Image Classifier Project.html

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

<title>Image Classifier Project</title>

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

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Imports here</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">import</span> <span class="nn">PIL</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</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">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">from</span> <span class="nn">collections</span> <span class="k">import</span> <span class="n">OrderedDict</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;
</pre></div>

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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"># Imports here</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">import</span> <span class="nn">PIL</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</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">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">from</span> <span class="nn">collections</span> <span class="k">import</span> <span class="n">OrderedDict</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="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>

<span class="c1"># TODO: Define your transforms for the training, validation, and testing sets</span>
<span class="n">train_transforms</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span><span class="n">transforms</span><span class="o">.</span><span class="n">RandomRotation</span><span class="p">(</span><span class="mi">30</span><span class="p">),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">RandomResizedCrop</span><span class="p">(</span><span class="mi">224</span><span class="p">),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">RandomHorizontalFlip</span><span class="p">(),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">([</span><span class="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="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">256</span><span class="p">),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">CenterCrop</span><span class="p">(</span><span class="mi">224</span><span class="p">),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">([</span><span class="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="n">test_transforms</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span><span class="n">transforms</span><span class="o">.</span><span class="n">Resize</span><span class="p">(</span><span class="mi">256</span><span class="p">),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">CenterCrop</span><span class="p">(</span><span class="mi">224</span><span class="p">),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">([</span><span class="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="c1"># TODO: Load the datasets with ImageFolder</span>
<span class="n">train_data</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">train_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">train_transforms</span><span class="p">)</span>
<span class="n">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">valid_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">valid_transforms</span><span class="p">)</span>
<span class="n">test_data</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">test_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">test_transforms</span><span class="p">)</span>

<span class="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">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">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>
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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="c1"># Imports here</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">import</span> <span class="nn">PIL</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</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">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">from</span> <span class="nn">collections</span> <span class="k">import</span> <span class="n">OrderedDict</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="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>

<span class="c1"># TODO: Define your transforms for the training, validation, and testing sets</span>
<span class="n">train_transforms</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span><span class="n">transforms</span><span class="o">.</span><span class="n">RandomRotation</span><span class="p">(</span><span class="mi">30</span><span class="p">),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">RandomResizedCrop</span><span class="p">(</span><span class="mi">224</span><span class="p">),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">RandomHorizontalFlip</span><span class="p">(),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">([</span><span class="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="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">256</span><span class="p">),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">CenterCrop</span><span class="p">(</span><span class="mi">224</span><span class="p">),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">([</span><span class="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="n">test_transforms</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span><span class="n">transforms</span><span class="o">.</span><span class="n">Resize</span><span class="p">(</span><span class="mi">256</span><span class="p">),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">CenterCrop</span><span class="p">(</span><span class="mi">224</span><span class="p">),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">([</span><span class="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="c1"># TODO: Load the datasets with ImageFolder</span>
<span class="n">train_data</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">train_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">train_transforms</span><span class="p">)</span>
<span class="n">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">valid_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">valid_transforms</span><span class="p">)</span>
<span class="n">test_data</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">test_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">test_transforms</span><span class="p">)</span>

<span class="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">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">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="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>
<p><strong>Note for Workspace users:</strong> If your network is over 1 GB when saved as a checkpoint, there might be issues with saving backups in your workspace. Typically this happens with wide dense layers after the convolutional layers. If your saved checkpoint is larger than 1 GB (you can open a terminal and check with <code>ls -lh</code>), you should reduce the size of your hidden layers and train again.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Imports here</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">import</span> <span class="nn">PIL</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</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">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">from</span> <span class="nn">collections</span> <span class="k">import</span> <span class="n">OrderedDict</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="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>

<span class="c1"># TODO: Define your transforms for the training, validation, and testing sets</span>
<span class="n">train_transforms</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span><span class="n">transforms</span><span class="o">.</span><span class="n">RandomRotation</span><span class="p">(</span><span class="mi">30</span><span class="p">),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">RandomResizedCrop</span><span class="p">(</span><span class="mi">224</span><span class="p">),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">RandomHorizontalFlip</span><span class="p">(),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
                                       <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">([</span><span class="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="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">256</span><span class="p">),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">CenterCrop</span><span class="p">(</span><span class="mi">224</span><span class="p">),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">([</span><span class="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="n">test_transforms</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span><span class="n">transforms</span><span class="o">.</span><span class="n">Resize</span><span class="p">(</span><span class="mi">256</span><span class="p">),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">CenterCrop</span><span class="p">(</span><span class="mi">224</span><span class="p">),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">(),</span>
                                      <span class="n">transforms</span><span class="o">.</span><span class="n">Normalize</span><span class="p">([</span><span class="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="c1"># TODO: Load the datasets with ImageFolder</span>
<span class="n">train_data</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">train_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">train_transforms</span><span class="p">)</span>
<span class="n">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">valid_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">valid_transforms</span><span class="p">)</span>
<span class="n">test_data</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">test_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">test_transforms</span><span class="p">)</span>

<span class="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">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">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="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>

<span class="c1"># TODO: Build and train your network</span>

<span class="c1"># Load a pre-trained network </span>
<span class="n">model</span> <span class="o">=</span> <span class="n">models</span><span class="o">.</span><span class="n">vgg16</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="n">model</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;vgg16&quot;</span>
<span class="n">model</span>
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<pre>Downloading: &#34;https://download.pytorch.org/models/vgg16-397923af.pth&#34; to /root/.torch/models/vgg16-397923af.pth
100%|██████████| 553433881/553433881 [00:58&lt;00:00, 9527574.01it/s] 
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<pre>VGG(
  (features): Sequential(
    (0): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (1): ReLU(inplace)
    (2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (3): ReLU(inplace)
    (4): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
    (5): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (6): ReLU(inplace)
    (7): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (8): ReLU(inplace)
    (9): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
    (10): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (11): ReLU(inplace)
    (12): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (13): ReLU(inplace)
    (14): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (15): ReLU(inplace)
    (16): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
    (17): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (18): ReLU(inplace)
    (19): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (20): ReLU(inplace)
    (21): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (22): ReLU(inplace)
    (23): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
    (24): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (25): ReLU(inplace)
    (26): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (27): ReLU(inplace)
    (28): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (29): ReLU(inplace)
    (30): 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="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>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#feed-forward network as a classifier, using ReLU activations and dropout</span>
<span class="n">classifier</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="n">OrderedDict</span><span class="p">([</span>
                          <span class="p">(</span><span class="s1">&#39;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="mi">25088</span><span class="p">,</span> <span class="mi">4096</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">True</span><span class="p">)),</span>
                          <span class="p">(</span><span class="s1">&#39;relu&#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;dropout&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">Dropout</span><span class="p">(</span><span class="n">p</span><span class="o">=</span><span class="mf">0.5</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">4096</span><span class="p">,</span> <span class="mi">102</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">True</span><span class="p">)),</span>
                          <span class="p">(</span><span class="s1">&#39;output&#39;</span><span class="p">,</span> <span class="n">nn</span><span class="o">.</span><span class="n">LogSoftmax</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">))</span>
                          <span class="p">]))</span>
    
<span class="n">model</span><span class="o">.</span><span class="n">classifier</span> <span class="o">=</span> <span class="n">classifier</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Device agnostic code, automatically uses CUDA if it&#39;s enabled</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="n">device</span>
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<pre>device(type=&#39;cuda&#39;, index=0)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># change to device</span>
<span class="n">model</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">);</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Define loss and optimizer</span>
<span class="n">criterion</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">NLLLoss</span><span class="p">()</span>
<span class="n">optimizer</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">classifier</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span><span class="o">=</span><span class="mf">0.001</span><span class="p">)</span>

<span class="c1"># Define deep learning method</span>
<span class="n">epochs</span> <span class="o">=</span> <span class="mi">5</span>
<span class="n">print_every</span> <span class="o">=</span> <span class="mi">30</span> <span class="c1"># Prints every 30 images out of batch of 64 images</span>
<span class="n">steps</span> <span class="o">=</span> <span class="mi">0</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Function for the validation pass</span>
<span class="k">def</span> <span class="nf">validation</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">testloader</span><span class="p">,</span> <span class="n">criterion</span><span class="p">):</span>
    <span class="n">test_loss</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="n">accuracy</span> <span class="o">=</span> <span class="mi">0</span>
    
    <span class="k">for</span> <span class="n">ii</span><span class="p">,</span> <span class="p">(</span><span class="n">inputs</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">testloader</span><span class="p">):</span>
        
        <span class="n">inputs</span><span class="p">,</span> <span class="n">labels</span> <span class="o">=</span> <span class="n">inputs</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">),</span> <span class="n">labels</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
        
        <span class="n">output</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">inputs</span><span class="p">)</span>
        <span class="n">test_loss</span> <span class="o">+=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">output</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>
        
        <span class="n">ps</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">output</span><span class="p">)</span>
        <span class="n">equality</span> <span class="o">=</span> <span class="p">(</span><span class="n">labels</span><span class="o">.</span><span class="n">data</span> <span class="o">==</span> <span class="n">ps</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)[</span><span class="mi">1</span><span class="p">])</span>
        <span class="n">accuracy</span> <span class="o">+=</span> <span class="n">equality</span><span class="o">.</span><span class="n">type</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">FloatTensor</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
    
    <span class="k">return</span> <span class="n">test_loss</span><span class="p">,</span> <span class="n">accuracy</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Train the classifier layers using backpropogation and the pre-trained network to get features</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Training starts..&quot;</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">epochs</span><span class="p">):</span>
    <span class="n">running_loss</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="n">model</span><span class="o">.</span><span class="n">train</span><span class="p">()</span> 
    
    <span class="k">for</span> <span class="n">ii</span><span class="p">,</span> <span class="p">(</span><span class="n">inputs</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">trainloader</span><span class="p">):</span>
        <span class="n">steps</span> <span class="o">+=</span> <span class="mi">1</span>
        
        <span class="n">inputs</span><span class="p">,</span> <span class="n">labels</span> <span class="o">=</span> <span class="n">inputs</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">),</span> <span class="n">labels</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
        
        <span class="n">optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
        
        <span class="c1"># Forward and backward passes</span>
        <span class="n">outputs</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">inputs</span><span class="p">)</span>
        <span class="n">loss</span> <span class="o">=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">outputs</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span>
        <span class="n">loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
        <span class="n">optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
        
        <span class="n">running_loss</span> <span class="o">+=</span> <span class="n">loss</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>
        
        <span class="k">if</span> <span class="n">steps</span> <span class="o">%</span> <span class="n">print_every</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
            <span class="n">model</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span>

            <span class="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">valid_loss</span><span class="p">,</span> <span class="n">accuracy</span> <span class="o">=</span> <span class="n">validation</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">validloader</span><span class="p">,</span> <span class="n">criterion</span><span class="p">)</span>
            
            <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Epoch: </span><span class="si">{}</span><span class="s2">/</span><span class="si">{}</span><span class="s2"> | &quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">e</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">epochs</span><span class="p">),</span>
                  <span class="s2">&quot;Training Loss: </span><span class="si">{:.4f}</span><span class="s2"> | &quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">running_loss</span><span class="o">/</span><span class="n">print_every</span><span class="p">),</span>
                  <span class="s2">&quot;Validation Loss: </span><span class="si">{:.4f}</span><span class="s2"> | &quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">valid_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;Validation Accuracy: </span><span class="si">{:.4f}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">accuracy</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="n">running_loss</span> <span class="o">=</span> <span class="mi">0</span>
            <span class="n">model</span><span class="o">.</span><span class="n">train</span><span class="p">()</span>

<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Training completed..&quot;</span><span class="p">)</span>
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<pre>
Training starts..
Epoch: 1/5 |  Training Loss: 5.0943 |  Validation Loss: 1.9888 |  Validation Accuracy: 0.5186
Epoch: 1/5 |  Training Loss: 2.2425 |  Validation Loss: 1.1840 |  Validation Accuracy: 0.6900
Epoch: 1/5 |  Training Loss: 1.8960 |  Validation Loss: 0.9407 |  Validation Accuracy: 0.7623
Epoch: 2/5 |  Training Loss: 0.9390 |  Validation Loss: 0.9318 |  Validation Accuracy: 0.7549
Epoch: 2/5 |  Training Loss: 1.5654 |  Validation Loss: 0.7148 |  Validation Accuracy: 0.8115
Epoch: 2/5 |  Training Loss: 1.3994 |  Validation Loss: 0.6812 |  Validation Accuracy: 0.8258
Epoch: 3/5 |  Training Loss: 0.1525 |  Validation Loss: 0.6290 |  Validation Accuracy: 0.8284
Epoch: 3/5 |  Training Loss: 1.3305 |  Validation Loss: 0.5713 |  Validation Accuracy: 0.8582
Epoch: 3/5 |  Training Loss: 1.4156 |  Validation Loss: 0.5634 |  Validation Accuracy: 0.8529
Epoch: 3/5 |  Training Loss: 1.2150 |  Validation Loss: 0.5641 |  Validation Accuracy: 0.8462
Epoch: 4/5 |  Training Loss: 0.8950 |  Validation Loss: 0.5811 |  Validation Accuracy: 0.8501
Epoch: 4/5 |  Training Loss: 1.2073 |  Validation Loss: 0.4934 |  Validation Accuracy: 0.8728
Epoch: 4/5 |  Training Loss: 1.2208 |  Validation Loss: 0.5206 |  Validation Accuracy: 0.8524
Epoch: 5/5 |  Training Loss: 0.3168 |  Validation Loss: 0.5494 |  Validation Accuracy: 0.8548
Epoch: 5/5 |  Training Loss: 1.1486 |  Validation Loss: 0.5188 |  Validation Accuracy: 0.8676
Epoch: 5/5 |  Training Loss: 1.1886 |  Validation Loss: 0.4919 |  Validation Accuracy: 0.8754
Epoch: 5/5 |  Training Loss: 1.1574 |  Validation Loss: 0.4805 |  Validation Accuracy: 0.8706

Training completed..
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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="n">correct</span> <span class="o">=</span> <span class="mi">0</span>
<span class="n">total</span> <span class="o">=</span> <span class="mi">0</span>
<span class="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">model</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span>
    <span class="k">for</span> <span class="n">data</span> <span class="ow">in</span> <span class="n">trainloader</span><span class="p">:</span>
        <span class="n">images</span><span class="p">,</span> <span class="n">labels</span> <span class="o">=</span> <span class="n">data</span>
        <span class="n">images</span><span class="p">,</span> <span class="n">labels</span> <span class="o">=</span> <span class="n">images</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">),</span> <span class="n">labels</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
        <span class="n">outputs</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="n">images</span><span class="p">)</span>
        <span class="n">_</span><span class="p">,</span> <span class="n">predicted</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">outputs</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
        <span class="n">total</span> <span class="o">+=</span> <span class="n">labels</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
        <span class="n">correct</span> <span class="o">+=</span> <span class="p">(</span><span class="n">predicted</span> <span class="o">==</span> <span class="n">labels</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">.</span><span class="n">item</span><span class="p">()</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy achieved by the network on test images is: </span><span class="si">%d%%</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="mi">100</span> <span class="o">*</span> <span class="n">correct</span> <span class="o">/</span> <span class="n">total</span><span class="p">))</span>
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<pre>Accuracy achieved by the network on test images is: 81%
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<h2 id="Save-the-checkpoint">Save the checkpoint<a class="anchor-link" href="#Save-the-checkpoint">&#182;</a></h2><p>Now that your network is trained, save the model so you can load it later for making predictions. You probably want to save other things such as the mapping of classes to indices which you get from one of the image datasets: <code>image_datasets['train'].class_to_idx</code>. You can attach this to the model as an attribute which makes inference easier later on.</p>
<p><code>model.class_to_idx = image_datasets['train'].class_to_idx</code></p>
<p>Remember that you'll want to completely rebuild the model later so you can use it for inference. Make sure to include any information you need in the checkpoint. If you want to load the model and keep training, you'll want to save the number of epochs as well as the optimizer state, <code>optimizer.state_dict</code>. You'll likely want to use this trained model in the next part of the project, so best to save it now.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Save the checkpoint </span>
<span class="n">model</span><span class="o">.</span><span class="n">class_to_idx</span> <span class="o">=</span> <span class="n">train_data</span><span class="o">.</span><span class="n">class_to_idx</span>

<span class="n">checkpoint</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;architecture&#39;</span><span class="p">:</span> <span class="n">model</span><span class="o">.</span><span class="n">name</span><span class="p">,</span>
             <span class="s1">&#39;classifier&#39;</span><span class="p">:</span> <span class="n">model</span><span class="o">.</span><span class="n">classifier</span><span class="p">,</span>
             <span class="s1">&#39;class_to_idx&#39;</span><span class="p">:</span> <span class="n">model</span><span class="o">.</span><span class="n">class_to_idx</span><span class="p">,</span>
             <span class="s1">&#39;state_dict&#39;</span><span class="p">:</span> <span class="n">model</span><span class="o">.</span><span class="n">state_dict</span><span class="p">()}</span>

<span class="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;own_chkpoint.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_checkpoint</span><span class="p">():</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Loads deep learning model checkpoint.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1"># Load the saved 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="s2">&quot;&#39;own_chkpoint.pth&quot;</span><span class="p">)</span>
    
    <span class="c1"># Download pretrained model</span>
    <span class="n">model</span> <span class="o">=</span> <span class="n">models</span><span class="o">.</span><span class="n">vgg16</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"># Freeze parameters so we don&#39;t backprop through them</span>
    <span class="k">for</span> <span class="n">param</span> <span class="ow">in</span> <span class="n">model</span><span class="o">.</span><span class="n">parameters</span><span class="p">():</span> <span class="n">param</span><span class="o">.</span><span class="n">requires_grad</span> <span class="o">=</span> <span class="kc">False</span>
    
    <span class="c1"># Load stuff from checkpoint</span>
    <span class="n">model</span><span class="o">.</span><span class="n">class_to_idx</span> <span class="o">=</span> <span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;class_to_idx&#39;</span><span class="p">]</span>
    <span class="n">model</span><span class="o">.</span><span class="n">classifier</span> <span class="o">=</span> <span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;classifier&#39;</span><span class="p">]</span>
    <span class="n">model</span><span class="o">.</span><span class="n">load_state_dict</span><span class="p">(</span><span class="n">checkpoint</span><span class="p">[</span><span class="s1">&#39;state_dict&#39;</span><span class="p">])</span>

    
    <span class="k">return</span> <span class="n">model</span>
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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="n">test_image</span> <span class="o">=</span> <span class="n">PIL</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"># Get original dimensions</span>
    <span class="n">orig_width</span><span class="p">,</span> <span class="n">orig_height</span> <span class="o">=</span> <span class="n">test_image</span><span class="o">.</span><span class="n">size</span>

    <span class="c1"># Find shorter size and create settings to crop shortest side to 256</span>
    <span class="k">if</span> <span class="n">orig_width</span> <span class="o">&lt;</span> <span class="n">orig_height</span><span class="p">:</span> <span class="n">resize_size</span><span class="o">=</span><span class="p">[</span><span class="mi">256</span><span class="p">,</span> <span class="mi">256</span><span class="o">**</span><span class="mi">600</span><span class="p">]</span>
    <span class="k">else</span><span class="p">:</span> <span class="n">resize_size</span><span class="o">=</span><span class="p">[</span><span class="mi">256</span><span class="o">**</span><span class="mi">600</span><span class="p">,</span> <span class="mi">256</span><span class="p">]</span>
        
    <span class="n">test_image</span><span class="o">.</span><span class="n">thumbnail</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="n">resize_size</span><span class="p">)</span>

    <span class="c1"># Find pixels to crop on to create 224x224 image</span>
    <span class="n">center</span> <span class="o">=</span> <span class="n">orig_width</span><span class="o">/</span><span class="mi">4</span><span class="p">,</span> <span class="n">orig_height</span><span class="o">/</span><span class="mi">4</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="o">=</span> <span class="n">center</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">-</span><span class="p">(</span><span class="mi">244</span><span class="o">/</span><span class="mi">2</span><span class="p">),</span> <span class="n">center</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">-</span><span class="p">(</span><span class="mi">244</span><span class="o">/</span><span class="mi">2</span><span class="p">),</span> <span class="n">center</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">+</span><span class="p">(</span><span class="mi">244</span><span class="o">/</span><span class="mi">2</span><span class="p">),</span> <span class="n">center</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">+</span><span class="p">(</span><span class="mi">244</span><span class="o">/</span><span class="mi">2</span><span class="p">)</span>
    <span class="n">test_image</span> <span class="o">=</span> <span class="n">test_image</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"># Converrt to numpy - 244x244 image w/ 3 channels (RGB)</span>
    <span class="n">np_image</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">test_image</span><span class="p">)</span><span class="o">/</span><span class="mi">255</span> <span class="c1"># Divided by 255 because imshow() expects integers (0:1)!!</span>

    <span class="c1"># Normalize each color channel</span>
    <span class="n">normalise_means</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.485</span><span class="p">,</span> <span class="mf">0.456</span><span class="p">,</span> <span class="mf">0.406</span><span class="p">]</span>
    <span class="n">normalise_std</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.229</span><span class="p">,</span> <span class="mf">0.224</span><span class="p">,</span> <span class="mf">0.225</span><span class="p">]</span>
    <span class="n">np_image</span> <span class="o">=</span> <span class="p">(</span><span class="n">np_image</span><span class="o">-</span><span class="n">normalise_means</span><span class="p">)</span><span class="o">/</span><span class="n">normalise_std</span>
        
    <span class="c1"># Set the color to the first channel</span>
    <span class="n">np_image</span> <span class="o">=</span> <span class="n">np_image</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">np_image</span>
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<p>To check your work, the function below converts a PyTorch tensor and displays it in the notebook. If your <code>process_image</code> function works, running the output through this function should return the original image (except for the cropped out portions).</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">imshow</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;Imshow for Tensor.&quot;&quot;&quot;</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="c1"># Test functions on an example</span>
<span class="n">imshow</span><span class="p">(</span><span class="n">process_image</span><span class="p">(</span><span class="s2">&quot;flowers/test/10/image_07090.jpg&quot;</span><span class="p">));</span>
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<h2 id="Class-Prediction">Class Prediction<a class="anchor-link" href="#Class-Prediction">&#182;</a></h2><p>Once you can get images in the correct format, it's time to write a function for making predictions with your model. A common practice is to predict the top 5 or so (usually called top-$K$) most probable classes. You'll want to calculate the class probabilities then find the $K$ largest values.</p>
<p>To get the top $K$ largest values in a tensor use <a href="http://pytorch.org/docs/master/torch.html#torch.topk"><code>x.topk(k)</code></a>. This method returns both the highest <code>k</code> probabilities and the indices of those probabilities corresponding to the classes. You need to convert from these indices to the actual class labels using <code>class_to_idx</code> which hopefully you added to the model or from an <code>ImageFolder</code> you used to load the data (<a href="#Save-the-checkpoint">see here</a>). Make sure to invert the dictionary so you get a mapping from index to class as well.</p>
<p>Again, this method should take a path to an image and a model checkpoint, then return the probabilities and classes.</p>
<div class="highlight"><pre><span></span><span class="n">probs</span><span class="p">,</span> <span class="n">classes</span> <span class="o">=</span> <span class="n">predict</span><span class="p">(</span><span class="n">image_path</span><span class="p">,</span> <span class="n">model</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">probs</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">classes</span><span class="p">)</span>
<span class="o">&gt;</span> <span class="p">[</span> <span class="mf">0.01558163</span>  <span class="mf">0.01541934</span>  <span class="mf">0.01452626</span>  <span class="mf">0.01443549</span>  <span class="mf">0.01407339</span><span class="p">]</span>
<span class="o">&gt;</span> <span class="p">[</span><span class="s1">&#39;70&#39;</span><span class="p">,</span> <span class="s1">&#39;3&#39;</span><span class="p">,</span> <span class="s1">&#39;45&#39;</span><span class="p">,</span> <span class="s1">&#39;62&#39;</span><span class="p">,</span> <span class="s1">&#39;55&#39;</span><span class="p">]</span>
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<div class=" 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">top_k</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"># No need for GPU on this part (as it causes problem)</span>
    <span class="n">model</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="s2">&quot;cpu&quot;</span><span class="p">)</span>
    
    <span class="c1"># Set model to evaluate</span>
    <span class="n">model</span><span class="o">.</span><span class="n">eval</span><span class="p">();</span>

    <span class="c1"># Convert image from numpy to torch</span>
    <span class="n">torch_image</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">np</span><span class="o">.</span><span class="n">expand_dims</span><span class="p">(</span><span class="n">process_image</span><span class="p">(</span><span class="n">image_path</span><span class="p">),</span> 
                                                  <span class="n">axis</span><span class="o">=</span><span class="mi">0</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="o">.</span><span class="n">to</span><span class="p">(</span><span class="s2">&quot;cpu&quot;</span><span class="p">)</span>

    <span class="c1"># Find probabilities (results) by passing through the function (note the log softmax means that its on a log scale)</span>
    <span class="n">log_probs</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="n">torch_image</span><span class="p">)</span>

    <span class="c1"># Convert to linear scale</span>
    <span class="n">linear_probs</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">log_probs</span><span class="p">)</span>

    <span class="c1"># Find the top 5 results</span>
    <span class="n">top_probs</span><span class="p">,</span> <span class="n">top_labels</span> <span class="o">=</span> <span class="n">linear_probs</span><span class="o">.</span><span class="n">topk</span><span class="p">(</span><span class="n">top_k</span><span class="p">)</span>
    
    <span class="c1"># Detatch all of the details</span>
    <span class="n">top_probs</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">top_probs</span><span class="o">.</span><span class="n">detach</span><span class="p">())[</span><span class="mi">0</span><span class="p">]</span> <span class="c1"># This is not the correct way to do it but the correct way isnt working thanks to cpu/gpu issues so I don&#39;t care.</span>
    <span class="n">top_labels</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">top_labels</span><span class="o">.</span><span class="n">detach</span><span class="p">())[</span><span class="mi">0</span><span class="p">]</span>
    
    <span class="c1"># Convert to classes</span>
    <span class="n">idx_to_class</span> <span class="o">=</span> <span class="p">{</span><span class="n">val</span><span class="p">:</span> <span class="n">key</span> <span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">val</span> <span class="ow">in</span>    
                                      <span class="n">model</span><span class="o">.</span><span class="n">class_to_idx</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>
    <span class="n">top_labels</span> <span class="o">=</span> <span class="p">[</span><span class="n">idx_to_class</span><span class="p">[</span><span class="n">lab</span><span class="p">]</span> <span class="k">for</span> <span class="n">lab</span> <span class="ow">in</span> <span class="n">top_labels</span><span class="p">]</span>
    <span class="n">top_flowers</span> <span class="o">=</span> <span class="p">[</span><span class="n">cat_to_name</span><span class="p">[</span><span class="n">lab</span><span class="p">]</span> <span class="k">for</span> <span class="n">lab</span> <span class="ow">in</span> <span class="n">top_labels</span><span class="p">]</span>
    
    <span class="k">return</span> <span class="n">top_probs</span><span class="p">,</span> <span class="n">top_labels</span><span class="p">,</span> <span class="n">top_flowers</span>
    <span class="c1"># TODO: Implement the code to predict the class from an image file</span>
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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="s2">&quot;flowers/test/10/image_07090.jpg&quot;</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">labs</span><span class="p">,</span> <span class="n">flowers</span> <span class="o">=</span> <span class="n">predict</span><span class="p">(</span><span class="n">image_path</span><span class="p">,</span> <span class="n">model</span><span class="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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