span class="n">ax</span><span class="p">,</span> <span class="n">img</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">axes</span><span class="o">.</span><span class="n">flatten</span><span class="p">(),</span> <span class="n">samples</span><span class="p">[</span><span class="n">epoch</span><span class="p">]):</span>
        <span class="n">img</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">detach</span><span class="p">()</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span>
        <span class="n">img</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">))</span>
        <span class="n">img</span> <span class="o">=</span> <span class="p">((</span><span class="n">img</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span><span class="o">*</span><span class="mi">255</span> <span class="o">/</span> <span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
        <span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set_visible</span><span class="p">(</span><span class="kc">False</span><span class="p">)</span>
        <span class="n">ax</span><span class="o">.</span><span class="n">yaxis</span><span class="o">.</span><span class="n">set_visible</span><span class="p">(</span><span class="kc">False</span><span class="p">)</span>
        <span class="n">im</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">32</span><span class="p">,</span><span class="mi">32</span><span class="p">,</span><span class="mi">3</span><span class="p">)))</span>
</pre></div>

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

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[23]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Load samples from generator, taken while training</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;train_samples.pkl&#39;</span><span class="p">,</span> <span class="s1">&#39;rb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    <span class="n">samples</span> <span class="o">=</span> <span class="n">pkl</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
</pre></div>

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

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[24]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">_</span> <span class="o">=</span> <span class="n">view_samples</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">samples</span><span class="p">)</span>
</pre></div>

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

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


<div class="output_area">

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


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

</div>

</div>
</div>

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

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p><strong>Answer:</strong> (Write your answer in this cell)</p>
<p>The generator is capable of creating images that could be recognized easily as human faces with the following weakness.</p>
<ol>
<li>The generated images are noisy.</li>
<li>Most of the generated images are white celebrity faces which is a cause of the biased dataset.</li>
<li>The generated images contains adults only, no children images are generated due to the biased dataset that doesn't contain children images.</li>
</ol>
<p>I think that training on more faces images of different ages, colors and expressions will result in more variety of faces that could be generated. The human faces are complex. So, I believe that using a deeper network with an increasing number of epochs enable the model to learn more features hence generates more realistic face images.</p>

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

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

 
</html>