report.html

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<title>Traffic_Sign_Classifier</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
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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 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.2.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1);
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1);
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

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

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

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

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul {
  list-style: disc;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ul ul {
  list-style: square;
  margin: 0em 2em;
}
.rendered_html ul ul ul {
  list-style: circle;
  margin: 0em 2em;
}
.rendered_html ol {
  list-style: decimal;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
  margin: 0em 2em;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  background-color: #fff;
  color: #000;
  font-size: 100%;
  padding: 0px;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: 1px solid black;
  border-collapse: collapse;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  border: 1px solid black;
  border-collapse: collapse;
  margin: 1em 2em;
}
.rendered_html td,
.rendered_html th {
  text-align: left;
  vertical-align: middle;
  padding: 4px;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget {
  float: right !important;
  float: right;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  margin-top: 6px;
}
span.save_widget span.filename {
  height: 1em;
  line-height: 1em;
  padding: 3px;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
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<h1 id="Traffic-Sign-Classifier">Traffic Sign Classifier<a class="anchor-link" href="#Traffic-Sign-Classifier">&#182;</a></h1>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">tensorflow</span> <span class="k">as</span> <span class="nn">tf</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</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="k">as</span> <span class="nn">cv</span>
<span class="kn">import</span> <span class="nn">math</span>
<span class="kn">import</span> <span class="nn">time</span>

<span class="kn">import</span> <span class="nn">os</span>

<span class="kn">import</span> <span class="nn">matplotlib.image</span> <span class="k">as</span> <span class="nn">mpimg</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">matplotlib.mlab</span> <span class="k">as</span> <span class="nn">mlab</span>
<span class="o">%</span><span class="k">matplotlib</span> inline

<span class="kn">from</span> <span class="nn">pylab</span> <span class="k">import</span> <span class="o">*</span>

<span class="c1"># Load pickled data</span>
<span class="kn">import</span> <span class="nn">pickle</span>
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<hr>
<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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<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>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">training_file</span> <span class="o">=</span> <span class="s2">&quot;../TrafficSignClassifier/traffic-signs-data/train.p&quot;</span>
<span class="n">validation_file</span> <span class="o">=</span> <span class="s2">&quot;../TrafficSignClassifier/traffic-signs-data/valid.p&quot;</span>
<span class="n">testing_file</span> <span class="o">=</span> <span class="s2">&quot;../TrafficSignClassifier/traffic-signs-data/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_validation</span><span class="p">,</span> <span class="n">y_validation</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>

<span class="k">assert</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="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">y_train</span><span class="p">))</span>
<span class="k">assert</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">X_validation</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">y_validation</span><span class="p">))</span>
<span class="k">assert</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">y_test</span><span class="p">))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Number of training examples</span>
<span class="n">n_train</span> <span class="o">=</span>  <span class="n">X_train</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>

<span class="c1"># Number of validation examples</span>
<span class="n">n_validation</span> <span class="o">=</span> <span class="n">X_validation</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>

<span class="c1"># Number of testing examples.</span>
<span class="n">n_test</span> <span class="o">=</span> <span class="n">X_test</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>

<span class="c1"># 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="o">.</span><span class="n">shape</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="c1"># How many unique classes/labels there are in the dataset.</span>
<span class="n">n_classes</span> <span class="o">=</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="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>

<span class="nb">print</span><span class="p">(</span><span class="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 training 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>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;All unique classes: &quot;</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>
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<pre>Number of training examples = 34799
Number of training examples = 4410
Number of testing examples = 12630
Image data shape = (32, 32)
Number of classes = 43
All unique classes:  [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42]
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<h2 id="Data-Preprocessing-Functions">Data Preprocessing Functions<a class="anchor-link" href="#Data-Preprocessing-Functions">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">gray</span><span class="p">(</span><span class="n">images</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Convert all images from RGB to gray using average of R, G, B values</span>
<span class="sd">    images shape: (n x w x l x 1)</span>
<span class="sd">    output shape: (n x w x l x 1)</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">gray</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">average</span><span class="p">(</span><span class="n">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">gray</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">expand_dims</span><span class="p">(</span><span class="n">gray</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="k">return</span> <span class="n">gray</span>

<span class="k">def</span> <span class="nf">normalize</span><span class="p">(</span><span class="n">images</span><span class="p">,</span> <span class="n">m</span><span class="o">=</span><span class="mi">128</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="mi">128</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Normalize each image in the set images</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1">#X = images.astype(&#39;float32&#39;)</span>
    <span class="n">X</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">images</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>
    
    <span class="n">out</span> <span class="o">=</span> <span class="p">(</span><span class="n">X</span> <span class="o">-</span> <span class="n">m</span><span class="p">)</span> <span class="o">/</span> <span class="n">s</span>
    <span class="k">return</span> <span class="n">out</span>

<span class="k">def</span> <span class="nf">preprocess</span><span class="p">(</span><span class="n">images</span><span class="p">,</span> <span class="n">grayscale</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">if</span> <span class="n">grayscale</span><span class="p">:</span>
        <span class="n">images</span> <span class="o">=</span> <span class="n">gray</span><span class="p">(</span><span class="n">images</span><span class="p">)</span>
        
    <span class="n">nimages</span> <span class="o">=</span> <span class="n">normalize</span><span class="p">(</span><span class="n">images</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">nimages</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>
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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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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">examplepath</span> <span class="o">=</span> <span class="p">(</span><span class="s2">&quot;examples_output/&quot;</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">isdir</span><span class="p">(</span><span class="n">examplepath</span><span class="p">):</span> <span class="n">os</span><span class="o">.</span><span class="n">makedirs</span><span class="p">(</span><span class="n">examplepath</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">## Plot each unique value</span>
<span class="n">u</span><span class="p">,</span> <span class="n">idxu</span> <span class="o">=</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="n">return_index</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">nimage</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">idxu</span><span class="p">)</span>

<span class="n">simages</span> <span class="o">=</span> <span class="n">X_train</span><span class="p">[</span><span class="n">idxu</span><span class="p">,]</span>
<span class="n">slabs</span> <span class="o">=</span> <span class="n">y_train</span><span class="p">[</span><span class="n">idxu</span><span class="p">]</span>
<span class="n">plt</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s2">&quot;figure.figsize&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="mi">10</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="p">,</span> <span class="n">image</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">simages</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="n">math</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="n">nimage</span><span class="o">/</span><span class="mi">5</span><span class="p">),</span> <span class="mi">5</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="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">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Label: </span><span class="si">%d</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="n">slabs</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
    
<span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">examplepath</span><span class="p">,</span> <span class="s2">&quot;1_AllClasses.png&quot;</span><span class="p">),</span> <span class="n">dpi</span><span class="o">=</span><span class="mi">600</span><span class="p">)</span>
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>
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<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[7]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">nimage</span> <span class="o">=</span> <span class="mi">10</span>
<span class="n">select</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">n_train</span><span class="p">,</span> <span class="n">nimage</span><span class="p">)</span>
<span class="n">simages</span> <span class="o">=</span> <span class="n">X_train</span><span class="p">[</span><span class="n">select</span><span class="p">,]</span>
<span class="n">slabs</span> <span class="o">=</span> <span class="n">y_train</span><span class="p">[</span><span class="n">select</span><span class="p">]</span>

<span class="n">plt</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s2">&quot;figure.figsize&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="mi">10</span><span class="p">,</span><span class="mi">5</span><span class="p">)</span>

<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">image</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">simages</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="n">math</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="n">nimage</span><span class="o">/</span><span class="mi">5</span><span class="p">),</span> <span class="mi">5</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="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">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Label: </span><span class="si">%d</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="n">slabs</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
    
<span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">examplepath</span><span class="p">,</span> <span class="s2">&quot;2_Rand10images.png&quot;</span><span class="p">),</span> <span class="n">dpi</span><span class="o">=</span><span class="mi">600</span><span class="p">)</span>
</pre></div>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">## Assess the difference within one class to have a sense of the model complexity needed</span>
<span class="n">selab</span> <span class="o">=</span> <span class="mi">18</span>
<span class="n">sel2</span><span class="p">,</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">y_train</span><span class="o">==</span><span class="n">selab</span><span class="p">)</span>
<span class="n">nims</span> <span class="o">=</span> <span class="n">sel2</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="k">if</span> <span class="n">nims</span> <span class="o">&gt;</span> <span class="mi">20</span><span class="p">:</span> <span class="n">sel2</span> <span class="o">=</span> <span class="n">sel2</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">20</span><span class="p">]</span>
<span class="n">simages2</span> <span class="o">=</span> <span class="n">X_train</span><span class="p">[</span><span class="n">sel2</span><span class="p">]</span>
<span class="n">slabs2</span> <span class="o">=</span> <span class="n">y_train</span><span class="p">[</span><span class="n">sel2</span><span class="p">]</span>
<span class="n">plt</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s2">&quot;figure.figsize&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="mi">10</span><span class="p">,</span><span class="mi">5</span><span class="p">)</span>
<span class="n">fig</span> <span class="o">=</span> <span class="n">gcf</span><span class="p">()</span>
<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">image</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">simages2</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="n">math</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="n">sel2</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">/</span><span class="mi">5</span><span class="p">),</span> <span class="mi">5</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="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">fig</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="s2">&quot;Label: &quot;</span><span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">selab</span><span class="p">))</span>
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<pre>Text(0.5,0.98,&#39;Label: 18&#39;)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Check grayscaling and normalization</span>
<span class="n">nimage</span> <span class="o">=</span> <span class="mi">10</span>
<span class="n">select</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">n_train</span><span class="p">,</span> <span class="n">nimage</span><span class="p">)</span>
<span class="n">simages</span> <span class="o">=</span> <span class="n">X_train</span><span class="p">[</span><span class="n">select</span><span class="p">]</span>
<span class="n">simages</span> <span class="o">=</span> <span class="n">gray</span><span class="p">(</span><span class="n">simages</span><span class="p">,)</span>
<span class="n">timages</span> <span class="o">=</span> <span class="n">normalize</span><span class="p">(</span><span class="n">simages</span><span class="p">)</span>
<span class="n">slabs</span> <span class="o">=</span> <span class="n">y_train</span><span class="p">[</span><span class="n">select</span><span class="p">]</span>
<span class="n">plt</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s2">&quot;figure.figsize&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="mi">10</span><span class="p">,</span><span class="mi">5</span><span class="p">)</span>

<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">image</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">simages</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="n">math</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="n">nimage</span><span class="o">/</span><span class="mi">5</span><span class="p">),</span> <span class="mi">5</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="n">image</span> <span class="o">=</span> <span class="n">image</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">cmap</span><span class="o">=</span><span class="s1">&#39;gray&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Label: </span><span class="si">%d</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="n">slabs</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
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<h3 id="Distribution-Histogram">Distribution Histogram<a class="anchor-link" href="#Distribution-Histogram">&#182;</a></h3>
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<div class="prompt input_prompt">In&nbsp;[10]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">c_tr</span><span class="p">,</span> <span class="n">nc_tr</span> <span class="o">=</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="n">return_counts</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">c_va</span><span class="p">,</span> <span class="n">nc_va</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">y_validation</span><span class="p">,</span> <span class="n">return_counts</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">c_te</span><span class="p">,</span> <span class="n">nc_te</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">return_counts</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>

<span class="nb">print</span><span class="p">((</span><span class="n">c_tr</span> <span class="o">==</span> <span class="n">c_te</span><span class="p">)</span><span class="o">.</span><span class="n">all</span><span class="p">())</span>
<span class="nb">print</span><span class="p">((</span><span class="n">c_te</span> <span class="o">==</span> <span class="n">c_va</span><span class="p">)</span><span class="o">.</span><span class="n">all</span><span class="p">())</span>

<span class="n">df2</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">column_stack</span><span class="p">((</span><span class="n">nc_tr</span><span class="p">,</span> <span class="n">nc_va</span><span class="p">,</span> <span class="n">nc_te</span><span class="p">)),</span>
                   <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Training&#39;</span><span class="p">,</span> <span class="s1">&#39;Validation&#39;</span><span class="p">,</span> <span class="s1">&#39;Testing&#39;</span><span class="p">])</span>

<span class="n">plt</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s2">&quot;figure.figsize&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="mi">18</span><span class="p">,</span><span class="mi">5</span><span class="p">)</span>
<span class="n">fig1</span> <span class="o">=</span> <span class="n">df2</span><span class="o">.</span><span class="n">plot</span><span class="o">.</span><span class="n">bar</span><span class="p">();</span>
<span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">examplepath</span><span class="p">,</span> <span class="s2">&quot;3_SampleDistribution.png&quot;</span><span class="p">),</span> <span class="n">dpi</span><span class="o">=</span><span class="mi">600</span><span class="p">)</span>
</pre></div>

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<pre>True
True
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<p>The sample of sign is not balanced, but some signs are more representative then others. However this representativenes proportion is kept among training, validation and testing sample.</p>
<p>As the sample is not uniformly distributed abong the classes it is possible that for some classes we can achieve better prediction than for other classes. As proportions of signs among training, validation and testing samples are relatively constant, we can expect the performance of between training, validation and between training and testing not being biased by sample selection</p>

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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>
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<p>The model architecture is based on the LeNet. An additional convolutional layer is added to it and itcan takes 3 channels as input for RGB images</p>
<h3 id="Input">Input<a class="anchor-link" href="#Input">&#182;</a></h3><p>The architecture accepts a 32x32xC image as input, where C is the number of color channels. If grayscale Since MNIST images are grayscale, C is 1 in this case.</p>
<h3 id="Architecture">Architecture<a class="anchor-link" href="#Architecture">&#182;</a></h3><p><strong>Layer 1: Convolutional.</strong>  Input = 32x32xnchannel. Output = 28x28x9.</p>
<p><strong>Activation.</strong> Relu</p>
<p><strong>Max Pooling.</strong> Input = 28x28x9. Output = 14x14x9.</p>
<p><strong>Layer 2: Convolutional.</strong> Input = 14x14x9. Output = 12x12x27.</p>
<p><strong>Activation.</strong> Relu</p>
<p><strong>Layer 3: Convolutional.</strong> 12x12x27. Output = 9x9x81.</p>
<p><strong>Activation.</strong> Relu</p>
<p><strong>Max Pooling.</strong> Input = 9x9x81. Output = (3x3x81)</p>
<p><strong>Flatten.</strong> Flatten the output shape of the final pooling layer such that it's 1D instead of 3D.
Input = 3x3x81. Output = (729x1)</p>
<p><strong>Layer 4: Fully Connected.</strong> This should have int(729/2.5) = 291 outputs.</p>
<p><strong>Activation.</strong> Relu</p>
<p><strong>Layer 5: Fully Connected.</strong> This should have int(291/2.5) = 116 outputs.</p>
<p><strong>Activation.</strong> Relu</p>
<p><strong>Layer 6: Fully Connected (Logits).</strong> This should have n_classes = 43 outputs.</p>
<h3 id="Output">Output<a class="anchor-link" href="#Output">&#182;</a></h3><p>Logits: the result of the Layer 6.</p>

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<div class=" highlight hl-ipython3"><pre><span></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="c1">### Model Architecture</span>
<span class="k">def</span> <span class="nf">MyNet1</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">nclasses</span><span class="p">,</span> <span class="n">nchannel</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Architectire of the neural network,</span>
<span class="sd">    Augment the LeNet architecture with additional layer and allow nchannel as input.</span>
<span class="sd">    Logit is array of nchannel</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1"># Arguments used for tf.truncated_normal, randomly defines variables for the weights and biases for each layer</span>
    <span class="c1"># hyperparameters for weight initialization</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">###############################</span>
    <span class="c1"># Layer 1: Convolutional. Input = 32x32xnchannel. Output = 28x28x9.</span>
    <span class="c1"># (32- 5 +1)/1 = 28 </span>
    <span class="c1"># Modification, allow possibility for 3 channel RGB data </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="n">nchannel</span><span class="p">,</span> <span class="mi">9</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">9</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 = 28x28x9. Output = 14x14x9</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">###############################</span>
    <span class="c1"># Layer 2: Convolutional.  Input =  14x14x9. Output = 12x12x27.</span>
    <span class="c1"># (14-3+1)/1 = 12</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">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">9</span><span class="p">,</span> <span class="mi">27</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">27</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">###############################</span>
    <span class="c1"># Add: Layer 3. Convolution, input 12x12x27, output:  12-4+1 = 9x9x81</span>
    <span class="n">conv3_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">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">27</span><span class="p">,</span> <span class="mi">81</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">conv3_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">81</span><span class="p">))</span>
    <span class="n">conv3</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">conv2</span><span class="p">,</span> <span class="n">conv3_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">conv3_b</span>
    
    <span class="c1"># Add Activation</span>
    <span class="n">conv3</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">conv3</span><span class="p">)</span>
    
    <span class="c1"># Add max Pooling: input = 9x9x81, output = (3x3x81) </span>
    <span class="n">conv3</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">conv3</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">3</span><span class="p">,</span> <span class="mi">3</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">3</span><span class="p">,</span> <span class="mi">3</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">###############################</span>
    <span class="c1"># Flatten. Input =3x3x81. Output = 729</span>
    <span class="n">fc0</span>   <span class="o">=</span> <span class="n">flatten</span><span class="p">(</span><span class="n">conv3</span><span class="p">)</span>
    
    <span class="n">fcdim</span> <span class="o">=</span> <span class="mi">729</span>
    <span class="n">nflattenlayer</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">while</span> <span class="p">(</span><span class="n">fcdim</span> <span class="o">&gt;</span> <span class="p">(</span><span class="mi">3</span><span class="o">*</span><span class="n">nclasses</span><span class="p">)):</span>     
        <span class="c1"># Layer 3+: Fully Connected. Input = 729. Output = nclasses.</span>
        <span class="n">fcdim2</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">fcdim</span><span class="o">/</span><span class="mf">2.5</span><span class="p">)</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="n">fcdim</span><span class="p">,</span> <span class="n">fcdim2</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="n">fcdim2</span><span class="p">))</span>
        <span class="n">fc0</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">fc0</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">fc0</span><span class="p">)</span>
        <span class="n">fcdim</span> <span class="o">=</span>  <span class="n">fcdim2</span> 
        <span class="n">nflattenlayer</span> <span class="o">=</span> <span class="n">nflattenlayer</span> <span class="o">+</span><span class="mi">1</span> 

<span class="c1">#     # Layer 4: Fully Connected. Input = 729. Output = 290.</span>
<span class="c1">#     fc1_W = tf.Variable(tf.truncated_normal(shape=(729, 290), mean = mu, stddev = sigma))</span>
<span class="c1">#     fc1_b = tf.Variable(tf.zeros(290))</span>
<span class="c1">#     fc1   = tf.matmul(fc0, fc1_W) + fc1_b</span>
    
<span class="c1">#     # Activation.</span>
<span class="c1">#     fc1    = tf.nn.relu(fc1)</span>

<span class="c1">#     # Layer 5: Fully Connected. Input = 290. Output = 110.</span>
<span class="c1">#     fc2_W  = tf.Variable(tf.truncated_normal(shape=(290, 110), mean = mu, stddev = sigma))</span>
<span class="c1">#     fc2_b  = tf.Variable(tf.zeros(84))</span>
<span class="c1">#     fc2    = tf.matmul(fc1, fc2_W) + fc2_b</span>
    
<span class="c1">#     # Activation.</span>
<span class="c1">#     fc2    = tf.nn.relu(fc2)</span>
        
    <span class="c1"># Last 6: Fully Connected. Input = 110. Output = nClasses</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="n">fcdim</span><span class="p">,</span> <span class="n">nclasses</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">nclasses</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">fc0</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="nb">print</span><span class="p">(</span> <span class="s2">&quot;Number of full connections layer is &quot;</span><span class="p">,</span> <span class="n">nflattenlayer</span><span class="p">)</span>
        
    
    <span class="k">return</span> <span class="n">logits</span>
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<h2 id="Global-Settings">Global Settings<a class="anchor-link" href="#Global-Settings">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">EPOCHS</span> <span class="o">=</span> <span class="mi">40</span>
<span class="n">BATCH_SIZE</span> <span class="o">=</span> <span class="mi">256</span> <span class="c1"># training images each time in the network</span>
<span class="n">img_size</span> <span class="o">=</span> <span class="mi">32</span>  <span class="c1"># square image of size IMG_SIZE x IMG_SIZE</span>
<span class="n">grayscale</span> <span class="o">=</span> <span class="kc">False</span>  <span class="c1"># convert image to grayscale?</span>
<span class="n">nchannel</span> <span class="o">=</span> <span class="mi">1</span> <span class="k">if</span> <span class="n">grayscale</span> <span class="k">else</span> <span class="mi">3</span>

<span class="n">SAVE</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">OUT_PATH</span> <span class="o">=</span> <span class="p">(</span><span class="s2">&quot;tfmodel/&quot;</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">isdir</span><span class="p">(</span><span class="n">OUT_PATH</span> <span class="p">):</span> <span class="n">os</span><span class="o">.</span><span class="n">makedirs</span><span class="p">(</span><span class="n">OUT_PATH</span> <span class="p">)</span>
<span class="n">MODEL_PATH</span> <span class="o">=</span> <span class="n">OUT_PATH</span><span class="o">+</span><span class="s2">&quot;My2.ckpt&quot;</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="mf">0.002</span><span class="p">)</span>
<span class="n">Architecture</span> <span class="o">=</span> <span class="n">MyNet1</span>
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<h3 id="Tensor-Flow-Optimization-operations-and-accuracy-evaluation-functions">Tensor Flow Optimization operations and accuracy evaluation functions<a class="anchor-link" href="#Tensor-Flow-Optimization-operations-and-accuracy-evaluation-functions">&#182;</a></h3>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Make output classes categorical</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="n">img_size</span><span class="p">,</span> <span class="n">img_size</span><span class="p">,</span> <span class="n">nchannel</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>

<span class="n">logits</span> <span class="o">=</span> <span class="n">Architecture</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">n_classes</span><span class="p">,</span> <span class="n">nchannel</span><span class="p">)</span> 

<span class="c1"># Loss function</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_v2</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="c1"># Train data with chosen Optimization algorithm  </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>

<span class="c1"># Returns the index with the largest value across axes of a tensor. </span>
<span class="n">predicted_operation</span> <span class="o">=</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">actual_operation</span> <span class="o">=</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">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">predicted_operation</span><span class="p">,</span> <span class="n">actual_operation</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="c1"># Start saver</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>
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<pre>Number of full connections layer is  3
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<div class=" highlight hl-ipython3"><pre><span></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">batch_x</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="n">x_train</span> <span class="o">=</span> <span class="n">preprocess</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">grayscale</span><span class="p">)</span>
<span class="n">x_valid</span> <span class="o">=</span> <span class="n">preprocess</span><span class="p">(</span><span class="n">X_validation</span><span class="p">,</span> <span class="n">grayscale</span><span class="p">)</span> 
<span class="n">x_test</span> <span class="o">=</span>  <span class="n">preprocess</span><span class="p">(</span><span class="n">X_test</span><span class="p">,</span> <span class="n">grayscale</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>
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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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<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="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="c1"># Variable initialization</span>
    <span class="n">init</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">global_variables_initializer</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">init</span><span class="p">)</span>
    
    <span class="c1">#  training and validation accuracy over epochs, like such:</span>
    <span class="n">accuracy_history</span> <span class="o">=</span> <span class="p">[]</span>

    <span class="c1"># Record time elapsed for performance check</span>
    <span class="n">last_time</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
    <span class="n">train_start_time</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</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">batch_x</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_validation</span><span class="p">)</span>
        <span class="n">accuracy_history</span><span class="o">.</span><span class="n">append</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="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;Validation Accuracy: </span><span class="si">%.4f</span><span class="s2">, Elapsed time: </span><span class="si">%.2f</span><span class="s2"> sec&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">validation_accuracy</span><span class="p">,</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span><span class="o">-</span><span class="n">last_time</span><span class="p">))</span>
        <span class="nb">print</span><span class="p">()</span>
        <span class="n">last_time</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>

    <span class="n">total_time</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span> <span class="o">-</span> <span class="n">train_start_time</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Total elapsed time: </span><span class="si">%.2f</span><span class="s1"> sec (</span><span class="si">%.2f</span><span class="s1"> min)&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">total_time</span><span class="p">,</span> <span class="n">total_time</span><span class="o">/</span><span class="mi">60</span><span class="p">))</span>

    <span class="k">if</span> <span class="n">SAVE</span><span class="p">:</span>
        <span class="n">save_path</span> <span class="o">=</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_PATH</span><span class="p">)</span>
        <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Trained model saved at: </span><span class="si">%s</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="n">save_path</span><span class="p">)</span>
        <span class="c1"># Save accuracy history</span>
        <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Accuracy history saved at accuracy_history.p&#39;</span><span class="p">)</span>
        <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;accuracy_history.p&#39;</span><span class="p">,</span> <span class="s1">&#39;wb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
            <span class="n">pickle</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">accuracy_history</span><span class="p">,</span> <span class="n">f</span><span class="p">)</span>
    
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<pre>EPOCH 1 ...
Validation Accuracy: 0.8612, Elapsed time: 60.16 sec

EPOCH 2 ...
Validation Accuracy: 0.8980, Elapsed time: 60.14 sec

EPOCH 3 ...
Validation Accuracy: 0.9358, Elapsed time: 60.37 sec

EPOCH 4 ...
Validation Accuracy: 0.9347, Elapsed time: 61.25 sec

EPOCH 5 ...
Validation Accuracy: 0.9422, Elapsed time: 61.27 sec

EPOCH 6 ...
Validation Accuracy: 0.9168, Elapsed time: 60.05 sec

EPOCH 7 ...
Validation Accuracy: 0.9490, Elapsed time: 59.55 sec

EPOCH 8 ...
Validation Accuracy: 0.9497, Elapsed time: 60.09 sec

EPOCH 9 ...
Validation Accuracy: 0.9374, Elapsed time: 60.17 sec

EPOCH 10 ...
Validation Accuracy: 0.9361, Elapsed time: 59.97 sec

EPOCH 11 ...
Validation Accuracy: 0.9454, Elapsed time: 60.44 sec

EPOCH 12 ...
Validation Accuracy: 0.9644, Elapsed time: 59.72 sec

EPOCH 13 ...
Validation Accuracy: 0.9449, Elapsed time: 59.67 sec

EPOCH 14 ...
Validation Accuracy: 0.9499, Elapsed time: 59.78 sec

EPOCH 15 ...
Validation Accuracy: 0.9608, Elapsed time: 59.81 sec

EPOCH 16 ...
Validation Accuracy: 0.9556, Elapsed time: 59.97 sec

EPOCH 17 ...
Validation Accuracy: 0.9361, Elapsed time: 59.58 sec

EPOCH 18 ...
Validation Accuracy: 0.9644, Elapsed time: 59.88 sec

EPOCH 19 ...
Validation Accuracy: 0.9170, Elapsed time: 59.47 sec

EPOCH 20 ...
Validation Accuracy: 0.9519, Elapsed time: 60.66 sec

EPOCH 21 ...
Validation Accuracy: 0.9678, Elapsed time: 60.51 sec

EPOCH 22 ...
Validation Accuracy: 0.9463, Elapsed time: 59.98 sec

EPOCH 23 ...
Validation Accuracy: 0.9612, Elapsed time: 59.54 sec

EPOCH 24 ...
Validation Accuracy: 0.9492, Elapsed time: 60.73 sec

EPOCH 25 ...
Validation Accuracy: 0.9522, Elapsed time: 59.68 sec

EPOCH 26 ...
Validation Accuracy: 0.9522, Elapsed time: 60.14 sec

EPOCH 27 ...
Validation Accuracy: 0.9635, Elapsed time: 59.52 sec

EPOCH 28 ...
Validation Accuracy: 0.9610, Elapsed time: 60.03 sec

EPOCH 29 ...
Validation Accuracy: 0.9433, Elapsed time: 59.66 sec

EPOCH 30 ...
Validation Accuracy: 0.9612, Elapsed time: 59.67 sec

EPOCH 31 ...
Validation Accuracy: 0.9678, Elapsed time: 59.56 sec

EPOCH 32 ...
Validation Accuracy: 0.9576, Elapsed time: 60.21 sec

EPOCH 33 ...
Validation Accuracy: 0.9683, Elapsed time: 60.32 sec

EPOCH 34 ...
Validation Accuracy: 0.9639, Elapsed time: 60.56 sec

EPOCH 35 ...
Validation Accuracy: 0.9483, Elapsed time: 59.71 sec

EPOCH 36 ...
Validation Accuracy: 0.9637, Elapsed time: 60.16 sec

EPOCH 37 ...
Validation Accuracy: 0.9472, Elapsed time: 59.85 sec

EPOCH 38 ...
Validation Accuracy: 0.9596, Elapsed time: 59.88 sec

EPOCH 39 ...
Validation Accuracy: 0.9710, Elapsed time: 59.84 sec

EPOCH 40 ...
Validation Accuracy: 0.9785, Elapsed time: 60.44 sec

Total elapsed time: 2401.98 sec (40.03 min)
Trained model saved at: tfmodel/My2.ckpt
Accuracy history saved at accuracy_history.p
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<div class=" highlight hl-ipython3"><pre><span></span>        
<span class="c1"># Plot Validatioon accuracy_history</span>
<span class="n">plt</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s2">&quot;figure.figsize&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="mi">15</span><span class="p">,</span><span class="mi">4</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Validation Accuracy&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Accuracy&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Epoch&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">accuracy_history</span><span class="p">,</span> <span class="s1">&#39;r&#39;</span><span class="p">)</span>  <span class="c1"># validation accuracy</span>

<span class="n">plt</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s2">&quot;figure.figsize&quot;</span><span class="p">]</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">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">examplepath</span><span class="p">,</span> <span class="s2">&quot;4_ValidationAccuracy.png&quot;</span><span class="p">),</span> <span class="n">dpi</span><span class="o">=</span><span class="mi">600</span><span class="p">)</span>
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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">## Test</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_PATH</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 tfmodel/My2.ckpt
Test Accuracy = 0.941
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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>
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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="n">eimages</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">image_files</span>  <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;examples/&#39;</span> <span class="o">+</span> <span class="n">image_file</span> <span class="k">for</span> <span class="n">image_file</span> <span class="ow">in</span> <span class="n">os</span><span class="o">.</span><span class="n">listdir</span><span class="p">(</span><span class="s1">&#39;examples&#39;</span><span class="p">)]</span>
<span class="n">nimage</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">image_files</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s2">&quot;figure.figsize&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="mi">10</span><span class="p">,</span><span class="mi">5</span><span class="p">)</span>
<span class="n">i</span><span class="o">=</span><span class="mi">0</span>
<span class="k">for</span> <span class="n">image_file</span> <span class="ow">in</span> <span class="n">image_files</span><span class="p">:</span>
    <span class="n">im</span> <span class="o">=</span> <span class="n">cv</span><span class="o">.</span><span class="n">imread</span><span class="p">(</span><span class="n">image_file</span><span class="p">)</span>
    <span class="n">im</span> <span class="o">=</span> <span class="n">cv</span><span class="o">.</span><span class="n">cvtColor</span><span class="p">(</span><span class="n">im</span><span class="p">,</span> <span class="n">cv</span><span class="o">.</span><span class="n">COLOR_BGR2RGB</span><span class="p">)</span> <span class="c1"># To RGB</span>
    <span class="n">height</span><span class="p">,</span> <span class="n">width</span> <span class="o">=</span> <span class="n">im</span><span class="o">.</span><span class="n">shape</span><span class="p">[:</span><span class="mi">2</span><span class="p">]</span>
    <span class="n">im</span> <span class="o">=</span> <span class="n">cv</span><span class="o">.</span><span class="n">resize</span><span class="p">(</span><span class="n">im</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">interpolation</span> <span class="o">=</span> <span class="n">cv</span><span class="o">.</span><span class="n">INTER_AREA</span><span class="p">)</span>
    <span class="c1">#plt.figure()</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="n">math</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="n">nimage</span><span class="o">/</span><span class="mi">5</span><span class="p">),</span> <span class="mi">5</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="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">im</span><span class="p">)</span>
    <span class="n">eimages</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">im</span><span class="p">)</span>
    <span class="n">i</span> <span class="o">+=</span><span class="mi">1</span>
    
<span class="n">plt</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s2">&quot;figure.figsize&quot;</span><span class="p">]</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">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">examplepath</span><span class="p">,</span> <span class="s2">&quot;5_SignsFromWeb.png&quot;</span><span class="p">),</span> <span class="n">dpi</span><span class="o">=</span><span class="mi">600</span><span class="p">)</span>

<span class="n">n_eimage</span> <span class="o">=</span> <span class="n">i</span>
</pre></div>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Load signnames.csv for sign label</span>
<span class="n">label_map</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">f</span><span class="p">:</span>
    <span class="n">first_line</span> <span class="o">=</span> <span class="kc">True</span>
    <span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="n">f</span><span class="p">:</span>
        <span class="c1"># Ignore first line</span>
        <span class="k">if</span> <span class="n">first_line</span><span class="p">:</span>
            <span class="n">first_line</span> <span class="o">=</span> <span class="kc">False</span>
            <span class="k">continue</span>
        <span class="c1"># Populate label_map</span>
        <span class="n">label_int</span><span class="p">,</span> <span class="n">label_string</span> <span class="o">=</span> <span class="n">line</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;,&#39;</span><span class="p">)</span>
        <span class="n">label_int</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">label_int</span><span class="p">)</span>
        <span class="n">label_map</span><span class="p">[</span><span class="n">label_int</span><span class="p">]</span> <span class="o">=</span> <span class="n">label_string</span>
<span class="c1">#label_map</span>
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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="n">x_ex</span> <span class="o">=</span> <span class="n">preprocess</span><span class="p">(</span><span class="n">eimages</span><span class="p">,</span> <span class="n">grayscale</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_PATH</span><span class="p">)</span>    
    <span class="n">predictions</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">predicted_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">x_ex</span><span class="p">})</span>

<span class="n">final_preds</span> <span class="o">=</span> <span class="p">[</span><span class="n">label_map</span><span class="p">[</span><span class="n">pred</span><span class="p">]</span> <span class="k">for</span> <span class="n">pred</span> <span class="ow">in</span> <span class="n">predictions</span><span class="p">]</span>

<span class="c1"># Print predictions </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_eimage</span><span class="p">):</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="si">%s</span><span class="s1"> --&gt; </span><span class="si">%s</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">image_files</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">final_preds</span><span class="p">[</span><span class="n">i</span><span class="p">]))</span>
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<pre>INFO:tensorflow:Restoring parameters from tfmodel/My2.ckpt
examples/sign1.png --&gt; Children crossing

examples/sign10.png --&gt; General caution

examples/sign2.png --&gt; No entry

examples/sign3.png --&gt; General caution

examples/sign4.png --&gt; Roundabout mandatory

examples/sign5.png --&gt; Stop

examples/sign6.png --&gt; Road work

examples/sign7.png --&gt; Roundabout mandatory

examples/sign8.png --&gt; Speed limit (70km/h)

examples/sign9.png --&gt; Yield

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<h3 id="Analyze-Performance">Analyze Performance<a class="anchor-link" href="#Analyze-Performance">&#182;</a></h3>
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<h4 id="Accuracy-for-these-10-new-images.">Accuracy for these 10 new images.<a class="anchor-link" href="#Accuracy-for-these-10-new-images.">&#182;</a></h4><ul>
<li>sign1: wrong. Speed limit 50 as Children crossing</li>
<li>sign10: wrong. Pedestrian crossing as general caution</li>
<li>sign2: right. No entry</li>
<li>sign3: wrong. Pedestrian crossing as general caution</li>
<li>sign4: wrong. Speed limit 120 as roundabout mandatory</li>
<li>sign5: rignt. Stop</li>
<li>sign6: right. Road work</li>
<li>sign7: right. Roundabout mandatory</li>
<li>sign8: right. speed limit 70 </li>
<li>sign9: right. Yield</li>
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<p>Out of the 10 signs, 6 are predicted correctly. The model achieve performance 60%
The 2 signs for pedestrian crossing are all misspredicted.</p>

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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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<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_PATH</span><span class="p">)</span>
    
    <span class="n">predictions</span><span class="p">,</span> <span class="n">probs</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span>
        <span class="p">[</span><span class="n">predicted_operation</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">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">k</span><span class="o">=</span><span class="mi">5</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">x_ex</span><span class="p">})</span>
    

<span class="c1"># Print predictions </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">predictions</span><span class="p">)):</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="si">%s</span><span class="s1"> --&gt; </span><span class="si">%s</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">predictions</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">probs</span><span class="o">.</span><span class="n">values</span><span class="p">[</span><span class="n">i</span><span class="p">]))</span>
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<pre>INFO:tensorflow:Restoring parameters from tfmodel/My2.ckpt
28 --&gt; [9.9999928e-01 7.2024005e-07 3.6727977e-12 6.7069299e-13 1.4098661e-13]
18 --&gt; [9.9974102e-01 2.5689884e-04 2.0036687e-06 7.2187256e-09 3.7400841e-10]
17 --&gt; [1.000000e+00 9.506732e-20 6.518231e-23 5.527943e-23 2.847786e-25]
18 --&gt; [0.8756573  0.0674255  0.04732626 0.0086319  0.00091004]
40 --&gt; [7.3885655e-01 2.1818408e-01 4.2041183e-02 5.6607992e-04 3.2989468e-04]
14 --&gt; [1.0000000e+00 3.0015321e-19 1.3218541e-19 5.1646014e-20 3.7274655e-20]
25 --&gt; [1.0000000e+00 3.7863995e-33 6.7678737e-35 2.2274603e-36 0.0000000e+00]
40 --&gt; [1.0000000e+00 4.1207113e-10 7.3074752e-14 4.4235174e-14 3.4916965e-14]
4 --&gt; [1.0000000e+00 2.0706099e-17 6.8943622e-19 1.1328134e-19 1.2673392e-22]
13 --&gt; [1. 0. 0. 0. 0.]
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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>
</blockquote>

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