Image Classifier Project.html

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

<title>Image Classifier Project</title>

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  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 */
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<style type="text/css">
    .highlight .hll { background-color: #ffffcc }
.highlight  { background: #f8f8f8; }
.highlight .c { color: #408080; font-style: italic } /* Comment */
.highlight .err { border: 1px solid #FF0000 } /* Error */
.highlight .k { color: #008000; font-weight: bold } /* Keyword */
.highlight .o { color: #666666 } /* Operator */
.highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
.highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
.highlight .gd { color: #A00000 } /* Generic.Deleted */
.highlight .ge { font-style: italic } /* Generic.Emph */
.highlight .gr { color: #FF0000 } /* Generic.Error */
.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
.highlight .gi { color: #00A000 } /* Generic.Inserted */
.highlight .go { color: #888888 } /* Generic.Output */
.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
.highlight .gs { font-weight: bold } /* Generic.Strong */
.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
.highlight .gt { color: #0044DD } /* Generic.Traceback */
.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
.highlight .kp { color: #008000 } /* Keyword.Pseudo */
.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
.highlight .kt { color: #B00040 } /* Keyword.Type */
.highlight .m { color: #666666 } /* Literal.Number */
.highlight .s { color: #BA2121 } /* Literal.String */
.highlight .na { color: #7D9029 } /* Name.Attribute */
.highlight .nb { color: #008000 } /* Name.Builtin */
.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
.highlight .no { color: #880000 } /* Name.Constant */
.highlight .nd { color: #AA22FF } /* Name.Decorator */
.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
.highlight .nf { color: #0000FF } /* Name.Function */
.highlight .nl { color: #A0A000 } /* Name.Label */
.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
.highlight .nv { color: #19177C } /* Name.Variable */
.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
.highlight .w { color: #bbbbbb } /* Text.Whitespace */
.highlight .mb { color: #666666 } /* Literal.Number.Bin */
.highlight .mf { color: #666666 } /* Literal.Number.Float */
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.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 */
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.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
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<style type="text/css">
    
/* Temporary definitions which will become obsolete with Notebook release 5.0 */
.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; }

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<style type="text/css">
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<h1 id="Developing-an-AI-application">Developing an AI application<a class="anchor-link" href="#Developing-an-AI-application">&#182;</a></h1><p>Going forward, AI algorithms will be incorporated into more and more everyday applications. For example, you might want to include an image classifier in a smart phone app. To do this, you'd use a deep learning model trained on hundreds of thousands of images as part of the overall application architecture. A large part of software development in the future will be using these types of models as common parts of applications.</p>
<p>In this project, you'll train an image classifier to recognize different species of flowers. You can imagine using something like this in a phone app that tells you the name of the flower your camera is looking at. In practice you'd train this classifier, then export it for use in your application. We'll be using <a href="http://www.robots.ox.ac.uk/~vgg/data/flowers/102/index.html">this dataset</a> of 102 flower categories, you can see a few examples below.</p>
<p><img src='assets/Flowers.png' width=500px></p>
<p>The project is broken down into multiple steps:</p>
<ul>
<li>Load and preprocess the image dataset</li>
<li>Train the image classifier on your dataset</li>
<li>Use the trained classifier to predict image content</li>
</ul>
<p>We'll lead you through each part which you'll implement in Python.</p>
<p>When you've completed this project, you'll have an application that can be trained on any set of labeled images. Here your network will be learning about flowers and end up as a command line application. But, what you do with your new skills depends on your imagination and effort in building a dataset. For example, imagine an app where you take a picture of a car, it tells you what the make and model is, then looks up information about it. Go build your own dataset and make something new.</p>
<p>First up is importing the packages you'll need. It's good practice to keep all the imports at the beginning of your code. As you work through this notebook and find you need to import a package, make sure to add the import up here.</p>
<p>Please make sure if you are running this notebook in the workspace that you have chosen GPU rather than CPU mode.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Imports here</span>
<span class="o">%</span><span class="k">matplotlib</span> inline
<span class="o">%</span><span class="k">config</span> InlineBackend.figure_format = &#39;retina&#39;

<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">seaborn</span> <span class="k">as</span> <span class="nn">sns</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">torch</span>
<span class="kn">from</span> <span class="nn">torch</span> <span class="k">import</span> <span class="n">nn</span>
<span class="kn">from</span> <span class="nn">torch</span> <span class="k">import</span> <span class="n">optim</span>
<span class="kn">import</span> <span class="nn">torch.nn.functional</span> <span class="k">as</span> <span class="nn">F</span>
<span class="kn">from</span> <span class="nn">torchvision</span> <span class="k">import</span> <span class="n">datasets</span><span class="p">,</span> <span class="n">transforms</span><span class="p">,</span> <span class="n">models</span>

<span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>

<span class="kn">from</span> <span class="nn">collections</span> <span class="k">import</span> <span class="n">OrderedDict</span>

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

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

<span class="c1"># Test &amp; Validate transforms include resizing and center-cropping</span>
<span class="c1"># Then convertinng images to tensors and normalizing</span>
<span class="n">test_n_valid_transforms</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span>
    <span class="n">transforms</span><span class="o">.</span><span class="n">Resize</span><span class="p">(</span><span class="mi">255</span><span class="p">),</span>
    <span class="n">transforms</span><span class="o">.</span><span class="n">CenterCrop</span><span class="p">(</span><span class="mi">224</span><span class="p">),</span>
    <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
    <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">([</span><span class="mf">0.485</span><span class="p">,</span> <span class="mf">0.456</span><span class="p">,</span> <span class="mf">0.406</span><span class="p">],</span>
                         <span class="p">[</span><span class="mf">0.229</span><span class="p">,</span> <span class="mf">0.224</span><span class="p">,</span> <span class="mf">0.225</span><span class="p">])</span>
<span class="p">])</span>

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

<span class="c1"># TODO: Using the image datasets and the trainforms, define the dataloaders</span>
<span class="n">trainloader</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">DataLoader</span><span class="p">(</span><span class="n">train_data</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">64</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">testloader</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">DataLoader</span><span class="p">(</span><span class="n">test_data</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">64</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="c1"># Unsure if shuffling is necessary</span>
<span class="n">validloader</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">DataLoader</span><span class="p">(</span><span class="n">valid_data</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">64</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="c1"># Unsure if shuffling is necessary</span>
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<h3 id="Label-mapping">Label mapping<a class="anchor-link" href="#Label-mapping">&#182;</a></h3><p>You'll also need to load in a mapping from category label to category name. You can find this in the file <code>cat_to_name.json</code>. It's a JSON object which you can read in with the <a href="https://docs.python.org/2/library/json.html"><code>json</code> module</a>. This will give you a dictionary mapping the integer encoded categories to the actual names of the flowers.</p>

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

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

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Build and train your network</span>
<span class="c1"># Deciding to use VGG-19 with batch normalization,</span>
<span class="c1"># to balance the robustness of VGG-19 (compared to VGG-16 or VGG-13)</span>
<span class="c1"># with a potential increase in learning speed.</span>

<span class="c1"># Benefits referred from Jansma, H. (2018), </span>
<span class="c1"># available at https://towardsdatascience.com/intuit-and-implement-batch-normalization-c05480333c5b</span>
<span class="n">vgg</span> <span class="o">=</span> <span class="n">models</span><span class="o">.</span><span class="n">vgg19_bn</span><span class="p">(</span><span class="n">pretrained</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>

<span class="c1"># Freezing all parameters to a) preserve pretrained parameters b) to speed up later training of classifier</span>
<span class="k">for</span> <span class="n">param</span> <span class="ow">in</span> <span class="n">vgg</span><span class="o">.</span><span class="n">parameters</span><span class="p">():</span>
    <span class="n">param</span><span class="o">.</span><span class="n">requires_grad</span> <span class="o">=</span> <span class="kc">False</span>
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<pre>Downloading: &#34;https://download.pytorch.org/models/vgg19_bn-c79401a0.pth&#34; to /root/.torch/models/vgg19_bn-c79401a0.pth
100%|██████████| 574769405/574769405 [00:34&lt;00:00, 16512243.39it/s]
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<span class="n">vgg</span>
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<pre>VGG(
  (features): Sequential(
    (0): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (2): ReLU(inplace)
    (3): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (4): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (5): ReLU(inplace)
    (6): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
    (7): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (8): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (9): ReLU(inplace)
    (10): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (11): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (12): ReLU(inplace)
    (13): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
    (14): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (15): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (16): ReLU(inplace)
    (17): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (18): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (19): ReLU(inplace)
    (20): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (21): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (22): ReLU(inplace)
    (23): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (24): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (25): ReLU(inplace)
    (26): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
    (27): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (28): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (29): ReLU(inplace)
    (30): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (31): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (32): ReLU(inplace)
    (33): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (34): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (35): ReLU(inplace)
    (36): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (37): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (38): ReLU(inplace)
    (39): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
    (40): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (41): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (42): ReLU(inplace)
    (43): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (44): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (45): ReLU(inplace)
    (46): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (47): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (48): ReLU(inplace)
    (49): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (50): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (51): ReLU(inplace)
    (52): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  )
  (classifier): Sequential(
    (0): Linear(in_features=25088, out_features=4096, bias=True)
    (1): ReLU(inplace)
    (2): Dropout(p=0.5)
    (3): Linear(in_features=4096, out_features=4096, bias=True)
    (4): ReLU(inplace)
    (5): Dropout(p=0.5)
    (6): Linear(in_features=4096, out_features=1000, bias=True)
  )
)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Define architecture of new classifier</span>
<span class="c1"># with dropout to increase training effectiveness</span>
<span class="n">in_features</span> <span class="o">=</span> <span class="n">vgg</span><span class="o">.</span><span class="n">classifier</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">in_features</span>
<span class="n">flower_classifier</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="n">OrderedDict</span><span class="p">([</span>
    
    <span class="c1"># First fully-connected layer of linear transformation takes in 25,088 input features</span>
    <span class="c1"># as shown in the pre-trained structure</span>
    <span class="p">(</span><span class="s1">&#39;fc1&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">in_features</span><span class="p">,</span> <span class="mi">8192</span><span class="p">)),</span>
    <span class="p">(</span><span class="s1">&#39;re1&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">ReLU</span><span class="p">()),</span>
    <span class="p">(</span><span class="s1">&#39;dr1&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Dropout</span><span class="p">(</span><span class="n">p</span><span class="o">=</span><span class="mf">0.25</span><span class="p">)),</span>
    
    <span class="p">(</span><span class="s1">&#39;fc2&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="mi">8192</span><span class="p">,</span> <span class="mi">4096</span><span class="p">)),</span>
    <span class="p">(</span><span class="s1">&#39;re2&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">ReLU</span><span class="p">()),</span>
    <span class="p">(</span><span class="s1">&#39;dr2&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Dropout</span><span class="p">(</span><span class="n">p</span><span class="o">=</span><span class="mf">0.25</span><span class="p">)),</span>
    
    <span class="p">(</span><span class="s1">&#39;fc3&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="mi">4096</span><span class="p">,</span> <span class="mi">1024</span><span class="p">)),</span>
    <span class="p">(</span><span class="s1">&#39;re3&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">ReLU</span><span class="p">()),</span>
    <span class="p">(</span><span class="s1">&#39;dr3&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Dropout</span><span class="p">(</span><span class="n">p</span><span class="o">=</span><span class="mf">0.25</span><span class="p">)),</span>
    
    <span class="c1"># Last fully-connected layer of linear transformations returns 102 output features</span>
    <span class="c1"># because there are 102 flower categories</span>
    <span class="p">(</span><span class="s1">&#39;fc4&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="mi">1024</span><span class="p">,</span> <span class="mi">102</span><span class="p">)),</span>
    <span class="c1"># No ReLU in the last layer</span>
    <span class="c1"># No dropout in the last layer</span>
    <span class="p">(</span><span class="s1">&#39;log&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">LogSoftmax</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">))</span>
<span class="p">]))</span>

<span class="c1"># Replacing pre-trained classifier with self-built classifier</span>
<span class="n">vgg</span><span class="o">.</span><span class="n">classifier</span> <span class="o">=</span> <span class="n">flower_classifier</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># View VGG-19_bn again to make sure flower_classifier is in place</span>
<span class="n">vgg</span>
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<pre>VGG(
  (features): Sequential(
    (0): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (2): ReLU(inplace)
    (3): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (4): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (5): ReLU(inplace)
    (6): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
    (7): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (8): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (9): ReLU(inplace)
    (10): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (11): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (12): ReLU(inplace)
    (13): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
    (14): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (15): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (16): ReLU(inplace)
    (17): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (18): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (19): ReLU(inplace)
    (20): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (21): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (22): ReLU(inplace)
    (23): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (24): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (25): ReLU(inplace)
    (26): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
    (27): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (28): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (29): ReLU(inplace)
    (30): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (31): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (32): ReLU(inplace)
    (33): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (34): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (35): ReLU(inplace)
    (36): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (37): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (38): ReLU(inplace)
    (39): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
    (40): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (41): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (42): ReLU(inplace)
    (43): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (44): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (45): ReLU(inplace)
    (46): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (47): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (48): ReLU(inplace)
    (49): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (50): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (51): ReLU(inplace)
    (52): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  )
  (classifier): Sequential(
    (fc1): Linear(in_features=25088, out_features=8192, bias=True)
    (re1): ReLU()
    (dr1): Dropout(p=0.25)
    (fc2): Linear(in_features=8192, out_features=4096, bias=True)
    (re2): ReLU()
    (dr2): Dropout(p=0.25)
    (fc3): Linear(in_features=4096, out_features=1024, bias=True)
    (re3): ReLU()
    (dr3): Dropout(p=0.25)
    (fc4): Linear(in_features=1024, out_features=102, bias=True)
    (log): LogSoftmax()
  )
)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">## Train VGG</span>
<span class="c1"># Initialize optimizer and criterion</span>
<span class="n">optimizer</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">SGD</span><span class="p">(</span><span class="n">params</span><span class="o">=</span><span class="n">vgg</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">momentum</span><span class="o">=</span><span class="mf">0.5</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">NLLLoss</span><span class="p">()</span>
<span class="n">scheduler</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">lr_scheduler</span><span class="o">.</span><span class="n">ReduceLROnPlateau</span><span class="p">(</span><span class="n">optimizer</span><span class="p">,</span> <span class="s1">&#39;min&#39;</span><span class="p">)</span>

<span class="c1"># Define some variables for the training process</span>
<span class="n">epoch</span> <span class="o">=</span> <span class="mi">5</span>
<span class="n">steps</span> <span class="o">=</span> <span class="mi">0</span>
<span class="n">print_every</span> <span class="o">=</span> <span class="mi">25</span>

<span class="c1"># Device-agnostic code</span>
<span class="n">device</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="s2">&quot;cuda:0&quot;</span> <span class="k">if</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">is_available</span><span class="p">()</span> <span class="k">else</span> <span class="s2">&quot;cpu&quot;</span><span class="p">)</span>
<span class="c1"># Move VGG to CUDA if available</span>
<span class="n">vgg</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>

<span class="k">with</span> <span class="n">active_session</span><span class="p">():</span>
    <span class="k">for</span> <span class="n">e</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">epoch</span><span class="p">):</span>
        <span class="c1"># Set running loss to 0</span>
        <span class="n">running_loss</span> <span class="o">=</span> <span class="mi">0</span>
        <span class="c1"># Put VGG in training mode</span>
        <span class="n">vgg</span><span class="o">.</span><span class="n">train</span><span class="p">()</span>
        <span class="k">for</span> <span class="n">image</span><span class="p">,</span> <span class="n">label</span> <span class="ow">in</span> <span class="n">trainloader</span><span class="p">:</span>
            <span class="c1"># Move image and label to CUDA if available</span>
            <span class="n">image</span><span class="p">,</span> <span class="n">label</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">),</span> <span class="n">label</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>

            <span class="c1"># Feed image forward through VGG</span>
            <span class="n">train_output</span> <span class="o">=</span> <span class="n">vgg</span><span class="p">(</span><span class="n">image</span><span class="p">)</span>

            <span class="c1"># Clear out optimizer</span>
            <span class="n">optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>

            <span class="c1"># Get training loss by comparing training output with label</span>
            <span class="n">train_loss</span> <span class="o">=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">train_output</span><span class="p">,</span> <span class="n">label</span><span class="p">)</span>

            <span class="c1"># Feed training loss backward through model</span>
            <span class="n">train_loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>

            <span class="c1"># Take one step for optimizer</span>
            <span class="n">optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
            <span class="n">steps</span> <span class="o">+=</span> <span class="mi">1</span>

            <span class="c1"># Increment running loss</span>
            <span class="n">running_loss</span> <span class="o">+=</span> <span class="n">train_loss</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>

            <span class="c1"># Evaluate and print results every 100 loops</span>
            <span class="k">if</span> <span class="n">steps</span> <span class="o">%</span> <span class="n">print_every</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="c1"># Put VGG in evaluation mode</span>
                <span class="n">vgg</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span>

                <span class="c1"># Turn off gradients for validation to speed up</span>
                <span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">():</span>
                    <span class="n">accuracy</span> <span class="o">=</span> <span class="mi">0</span>
                    <span class="n">valid_loss</span> <span class="o">=</span> <span class="mi">0</span>
                    <span class="k">for</span> <span class="n">image</span><span class="p">,</span> <span class="n">label</span> <span class="ow">in</span> <span class="n">validloader</span><span class="p">:</span>
                        <span class="c1"># Move image and label to CUDA if available</span>
                        <span class="n">image</span><span class="p">,</span> <span class="n">label</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">),</span> <span class="n">label</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>

                        <span class="c1"># Feed image forward through VGG</span>
                        <span class="n">valid_output</span> <span class="o">=</span> <span class="n">vgg</span><span class="p">(</span><span class="n">image</span><span class="p">)</span>

                        <span class="c1"># Increment evaluation loss</span>
                        <span class="n">valid_loss</span> <span class="o">+=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">valid_output</span><span class="p">,</span> <span class="n">label</span><span class="p">)</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>

                        <span class="c1"># Accuracy</span>
                        <span class="c1"># Take exponential of log-softmax to get the probabilities , </span>
                        <span class="n">ps</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">valid_output</span><span class="p">)</span>
                        <span class="c1"># Class with highest probability is our predicted class, compare with true label</span>
                        <span class="n">top_p</span><span class="p">,</span> <span class="n">top_class</span> <span class="o">=</span> <span class="n">ps</span><span class="o">.</span><span class="n">topk</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
                        <span class="n">equality</span> <span class="o">=</span> <span class="p">(</span><span class="n">label</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">*</span><span class="n">top_class</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span> <span class="o">==</span> <span class="n">top_class</span><span class="p">)</span>
                        <span class="c1"># Take the mean of equality to get accuracy</span>
                        <span class="n">accuracy</span> <span class="o">+=</span> <span class="n">equality</span><span class="o">.</span><span class="n">type_as</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">FloatTensor</span><span class="p">())</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>

                <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Epoch: </span><span class="si">{}</span><span class="s2">/</span><span class="si">{}</span><span class="s2">.. &quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">e</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">epoch</span><span class="p">),</span>
                      <span class="s2">&quot;Training Loss: </span><span class="si">{:.3f}</span><span class="s2">.. &quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">running_loss</span><span class="o">/</span><span class="n">print_every</span><span class="p">),</span>
                      <span class="s2">&quot;Validation Loss: </span><span class="si">{:.3f}</span><span class="s2">.. &quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">valid_loss</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">validloader</span><span class="p">)),</span>
                      <span class="s2">&quot;Validation Accuracy: </span><span class="si">{:.2%}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">accuracy</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">validloader</span><span class="p">)))</span>
                
                <span class="n">scheduler</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">valid_loss</span><span class="p">)</span>
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<pre>Epoch: 1/5..  Training Loss: 4.586..  Validation Loss: 4.493..  Validation Accuracy: 2.56%
Epoch: 1/5..  Training Loss: 9.080..  Validation Loss: 4.410..  Validation Accuracy: 4.94%
Epoch: 1/5..  Training Loss: 13.417..  Validation Loss: 4.076..  Validation Accuracy: 11.41%
Epoch: 1/5..  Training Loss: 17.324..  Validation Loss: 3.862..  Validation Accuracy: 11.89%
Epoch: 2/5..  Training Loss: 3.016..  Validation Loss: 3.776..  Validation Accuracy: 12.62%
Epoch: 2/5..  Training Loss: 5.966..  Validation Loss: 2.390..  Validation Accuracy: 39.35%
Epoch: 2/5..  Training Loss: 8.533..  Validation Loss: 2.007..  Validation Accuracy: 47.10%
Epoch: 2/5..  Training Loss: 10.636..  Validation Loss: 1.659..  Validation Accuracy: 50.01%
Epoch: 3/5..  Training Loss: 1.431..  Validation Loss: 1.351..  Validation Accuracy: 61.14%
Epoch: 3/5..  Training Loss: 3.095..  Validation Loss: 1.137..  Validation Accuracy: 66.32%
Epoch: 3/5..  Training Loss: 4.487..  Validation Loss: 1.219..  Validation Accuracy: 65.00%
Epoch: 3/5..  Training Loss: 5.877..  Validation Loss: 0.957..  Validation Accuracy: 71.83%
Epoch: 4/5..  Training Loss: 0.854..  Validation Loss: 0.981..  Validation Accuracy: 72.79%
Epoch: 4/5..  Training Loss: 2.059..  Validation Loss: 0.895..  Validation Accuracy: 75.04%
Epoch: 4/5..  Training Loss: 3.087..  Validation Loss: 0.752..  Validation Accuracy: 79.01%
Epoch: 4/5..  Training Loss: 4.163..  Validation Loss: 0.753..  Validation Accuracy: 77.31%
Epoch: 5/5..  Training Loss: 0.558..  Validation Loss: 1.039..  Validation Accuracy: 71.21%
Epoch: 5/5..  Training Loss: 1.500..  Validation Loss: 0.762..  Validation Accuracy: 76.95%
Epoch: 5/5..  Training Loss: 2.383..  Validation Loss: 0.586..  Validation Accuracy: 82.34%
Epoch: 5/5..  Training Loss: 3.333..  Validation Loss: 0.581..  Validation Accuracy: 82.36%
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<h2 id="Testing-your-network">Testing your network<a class="anchor-link" href="#Testing-your-network">&#182;</a></h2><p>It's good practice to test your trained network on test data, images the network has never seen either in training or validation. This will give you a good estimate for the model's performance on completely new images. Run the test images through the network and measure the accuracy, the same way you did validation. You should be able to reach around 70% accuracy on the test set if the model has been trained well.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Do validation on the test set</span>
<span class="c1"># Essentially copy-and-paste of the valid phase above</span>
<span class="c1"># except with testloader instead of validloader</span>

<span class="n">vgg</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span>

<span class="k">with</span> <span class="n">active_session</span><span class="p">():</span>

    <span class="c1"># Turn off gradients for validation to speed up</span>
    <span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">():</span>
        <span class="n">accuracy</span> <span class="o">=</span> <span class="mi">0</span>
        <span class="n">test_loss</span> <span class="o">=</span> <span class="mi">0</span>
        <span class="k">for</span> <span class="n">image</span><span class="p">,</span> <span class="n">label</span> <span class="ow">in</span> <span class="n">testloader</span><span class="p">:</span>
            <span class="c1"># Move image and label to CUDA if available</span>
            <span class="n">image</span><span class="p">,</span> <span class="n">label</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">),</span> <span class="n">label</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>

            <span class="c1"># Feed image forward through VGG</span>
            <span class="n">test_output</span> <span class="o">=</span> <span class="n">vgg</span><span class="p">(</span><span class="n">image</span><span class="p">)</span>

            <span class="c1"># Increment evaluation loss</span>
            <span class="n">test_loss</span> <span class="o">+=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">test_output</span><span class="p">,</span> <span class="n">label</span><span class="p">)</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>

            <span class="c1"># Accuracy</span>
            <span class="c1"># Take exponential of log-softmax to get the probabilities , </span>
            <span class="n">ps</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">test_output</span><span class="p">)</span>
            <span class="c1"># Class with highest probability is our predicted class, compare with true label</span>
            <span class="n">top_p</span><span class="p">,</span> <span class="n">top_class</span> <span class="o">=</span> <span class="n">ps</span><span class="o">.</span><span class="n">topk</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
            <span class="n">equality</span> <span class="o">=</span> <span class="p">(</span><span class="n">label</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">*</span><span class="n">top_class</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span> <span class="o">==</span> <span class="n">top_class</span><span class="p">)</span>
            <span class="c1"># Take the mean of equality to get accuracy</span>
            <span class="n">accuracy</span> <span class="o">+=</span> <span class="n">equality</span><span class="o">.</span><span class="n">type_as</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">FloatTensor</span><span class="p">())</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>

    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Test Loss: </span><span class="si">{:.3f}</span><span class="s2">.. &quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">test_loss</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">testloader</span><span class="p">)),</span>
          <span class="s2">&quot;Test Accuracy: </span><span class="si">{:.2%}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">accuracy</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">testloader</span><span class="p">)))</span>
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<pre>Test Loss: 0.668..  Test Accuracy: 80.52%
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<h2 id="Save-the-checkpoint">Save the checkpoint<a class="anchor-link" href="#Save-the-checkpoint">&#182;</a></h2><p>Now that your network is trained, save the model so you can load it later for making predictions. You probably want to save other things such as the mapping of classes to indices which you get from one of the image datasets: <code>image_datasets['train'].class_to_idx</code>. You can attach this to the model as an attribute which makes inference easier later on.</p>
<p><code>model.class_to_idx = image_datasets['train'].class_to_idx</code></p>
<p>Remember that you'll want to completely rebuild the model later so you can use it for inference. Make sure to include any information you need in the checkpoint. If you want to load the model and keep training, you'll want to save the number of epochs as well as the optimizer state, <code>optimizer.state_dict</code>. You'll likely want to use this trained model in the next part of the project, so best to save it now.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_data</span>
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<pre>Dataset ImageFolder
    Number of datapoints: 6552
    Root Location: flowers/train
    Transforms (if any): Compose(
                             RandomRotation(degrees=(-30, 30), resample=False, expand=False)
                             RandomResizedCrop(size=(224, 224), scale=(0.08, 1.0), ratio=(0.75, 1.3333), interpolation=PIL.Image.BILINEAR)
                             RandomHorizontalFlip(p=0.5)
                             ToTensor()
                             Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
                         )
    Target Transforms (if any): None</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Save the checkpoint </span>
<span class="n">vgg</span><span class="o">.</span><span class="n">class_to_idx</span> <span class="o">=</span> <span class="n">train_data</span><span class="o">.</span><span class="n">class_to_idx</span>
<span class="n">checkpoint</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;input&#39;</span><span class="p">:</span> <span class="n">in_features</span><span class="p">,</span>
              <span class="s1">&#39;output&#39;</span><span class="p">:</span> <span class="mi">102</span><span class="p">,</span>
              <span class="s1">&#39;hidden&#39;</span><span class="p">:</span> <span class="p">[</span><span class="mi">8192</span><span class="p">,</span> <span class="mi">4096</span><span class="p">,</span> <span class="mi">1024</span><span class="p">],</span>
              <span class="s1">&#39;p_drop&#39;</span><span class="p">:</span> <span class="mf">0.25</span><span class="p">,</span>
              <span class="s1">&#39;state_dict&#39;</span><span class="p">:</span> <span class="n">vgg</span><span class="o">.</span><span class="n">state_dict</span><span class="p">(),</span>
              <span class="s1">&#39;optimizer&#39;</span><span class="p">:</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">state_dict</span><span class="p">(),</span>
              <span class="s1">&#39;epoch&#39;</span><span class="p">:</span> <span class="n">epoch</span><span class="p">,</span>
              <span class="s1">&#39;print_every&#39;</span><span class="p">:</span> <span class="n">print_every</span><span class="p">,</span>
              <span class="s1">&#39;class_to_idx&#39;</span><span class="p">:</span> <span class="n">vgg</span><span class="o">.</span><span class="n">class_to_idx</span><span class="p">,</span>
             <span class="p">}</span>

<span class="n">torch</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">,</span> <span class="s1">&#39;checkpoint.pth&#39;</span><span class="p">)</span>
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<h2 id="Loading-the-checkpoint">Loading the checkpoint<a class="anchor-link" href="#Loading-the-checkpoint">&#182;</a></h2><p>At this point it's good to write a function that can load a checkpoint and rebuild the model. That way you can come back to this project and keep working on it without having to retrain the network.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Write a function that loads a checkpoint and rebuilds the model</span>
<span class="k">def</span> <span class="nf">load_model</span><span class="p">(</span><span class="n">filepath</span><span class="p">):</span>
    <span class="c1"># Load checkpoint file</span>
    <span class="n">checkpoint</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">filepath</span><span class="p">)</span>
    <span class="c1"># Get VGG19</span>
    <span class="n">model</span> <span class="o">=</span> <span class="n">models</span><span class="o">.</span><span class="n">vgg19_bn</span><span class="p">(</span><span class="n">pretrained</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># or model = checkpoint[&#39;model&#39;]</span>
    
    <span class="c1"># Build classifier architecture</span>
    <span class="k">for</span> <span class="n">param</span> <span class="ow">in</span> <span class="n">model</span><span class="o">.</span><span class="n">parameters</span><span class="p">():</span>
        <span class="n">param</span><span class="o">.</span><span class="n">requires_grad</span> <span class="o">=</span> <span class="kc">False</span>
    
    <span class="n">architecture</span> <span class="o">=</span> <span class="n">OrderedDict</span><span class="p">([</span>
        <span class="p">(</span><span class="s1">&#39;fc1&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;input&#39;</span><span class="p">],</span> <span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;hidden&#39;</span><span class="p">][</span><span class="mi">0</span><span class="p">])),</span>
        <span class="p">(</span><span class="s1">&#39;re1&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">ReLU</span><span class="p">()),</span>
        <span class="p">(</span><span class="s1">&#39;dr1&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Dropout</span><span class="p">(</span><span class="n">p</span><span class="o">=</span><span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;p_drop&#39;</span><span class="p">])),</span>
    <span class="p">])</span>
    
    <span class="k">for</span> <span class="n">index</span><span class="p">,</span> <span class="n">layer_size</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;hidden&#39;</span><span class="p">][:</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;hidden&#39;</span><span class="p">][</span><span class="mi">1</span><span class="p">:])):</span>
        <span class="n">architecture</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="s1">&#39;fc</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">index</span><span class="o">+</span><span class="mi">2</span><span class="p">):</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">layer_size</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">layer_size</span><span class="p">[</span><span class="mi">1</span><span class="p">])})</span>
        <span class="n">architecture</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="s1">&#39;re</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">index</span><span class="o">+</span><span class="mi">2</span><span class="p">):</span> <span class="n">nn</span><span class="o">.</span><span class="n">ReLU</span><span class="p">()})</span>
        <span class="n">architecture</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="s1">&#39;dr</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">index</span><span class="o">+</span><span class="mi">2</span><span class="p">):</span> <span class="n">nn</span><span class="o">.</span><span class="n">Dropout</span><span class="p">(</span><span class="n">p</span><span class="o">=</span><span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;p_drop&#39;</span><span class="p">])})</span>
        
    <span class="n">architecture</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="s1">&#39;fc</span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">index</span><span class="o">+</span><span class="mi">3</span><span class="p">):</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;hidden&#39;</span><span class="p">][</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;output&#39;</span><span class="p">])})</span>
    <span class="n">architecture</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="s1">&#39;log&#39;</span><span class="p">:</span> <span class="n">nn</span><span class="o">.</span><span class="n">LogSoftmax</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)})</span>
    
    <span class="n">classifier</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="n">architecture</span><span class="p">)</span>
    <span class="n">model</span><span class="o">.</span><span class="n">classifier</span> <span class="o">=</span> <span class="n">classifier</span>
    
    <span class="c1"># Load state dict</span>
    <span class="n">model</span><span class="o">.</span><span class="n">load_state_dict</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;state_dict&#39;</span><span class="p">])</span>
    
    <span class="c1"># Load classifier</span>
    <span class="n">optimizer</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">SGD</span><span class="p">(</span><span class="n">params</span><span class="o">=</span><span class="n">model</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">momentum</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
    <span class="n">optimizer</span><span class="o">.</span><span class="n">load_state_dict</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;optimizer&#39;</span><span class="p">])</span>
    
    <span class="k">return</span> <span class="n">model</span><span class="p">,</span> <span class="n">optimizer</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">vgg_test</span><span class="p">,</span> <span class="n">vgg_optimizer</span> <span class="o">=</span> <span class="n">load_model</span><span class="p">(</span><span class="s1">&#39;checkpoint.pth&#39;</span><span class="p">)</span>
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<h1 id="Inference-for-classification">Inference for classification<a class="anchor-link" href="#Inference-for-classification">&#182;</a></h1><p>Now you'll write a function to use a trained network for inference. That is, you'll pass an image into the network and predict the class of the flower in the image. Write a function called <code>predict</code> that takes an image and a model, then returns the top $K$ most likely classes along with the probabilities. It should look like</p>
<div class="highlight"><pre><span></span><span class="n">probs</span><span class="p">,</span> <span class="n">classes</span> <span class="o">=</span> <span class="n">predict</span><span class="p">(</span><span class="n">image_path</span><span class="p">,</span> <span class="n">model</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">probs</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">classes</span><span class="p">)</span>
<span class="o">&gt;</span> <span class="p">[</span> <span class="mf">0.01558163</span>  <span class="mf">0.01541934</span>  <span class="mf">0.01452626</span>  <span class="mf">0.01443549</span>  <span class="mf">0.01407339</span><span class="p">]</span>
<span class="o">&gt;</span> <span class="p">[</span><span class="s1">&#39;70&#39;</span><span class="p">,</span> <span class="s1">&#39;3&#39;</span><span class="p">,</span> <span class="s1">&#39;45&#39;</span><span class="p">,</span> <span class="s1">&#39;62&#39;</span><span class="p">,</span> <span class="s1">&#39;55&#39;</span><span class="p">]</span>
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<p>First you'll need to handle processing the input image such that it can be used in your network.</p>
<h2 id="Image-Preprocessing">Image Preprocessing<a class="anchor-link" href="#Image-Preprocessing">&#182;</a></h2><p>You'll want to use <code>PIL</code> to load the image (<a href="https://pillow.readthedocs.io/en/latest/reference/Image.html">documentation</a>). It's best to write a function that preprocesses the image so it can be used as input for the model. This function should process the images in the same manner used for training.</p>
<p>First, resize the images where the shortest side is 256 pixels, keeping the aspect ratio. This can be done with the <a href="http://pillow.readthedocs.io/en/3.1.x/reference/Image.html#PIL.Image.Image.thumbnail"><code>thumbnail</code></a> or <a href="http://pillow.readthedocs.io/en/3.1.x/reference/Image.html#PIL.Image.Image.thumbnail"><code>resize</code></a> methods. Then you'll need to crop out the center 224x224 portion of the image.</p>
<p>Color channels of images are typically encoded as integers 0-255, but the model expected floats 0-1. You'll need to convert the values. It's easiest with a Numpy array, which you can get from a PIL image like so <code>np_image = np.array(pil_image)</code>.</p>
<p>As before, the network expects the images to be normalized in a specific way. For the means, it's <code>[0.485, 0.456, 0.406]</code> and for the standard deviations <code>[0.229, 0.224, 0.225]</code>. You'll want to subtract the means from each color channel, then divide by the standard deviation.</p>
<p>And finally, PyTorch expects the color channel to be the first dimension but it's the third dimension in the PIL image and Numpy array. You can reorder dimensions using <a href="https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.ndarray.transpose.html"><code>ndarray.transpose</code></a>. The color channel needs to be first and retain the order of the other two dimensions.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">process_image</span><span class="p">(</span><span class="n">image</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39; Scales, crops, and normalizes a PIL image for a PyTorch model,</span>
<span class="sd">        returns an Numpy array</span>
<span class="sd">    &#39;&#39;&#39;</span>    
    <span class="c1"># TODO: Process a PIL image for use in a PyTorch model</span>
    <span class="c1"># Opening</span>
    <span class="n">im</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">image</span><span class="p">)</span>
    <span class="c1"># Resizing</span>
    <span class="n">im</span><span class="o">.</span><span class="n">thumbnail</span><span class="p">((</span><span class="mi">256</span><span class="p">,</span> <span class="mi">256</span><span class="p">))</span>
    
    <span class="c1"># Center cropping</span>
    <span class="n">width</span><span class="p">,</span> <span class="n">height</span> <span class="o">=</span> <span class="n">im</span><span class="o">.</span><span class="n">size</span>   
    <span class="n">new_width</span> <span class="o">=</span> <span class="mi">224</span>
    <span class="n">new_height</span> <span class="o">=</span> <span class="mi">224</span>
    
    <span class="n">left</span> <span class="o">=</span> <span class="p">(</span><span class="n">width</span> <span class="o">-</span> <span class="n">new_width</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span>
    <span class="n">top</span> <span class="o">=</span> <span class="p">(</span><span class="n">height</span> <span class="o">-</span> <span class="n">new_height</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span>
    <span class="n">right</span> <span class="o">=</span> <span class="p">(</span><span class="n">width</span> <span class="o">+</span> <span class="n">new_width</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span>
    <span class="n">bottom</span> <span class="o">=</span> <span class="p">(</span><span class="n">height</span> <span class="o">+</span> <span class="n">new_height</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span>

    <span class="n">im</span> <span class="o">=</span> <span class="n">im</span><span class="o">.</span><span class="n">crop</span><span class="p">((</span><span class="n">left</span><span class="p">,</span> <span class="n">top</span><span class="p">,</span> <span class="n">right</span><span class="p">,</span> <span class="n">bottom</span><span class="p">))</span>
    
    <span class="c1"># Converting PIL.Image(min=0, max=255) to NumPy.ndarray(min=0, max=1)</span>
    <span class="n">np_im</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">im</span><span class="p">)</span> <span class="o">/</span> <span class="mi">255</span>
    
    <span class="c1"># Normalizing</span>
    <span class="n">mean</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="mf">0.485</span><span class="p">,</span> <span class="mf">0.456</span><span class="p">,</span> <span class="mf">0.406</span><span class="p">])</span>
    <span class="n">stdev</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="mf">0.229</span><span class="p">,</span> <span class="mf">0.224</span><span class="p">,</span> <span class="mf">0.225</span><span class="p">])</span>
    <span class="n">np_im</span> <span class="o">=</span> <span class="p">(</span><span class="n">np_im</span> <span class="o">-</span> <span class="n">mean</span><span class="p">)</span> <span class="o">/</span> <span class="n">stdev</span>
    
    <span class="c1"># Transposing</span>
    <span class="n">np_im</span> <span class="o">=</span> <span class="n">np_im</span><span class="o">.</span><span class="n">transpose</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span>
    <span class="k">return</span> <span class="n">np_im</span>
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<p>To check your work, the function below converts a PyTorch tensor and displays it in the notebook. If your <code>process_image</code> function works, running the output through this function should return the original image (except for the cropped out portions).</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">imshow</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
    <span class="k">if</span> <span class="n">ax</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
        <span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
    
    <span class="c1"># PyTorch tensors assume the color channel is the first dimension</span>
    <span class="c1"># but matplotlib assumes is the third dimension</span>
    <span class="n">image</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">transpose</span><span class="p">((</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">))</span>
    
    <span class="c1"># Undo preprocessing</span>
    <span class="n">mean</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="mf">0.485</span><span class="p">,</span> <span class="mf">0.456</span><span class="p">,</span> <span class="mf">0.406</span><span class="p">])</span>
    <span class="n">std</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mf">0.229</span><span class="p">,</span> <span class="mf">0.224</span><span class="p">,</span> <span class="mf">0.225</span><span class="p">])</span>
    <span class="n">image</span> <span class="o">=</span> <span class="n">std</span> <span class="o">*</span> <span class="n">image</span> <span class="o">+</span> <span class="n">mean</span>
    
    <span class="c1"># Image needs to be clipped between 0 and 1 or it looks like noise when displayed</span>
    <span class="n">image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">clip</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
    
    <span class="n">ax</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">image</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">ax</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">imshow</span><span class="p">(</span><span class="n">process_image</span><span class="p">(</span><span class="n">train_dir</span> <span class="o">+</span> <span class="s1">&#39;/1/image_06734.jpg&#39;</span><span class="p">))</span>
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<h2 id="Class-Prediction">Class Prediction<a class="anchor-link" href="#Class-Prediction">&#182;</a></h2><p>Once you can get images in the correct format, it's time to write a function for making predictions with your model. A common practice is to predict the top 5 or so (usually called top-$K$) most probable classes. You'll want to calculate the class probabilities then find the $K$ largest values.</p>
<p>To get the top $K$ largest values in a tensor use <a href="http://pytorch.org/docs/master/torch.html#torch.topk"><code>x.topk(k)</code></a>. This method returns both the highest <code>k</code> probabilities and the indices of those probabilities corresponding to the classes. You need to convert from these indices to the actual class labels using <code>class_to_idx</code> which hopefully you added to the model or from an <code>ImageFolder</code> you used to load the data (<a href="#Save-the-checkpoint">see here</a>). Make sure to invert the dictionary so you get a mapping from index to class as well.</p>
<p>Again, this method should take a path to an image and a model checkpoint, then return the probabilities and classes.</p>
<div class="highlight"><pre><span></span><span class="n">probs</span><span class="p">,</span> <span class="n">classes</span> <span class="o">=</span> <span class="n">predict</span><span class="p">(</span><span class="n">image_path</span><span class="p">,</span> <span class="n">model</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">probs</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">classes</span><span class="p">)</span>
<span class="o">&gt;</span> <span class="p">[</span> <span class="mf">0.01558163</span>  <span class="mf">0.01541934</span>  <span class="mf">0.01452626</span>  <span class="mf">0.01443549</span>  <span class="mf">0.01407339</span><span class="p">]</span>
<span class="o">&gt;</span> <span class="p">[</span><span class="s1">&#39;70&#39;</span><span class="p">,</span> <span class="s1">&#39;3&#39;</span><span class="p">,</span> <span class="s1">&#39;45&#39;</span><span class="p">,</span> <span class="s1">&#39;62&#39;</span><span class="p">,</span> <span class="s1">&#39;55&#39;</span><span class="p">]</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">idx_to_class</span> <span class="o">=</span> <span class="p">{</span><span class="n">val</span><span class="p">:</span> <span class="n">key</span> <span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">val</span> <span class="ow">in</span> <span class="n">train_data</span><span class="o">.</span><span class="n">class_to_idx</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>
<span class="c1"># Or idx_to_class = {val: key for key, val in vgg_test.class_to_idx.items()} - same thing, but will work across two .py files</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="n">image_path</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="n">topk</span><span class="o">=</span><span class="mi">5</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39; Predict the class (or classes) of an image using a trained deep learning model.</span>
<span class="sd">    &#39;&#39;&#39;</span>
    <span class="c1"># TODO: Implement the code to predict the class from an image file</span>
    <span class="n">im</span> <span class="o">=</span> <span class="n">process_image</span><span class="p">(</span><span class="n">image_path</span><span class="p">)</span>
    <span class="n">tensor_im</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">im</span><span class="p">)</span><span class="o">.</span><span class="n">type</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">FloatTensor</span><span class="p">)</span>
    <span class="n">output</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">model</span><span class="p">(</span><span class="n">tensor_im</span><span class="o">.</span><span class="n">unsqueeze</span><span class="p">(</span><span class="mi">0</span><span class="p">)))</span>
    
    <span class="n">probs</span><span class="p">,</span> <span class="n">labels</span> <span class="o">=</span> <span class="n">output</span><span class="o">.</span><span class="n">topk</span><span class="p">(</span><span class="n">topk</span><span class="p">)</span>
    <span class="n">probs</span> <span class="o">=</span> <span class="n">probs</span><span class="o">.</span><span class="n">tolist</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>
    <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">tolist</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>

    <span class="n">flowers</span> <span class="o">=</span> <span class="p">[</span><span class="n">cat_to_name</span><span class="p">[</span><span class="n">idx_to_class</span><span class="p">[</span><span class="n">label</span><span class="p">]]</span> <span class="k">for</span> <span class="n">label</span> <span class="ow">in</span> <span class="n">labels</span><span class="p">]</span>
    <span class="k">return</span> <span class="n">probs</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">flowers</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">plot_solution</span><span class="p">(</span><span class="n">image_path</span><span class="p">,</span> <span class="n">model</span><span class="p">):</span>
    <span class="c1"># Set up plot</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span> <span class="o">=</span> <span class="p">(</span><span class="mi">6</span><span class="p">,</span><span class="mi">10</span><span class="p">))</span>
    <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
    
    <span class="c1"># Set up title</span>
    <span class="n">flower_num</span> <span class="o">=</span> <span class="n">image_path</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;/&#39;</span><span class="p">)[</span><span class="mi">2</span><span class="p">]</span>
    <span class="n">title_</span> <span class="o">=</span> <span class="n">cat_to_name</span><span class="p">[</span><span class="n">flower_num</span><span class="p">]</span>
    
    <span class="c1"># Plot flower</span>
    <span class="n">img</span> <span class="o">=</span> <span class="n">process_image</span><span class="p">(</span><span class="n">image_path</span><span class="p">)</span>
    <span class="n">imshow</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">ax</span><span class="p">,</span> <span class="n">title</span> <span class="o">=</span> <span class="n">title_</span><span class="p">)</span>
    
    <span class="c1"># Make prediction</span>
    <span class="n">probs</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">flowers</span> <span class="o">=</span> <span class="n">predict</span><span class="p">(</span><span class="n">image_path</span><span class="p">,</span> <span class="n">model</span><span class="p">)</span> 
    
    
    <span class="c1"># Plot bar chart</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">)</span>
    <span class="n">sns</span><span class="o">.</span><span class="n">barplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="n">probs</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="n">flowers</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="n">sns</span><span class="o">.</span><span class="n">color_palette</span><span class="p">()[</span><span class="mi">0</span><span class="p">]);</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<h2 id="Sanity-Checking">Sanity Checking<a class="anchor-link" href="#Sanity-Checking">&#182;</a></h2><p>Now that you can use a trained model for predictions, check to make sure it makes sense. Even if the testing accuracy is high, it's always good to check that there aren't obvious bugs. Use <code>matplotlib</code> to plot the probabilities for the top 5 classes as a bar graph, along with the input image. It should look like this:</p>
<p><img src='assets/inference_example.png' width=300px></p>
<p>You can convert from the class integer encoding to actual flower names with the <code>cat_to_name.json</code> file (should have been loaded earlier in the notebook). To show a PyTorch tensor as an image, use the <code>imshow</code> function defined above.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Display an image along with the top 5 classes</span>
<span class="n">image_path</span> <span class="o">=</span> <span class="n">train_dir</span> <span class="o">+</span> <span class="s1">&#39;/1/image_06740.jpg&#39;</span>

<span class="n">plot_solution</span><span class="p">(</span><span class="n">image_path</span><span class="p">,</span> <span class="n">vgg_test</span><span class="p">)</span>
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