Traffic_Sign_Classifier.html

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

<title>Traffic_Sign_Classifier</title>

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

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

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

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

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

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

    </style>
<style type="text/css">
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<h1 id="Self-Driving-Car-Engineer-Nanodegree">Self-Driving Car Engineer Nanodegree<a class="anchor-link" href="#Self-Driving-Car-Engineer-Nanodegree">&#182;</a></h1><h2 id="Deep-Learning">Deep Learning<a class="anchor-link" href="#Deep-Learning">&#182;</a></h2><h2 id="Project:-Build-a-Traffic-Sign-Recognition-Classifier">Project: Build a Traffic Sign Recognition Classifier<a class="anchor-link" href="#Project:-Build-a-Traffic-Sign-Recognition-Classifier">&#182;</a></h2><p>In this notebook, a template is provided for you to implement your functionality in stages, which is required to successfully complete this project. If additional code is required that cannot be included in the notebook, be sure that the Python code is successfully imported and included in your submission if necessary.</p>
<blockquote><p><strong>Note</strong>: Once you have completed all of the code implementations, you need to finalize your work by exporting the iPython Notebook as an HTML document. Before exporting the notebook to html, all of the code cells need to have been run so that reviewers can see the final implementation and output. You can then export the notebook by using the menu above and navigating to  \n",
    "<strong>File -&gt; Download as -&gt; HTML (.html)</strong>. Include the finished document along with this notebook as your submission.</p>
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<p>In addition to implementing code, there is a writeup to complete. The writeup should be completed in a separate file, which can be either a markdown file or a pdf document. There is a <a href="https://github.com/udacity/CarND-Traffic-Sign-Classifier-Project/blob/master/writeup_template.md">write up template</a> that can be used to guide the writing process. Completing the code template and writeup template will cover all of the <a href="https://review.udacity.com/#!/rubrics/481/view">rubric points</a> for this project.</p>
<p>The <a href="https://review.udacity.com/#!/rubrics/481/view">rubric</a> contains "Stand Out Suggestions" for enhancing the project beyond the minimum requirements. The stand out suggestions are optional. If you decide to pursue the "stand out suggestions", you can include the code in this Ipython notebook and also discuss the results in the writeup file.</p>
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<h2 id="Step-0:-Load-The-Data">Step 0: Load The Data<a class="anchor-link" href="#Step-0:-Load-The-Data">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Load pickled data</span>
<span class="kn">import</span> <span class="nn">pickle</span>
<span class="kn">import</span> <span class="nn">os</span>
<span class="kn">from</span> <span class="nn">pathlib</span> <span class="k">import</span> <span class="n">Path</span>

<span class="c1"># DONE: Fill this in based on where you saved the training and testing data</span>

<span class="n">data_path</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">Path</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">getcwd</span><span class="p">())</span><span class="o">.</span><span class="n">parent</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot;/data/&quot;</span>
<span class="n">training_file</span> <span class="o">=</span> <span class="n">data_path</span> <span class="o">+</span> <span class="s2">&quot;train.p&quot;</span>
<span class="n">validation_file</span> <span class="o">=</span> <span class="n">data_path</span> <span class="o">+</span> <span class="s2">&quot;valid.p&quot;</span>
<span class="n">testing_file</span> <span class="o">=</span> <span class="n">data_path</span> <span class="o">+</span> <span class="s2">&quot;test.p&quot;</span>

<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">training_file</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;rb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    <span class="n">train</span> <span class="o">=</span> <span class="n">pickle</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="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">validation_file</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;rb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    <span class="n">valid</span> <span class="o">=</span> <span class="n">pickle</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="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">testing_file</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;rb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    <span class="n">test</span> <span class="o">=</span> <span class="n">pickle</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="n">X_train</span><span class="p">,</span> <span class="n">y_train</span> <span class="o">=</span> <span class="n">train</span><span class="p">[</span><span class="s1">&#39;features&#39;</span><span class="p">],</span> <span class="n">train</span><span class="p">[</span><span class="s1">&#39;labels&#39;</span><span class="p">]</span>
<span class="n">X_valid</span><span class="p">,</span> <span class="n">y_valid</span> <span class="o">=</span> <span class="n">valid</span><span class="p">[</span><span class="s1">&#39;features&#39;</span><span class="p">],</span> <span class="n">valid</span><span class="p">[</span><span class="s1">&#39;labels&#39;</span><span class="p">]</span>
<span class="n">X_test</span><span class="p">,</span> <span class="n">y_test</span> <span class="o">=</span> <span class="n">test</span><span class="p">[</span><span class="s1">&#39;features&#39;</span><span class="p">],</span> <span class="n">test</span><span class="p">[</span><span class="s1">&#39;labels&#39;</span><span class="p">]</span>
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<h2 id="Step-1:-Dataset-Summary-&amp;-Exploration">Step 1: Dataset Summary &amp; Exploration<a class="anchor-link" href="#Step-1:-Dataset-Summary-&amp;-Exploration">&#182;</a></h2><p>The pickled data is a dictionary with 4 key/value pairs:</p>
<ul>
<li><code>'features'</code> is a 4D array containing raw pixel data of the traffic sign images, (num examples, width, height, channels).</li>
<li><code>'labels'</code> is a 1D array containing the label/class id of the traffic sign. The file <code>signnames.csv</code> contains id -&gt; name mappings for each id.</li>
<li><code>'sizes'</code> is a list containing tuples, (width, height) representing the original width and height the image.</li>
<li><code>'coords'</code> is a list containing tuples, (x1, y1, x2, y2) representing coordinates of a bounding box around the sign in the image. <strong>THESE COORDINATES ASSUME THE ORIGINAL IMAGE. THE PICKLED DATA CONTAINS RESIZED VERSIONS (32 by 32) OF THESE IMAGES</strong></li>
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<p>Complete the basic data summary below. Use python, numpy and/or pandas methods to calculate the data summary rather than hard coding the results. For example, the <a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.shape.html">pandas shape method</a> might be useful for calculating some of the summary results.</p>

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<h3 id="Provide-a-Basic-Summary-of-the-Data-Set-Using-Python,-Numpy-and/or-Pandas">Provide a Basic Summary of the Data Set Using Python, Numpy and/or Pandas<a class="anchor-link" href="#Provide-a-Basic-Summary-of-the-Data-Set-Using-Python,-Numpy-and/or-Pandas">&#182;</a></h3>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### Replace each question mark with the appropriate value. </span>
<span class="c1">### Use python, pandas or numpy methods rather than hard coding the results</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>

<span class="c1"># Done: Number of training examples</span>
<span class="n">n_train</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">X_train</span><span class="p">)</span>

<span class="c1"># Done: Number of validation examples</span>
<span class="n">n_validation</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">X_valid</span><span class="p">)</span>

<span class="c1"># Done: Number of testing examples.</span>
<span class="n">n_test</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>

<span class="c1"># Done: What&#39;s the shape of an traffic sign image?</span>
<span class="n">image_shape</span> <span class="o">=</span> <span class="n">X_train</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">shape</span>

<span class="c1"># Done: How many unique classes/labels there are in the dataset.</span>
<span class="n">n_classes</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">y_train</span><span class="p">))</span>

<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Number of training examples =&quot;</span><span class="p">,</span> <span class="n">n_train</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Number of valid examples =&quot;</span><span class="p">,</span> <span class="n">n_validation</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Number of testing examples =&quot;</span><span class="p">,</span> <span class="n">n_test</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Image data shape =&quot;</span><span class="p">,</span> <span class="n">image_shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Number of classes =&quot;</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">)</span>
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<pre>Number of training examples = 34799
Number of valid examples = 4410
Number of testing examples = 12630
Image data shape = (32, 32, 3)
Number of classes = 43
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<h3 id="Include-an-exploratory-visualization-of-the-dataset">Include an exploratory visualization of the dataset<a class="anchor-link" href="#Include-an-exploratory-visualization-of-the-dataset">&#182;</a></h3>
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<p>Visualize the German Traffic Signs Dataset using the pickled file(s). This is open ended, suggestions include: plotting traffic sign images, plotting the count of each sign, etc.</p>
<p>The <a href="http://matplotlib.org/">Matplotlib</a> <a href="http://matplotlib.org/examples/index.html">examples</a> and <a href="http://matplotlib.org/gallery.html">gallery</a> pages are a great resource for doing visualizations in Python.</p>
<p><strong>NOTE:</strong> It's recommended you start with something simple first. If you wish to do more, come back to it after you've completed the rest of the sections. It can be interesting to look at the distribution of classes in the training, validation and test set. Is the distribution the same? Are there more examples of some classes than others?</p>

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<h4 id="Load-the-traffic-signs-labels-from-CSV-file-and-print-the-first-10">Load the traffic signs labels from CSV file and print the first 10<a class="anchor-link" href="#Load-the-traffic-signs-labels-from-CSV-file-and-print-the-first-10">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">csv</span>
<span class="n">labels</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;signnames.csv&#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">file</span><span class="p">:</span>
    <span class="n">reader</span> <span class="o">=</span> <span class="n">csv</span><span class="o">.</span><span class="n">reader</span><span class="p">(</span><span class="n">file</span><span class="p">)</span>
    <span class="k">for</span> <span class="n">label</span> <span class="ow">in</span> <span class="n">reader</span><span class="p">:</span>
        <span class="n">labels</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">label</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
<span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="p">[</span><span class="mi">1</span><span class="p">:]</span> <span class="c1"># remove header</span>

<span class="nb">print</span><span class="p">(</span><span class="n">labels</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">10</span><span class="p">])</span>
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<pre>[&#39;Speed limit (20km/h)&#39;, &#39;Speed limit (30km/h)&#39;, &#39;Speed limit (50km/h)&#39;, &#39;Speed limit (60km/h)&#39;, &#39;Speed limit (70km/h)&#39;, &#39;Speed limit (80km/h)&#39;, &#39;End of speed limit (80km/h)&#39;, &#39;Speed limit (100km/h)&#39;, &#39;Speed limit (120km/h)&#39;, &#39;No passing&#39;]
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### Data exploration visualization code goes here.</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">random</span>

<span class="c1"># Visualizations will be shown in the notebook.</span>
<span class="o">%</span><span class="k">matplotlib</span> inline

<span class="n">index</span> <span class="o">=</span> <span class="n">random</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">X_train</span><span class="p">))</span>
<span class="n">image</span> <span class="o">=</span> <span class="n">X_train</span><span class="p">[</span><span class="n">index</span><span class="p">]</span><span class="o">.</span><span class="n">squeeze</span><span class="p">()</span>

<span class="n">rows</span> <span class="o">=</span> <span class="mi">7</span>
<span class="n">cols</span> <span class="o">=</span> <span class="mi">7</span>

<span class="n">fig</span><span class="p">,</span> <span class="n">axs</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">rows</span><span class="p">,</span> <span class="n">cols</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">set_size_inches</span><span class="p">(</span><span class="mi">25</span><span class="p">,</span> <span class="mi">25</span><span class="p">)</span>

<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_classes</span><span class="p">):</span>
    <span class="n">class_images</span> <span class="o">=</span> <span class="n">X_train</span><span class="p">[</span><span class="n">y_train</span> <span class="o">==</span> <span class="n">i</span><span class="p">]</span>
    <span class="n">index</span> <span class="o">=</span> <span class="n">index</span> <span class="o">=</span> <span class="n">random</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">class_images</span><span class="p">))</span>
    <span class="n">image</span> <span class="o">=</span> <span class="n">class_images</span><span class="p">[</span><span class="n">index</span><span class="p">]</span>
    
    <span class="n">axs</span><span class="p">[</span><span class="nb">int</span><span class="p">(</span><span class="n">i</span> <span class="o">/</span> <span class="n">rows</span><span class="p">)][</span><span class="n">i</span> <span class="o">%</span> <span class="n">cols</span><span class="p">]</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="n">axs</span><span class="p">[</span><span class="nb">int</span><span class="p">(</span><span class="n">i</span> <span class="o">/</span> <span class="n">rows</span><span class="p">)][</span><span class="n">i</span> <span class="o">%</span> <span class="n">cols</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="n">labels</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">12</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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<h3 id="Histogram-Distribution">Histogram Distribution<a class="anchor-link" href="#Histogram-Distribution">&#182;</a></h3><p>This section explores the distribution of the classes in the training, test and validation dataset.</p>
<p>From the graphs, we see that the distribution in all datasets are almost the same, there is a variation in the distribution from one class to another is large.</p>
<p>Data normalisation would be used to mitigate this challenge.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Dataset visualisation</span>
<span class="n">fig</span><span class="p">,</span> <span class="n">axs</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="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">sharey</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">tight_layout</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">[</span><span class="mi">15</span><span class="p">,</span><span class="mi">5</span><span class="p">])</span>

<span class="n">axs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Train classes distribution&#39;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">11</span><span class="p">)</span>
<span class="n">axs</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Validation classes distribution&#39;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">11</span><span class="p">)</span>
<span class="n">axs</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Test classes distribution&#39;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">11</span><span class="p">)</span>

<span class="n">x_train_hist</span><span class="p">,</span> <span class="n">y_train_hist</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">axs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">y_train</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="n">n_classes</span><span class="p">)</span>
<span class="n">x_valid_hist</span><span class="p">,</span> <span class="n">y_valid_hist</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">axs</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">y_valid</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="n">n_classes</span><span class="p">)</span>
<span class="n">x_test_hist</span><span class="p">,</span> <span class="n">y_test_hist</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">axs</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="n">n_classes</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Maximum class labels in train data&quot;</span><span class="p">,</span><span class="n">x_train_hist</span><span class="o">.</span><span class="n">max</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Minimum class labels in test data&quot;</span><span class="p">,</span><span class="n">x_train_hist</span><span class="o">.</span><span class="n">min</span><span class="p">(),</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Maximum class labels in validation data&quot;</span><span class="p">,</span><span class="n">x_valid_hist</span><span class="o">.</span><span class="n">max</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Mininum class labels in validation data&quot;</span><span class="p">,</span><span class="n">x_valid_hist</span><span class="o">.</span><span class="n">min</span><span class="p">(),</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Maximum class labels in test data&quot;</span><span class="p">,</span><span class="n">x_test_hist</span><span class="o">.</span><span class="n">max</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Minimum class labels in test data&quot;</span><span class="p">,</span><span class="n">x_test_hist</span><span class="o">.</span><span class="n">min</span><span class="p">())</span>
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<pre>Maximum class labels in train data 2010.0
Minimum class labels in test data 180.0 

Maximum class labels in validation data 240.0
Mininum class labels in validation data 30.0 

Maximum class labels in test data 750.0
Minimum class labels in test data 60.0
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<pre>/opt/conda/lib/python3.6/site-packages/matplotlib/figure.py:1999: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.
  warnings.warn(&#34;This figure includes Axes that are not compatible &#34;
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<h2 id="Step-2:-Design-and-Test-a-Model-Architecture">Step 2: Design and Test a Model Architecture<a class="anchor-link" href="#Step-2:-Design-and-Test-a-Model-Architecture">&#182;</a></h2><p>Design and implement a deep learning model that learns to recognize traffic signs. Train and test your model on the <a href="http://benchmark.ini.rub.de/?section=gtsrb&amp;subsection=dataset">German Traffic Sign Dataset</a>.</p>
<p>The LeNet-5 implementation shown in the <a href="https://classroom.udacity.com/nanodegrees/nd013/parts/fbf77062-5703-404e-b60c-95b78b2f3f9e/modules/6df7ae49-c61c-4bb2-a23e-6527e69209ec/lessons/601ae704-1035-4287-8b11-e2c2716217ad/concepts/d4aca031-508f-4e0b-b493-e7b706120f81">classroom</a> at the end of the CNN lesson is a solid starting point. You'll have to change the number of classes and possibly the preprocessing, but aside from that it's plug and play!</p>
<p>With the LeNet-5 solution from the lecture, you should expect a validation set accuracy of about 0.89. To meet specifications, the validation set accuracy will need to be at least 0.93. It is possible to get an even higher accuracy, but 0.93 is the minimum for a successful project submission.</p>
<p>There are various aspects to consider when thinking about this problem:</p>
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<li>Neural network architecture (is the network over or underfitting?)</li>
<li>Play around preprocessing techniques (normalization, rgb to grayscale, etc)</li>
<li>Number of examples per label (some have more than others).</li>
<li>Generate fake data.</li>
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<p>Here is an example of a <a href="http://yann.lecun.com/exdb/publis/pdf/sermanet-ijcnn-11.pdf">published baseline model on this problem</a>. It's not required to be familiar with the approach used in the paper but, it's good practice to try to read papers like these.</p>

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<h3 id="Pre-process-the-Data-Set-(normalization,-grayscale,-etc.)">Pre-process the Data Set (normalization, grayscale, etc.)<a class="anchor-link" href="#Pre-process-the-Data-Set-(normalization,-grayscale,-etc.)">&#182;</a></h3>
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<p>Minimally, the image data should be normalized so that the data has mean zero and equal variance. For image data, <code>(pixel - 128)/ 128</code> is a quick way to approximately normalize the data and can be used in this project.</p>
<p>Other pre-processing steps are optional. You can try different techniques to see if it improves performance.</p>
<p>Use the code cell (or multiple code cells, if necessary) to implement the first step of your project.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### Preprocess the data here. It is required to normalize the data. Other preprocessing steps could include </span>
<span class="c1">### converting to grayscale, etc.</span>
<span class="c1">### Feel free to use as many code cells as needed.</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">cv2</span>
<span class="kn">import</span> <span class="nn">random</span>

<span class="k">def</span> <span class="nf">gray_and_equalize</span><span class="p">(</span><span class="n">img</span><span class="p">):</span>
    <span class="n">img</span> <span class="o">=</span> <span class="n">cv2</span><span class="o">.</span><span class="n">cvtColor</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">cv2</span><span class="o">.</span><span class="n">COLOR_RGB2GRAY</span><span class="p">)</span>
    <span class="n">clahe</span> <span class="o">=</span> <span class="n">cv2</span><span class="o">.</span><span class="n">createCLAHE</span><span class="p">(</span><span class="n">clipLimit</span><span class="o">=</span><span class="mf">2.0</span><span class="p">,</span> <span class="n">tileGridSize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span><span class="mi">8</span><span class="p">))</span>
    <span class="n">img</span> <span class="o">=</span> <span class="n">clahe</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">img</span>


<span class="n">index</span> <span class="o">=</span> <span class="mi">22188</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">1</span><span class="p">,</span><span class="mi">1</span><span class="p">))</span>
<span class="n">image</span> <span class="o">=</span> <span class="n">X_train</span><span class="p">[</span><span class="n">index</span><span class="p">]</span><span class="o">.</span><span class="n">squeeze</span><span class="p">()</span>
<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">image</span><span class="p">)</span>

<span class="n">X_train</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">stack</span><span class="p">([</span><span class="n">gray_and_equalize</span><span class="p">(</span><span class="n">img</span><span class="p">)</span> <span class="k">for</span> <span class="n">img</span> <span class="ow">in</span> <span class="n">X_train</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="n">X_test</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">stack</span><span class="p">([</span><span class="n">gray_and_equalize</span><span class="p">(</span><span class="n">img</span><span class="p">)</span> <span class="k">for</span> <span class="n">img</span> <span class="ow">in</span> <span class="n">X_test</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="n">X_valid</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">stack</span><span class="p">([</span><span class="n">gray_and_equalize</span><span class="p">(</span><span class="n">img</span><span class="p">)</span> <span class="k">for</span> <span class="n">img</span> <span class="ow">in</span> <span class="n">X_valid</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="n">image</span> <span class="o">=</span> <span class="n">X_train</span><span class="p">[</span><span class="n">index</span><span class="p">]</span><span class="o">.</span><span class="n">squeeze</span><span class="p">()</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">1</span><span class="p">,</span><span class="mi">2</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s1">&#39;gray&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">labels</span><span class="p">[</span><span class="n">y_train</span><span class="p">[</span><span class="n">index</span><span class="p">]])</span>
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<pre>Yield
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<h3 id="Model-Architecture">Model Architecture<a class="anchor-link" href="#Model-Architecture">&#182;</a></h3>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### Define your architecture here.</span>
<span class="c1">### Feel free to use as many code cells as needed.</span>
<span class="kn">from</span> <span class="nn">tensorflow.contrib.layers</span> <span class="k">import</span> <span class="n">flatten</span>

<span class="k">def</span> <span class="nf">LeNet</span><span class="p">(</span><span class="n">x</span><span class="p">):</span>    
    <span class="c1"># Arguments used for tf.truncated_normal, randomly defines variables for the weights and biases for each layer</span>
    <span class="n">mu</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="n">sigma</span> <span class="o">=</span> <span class="mf">0.1</span>
    
    <span class="c1"># Layer 1: Convolutional. Input = 32x32x1. Output = 28x28x32.</span>
    <span class="n">conv1_W</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">truncated_normal</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">32</span><span class="p">),</span> <span class="n">mean</span> <span class="o">=</span> <span class="n">mu</span><span class="p">,</span> <span class="n">stddev</span> <span class="o">=</span> <span class="n">sigma</span><span class="p">))</span>
    <span class="n">conv1_b</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="mi">32</span><span class="p">))</span>
    <span class="n">conv1</span>   <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">conv2d</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">conv1_W</span><span class="p">,</span> <span class="n">strides</span><span class="o">=</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="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">padding</span><span class="o">=</span><span class="s1">&#39;VALID&#39;</span><span class="p">)</span> <span class="o">+</span> <span class="n">conv1_b</span>

    <span class="c1"># Activation.</span>
    <span class="n">conv1</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="n">conv1</span><span class="p">)</span>

    <span class="c1"># Pooling. Input = 28x28x32. Output = 14x14x32.</span>
    <span class="n">conv1</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">max_pool</span><span class="p">(</span><span class="n">conv1</span><span class="p">,</span> <span class="n">ksize</span><span class="o">=</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">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">strides</span><span class="o">=</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">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">padding</span><span class="o">=</span><span class="s1">&#39;VALID&#39;</span><span class="p">)</span>

    <span class="c1"># Layer 2: Convolutional. Output = 10x10x64.</span>
    <span class="n">conv2_W</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">truncated_normal</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">32</span><span class="p">,</span> <span class="mi">64</span><span class="p">),</span> <span class="n">mean</span> <span class="o">=</span> <span class="n">mu</span><span class="p">,</span> <span class="n">stddev</span> <span class="o">=</span> <span class="n">sigma</span><span class="p">))</span>
    <span class="n">conv2_b</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="mi">64</span><span class="p">))</span>
    <span class="n">conv2</span>   <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">conv2d</span><span class="p">(</span><span class="n">conv1</span><span class="p">,</span> <span class="n">conv2_W</span><span class="p">,</span> <span class="n">strides</span><span class="o">=</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="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">padding</span><span class="o">=</span><span class="s1">&#39;VALID&#39;</span><span class="p">)</span> <span class="o">+</span> <span class="n">conv2_b</span>
    
    <span class="c1"># Activation.</span>
    <span class="n">conv2</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="n">conv2</span><span class="p">)</span>

    <span class="c1"># Pooling. Input = 10x10x64. Output = 5x5x64.</span>
    <span class="n">conv2</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">max_pool</span><span class="p">(</span><span class="n">conv2</span><span class="p">,</span> <span class="n">ksize</span><span class="o">=</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">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">strides</span><span class="o">=</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">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">padding</span><span class="o">=</span><span class="s1">&#39;VALID&#39;</span><span class="p">)</span>

    <span class="c1"># Flatten. Input = 5x5x64. Output = 1600.</span>
    <span class="n">fc0</span>   <span class="o">=</span> <span class="n">flatten</span><span class="p">(</span><span class="n">conv2</span><span class="p">)</span>
    
    <span class="c1"># Layer 3: Fully Connected. Input = 1600. Output = 400.</span>
    <span class="n">fc1_W</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">truncated_normal</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">1600</span><span class="p">,</span> <span class="mi">400</span><span class="p">),</span> <span class="n">mean</span> <span class="o">=</span> <span class="n">mu</span><span class="p">,</span> <span class="n">stddev</span> <span class="o">=</span> <span class="n">sigma</span><span class="p">))</span>
    <span class="n">fc1_b</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="mi">400</span><span class="p">))</span>
    <span class="n">fc1</span>   <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">matmul</span><span class="p">(</span><span class="n">fc0</span><span class="p">,</span> <span class="n">fc1_W</span><span class="p">)</span> <span class="o">+</span> <span class="n">fc1_b</span>
    
    <span class="c1"># Activation.</span>
    <span class="n">fc1</span>    <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="n">fc1</span><span class="p">)</span>

    <span class="c1"># Layer 4: Fully Connected. Input = 400. Output = 100.</span>
    <span class="n">fc2_W</span>  <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">truncated_normal</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">400</span><span class="p">,</span> <span class="mi">100</span><span class="p">),</span> <span class="n">mean</span> <span class="o">=</span> <span class="n">mu</span><span class="p">,</span> <span class="n">stddev</span> <span class="o">=</span> <span class="n">sigma</span><span class="p">))</span>
    <span class="n">fc2_b</span>  <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="mi">100</span><span class="p">))</span>
    <span class="n">fc2</span>    <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">matmul</span><span class="p">(</span><span class="n">fc1</span><span class="p">,</span> <span class="n">fc2_W</span><span class="p">)</span> <span class="o">+</span> <span class="n">fc2_b</span>
    
    <span class="c1"># Activation.</span>
    <span class="n">fc2</span>    <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="n">fc2</span><span class="p">)</span>

    <span class="c1"># Layer 5: Fully Connected. Input = 100. Output = 43.</span>
    <span class="n">fc3_W</span>  <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">truncated_normal</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">100</span><span class="p">,</span> <span class="mi">43</span><span class="p">),</span> <span class="n">mean</span> <span class="o">=</span> <span class="n">mu</span><span class="p">,</span> <span class="n">stddev</span> <span class="o">=</span> <span class="n">sigma</span><span class="p">))</span>
    <span class="n">fc3_b</span>  <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">n_classes</span><span class="p">))</span>
    <span class="n">logits</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">matmul</span><span class="p">(</span><span class="n">fc2</span><span class="p">,</span> <span class="n">fc3_W</span><span class="p">)</span> <span class="o">+</span> <span class="n">fc3_b</span>
    
    <span class="k">return</span> <span class="n">logits</span>
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<h3 id="Train,-Validate-and-Test-the-Model">Train, Validate and Test the Model<a class="anchor-link" href="#Train,-Validate-and-Test-the-Model">&#182;</a></h3>
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<p>A validation set can be used to assess how well the model is performing. A low accuracy on the training and validation
sets imply underfitting. A high accuracy on the training set but low accuracy on the validation set implies overfitting.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### Train your model here.</span>
<span class="c1">### Calculate and report the accuracy on the training and validation set.</span>
<span class="c1">### Once a final model architecture is selected, </span>
<span class="c1">### the accuracy on the test set should be calculated and reported as well.</span>
<span class="c1">### Feel free to use as many code cells as needed.</span>
<span class="kn">import</span> <span class="nn">tensorflow</span> <span class="k">as</span> <span class="nn">tf</span>

<span class="c1"># Hyperparamters</span>
<span class="n">EPOCHS</span> <span class="o">=</span> <span class="mi">20</span>
<span class="n">BATCH_SIZE</span> <span class="o">=</span> <span class="mi">64</span>
<span class="n">rate</span> <span class="o">=</span> <span class="mf">0.001</span>

<span class="c1"># Features and Labels</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="p">(</span><span class="kc">None</span><span class="p">,</span> <span class="mi">32</span><span class="p">,</span> <span class="mi">32</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span> <span class="p">(</span><span class="kc">None</span><span class="p">))</span>
<span class="n">one_hot_y</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">one_hot</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Setup the pipeline</span>
<span class="n">logits</span> <span class="o">=</span> <span class="n">LeNet</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="n">cross_entropy</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">softmax_cross_entropy_with_logits</span><span class="p">(</span><span class="n">labels</span><span class="o">=</span><span class="n">one_hot_y</span><span class="p">,</span> <span class="n">logits</span><span class="o">=</span><span class="n">logits</span><span class="p">)</span>
<span class="n">loss_operation</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">reduce_mean</span><span class="p">(</span><span class="n">cross_entropy</span><span class="p">)</span>
<span class="n">optimizer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">train</span><span class="o">.</span><span class="n">AdamOptimizer</span><span class="p">(</span><span class="n">learning_rate</span> <span class="o">=</span> <span class="n">rate</span><span class="p">)</span>
<span class="n">training_operation</span> <span class="o">=</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">minimize</span><span class="p">(</span><span class="n">loss_operation</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Evaluating the Model</span>
<span class="n">correct_prediction</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">equal</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">logits</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">tf</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">one_hot_y</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span>
<span class="n">accuracy_operation</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">reduce_mean</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">cast</span><span class="p">(</span><span class="n">correct_prediction</span><span class="p">,</span> <span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">))</span>
<span class="n">saver</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">train</span><span class="o">.</span><span class="n">Saver</span><span class="p">()</span>

<span class="k">def</span> <span class="nf">evaluate</span><span class="p">(</span><span class="n">X_data</span><span class="p">,</span> <span class="n">y_data</span><span class="p">):</span>
    <span class="n">num_examples</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">X_data</span><span class="p">)</span>
    <span class="n">total_accuracy</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="n">sess</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">get_default_session</span><span class="p">()</span>
    <span class="k">for</span> <span class="n">offset</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">num_examples</span><span class="p">,</span> <span class="n">BATCH_SIZE</span><span class="p">):</span>
        <span class="n">batch_x</span><span class="p">,</span> <span class="n">batch_y</span> <span class="o">=</span> <span class="n">X_data</span><span class="p">[</span><span class="n">offset</span><span class="p">:</span><span class="n">offset</span><span class="o">+</span><span class="n">BATCH_SIZE</span><span class="p">],</span> <span class="n">y_data</span><span class="p">[</span><span class="n">offset</span><span class="p">:</span><span class="n">offset</span><span class="o">+</span><span class="n">BATCH_SIZE</span><span class="p">]</span>
        <span class="n">accuracy</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">accuracy_operation</span><span class="p">,</span> <span class="n">feed_dict</span><span class="o">=</span><span class="p">{</span><span class="n">x</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">batch_x</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">3</span><span class="p">),</span> <span class="n">y</span><span class="p">:</span> <span class="n">batch_y</span><span class="p">})</span>
        <span class="n">total_accuracy</span> <span class="o">+=</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">batch_x</span><span class="p">))</span>
    <span class="k">return</span> <span class="n">total_accuracy</span> <span class="o">/</span> <span class="n">num_examples</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.utils</span> <span class="k">import</span> <span class="n">shuffle</span>

<span class="n">model_file</span> <span class="o">=</span> <span class="s1">&#39;./lenet&#39;</span>

<span class="c1"># Training the model</span>
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
    <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">global_variables_initializer</span><span class="p">())</span>
    <span class="n">num_examples</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">X_train</span><span class="p">)</span>
    
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Training...&quot;</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">()</span>
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">EPOCHS</span><span class="p">):</span>
        <span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span> <span class="o">=</span> <span class="n">shuffle</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">)</span>
        <span class="k">for</span> <span class="n">offset</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">num_examples</span><span class="p">,</span> <span class="n">BATCH_SIZE</span><span class="p">):</span>
            <span class="n">end</span> <span class="o">=</span> <span class="n">offset</span> <span class="o">+</span> <span class="n">BATCH_SIZE</span>
            <span class="n">batch_x</span><span class="p">,</span> <span class="n">batch_y</span> <span class="o">=</span> <span class="n">X_train</span><span class="p">[</span><span class="n">offset</span><span class="p">:</span><span class="n">end</span><span class="p">],</span> <span class="n">y_train</span><span class="p">[</span><span class="n">offset</span><span class="p">:</span><span class="n">end</span><span class="p">]</span>
            <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">training_operation</span><span class="p">,</span> <span class="n">feed_dict</span><span class="o">=</span><span class="p">{</span><span class="n">x</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">batch_x</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">3</span><span class="p">),</span> <span class="n">y</span><span class="p">:</span> <span class="n">batch_y</span><span class="p">})</span>
            
        <span class="n">validation_accuracy</span> <span class="o">=</span> <span class="n">evaluate</span><span class="p">(</span><span class="n">X_valid</span><span class="p">,</span> <span class="n">y_valid</span><span class="p">)</span>
        <span class="n">training_accuracy</span> <span class="o">=</span> <span class="n">evaluate</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</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"> ...&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="p">))</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Training Accuracy = </span><span class="si">{:.3f}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">training_accuracy</span><span class="p">))</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Validation Accuracy = </span><span class="si">{:.3f}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">validation_accuracy</span><span class="p">))</span>
        <span class="nb">print</span><span class="p">()</span>
        
    <span class="n">saver</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">sess</span><span class="p">,</span> <span class="n">model_file</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Model saved&quot;</span><span class="p">)</span>
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<pre>Training...

EPOCH 1 ...
Training Accuracy = 0.438
Validation Accuracy = 0.413

EPOCH 2 ...
Training Accuracy = 0.653
Validation Accuracy = 0.603

EPOCH 3 ...
Training Accuracy = 0.794
Validation Accuracy = 0.746

EPOCH 4 ...
Training Accuracy = 0.871
Validation Accuracy = 0.800

EPOCH 5 ...
Training Accuracy = 0.921
Validation Accuracy = 0.855

EPOCH 6 ...
Training Accuracy = 0.961
Validation Accuracy = 0.889

EPOCH 7 ...
Training Accuracy = 0.968
Validation Accuracy = 0.908

EPOCH 8 ...
Training Accuracy = 0.969
Validation Accuracy = 0.916

EPOCH 9 ...
Training Accuracy = 0.971
Validation Accuracy = 0.919

EPOCH 10 ...
Training Accuracy = 0.978
Validation Accuracy = 0.926

EPOCH 11 ...
Training Accuracy = 0.963
Validation Accuracy = 0.908

EPOCH 12 ...
Training Accuracy = 0.988
Validation Accuracy = 0.943

EPOCH 13 ...
Training Accuracy = 0.979
Validation Accuracy = 0.928

EPOCH 14 ...
Training Accuracy = 0.979
Validation Accuracy = 0.927

EPOCH 15 ...
Training Accuracy = 0.988
Validation Accuracy = 0.941

EPOCH 16 ...
Training Accuracy = 0.992
Validation Accuracy = 0.945

EPOCH 17 ...
Training Accuracy = 0.990
Validation Accuracy = 0.950

EPOCH 18 ...
Training Accuracy = 0.990
Validation Accuracy = 0.954

EPOCH 19 ...
Training Accuracy = 0.989
Validation Accuracy = 0.947

EPOCH 20 ...
Training Accuracy = 0.994
Validation Accuracy = 0.954

Model saved
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Evaluating the model</span>
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
    <span class="n">saver</span><span class="o">.</span><span class="n">restore</span><span class="p">(</span><span class="n">sess</span><span class="p">,</span> <span class="n">tf</span><span class="o">.</span><span class="n">train</span><span class="o">.</span><span class="n">latest_checkpoint</span><span class="p">(</span><span class="s1">&#39;.&#39;</span><span class="p">))</span>

    <span class="n">test_accuracy</span> <span class="o">=</span> <span class="n">evaluate</span><span class="p">(</span><span class="n">X_test</span><span class="p">,</span> <span class="n">y_test</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Test Accuracy = </span><span class="si">{:.3f}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">test_accuracy</span><span class="p">))</span>
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<pre>INFO:tensorflow:Restoring parameters from ./lenet
Test Accuracy = 0.943
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<h2 id="Step-3:-Test-a-Model-on-New-Images">Step 3: Test a Model on New Images<a class="anchor-link" href="#Step-3:-Test-a-Model-on-New-Images">&#182;</a></h2><p>To give yourself more insight into how your model is working, download at least five pictures of German traffic signs from the web and use your model to predict the traffic sign type.</p>
<p>You may find <code>signnames.csv</code> useful as it contains mappings from the class id (integer) to the actual sign name.</p>

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<h3 id="Load-and-Output-the-Images">Load and Output the Images<a class="anchor-link" href="#Load-and-Output-the-Images">&#182;</a></h3>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### Load the images and plot them here.</span>
<span class="c1">### Feel free to use as many code cells as needed.</span>
<span class="kn">import</span> <span class="nn">glob</span>

<span class="n">image_files</span> <span class="o">=</span> <span class="n">glob</span><span class="o">.</span><span class="n">glob</span><span class="p">(</span><span class="s1">&#39;test_images/*.jpg&#39;</span><span class="p">)</span>

<span class="n">images</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">my_labels</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">index</span><span class="p">,</span> <span class="n">filename</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">image_files</span><span class="p">):</span>
    <span class="n">img</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">imread</span><span class="p">(</span><span class="n">filename</span><span class="p">)</span>
    <span class="n">img</span> <span class="o">=</span> <span class="n">cv2</span><span class="o">.</span><span class="n">resize</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="p">(</span><span class="mi">32</span><span class="p">,</span> <span class="mi">32</span><span class="p">))</span>
    
    <span class="n">images</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
    <span class="n">my_labels</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">int</span><span class="p">(</span><span class="n">filename</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">&quot;.&quot;</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">&quot;/&quot;</span><span class="p">)[</span><span class="mi">1</span><span class="p">]))</span>
    
<span class="n">rows</span> <span class="o">=</span> <span class="mi">5</span>
<span class="n">cols</span> <span class="o">=</span> <span class="mi">5</span>

<span class="n">fig</span><span class="p">,</span> <span class="n">axs</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">rows</span><span class="p">,</span> <span class="n">cols</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">set_size_inches</span><span class="p">(</span><span class="mi">25</span><span class="p">,</span> <span class="mi">25</span><span class="p">)</span>

<span class="n">num_of_images</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">images</span><span class="p">)</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_of_images</span><span class="p">):</span>
    <span class="n">axs</span><span class="p">[</span><span class="nb">int</span><span class="p">(</span><span class="n">i</span> <span class="o">/</span> <span class="n">rows</span><span class="p">)][</span><span class="n">i</span> <span class="o">%</span> <span class="n">cols</span><span class="p">]</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">images</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
    <span class="n">axs</span><span class="p">[</span><span class="nb">int</span><span class="p">(</span><span class="n">i</span> <span class="o">/</span> <span class="n">rows</span><span class="p">)][</span><span class="n">i</span> <span class="o">%</span> <span class="n">cols</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="n">labels</span><span class="p">[</span><span class="n">my_labels</span><span class="p">[</span><span class="n">i</span><span class="p">]],</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

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<h3 id="Predict-the-Sign-Type-for-Each-Image">Predict the Sign Type for Each Image<a class="anchor-link" href="#Predict-the-Sign-Type-for-Each-Image">&#182;</a></h3>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### Run the predictions here and use the model to output the prediction for each image.</span>
<span class="c1">### Make sure to pre-process the images with the same pre-processing pipeline used earlier.</span>
<span class="c1">### Feel free to use as many code cells as needed.</span>

<span class="n">preprocessed_images</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">stack</span><span class="p">([</span><span class="n">gray_and_equalize</span><span class="p">(</span><span class="n">img</span><span class="p">)</span> <span class="k">for</span> <span class="n">img</span> <span class="ow">in</span> <span class="n">images</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="n">keep_prob</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>

<span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="n">features</span><span class="p">):</span>
    <span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
        <span class="n">saver</span><span class="o">.</span><span class="n">restore</span><span class="p">(</span><span class="n">sess</span><span class="p">,</span> <span class="n">model_file</span><span class="p">)</span>
        <span class="n">results</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">logits</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="p">{</span><span class="n">x</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">features</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">3</span><span class="p">),</span> <span class="n">keep_prob</span><span class="p">:</span><span class="mf">1.0</span><span class="p">})</span>
        <span class="k">return</span> <span class="n">results</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">predictions</span> <span class="o">=</span> <span class="n">predict</span><span class="p">(</span><span class="n">preprocessed_images</span><span class="p">)</span>

<span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">for</span> <span class="n">prediction</span> <span class="ow">in</span> <span class="n">predictions</span><span class="p">:</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Prediction: </span><span class="si">{}</span><span class="s2"> | Actual: </span><span class="si">{}</span><span class="s2"> </span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">labels</span><span class="p">[</span><span class="n">prediction</span><span class="p">],</span> <span class="n">labels</span><span class="p">[</span><span class="n">my_labels</span><span class="p">[</span><span class="n">count</span><span class="p">]]))</span>
    <span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
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<pre>INFO:tensorflow:Restoring parameters from ./lenet
Prediction: Go straight or left | Actual: Go straight or left 

Prediction: Bumpy road | Actual: Bumpy road 

Prediction: Yield | Actual: Yield 

Prediction: Speed limit (50km/h) | Actual: Speed limit (30km/h) 

Prediction: Go straight or right | Actual: Go straight or right 

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<h3 id="Analyze-Performance">Analyze Performance<a class="anchor-link" href="#Analyze-Performance">&#182;</a></h3>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### Calculate the accuracy for these 5 new images. </span>
<span class="c1">### For example, if the model predicted 1 out of 5 signs correctly, it&#39;s 20% accurate on these new images.</span>
<span class="kn">import</span> <span class="nn">tensorflow</span> <span class="k">as</span> <span class="nn">tf</span>

<span class="n">model_file</span> <span class="o">=</span> <span class="s1">&#39;./lenet&#39;</span>
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
    <span class="n">saver</span><span class="o">.</span><span class="n">restore</span><span class="p">(</span><span class="n">sess</span><span class="p">,</span> <span class="n">model_file</span><span class="p">)</span>
    <span class="n">acc</span> <span class="o">=</span> <span class="n">evaluate</span><span class="p">(</span><span class="n">preprocessed_images</span><span class="p">,</span> <span class="n">my_labels</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;accuracy is </span><span class="si">{:.3f}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">acc</span><span class="p">))</span>
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<pre>INFO:tensorflow:Restoring parameters from ./lenet
accuracy is 0.800
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<h3 id="Output-Top-5-Softmax-Probabilities-For-Each-Image-Found-on-the-Web">Output Top 5 Softmax Probabilities For Each Image Found on the Web<a class="anchor-link" href="#Output-Top-5-Softmax-Probabilities-For-Each-Image-Found-on-the-Web">&#182;</a></h3>
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<p>For each of the new images, print out the model's softmax probabilities to show the <strong>certainty</strong> of the model's predictions (limit the output to the top 5 probabilities for each image). <a href="https://www.tensorflow.org/versions/r0.12/api_docs/python/nn.html#top_k"><code>tf.nn.top_k</code></a> could prove helpful here.</p>
<p>The example below demonstrates how tf.nn.top_k can be used to find the top k predictions for each image.</p>
<p><code>tf.nn.top_k</code> will return the values and indices (class ids) of the top k predictions. So if k=3, for each sign, it'll return the 3 largest probabilities (out of a possible 43) and the correspoding class ids.</p>
<p>Take this numpy array as an example. The values in the array represent predictions. The array contains softmax probabilities for five candidate images with six possible classes. <code>tf.nn.top_k</code> is used to choose the three classes with the highest probability:</p>

<pre><code># (5, 6) array
a = np.array([[ 0.24879643,  0.07032244,  0.12641572,  0.34763842,  0.07893497,
         0.12789202],
       [ 0.28086119,  0.27569815,  0.08594638,  0.0178669 ,  0.18063401,
         0.15899337],
       [ 0.26076848,  0.23664738,  0.08020603,  0.07001922,  0.1134371 ,
         0.23892179],
       [ 0.11943333,  0.29198961,  0.02605103,  0.26234032,  0.1351348 ,
         0.16505091],
       [ 0.09561176,  0.34396535,  0.0643941 ,  0.16240774,  0.24206137,
         0.09155967]])</code></pre>
<p>Running it through <code>sess.run(tf.nn.top_k(tf.constant(a), k=3))</code> produces:</p>

<pre><code>TopKV2(values=array([[ 0.34763842,  0.24879643,  0.12789202],
       [ 0.28086119,  0.27569815,  0.18063401],
       [ 0.26076848,  0.23892179,  0.23664738],
       [ 0.29198961,  0.26234032,  0.16505091],
       [ 0.34396535,  0.24206137,  0.16240774]]), indices=array([[3, 0, 5],
       [0, 1, 4],
       [0, 5, 1],
       [1, 3, 5],
       [1, 4, 3]], dtype=int32))</code></pre>
<p>Looking just at the first row we get <code>[ 0.34763842,  0.24879643,  0.12789202]</code>, you can confirm these are the 3 largest probabilities in <code>a</code>. You'll also notice <code>[3, 0, 5]</code> are the corresponding indices.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### Print out the top five softmax probabilities for the predictions on the German traffic sign images found on the web. </span>
<span class="c1">### Feel free to use as many code cells as needed.</span>

<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">()</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
    <span class="n">saver</span><span class="o">.</span><span class="n">restore</span><span class="p">(</span><span class="n">sess</span><span class="p">,</span> <span class="n">model_file</span><span class="p">)</span>
    <span class="n">pred</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">softmax</span><span class="p">(</span><span class="n">logits</span><span class="p">)</span>
    <span class="n">results</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">top_k</span><span class="p">(</span><span class="n">pred</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mi">5</span><span class="p">),</span> <span class="p">{</span><span class="n">x</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">preprocessed_images</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">3</span><span class="p">),</span> <span class="n">keep_prob</span><span class="p">:</span><span class="mf">1.0</span><span class="p">})</span>
    
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Top Five Softmax Probabilities for Images from the Web&quot;</span><span class="p">)</span>
    <span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
    
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">images</span><span class="p">)):</span>
        <span class="nb">print</span><span class="p">(</span><span class="n">labels</span><span class="p">[</span><span class="n">my_labels</span><span class="p">[</span><span class="n">count</span><span class="p">]])</span>
        <span class="n">accuracy</span> <span class="o">=</span> <span class="n">results</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="n">i</span><span class="p">]</span>
        <span class="n">classes</span> <span class="o">=</span> <span class="n">results</span><span class="p">[</span><span class="mi">1</span><span class="p">][</span><span class="n">i</span><span class="p">]</span>
        <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">):</span>
            <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="si">{}</span><span class="s2">: </span><span class="si">{:.3f}</span><span class="s2"> &quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">labels</span><span class="p">[</span><span class="n">classes</span><span class="p">[</span><span class="n">j</span><span class="p">]],</span> <span class="n">accuracy</span><span class="p">[</span><span class="n">j</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">&quot;</span><span class="p">)</span>
        <span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
        
        
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<pre>INFO:tensorflow:Restoring parameters from ./lenet
Top Five Softmax Probabilities for Images from the Web
Go straight or left
Go straight or left: 1.000 
Turn left ahead: 0.000 
Keep left: 0.000 
Ahead only: 0.000 
Dangerous curve to the right: 0.000 


Bumpy road
Bumpy road: 1.000 
Bicycles crossing: 0.000 
Children crossing: 0.000 
Slippery road: 0.000 
Beware of ice/snow: 0.000 


Yield
Yield: 0.838 
Traffic signals: 0.158 
Priority road: 0.004 
General caution: 0.000 
Speed limit (80km/h): 0.000 


Speed limit (30km/h)
Speed limit (50km/h): 0.807 
Speed limit (30km/h): 0.129 
Wild animals crossing: 0.040 
Speed limit (80km/h): 0.017 
Speed limit (60km/h): 0.002 


Go straight or right
Go straight or right: 1.000 
Dangerous curve to the right: 0.000 
Keep right: 0.000 
Road work: 0.000 
End of speed limit (80km/h): 0.000 


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<h3 id="Project-Writeup">Project Writeup<a class="anchor-link" href="#Project-Writeup">&#182;</a></h3><p>Once you have completed the code implementation, document your results in a project writeup using this <a href="https://github.com/udacity/CarND-Traffic-Sign-Classifier-Project/blob/master/writeup_template.md">template</a> as a guide. The writeup can be in a markdown or pdf file.</p>

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<blockquote><p><strong>Note</strong>: Once you have completed all of the code implementations and successfully answered each question above, you may finalize your work by exporting the iPython Notebook as an HTML document. You can do this by using the menu above and navigating to  \n",
    "<strong>File -&gt; Download as -&gt; HTML (.html)</strong>. Include the finished document along with this notebook as your submission.</p>
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<hr>
<h2 id="Step-4-(Optional):-Visualize-the-Neural-Network's-State-with-Test-Images">Step 4 (Optional): Visualize the Neural Network's State with Test Images<a class="anchor-link" href="#Step-4-(Optional):-Visualize-the-Neural-Network's-State-with-Test-Images">&#182;</a></h2><p>This Section is not required to complete but acts as an additional excersise for understaning the output of a neural network's weights. While neural networks can be a great learning device they are often referred to as a black box. We can understand what the weights of a neural network look like better by plotting their feature maps. After successfully training your neural network you can see what it's feature maps look like by plotting the output of the network's weight layers in response to a test stimuli image. From these plotted feature maps, it's possible to see what characteristics of an image the network finds interesting. For a sign, maybe the inner network feature maps react with high activation to the sign's boundary outline or to the contrast in the sign's painted symbol.</p>
<p>Provided for you below is the function code that allows you to get the visualization output of any tensorflow weight layer you want. The inputs to the function should be a stimuli image, one used during training or a new one you provided, and then the tensorflow variable name that represents the layer's state during the training process, for instance if you wanted to see what the <a href="https://classroom.udacity.com/nanodegrees/nd013/parts/fbf77062-5703-404e-b60c-95b78b2f3f9e/modules/6df7ae49-c61c-4bb2-a23e-6527e69209ec/lessons/601ae704-1035-4287-8b11-e2c2716217ad/concepts/d4aca031-508f-4e0b-b493-e7b706120f81">LeNet lab's</a> feature maps looked like for it's second convolutional layer you could enter conv2 as the tf_activation variable.</p>
<p>For an example of what feature map outputs look like, check out NVIDIA's results in their paper <a href="https://devblogs.nvidia.com/parallelforall/deep-learning-self-driving-cars/">End-to-End Deep Learning for Self-Driving Cars</a> in the section Visualization of internal CNN State. NVIDIA was able to show that their network's inner weights had high activations to road boundary lines by comparing feature maps from an image with a clear path to one without. Try experimenting with a similar test to show that your trained network's weights are looking for interesting features, whether it's looking at differences in feature maps from images with or without a sign, or even what feature maps look like in a trained network vs a completely untrained one on the same sign image.</p>
<p><figure>
 <img src="visualize_cnn.png" width="380" alt="Combined Image" />
 <figcaption>
 <p></p> 
 <p style="text-align: center;"> Your output should look something like this (above)</p> 
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">### Visualize your network&#39;s feature maps here.</span>
<span class="c1">### Feel free to use as many code cells as needed.</span>

<span class="c1"># image_input: the test image being fed into the network to produce the feature maps</span>
<span class="c1"># tf_activation: should be a tf variable name used during your training procedure that represents the calculated state of a specific weight layer</span>
<span class="c1"># activation_min/max: can be used to view the activation contrast in more detail, by default matplot sets min and max to the actual min and max values of the output</span>
<span class="c1"># plt_num: used to plot out multiple different weight feature map sets on the same block, just extend the plt number for each new feature map entry</span>

<span class="k">def</span> <span class="nf">outputFeatureMap</span><span class="p">(</span><span class="n">image_input</span><span class="p">,</span> <span class="n">tf_activation</span><span class="p">,</span> <span class="n">activation_min</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">activation_max</span><span class="o">=-</span><span class="mi">1</span> <span class="p">,</span><span class="n">plt_num</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
    <span class="c1"># Here make sure to preprocess your image_input in a way your network expects</span>
    <span class="c1"># with size, normalization, ect if needed</span>
    <span class="c1"># image_input =</span>
    <span class="c1"># Note: x should be the same name as your network&#39;s tensorflow data placeholder variable</span>
    <span class="c1"># If you get an error tf_activation is not defined it may be having trouble accessing the variable from inside a function</span>
    <span class="n">activation</span> <span class="o">=</span> <span class="n">tf_activation</span><span class="o">.</span><span class="n">eval</span><span class="p">(</span><span class="n">session</span><span class="o">=</span><span class="n">sess</span><span class="p">,</span><span class="n">feed_dict</span><span class="o">=</span><span class="p">{</span><span class="n">x</span> <span class="p">:</span> <span class="n">image_input</span><span class="p">})</span>
    <span class="n">featuremaps</span> <span class="o">=</span> <span class="n">activation</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">plt_num</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span><span class="mi">15</span><span class="p">))</span>
    <span class="k">for</span> <span class="n">featuremap</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">featuremaps</span><span class="p">):</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">6</span><span class="p">,</span><span class="mi">8</span><span class="p">,</span> <span class="n">featuremap</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span> <span class="c1"># sets the number of feature maps to show on each row and column</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;FeatureMap &#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">featuremap</span><span class="p">))</span> <span class="c1"># displays the feature map number</span>
        <span class="k">if</span> <span class="n">activation_min</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span> <span class="o">&amp;</span> <span class="n">activation_max</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="p">:</span>
            <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">activation</span><span class="p">[</span><span class="mi">0</span><span class="p">,:,:,</span> <span class="n">featuremap</span><span class="p">],</span> <span class="n">interpolation</span><span class="o">=</span><span class="s2">&quot;nearest&quot;</span><span class="p">,</span> <span class="n">vmin</span> <span class="o">=</span><span class="n">activation_min</span><span class="p">,</span> <span class="n">vmax</span><span class="o">=</span><span class="n">activation_max</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s2">&quot;gray&quot;</span><span class="p">)</span>
        <span class="k">elif</span> <span class="n">activation_max</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="p">:</span>
            <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">activation</span><span class="p">[</span><span class="mi">0</span><span class="p">,:,:,</span> <span class="n">featuremap</span><span class="p">],</span> <span class="n">interpolation</span><span class="o">=</span><span class="s2">&quot;nearest&quot;</span><span class="p">,</span> <span class="n">vmax</span><span class="o">=</span><span class="n">activation_max</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s2">&quot;gray&quot;</span><span class="p">)</span>
        <span class="k">elif</span> <span class="n">activation_min</span> <span class="o">!=-</span><span class="mi">1</span><span class="p">:</span>
            <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">activation</span><span class="p">[</span><span class="mi">0</span><span class="p">,:,:,</span> <span class="n">featuremap</span><span class="p">],</span> <span class="n">interpolation</span><span class="o">=</span><span class="s2">&quot;nearest&quot;</span><span class="p">,</span> <span class="n">vmin</span><span class="o">=</span><span class="n">activation_min</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s2">&quot;gray&quot;</span><span class="p">)</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">activation</span><span class="p">[</span><span class="mi">0</span><span class="p">,:,:,</span> <span class="n">featuremap</span><span class="p">],</span> <span class="n">interpolation</span><span class="o">=</span><span class="s2">&quot;nearest&quot;</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s2">&quot;gray&quot;</span><span class="p">)</span>
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