report.html

<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />
<title>vui_notebook</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
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<style type="text/css">
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/*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */
html {
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sub {
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svg:not(:root) {
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figure {
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}
.glyphicon-triangle-bottom:before {
  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.2.0 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="Artificial-Intelligence-Nanodegree">Artificial Intelligence Nanodegree<a class="anchor-link" href="#Artificial-Intelligence-Nanodegree">&#182;</a></h1><h2 id="Voice-User-Interfaces">Voice User Interfaces<a class="anchor-link" href="#Voice-User-Interfaces">&#182;</a></h2><h2 id="Project:-Speech-Recognition-with-Neural-Networks">Project: Speech Recognition with Neural Networks<a class="anchor-link" href="#Project:-Speech-Recognition-with-Neural-Networks">&#182;</a></h2><hr>
<p>In this notebook, some template code has already been provided for you, and you will need to implement additional functionality to successfully complete this project. You will not need to modify the included code beyond what is requested. Sections that begin with <strong>'(IMPLEMENTATION)'</strong> in the header indicate that the following blocks of code will require additional functionality which you must provide. Please be sure to read the instructions carefully!</p>
<blockquote><p><strong>Note</strong>: Once you have completed all of the code implementations, you need to finalize your work by exporting the Jupyter Notebook as an HTML document. Before exporting the notebook to html, all of the code cells need to have been run so that reviewers can see the final implementation and output. You can then export the notebook by using the menu above and navigating to  \n",
    "<strong>File -&gt; Download as -&gt; HTML (.html)</strong>. Include the finished document along with this notebook as your submission.</p>
</blockquote>
<p>In addition to implementing code, there will be questions that you must answer which relate to the project and your implementation. Each section where you will answer a question is preceded by a <strong>'Question X'</strong> header. Carefully read each question and provide thorough answers in the following text boxes that begin with <strong>'Answer:'</strong>. Your project submission will be evaluated based on your answers to each of the questions and the implementation you provide.</p>
<blockquote><p><strong>Note:</strong> Code and Markdown cells can be executed using the <strong>Shift + Enter</strong> keyboard shortcut.  Markdown cells can be edited by double-clicking the cell to enter edit mode.</p>
</blockquote>
<p>The rubric contains <em>optional</em> "Stand Out Suggestions" for enhancing the project beyond the minimum requirements. If you decide to pursue the "Stand Out Suggestions", you should include the code in this Jupyter notebook.</p>
<hr>
<h2 id="Introduction">Introduction<a class="anchor-link" href="#Introduction">&#182;</a></h2><p>In this notebook, you will build a deep neural network that functions as part of an end-to-end automatic speech recognition (ASR) pipeline!  Your completed pipeline will accept raw audio as input and return a predicted transcription of the spoken language.  The full pipeline is summarized in the figure below.</p>
<p><img src="images/pipeline.png"></p>
<ul>
<li><strong>STEP 1</strong> is a pre-processing step that converts raw audio to one of two feature representations that are commonly used for ASR. </li>
<li><strong>STEP 2</strong> is an acoustic model which accepts audio features as input and returns a probability distribution over all potential transcriptions.  After learning about the basic types of neural networks that are often used for acoustic modeling, you will engage in your own investigations, to design your own acoustic model!</li>
<li><strong>STEP 3</strong> in the pipeline takes the output from the acoustic model and returns a predicted transcription.  </li>
</ul>
<p>Feel free to use the links below to navigate the notebook:</p>
<ul>
<li><a href="#thedata">The Data</a></li>
<li><a href="#step1"><strong>STEP 1</strong></a>: Acoustic Features for Speech Recognition</li>
<li><a href="#step2"><strong>STEP 2</strong></a>: Deep Neural Networks for Acoustic Modeling<ul>
<li><a href="#model0">Model 0</a>: RNN</li>
<li><a href="#model1">Model 1</a>: RNN + TimeDistributed Dense</li>
<li><a href="#model2">Model 2</a>: CNN + RNN + TimeDistributed Dense</li>
<li><a href="#model3">Model 3</a>: Deeper RNN + TimeDistributed Dense</li>
<li><a href="#model4">Model 4</a>: Bidirectional RNN + TimeDistributed Dense</li>
<li><a href="#model5">Models 5+</a></li>
<li><a href="#compare">Compare the Models</a></li>
<li><a href="#final">Final Model</a></li>
</ul>
</li>
<li><a href="#step3"><strong>STEP 3</strong></a>: Obtain Predictions</li>
</ul>
<p><a id='thedata'></a></p>
<h2 id="The-Data">The Data<a class="anchor-link" href="#The-Data">&#182;</a></h2><p>We begin by investigating the dataset that will be used to train and evaluate your pipeline.  <a href="http://www.danielpovey.com/files/2015_icassp_librispeech.pdf">LibriSpeech</a> is a large corpus of English-read speech, designed for training and evaluating models for ASR.  The dataset contains 1000 hours of speech derived from audiobooks.  We will work with a small subset in this project, since larger-scale data would take a long while to train.  However, after completing this project, if you are interested in exploring further, you are encouraged to work with more of the data that is provided <a href="http://www.openslr.org/12/">online</a>.</p>
<p>In the code cells below, you will use the <code>vis_train_features</code> module to visualize a training example.  The supplied argument <code>index=0</code> tells the module to extract the first example in the training set.  (You are welcome to change <code>index=0</code> to point to a different training example, if you like, but please <strong>DO NOT</strong> amend any other code in the cell.)  The returned variables are:</p>
<ul>
<li><code>vis_text</code> - transcribed text (label) for the training example.</li>
<li><code>vis_raw_audio</code> - raw audio waveform for the training example.</li>
<li><code>vis_mfcc_feature</code> - mel-frequency cepstral coefficients (MFCCs) for the training example.</li>
<li><code>vis_spectrogram_feature</code> - spectrogram for the training example. </li>
<li><code>vis_audio_path</code> - the file path to the training example.</li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">data_generator</span> <span class="k">import</span> <span class="n">vis_train_features</span>

<span class="c1"># extract label and audio features for a single training example</span>
<span class="n">vis_text</span><span class="p">,</span> <span class="n">vis_raw_audio</span><span class="p">,</span> <span class="n">vis_mfcc_feature</span><span class="p">,</span> <span class="n">vis_spectrogram_feature</span><span class="p">,</span> <span class="n">vis_audio_path</span> <span class="o">=</span> <span class="n">vis_train_features</span><span class="p">()</span>
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<pre>There are 2136 total training examples.
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<p>The following code cell visualizes the audio waveform for your chosen example, along with the corresponding transcript.  You also have the option to play the audio in the notebook!</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">IPython.display</span> <span class="k">import</span> <span class="n">Markdown</span><span class="p">,</span> <span class="n">display</span>
<span class="kn">from</span> <span class="nn">data_generator</span> <span class="k">import</span> <span class="n">vis_train_features</span><span class="p">,</span> <span class="n">plot_raw_audio</span>
<span class="kn">from</span> <span class="nn">IPython.display</span> <span class="k">import</span> <span class="n">Audio</span>
<span class="o">%</span><span class="k">matplotlib</span> inline

<span class="c1"># plot audio signal</span>
<span class="n">plot_raw_audio</span><span class="p">(</span><span class="n">vis_raw_audio</span><span class="p">)</span>
<span class="c1"># print length of audio signal</span>
<span class="n">display</span><span class="p">(</span><span class="n">Markdown</span><span class="p">(</span><span class="s1">&#39;**Shape of Audio Signal** : &#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">vis_raw_audio</span><span class="o">.</span><span class="n">shape</span><span class="p">)))</span>
<span class="c1"># print transcript corresponding to audio clip</span>
<span class="n">display</span><span class="p">(</span><span class="n">Markdown</span><span class="p">(</span><span class="s1">&#39;**Transcript** : &#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">vis_text</span><span class="p">)))</span>
<span class="c1"># play the audio file</span>
<span class="n">Audio</span><span class="p">(</span><span class="n">vis_audio_path</span><span class="p">)</span>
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"
>
</div>

</div>

<div class="output_area">

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


<div class="output_markdown rendered_html output_subarea ">
<p><strong>Shape of Audio Signal</strong> : (103966,)</p>

</div>

</div>

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


<div class="output_markdown rendered_html output_subarea ">
<p><strong>Transcript</strong> : the last two days of the voyage bartley found almost intolerable</p>

</div>

</div>

<div class="output_area">

<div class="prompt output_prompt">Out[2]:</div>


<div class="output_html rendered_html output_subarea output_execute_result">

                <audio controls="controls" >
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<p><a id='step1'></a></p>
<h2 id="STEP-1:-Acoustic-Features-for-Speech-Recognition">STEP 1: Acoustic Features for Speech Recognition<a class="anchor-link" href="#STEP-1:-Acoustic-Features-for-Speech-Recognition">&#182;</a></h2><p>For this project, you won't use the raw audio waveform as input to your model.  Instead, we provide code that first performs a pre-processing step to convert the raw audio to a feature representation that has historically proven successful for ASR models.  Your acoustic model will accept the feature representation as input.</p>
<p>In this project, you will explore two possible feature representations.  <em>After completing the project</em>, if you'd like to read more about deep learning architectures that can accept raw audio input, you are encouraged to explore this <a href="https://pdfs.semanticscholar.org/a566/cd4a8623d661a4931814d9dffc72ecbf63c4.pdf">research paper</a>.</p>
<h3 id="Spectrograms">Spectrograms<a class="anchor-link" href="#Spectrograms">&#182;</a></h3><p>The first option for an audio feature representation is the <a href="https://www.youtube.com/watch?v=_FatxGN3vAM">spectrogram</a>.  In order to complete this project, you will <strong>not</strong> need to dig deeply into the details of how a spectrogram is calculated; but, if you are curious, the code for calculating the spectrogram was borrowed from <a href="https://github.com/baidu-research/ba-dls-deepspeech">this repository</a>.  The implementation appears in the <code>utils.py</code> file in your repository.</p>
<p>The code that we give you returns the spectrogram as a 2D tensor, where the first (<em>vertical</em>) dimension indexes time, and the second (<em>horizontal</em>) dimension indexes frequency.  To speed the convergence of your algorithm, we have also normalized the spectrogram.  (You can see this quickly in the visualization below by noting that the mean value hovers around zero, and most entries in the tensor assume values close to zero.)</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">data_generator</span> <span class="k">import</span> <span class="n">plot_spectrogram_feature</span>

<span class="c1"># plot normalized spectrogram</span>
<span class="n">plot_spectrogram_feature</span><span class="p">(</span><span class="n">vis_spectrogram_feature</span><span class="p">)</span>
<span class="c1"># print shape of spectrogram</span>
<span class="n">display</span><span class="p">(</span><span class="n">Markdown</span><span class="p">(</span><span class="s1">&#39;**Shape of Spectrogram** : &#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">vis_spectrogram_feature</span><span class="o">.</span><span class="n">shape</span><span class="p">)))</span>
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<p><strong>Shape of Spectrogram</strong> : (470, 161)</p>

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<h3 id="Mel-Frequency-Cepstral-Coefficients-(MFCCs)">Mel-Frequency Cepstral Coefficients (MFCCs)<a class="anchor-link" href="#Mel-Frequency-Cepstral-Coefficients-(MFCCs)">&#182;</a></h3><p>The second option for an audio feature representation is <a href="https://en.wikipedia.org/wiki/Mel-frequency_cepstrum">MFCCs</a>.  You do <strong>not</strong> need to dig deeply into the details of how MFCCs are calculated, but if you would like more information, you are welcome to peruse the <a href="https://github.com/jameslyons/python_speech_features">documentation</a> of the <code>python_speech_features</code> Python package.  Just as with the spectrogram features, the MFCCs are normalized in the supplied code.</p>
<p>The main idea behind MFCC features is the same as spectrogram features: at each time window, the MFCC feature yields a feature vector that characterizes the sound within the window.  Note that the MFCC feature is much lower-dimensional than the spectrogram feature, which could help an acoustic model to avoid overfitting to the training dataset.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">data_generator</span> <span class="k">import</span> <span class="n">plot_mfcc_feature</span>

<span class="c1"># plot normalized MFCC</span>
<span class="n">plot_mfcc_feature</span><span class="p">(</span><span class="n">vis_mfcc_feature</span><span class="p">)</span>
<span class="c1"># print shape of MFCC</span>
<span class="n">display</span><span class="p">(</span><span class="n">Markdown</span><span class="p">(</span><span class="s1">&#39;**Shape of MFCC** : &#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">vis_mfcc_feature</span><span class="o">.</span><span class="n">shape</span><span class="p">)))</span>
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IYRQZWKQHkIIIYQQQpWJQXoIIYQQQghVJgbpIYQQQgghVJn/BwzA7MlpHjk/AAAAAElFTkSuQmCC
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<p><strong>Shape of MFCC</strong> : (470, 13)</p>

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<p>When you construct your pipeline, you will be able to choose to use either spectrogram or MFCC features.  If you would like to see different implementations that make use of MFCCs and/or spectrograms, please check out the links below:</p>
<ul>
<li>This <a href="https://github.com/baidu-research/ba-dls-deepspeech">repository</a> uses spectrograms.</li>
<li>This <a href="https://github.com/mozilla/DeepSpeech">repository</a> uses MFCCs.</li>
<li>This <a href="https://github.com/buriburisuri/speech-to-text-wavenet">repository</a> also uses MFCCs.</li>
<li>This <a href="https://github.com/pannous/tensorflow-speech-recognition/blob/master/speech_data.py">repository</a> experiments with raw audio, spectrograms, and MFCCs as features.</li>
</ul>

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<p><a id='step2'></a></p>
<h2 id="STEP-2:-Deep-Neural-Networks-for-Acoustic-Modeling">STEP 2: Deep Neural Networks for Acoustic Modeling<a class="anchor-link" href="#STEP-2:-Deep-Neural-Networks-for-Acoustic-Modeling">&#182;</a></h2><p>In this section, you will experiment with various neural network architectures for acoustic modeling.</p>
<p>You will begin by training five relatively simple architectures.  <strong>Model 0</strong> is provided for you.  You will write code to implement <strong>Models 1</strong>, <strong>2</strong>, <strong>3</strong>, and <strong>4</strong>.  If you would like to experiment further, you are welcome to create and train more models under the <strong>Models 5+</strong> heading.</p>
<p>All models will be specified in the <code>sample_models.py</code> file.  After importing the <code>sample_models</code> module, you will train your architectures in the notebook.</p>
<p>After experimenting with the five simple architectures, you will have the opportunity to compare their performance.  Based on your findings, you will construct a deeper architecture that is designed to outperform all of the shallow models.</p>
<p>For your convenience, we have designed the notebook so that each model can be specified and trained on separate occasions.  That is, say you decide to take a break from the notebook after training <strong>Model 1</strong>.  Then, you need not re-execute all prior code cells in the notebook before training <strong>Model 2</strong>.  You need only re-execute the code cell below, that is marked with <strong><code>RUN THIS CODE CELL IF YOU ARE RESUMING THE NOTEBOOK AFTER A BREAK</code></strong>, before transitioning to the code cells corresponding to <strong>Model 2</strong>.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#####################################################################</span>
<span class="c1"># RUN THIS CODE CELL IF YOU ARE RESUMING THE NOTEBOOK AFTER A BREAK #</span>
<span class="c1">#####################################################################</span>

<span class="c1"># allocate 50% of GPU memory (if you like, feel free to change this)</span>
<span class="kn">from</span> <span class="nn">keras.backend.tensorflow_backend</span> <span class="k">import</span> <span class="n">set_session</span>
<span class="kn">import</span> <span class="nn">tensorflow</span> <span class="k">as</span> <span class="nn">tf</span> 
<span class="n">config</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">ConfigProto</span><span class="p">()</span>
<span class="n">config</span><span class="o">.</span><span class="n">gpu_options</span><span class="o">.</span><span class="n">per_process_gpu_memory_fraction</span> <span class="o">=</span> <span class="mf">0.5</span>
<span class="n">set_session</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">(</span><span class="n">config</span><span class="o">=</span><span class="n">config</span><span class="p">))</span>

<span class="c1"># watch for any changes in the sample_models module, and reload it automatically</span>
<span class="o">%</span><span class="k">load_ext</span> autoreload
<span class="o">%</span><span class="k">autoreload</span> 2
<span class="c1"># import NN architectures for speech recognition</span>
<span class="kn">from</span> <span class="nn">sample_models</span> <span class="k">import</span> <span class="o">*</span>
<span class="c1"># import function for training acoustic model</span>
<span class="kn">from</span> <span class="nn">train_utils</span> <span class="k">import</span> <span class="n">train_model</span>
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<pre>Using TensorFlow backend.
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<p><a id='model0'></a></p>
<h3 id="Model-0:-RNN">Model 0: RNN<a class="anchor-link" href="#Model-0:-RNN">&#182;</a></h3><p>Given their effectiveness in modeling sequential data, the first acoustic model you will use is an RNN.  As shown in the figure below, the RNN we supply to you will take the time sequence of audio features as input.</p>
<p><img src="images/simple_rnn.png" width="50%"></p>
<p>At each time step, the speaker pronounces one of 28 possible characters, including each of the 26 letters in the English alphabet, along with a space character (" "), and an apostrophe (').</p>
<p>The output of the RNN at each time step is a vector of probabilities with 29 entries, where the $i$-th entry encodes the probability that the $i$-th character is spoken in the time sequence.  (The extra 29th character is an empty "character" used to pad training examples within batches containing uneven lengths.)  If you would like to peek under the hood at how characters are mapped to indices in the probability vector, look at the <code>char_map.py</code> file in the repository.  The figure below shows an equivalent, rolled depiction of the RNN that shows the output layer in greater detail.</p>
<p><img src="images/simple_rnn_unrolled.png" width="60%"></p>
<p>The model has already been specified for you in Keras.  To import it, you need only run the code cell below.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model_0</span> <span class="o">=</span> <span class="n">simple_rnn_model</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="mi">161</span><span class="p">)</span> <span class="c1"># change to 13 if you would like to use MFCC features</span>
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
the_input (InputLayer)       (None, None, 161)         0         
_________________________________________________________________
rnn (GRU)                    (None, None, 29)          16617     
_________________________________________________________________
softmax (Activation)         (None, None, 29)          0         
=================================================================
Total params: 16,617
Trainable params: 16,617
Non-trainable params: 0
_________________________________________________________________
None
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<p>As explored in the lesson, you will train the acoustic model with the <a href="http://www.cs.toronto.edu/~graves/icml_2006.pdf">CTC loss</a> criterion.  Custom loss functions take a bit of hacking in Keras, and so we have implemented the CTC loss function for you, so that you can focus on trying out as many deep learning architectures as possible :).  If you'd like to peek at the implementation details, look at the <code>add_ctc_loss</code> function within the <code>train_utils.py</code> file in the repository.</p>
<p>To train your architecture, you will use the <code>train_model</code> function within the <code>train_utils</code> module; it has already been imported in one of the above code cells.  The <code>train_model</code> function takes three <strong>required</strong> arguments:</p>
<ul>
<li><code>input_to_softmax</code> - a Keras model instance.</li>
<li><code>pickle_path</code> - the name of the pickle file where the loss history will be saved.</li>
<li><code>save_model_path</code> - the name of the HDF5 file where the model will be saved.</li>
</ul>
<p>If we have already supplied values for <code>input_to_softmax</code>, <code>pickle_path</code>, and <code>save_model_path</code>, please <strong>DO NOT</strong> modify these values.</p>
<p>There are several <strong>optional</strong> arguments that allow you to have more control over the training process.  You are welcome to, but not required to, supply your own values for these arguments.</p>
<ul>
<li><code>minibatch_size</code> - the size of the minibatches that are generated while training the model (default: <code>20</code>).</li>
<li><code>spectrogram</code> - Boolean value dictating whether spectrogram (<code>True</code>) or MFCC (<code>False</code>) features are used for training (default: <code>True</code>).</li>
<li><code>mfcc_dim</code> - the size of the feature dimension to use when generating MFCC features (default: <code>13</code>).</li>
<li><code>optimizer</code> - the Keras optimizer used to train the model (default: <code>SGD(lr=0.02, decay=1e-6, momentum=0.9, nesterov=True, clipnorm=5)</code>).  </li>
<li><code>epochs</code> - the number of epochs to use to train the model (default: <code>20</code>).  If you choose to modify this parameter, make sure that it is <em>at least</em> 20.</li>
<li><code>verbose</code> - controls the verbosity of the training output in the <code>model.fit_generator</code> method (default: <code>1</code>).</li>
<li><code>sort_by_duration</code> - Boolean value dictating whether the training and validation sets are sorted by (increasing) duration before the start of the first epoch (default: <code>False</code>).</li>
</ul>
<p>The <code>train_model</code> function defaults to using spectrogram features; if you choose to use these features, note that the acoustic model in <code>simple_rnn_model</code> should have <code>input_dim=161</code>.  Otherwise, if you choose to use MFCC features, the acoustic model should have <code>input_dim=13</code>.</p>
<p>We have chosen to use <code>GRU</code> units in the supplied RNN.  If you would like to experiment with <code>LSTM</code> or <code>SimpleRNN</code> cells, feel free to do so here.  If you change the <code>GRU</code> units to <code>SimpleRNN</code> cells in <code>simple_rnn_model</code>, you may notice that the loss quickly becomes undefined (<code>nan</code>) - you are strongly encouraged to check this for yourself!  This is due to the <a href="http://www.wildml.com/2015/10/recurrent-neural-networks-tutorial-part-3-backpropagation-through-time-and-vanishing-gradients/">exploding gradients problem</a>.  We have already implemented <a href="https://arxiv.org/pdf/1211.5063.pdf">gradient clipping</a> in your optimizer to help you avoid this issue.</p>
<p><strong>IMPORTANT NOTE:</strong> If you notice that your gradient has exploded in any of the models below, feel free to explore more with gradient clipping (the <code>clipnorm</code> argument in your optimizer) or swap out any <code>SimpleRNN</code> cells for <code>LSTM</code> or <code>GRU</code> cells.  You can also try restarting the kernel to restart the training process.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_model</span><span class="p">(</span><span class="n">input_to_softmax</span><span class="o">=</span><span class="n">model_0</span><span class="p">,</span> 
            <span class="n">pickle_path</span><span class="o">=</span><span class="s1">&#39;model_0.pickle&#39;</span><span class="p">,</span> 
            <span class="n">save_model_path</span><span class="o">=</span><span class="s1">&#39;model_0.h5&#39;</span><span class="p">,</span>
            <span class="n">spectrogram</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># change to False if you would like to use MFCC features</span>
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<pre>Epoch 1/20
106/106 [==============================] - 223s - loss: 841.2238 - val_loss: 737.5177
Epoch 2/20
106/106 [==============================] - 223s - loss: 758.9980 - val_loss: 729.5508
Epoch 3/20
106/106 [==============================] - 221s - loss: 751.9652 - val_loss: 727.8422
Epoch 4/20
106/106 [==============================] - 222s - loss: 751.6565 - val_loss: 728.0686
Epoch 5/20
106/106 [==============================] - 223s - loss: 752.3925 - val_loss: 726.7905
Epoch 6/20
106/106 [==============================] - 223s - loss: 753.0102 - val_loss: 724.1257
Epoch 7/20
106/106 [==============================] - 223s - loss: 752.5333 - val_loss: 731.5176
Epoch 8/20
106/106 [==============================] - 223s - loss: 752.2540 - val_loss: 732.7433
Epoch 9/20
106/106 [==============================] - 220s - loss: 751.1169 - val_loss: 724.6210
Epoch 10/20
106/106 [==============================] - 221s - loss: 751.8646 - val_loss: 722.1209
Epoch 11/20
106/106 [==============================] - 221s - loss: 752.2552 - val_loss: 726.9070
Epoch 12/20
106/106 [==============================] - 222s - loss: 752.6756 - val_loss: 724.5285
Epoch 13/20
106/106 [==============================] - 223s - loss: 752.5782 - val_loss: 731.7611
Epoch 14/20
106/106 [==============================] - 220s - loss: 751.9713 - val_loss: 717.2001
Epoch 15/20
106/106 [==============================] - 222s - loss: 751.7278 - val_loss: 728.0450
Epoch 16/20
106/106 [==============================] - 222s - loss: 752.7618 - val_loss: 728.7683
Epoch 17/20
106/106 [==============================] - 222s - loss: 752.3442 - val_loss: 725.6183
Epoch 18/20
106/106 [==============================] - 221s - loss: 752.3454 - val_loss: 724.9380
Epoch 19/20
106/106 [==============================] - 222s - loss: 751.3731 - val_loss: 728.9169
Epoch 20/20
106/106 [==============================] - 223s - loss: 753.5150 - val_loss: 727.9232
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<p><a id='model1'></a></p>
<h3 id="(IMPLEMENTATION)-Model-1:-RNN-+-TimeDistributed-Dense">(IMPLEMENTATION) Model 1: RNN + TimeDistributed Dense<a class="anchor-link" href="#(IMPLEMENTATION)-Model-1:-RNN-+-TimeDistributed-Dense">&#182;</a></h3><p>Read about the <a href="https://keras.io/layers/wrappers/">TimeDistributed</a> wrapper and the <a href="https://keras.io/layers/normalization/">BatchNormalization</a> layer in the Keras documentation.  For your next architecture, you will add <a href="https://arxiv.org/pdf/1510.01378.pdf">batch normalization</a> to the recurrent layer to reduce training times.  The <code>TimeDistributed</code> layer will be used to find more complex patterns in the dataset.  The unrolled snapshot of the architecture is depicted below.</p>
<p><img src="images/rnn_model.png" width="60%"></p>
<p>The next figure shows an equivalent, rolled depiction of the RNN that shows the (<code>TimeDistrbuted</code>) dense and output layers in greater detail.</p>
<p><img src="images/rnn_model_unrolled.png" width="60%"></p>
<p>Use your research to complete the <code>rnn_model</code> function within the <code>sample_models.py</code> file.  The function should specify an architecture that satisfies the following requirements:</p>
<ul>
<li>The first layer of the neural network should be an RNN (<code>SimpleRNN</code>, <code>LSTM</code>, or <code>GRU</code>) that takes the time sequence of audio features as input.  We have added <code>GRU</code> units for you, but feel free to change <code>GRU</code> to <code>SimpleRNN</code> or <code>LSTM</code>, if you like!</li>
<li>Whereas the architecture in <code>simple_rnn_model</code> treated the RNN output as the final layer of the model, you will use the output of your RNN as a hidden layer.  Use <code>TimeDistributed</code> to apply a <code>Dense</code> layer to each of the time steps in the RNN output.  Ensure that each <code>Dense</code> layer has <code>output_dim</code> units.</li>
</ul>
<p>Use the code cell below to load your model into the <code>model_1</code> variable.  Use a value for <code>input_dim</code> that matches your chosen audio features, and feel free to change the values for <code>units</code> and <code>activation</code> to tweak the behavior of your recurrent layer.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model_1</span> <span class="o">=</span> <span class="n">rnn_model</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="mi">161</span><span class="p">,</span> <span class="c1"># change to 13 if you would like to use MFCC features</span>
                    <span class="n">units</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
                    <span class="n">activation</span><span class="o">=</span><span class="s1">&#39;relu&#39;</span><span class="p">)</span>
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
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the_input (InputLayer)       (None, None, 161)         0         
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rnn (GRU)                    (None, None, 200)         217200    
_________________________________________________________________
batch_normalization_1 (Batch (None, None, 200)         800       
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time_distributed_1 (TimeDist (None, None, 29)          5829      
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softmax (Activation)         (None, None, 29)          0         
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Total params: 223,829
Trainable params: 223,429
Non-trainable params: 400
_________________________________________________________________
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<p>Please execute the code cell below to train the neural network you specified in <code>input_to_softmax</code>.  After the model has finished training, the model is <a href="https://keras.io/getting-started/faq/#how-can-i-save-a-keras-model">saved</a> in the HDF5 file <code>model_1.h5</code>.  The loss history is <a href="https://wiki.python.org/moin/UsingPickle">saved</a> in <code>model_1.pickle</code>.  You are welcome to tweak any of the optional parameters while calling the <code>train_model</code> function, but this is not required.</p>

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            <span class="n">pickle_path</span><span class="o">=</span><span class="s1">&#39;model_1.pickle&#39;</span><span class="p">,</span> 
            <span class="n">save_model_path</span><span class="o">=</span><span class="s1">&#39;model_1.h5&#39;</span><span class="p">,</span>
            <span class="n">spectrogram</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># change to False if you would like to use MFCC features</span>
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<pre>Epoch 1/20
106/106 [==============================] - 229s - loss: 406.9345 - val_loss: 337.3226
Epoch 2/20
106/106 [==============================] - 230s - loss: 252.5815 - val_loss: 222.1327
Epoch 3/20
106/106 [==============================] - 228s - loss: 200.9934 - val_loss: 195.8260
Epoch 4/20
106/106 [==============================] - 226s - loss: 182.3809 - val_loss: 175.4300
Epoch 5/20
106/106 [==============================] - 225s - loss: 166.9986 - val_loss: 163.3010
Epoch 6/20
106/106 [==============================] - 224s - loss: 156.1938 - val_loss: 158.6230
Epoch 7/20
106/106 [==============================] - 222s - loss: 149.9541 - val_loss: 149.7877
Epoch 8/20
106/106 [==============================] - 225s - loss: 145.4194 - val_loss: 152.8585
Epoch 9/20
106/106 [==============================] - 223s - loss: 142.5402 - val_loss: 144.0245
Epoch 10/20
106/106 [==============================] - 225s - loss: 140.2266 - val_loss: 144.6329
Epoch 11/20
106/106 [==============================] - 223s - loss: 138.6763 - val_loss: 143.9470
Epoch 12/20
106/106 [==============================] - 224s - loss: 137.9646 - val_loss: 147.9799
Epoch 13/20
106/106 [==============================] - 224s - loss: 137.8269 - val_loss: 144.0487
Epoch 14/20
106/106 [==============================] - 224s - loss: 136.9030 - val_loss: 141.6343
Epoch 15/20
106/106 [==============================] - 224s - loss: 137.3624 - val_loss: 145.1638
Epoch 16/20
106/106 [==============================] - 224s - loss: 136.7356 - val_loss: 144.8835
Epoch 17/20
106/106 [==============================] - 224s - loss: 136.2908 - val_loss: 147.4591
Epoch 18/20
106/106 [==============================] - 223s - loss: 134.5967 - val_loss: 147.0977
Epoch 19/20
106/106 [==============================] - 225s - loss: 135.7818 - val_loss: 147.0533
Epoch 20/20
106/106 [==============================] - 224s - loss: 138.9203 - val_loss: 152.1336
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<p><a id='model2'></a></p>
<h3 id="(IMPLEMENTATION)-Model-2:-CNN-+-RNN-+-TimeDistributed-Dense">(IMPLEMENTATION) Model 2: CNN + RNN + TimeDistributed Dense<a class="anchor-link" href="#(IMPLEMENTATION)-Model-2:-CNN-+-RNN-+-TimeDistributed-Dense">&#182;</a></h3><p>The architecture in <code>cnn_rnn_model</code> adds an additional level of complexity, by introducing a <a href="https://keras.io/layers/convolutional/#conv1d">1D convolution layer</a>.</p>
<p><img src="images/cnn_rnn_model.png" width="100%"></p>
<p>This layer incorporates many arguments that can be (optionally) tuned when calling the <code>cnn_rnn_model</code> module.  We provide sample starting parameters, which you might find useful if you choose to use spectrogram audio features.</p>
<p>If you instead want to use MFCC features, these arguments will have to be tuned.  Note that the current architecture only supports values of <code>'same'</code> or <code>'valid'</code> for the <code>conv_border_mode</code> argument.</p>
<p>When tuning the parameters, be careful not to choose settings that make the convolutional layer overly small.  If the temporal length of the CNN layer is shorter than the length of the transcribed text label, your code will throw an error.</p>
<p>Before running the code cell below, you must modify the <code>cnn_rnn_model</code> function in <code>sample_models.py</code>.  Please add batch normalization to the recurrent layer, and provide the same <code>TimeDistributed</code> layer as before.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model_2</span> <span class="o">=</span> <span class="n">cnn_rnn_model</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="mi">161</span><span class="p">,</span> <span class="c1"># change to 13 if you would like to use MFCC features</span>
                        <span class="n">filters</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
                        <span class="n">kernel_size</span><span class="o">=</span><span class="mi">11</span><span class="p">,</span> 
                        <span class="n">conv_stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
                        <span class="n">conv_border_mode</span><span class="o">=</span><span class="s1">&#39;valid&#39;</span><span class="p">,</span>
                        <span class="n">units</span><span class="o">=</span><span class="mi">200</span><span class="p">)</span>
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
the_input (InputLayer)       (None, None, 161)         0         
_________________________________________________________________
conv1d (Conv1D)              (None, None, 200)         354400    
_________________________________________________________________
bn_conv_1d (BatchNormalizati (None, None, 200)         800       
_________________________________________________________________
rnn (SimpleRNN)              (None, None, 200)         80200     
_________________________________________________________________
batch_normalization_2 (Batch (None, None, 200)         800       
_________________________________________________________________
time_distributed_2 (TimeDist (None, None, 29)          5829      
_________________________________________________________________
softmax (Activation)         (None, None, 29)          0         
=================================================================
Total params: 442,029
Trainable params: 441,229
Non-trainable params: 800
_________________________________________________________________
None
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<p>Please execute the code cell below to train the neural network you specified in <code>input_to_softmax</code>.  After the model has finished training, the model is <a href="https://keras.io/getting-started/faq/#how-can-i-save-a-keras-model">saved</a> in the HDF5 file <code>model_2.h5</code>.  The loss history is <a href="https://wiki.python.org/moin/UsingPickle">saved</a> in <code>model_2.pickle</code>.  You are welcome to tweak any of the optional parameters while calling the <code>train_model</code> function, but this is not required.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_model</span><span class="p">(</span><span class="n">input_to_softmax</span><span class="o">=</span><span class="n">model_2</span><span class="p">,</span> 
            <span class="n">pickle_path</span><span class="o">=</span><span class="s1">&#39;model_2.pickle&#39;</span><span class="p">,</span> 
            <span class="n">save_model_path</span><span class="o">=</span><span class="s1">&#39;model_2.h5&#39;</span><span class="p">,</span> 
            <span class="n">spectrogram</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># change to False if you would like to use MFCC features</span>
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<pre>Epoch 1/20
106/106 [==============================] - 61s - loss: 233.4742 - val_loss: 226.2600
Epoch 2/20
106/106 [==============================] - 59s - loss: 170.8519 - val_loss: 209.6630
Epoch 3/20
106/106 [==============================] - 60s - loss: 149.5085 - val_loss: 207.7376
Epoch 4/20
106/106 [==============================] - 58s - loss: 137.9058 - val_loss: 205.5938
Epoch 5/20
106/106 [==============================] - 59s - loss: 130.2679 - val_loss: 202.0919
Epoch 6/20
106/106 [==============================] - 59s - loss: 123.3250 - val_loss: 192.4598
Epoch 7/20
106/106 [==============================] - 58s - loss: 117.9812 - val_loss: 183.2249
Epoch 8/20
106/106 [==============================] - 57s - loss: 113.5550 - val_loss: 156.4507
Epoch 9/20
106/106 [==============================] - 57s - loss: 109.9467 - val_loss: 142.3602
Epoch 10/20
106/106 [==============================] - 59s - loss: 106.0203 - val_loss: 130.0810
Epoch 11/20
106/106 [==============================] - 59s - loss: 102.8122 - val_loss: 131.5752
Epoch 12/20
106/106 [==============================] - 58s - loss: 99.6910 - val_loss: 127.1500
Epoch 13/20
106/106 [==============================] - 58s - loss: 96.3618 - val_loss: 130.0220
Epoch 14/20
106/106 [==============================] - 58s - loss: 94.0996 - val_loss: 133.4094
Epoch 15/20
106/106 [==============================] - 59s - loss: 91.9226 - val_loss: 129.5138
Epoch 16/20
106/106 [==============================] - 59s - loss: 89.4229 - val_loss: 129.6829
Epoch 17/20
106/106 [==============================] - 59s - loss: 86.9180 - val_loss: 131.7057
Epoch 18/20
106/106 [==============================] - 57s - loss: 84.4827 - val_loss: 131.3496
Epoch 19/20
106/106 [==============================] - 58s - loss: 82.3777 - val_loss: 139.1281
Epoch 20/20
106/106 [==============================] - 57s - loss: 80.2403 - val_loss: 135.0575
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<p><a id='model3'></a></p>
<h3 id="(IMPLEMENTATION)-Model-3:-Deeper-RNN-+-TimeDistributed-Dense">(IMPLEMENTATION) Model 3: Deeper RNN + TimeDistributed Dense<a class="anchor-link" href="#(IMPLEMENTATION)-Model-3:-Deeper-RNN-+-TimeDistributed-Dense">&#182;</a></h3><p>Review the code in <code>rnn_model</code>, which makes use of a single recurrent layer.  Now, specify an architecture in <code>deep_rnn_model</code> that utilizes a variable number <code>recur_layers</code> of recurrent layers.  The figure below shows the architecture that should be returned if <code>recur_layers=2</code>.  In the figure, the output sequence of the first recurrent layer is used as input for the next recurrent layer.</p>
<p><img src="images/deep_rnn_model.png" width="80%"></p>
<p>Feel free to change the supplied values of <code>units</code> to whatever you think performs best.  You can change the value of <code>recur_layers</code>, as long as your final value is greater than 1. (As a quick check that you have implemented the additional functionality in <code>deep_rnn_model</code> correctly, make sure that the architecture that you specify here is identical to <code>rnn_model</code> if <code>recur_layers=1</code>.)</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model_3</span> <span class="o">=</span> <span class="n">deep_rnn_model</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="mi">161</span><span class="p">,</span> <span class="c1"># change to 13 if you would like to use MFCC features</span>
                         <span class="n">units</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
                         <span class="n">recur_layers</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span> 
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
the_input (InputLayer)       (None, None, 161)         0         
_________________________________________________________________
rnn0 (GRU)                   (None, None, 200)         217200    
_________________________________________________________________
batch_normalization_1 (Batch (None, None, 200)         800       
_________________________________________________________________
rnn1 (GRU)                   (None, None, 200)         240600    
_________________________________________________________________
batch_normalization_2 (Batch (None, None, 200)         800       
_________________________________________________________________
time_distributed_1 (TimeDist (None, None, 29)          5829      
_________________________________________________________________
softmax (Activation)         (None, None, 29)          0         
=================================================================
Total params: 465,229
Trainable params: 464,429
Non-trainable params: 800
_________________________________________________________________
None
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<p>Please execute the code cell below to train the neural network you specified in <code>input_to_softmax</code>.  After the model has finished training, the model is <a href="https://keras.io/getting-started/faq/#how-can-i-save-a-keras-model">saved</a> in the HDF5 file <code>model_3.h5</code>.  The loss history is <a href="https://wiki.python.org/moin/UsingPickle">saved</a> in <code>model_3.pickle</code>.  You are welcome to tweak any of the optional parameters while calling the <code>train_model</code> function, but this is not required.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_model</span><span class="p">(</span><span class="n">input_to_softmax</span><span class="o">=</span><span class="n">model_3</span><span class="p">,</span> 
            <span class="n">pickle_path</span><span class="o">=</span><span class="s1">&#39;model_3.pickle&#39;</span><span class="p">,</span> 
            <span class="n">save_model_path</span><span class="o">=</span><span class="s1">&#39;model_3.h5&#39;</span><span class="p">,</span> 
            <span class="n">spectrogram</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># change to False if you would like to use MFCC features</span>
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<pre>Epoch 1/20
106/106 [==============================] - 381s - loss: 259.8366 - val_loss: 221.1292
Epoch 2/20
106/106 [==============================] - 382s - loss: 219.3495 - val_loss: 208.9818
Epoch 3/20
106/106 [==============================] - 380s - loss: 203.2672 - val_loss: 206.5054
Epoch 4/20
106/106 [==============================] - 377s - loss: 173.4896 - val_loss: 183.9415
Epoch 5/20
106/106 [==============================] - 380s - loss: 154.8167 - val_loss: 154.3973
Epoch 6/20
106/106 [==============================] - 379s - loss: 143.1883 - val_loss: 144.1944
Epoch 7/20
106/106 [==============================] - 382s - loss: 136.6433 - val_loss: 147.4628
Epoch 8/20
106/106 [==============================] - 379s - loss: 135.3485 - val_loss: 147.2785
Epoch 9/20
106/106 [==============================] - 376s - loss: 129.0251 - val_loss: 136.5343
Epoch 10/20
106/106 [==============================] - 380s - loss: 125.4493 - val_loss: 138.4362
Epoch 11/20
106/106 [==============================] - 378s - loss: 123.9016 - val_loss: 134.8892
Epoch 12/20
106/106 [==============================] - 378s - loss: 122.1527 - val_loss: 130.8136
Epoch 13/20
106/106 [==============================] - 379s - loss: 118.8920 - val_loss: 128.8695
Epoch 14/20
106/106 [==============================] - 379s - loss: 118.2464 - val_loss: 132.9381
Epoch 15/20
106/106 [==============================] - 381s - loss: 118.7094 - val_loss: 133.1962
Epoch 16/20
106/106 [==============================] - 378s - loss: 119.5405 - val_loss: 165.9534
Epoch 17/20
106/106 [==============================] - 376s - loss: 123.2865 - val_loss: 130.6875
Epoch 18/20
106/106 [==============================] - 382s - loss: 119.1013 - val_loss: 140.1095
Epoch 19/20
106/106 [==============================] - 381s - loss: 119.5738 - val_loss: 130.7571
Epoch 20/20
106/106 [==============================] - 379s - loss: 122.2988 - val_loss: 142.3309
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<p><a id='model4'></a></p>
<h3 id="(IMPLEMENTATION)-Model-4:-Bidirectional-RNN-+-TimeDistributed-Dense">(IMPLEMENTATION) Model 4: Bidirectional RNN + TimeDistributed Dense<a class="anchor-link" href="#(IMPLEMENTATION)-Model-4:-Bidirectional-RNN-+-TimeDistributed-Dense">&#182;</a></h3><p>Read about the <a href="https://keras.io/layers/wrappers/">Bidirectional</a> wrapper in the Keras documentation.  For your next architecture, you will specify an architecture that uses a single bidirectional RNN layer, before a (<code>TimeDistributed</code>) dense layer.  The added value of a bidirectional RNN is described well in <a href="http://www.cs.toronto.edu/~hinton/absps/DRNN_speech.pdf">this paper</a>.</p>
<blockquote><p>One shortcoming of conventional RNNs is that they are only able to make use of previous context. In speech recognition, where whole utterances are transcribed at once, there is no reason not to exploit future context as well.  Bidirectional RNNs (BRNNs) do this by processing the data in both directions with two separate hidden layers which are then fed forwards to the same output layer.</p>
</blockquote>
<p><img src="images/bidirectional_rnn_model.png" width="80%"></p>
<p>Before running the code cell below, you must complete the <code>bidirectional_rnn_model</code> function in <code>sample_models.py</code>.  Feel free to use <code>SimpleRNN</code>, <code>LSTM</code>, or <code>GRU</code> units.  When specifying the <code>Bidirectional</code> wrapper, use <code>merge_mode='concat'</code>.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model_4</span> <span class="o">=</span> <span class="n">bidirectional_rnn_model</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="mi">161</span><span class="p">,</span> <span class="c1"># change to 13 if you would like to use MFCC features</span>
                                  <span class="n">units</span><span class="o">=</span><span class="mi">200</span><span class="p">)</span>
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
the_input (InputLayer)       (None, None, 161)         0         
_________________________________________________________________
bidirectional_1 (Bidirection (None, None, 400)         434400    
_________________________________________________________________
time_distributed_2 (TimeDist (None, None, 29)          11629     
_________________________________________________________________
softmax (Activation)         (None, None, 29)          0         
=================================================================
Total params: 446,029
Trainable params: 446,029
Non-trainable params: 0
_________________________________________________________________
None
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<p>Please execute the code cell below to train the neural network you specified in <code>input_to_softmax</code>.  After the model has finished training, the model is <a href="https://keras.io/getting-started/faq/#how-can-i-save-a-keras-model">saved</a> in the HDF5 file <code>model_4.h5</code>.  The loss history is <a href="https://wiki.python.org/moin/UsingPickle">saved</a> in <code>model_4.pickle</code>.  You are welcome to tweak any of the optional parameters while calling the <code>train_model</code> function, but this is not required.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_model</span><span class="p">(</span><span class="n">input_to_softmax</span><span class="o">=</span><span class="n">model_4</span><span class="p">,</span> 
            <span class="n">pickle_path</span><span class="o">=</span><span class="s1">&#39;model_4.pickle&#39;</span><span class="p">,</span> 
            <span class="n">save_model_path</span><span class="o">=</span><span class="s1">&#39;model_4.h5&#39;</span><span class="p">,</span> 
            <span class="n">spectrogram</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># change to False if you would like to use MFCC features</span>
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<pre>Epoch 1/20
106/106 [==============================] - 369s - loss: 256.5967 - val_loss: 210.3117
Epoch 2/20
106/106 [==============================] - 373s - loss: 206.9104 - val_loss: 194.3327
Epoch 3/20
106/106 [==============================] - 373s - loss: 195.2138 - val_loss: 186.1162
Epoch 4/20
106/106 [==============================] - 376s - loss: 185.5421 - val_loss: 179.2724
Epoch 5/20
106/106 [==============================] - 373s - loss: 176.6331 - val_loss: 171.6082
Epoch 6/20
106/106 [==============================] - 376s - loss: 168.0613 - val_loss: 164.5045
Epoch 7/20
106/106 [==============================] - 371s - loss: 160.6109 - val_loss: 161.1474
Epoch 8/20
106/106 [==============================] - 375s - loss: 154.4030 - val_loss: 156.5542
Epoch 9/20
106/106 [==============================] - 374s - loss: 148.8396 - val_loss: 151.2190
Epoch 10/20
106/106 [==============================] - 373s - loss: 144.1927 - val_loss: 148.3285
Epoch 11/20
106/106 [==============================] - 376s - loss: 139.4251 - val_loss: 147.1954
Epoch 12/20
106/106 [==============================] - 373s - loss: 135.4763 - val_loss: 144.0890
Epoch 13/20
106/106 [==============================] - 374s - loss: 131.4776 - val_loss: 142.0208
Epoch 14/20
106/106 [==============================] - 373s - loss: 127.9746 - val_loss: 141.4526
Epoch 15/20
106/106 [==============================] - 373s - loss: 124.3294 - val_loss: 137.8553
Epoch 16/20
106/106 [==============================] - 374s - loss: 121.5938 - val_loss: 140.0293
Epoch 17/20
106/106 [==============================] - 373s - loss: 118.6560 - val_loss: 137.1314
Epoch 18/20
106/106 [==============================] - 376s - loss: 115.6975 - val_loss: 136.8782
Epoch 19/20
106/106 [==============================] - 376s - loss: 112.8994 - val_loss: 136.8725
Epoch 20/20
106/106 [==============================] - 373s - loss: 110.2620 - val_loss: 137.4831
</pre>
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<p><a id='model5'></a></p>
<h3 id="(OPTIONAL-IMPLEMENTATION)-Models-5+">(OPTIONAL IMPLEMENTATION) Models 5+<a class="anchor-link" href="#(OPTIONAL-IMPLEMENTATION)-Models-5+">&#182;</a></h3><p>If you would like to try out more architectures than the ones above, please use the code cell below.  Please continue to follow the same convention for saving the models; for the $i$-th sample model, please save the loss at <strong><code>model_i.pickle</code></strong> and saving the trained model at <strong><code>model_i.h5</code></strong>.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">## (Optional) TODO: Try out some more models!</span>
<span class="c1">### Feel free to use as many code cells as needed.</span>
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<h3 id="Compare-the-Models">Compare the Models<a class="anchor-link" href="#Compare-the-Models">&#182;</a></h3><p>Execute the code cell below to evaluate the performance of the drafted deep learning models.  The training and validation loss are plotted for each model.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">glob</span> <span class="k">import</span> <span class="n">glob</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">_pickle</span> <span class="k">as</span> <span class="nn">pickle</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="o">%</span><span class="k">matplotlib</span> inline
<span class="n">sns</span><span class="o">.</span><span class="n">set_style</span><span class="p">(</span><span class="n">style</span><span class="o">=</span><span class="s1">&#39;white&#39;</span><span class="p">)</span>

<span class="c1"># obtain the paths for the saved model history</span>
<span class="n">all_pickles</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">glob</span><span class="p">(</span><span class="s2">&quot;results/*.pickle&quot;</span><span class="p">))</span>
<span class="c1"># extract the name of each model</span>
<span class="n">model_names</span> <span class="o">=</span> <span class="p">[</span><span class="n">item</span><span class="p">[</span><span class="mi">8</span><span class="p">:</span><span class="o">-</span><span class="mi">7</span><span class="p">]</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">all_pickles</span><span class="p">]</span>
<span class="c1"># extract the loss history for each model</span>
<span class="n">valid_loss</span> <span class="o">=</span> <span class="p">[</span><span class="n">pickle</span><span class="o">.</span><span class="n">load</span><span class="p">(</span> <span class="nb">open</span><span class="p">(</span> <span class="n">i</span><span class="p">,</span> <span class="s2">&quot;rb&quot;</span> <span class="p">)</span> <span class="p">)[</span><span class="s1">&#39;val_loss&#39;</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">all_pickles</span><span class="p">]</span>
<span class="n">train_loss</span> <span class="o">=</span> <span class="p">[</span><span class="n">pickle</span><span class="o">.</span><span class="n">load</span><span class="p">(</span> <span class="nb">open</span><span class="p">(</span> <span class="n">i</span><span class="p">,</span> <span class="s2">&quot;rb&quot;</span> <span class="p">)</span> <span class="p">)[</span><span class="s1">&#39;loss&#39;</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">all_pickles</span><span class="p">]</span>
<span class="c1"># save the number of epochs used to train each model</span>
<span class="n">num_epochs</span> <span class="o">=</span> <span class="p">[</span><span class="nb">len</span><span class="p">(</span><span class="n">valid_loss</span><span class="p">[</span><span class="n">i</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="nb">len</span><span class="p">(</span><span class="n">valid_loss</span><span class="p">))]</span>

<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">16</span><span class="p">,</span><span class="mi">5</span><span class="p">))</span>

<span class="c1"># plot the training loss vs. epoch for each model</span>
<span class="n">ax1</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">121</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="nb">len</span><span class="p">(</span><span class="n">all_pickles</span><span class="p">)):</span>
    <span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_epochs</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">num_epochs</span><span class="p">[</span><span class="n">i</span><span class="p">]),</span> 
            <span class="n">train_loss</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="n">model_names</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
<span class="c1"># clean up the plot</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>  
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="nb">max</span><span class="p">(</span><span class="n">num_epochs</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">ylabel</span><span class="p">(</span><span class="s1">&#39;Training Loss&#39;</span><span class="p">)</span>

<span class="c1"># plot the validation loss vs. epoch for each model</span>
<span class="n">ax2</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">122</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="nb">len</span><span class="p">(</span><span class="n">all_pickles</span><span class="p">)):</span>
    <span class="n">ax2</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">num_epochs</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">num_epochs</span><span class="p">[</span><span class="n">i</span><span class="p">]),</span> 
            <span class="n">valid_loss</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="n">model_names</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
<span class="c1"># clean up the plot</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>  
<span class="n">ax2</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="nb">max</span><span class="p">(</span><span class="n">num_epochs</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">ylabel</span><span class="p">(</span><span class="s1">&#39;Validation Loss&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<p><strong>Question 1:</strong> Use the plot above to analyze the performance of each of the attempted architectures.  Which performs best?  Provide an explanation regarding why you think some models perform better than others.</p>
<p><strong>Answer:</strong></p>
<ul>
<li><strong>model_0</strong>: The first one layer GRU model is the simplest. It relies on the softmax layer to predict the output character but it doesn't apply a dense layer to each time step. This resulted in very poor performance in both the training and the validation sets.</li>
<li><strong>model_1</strong>: The second model which utilitzes the time distributed dense layer proves how effective this technique is. The difference is very clear as the loss drops in the figure to start at 400 and it goes down from there. Although not the best performance with a single layer, it paved the path towards the right direction.</li>
<li><strong>model_2</strong>: In the third model, the use of a convolutional layer was tested. Regardless of the significant decrease in time consumed for training, the use of the single conv layer before a simple rnn layer successfully exceeded all models in the training phase. The validation set shows slight overlapping with other models due to overfitting. Another observation is that the curve of the validation set shows that it took this model about 8 epochs before it could compete with other models.</li>
<li><strong>model_3</strong>: The forth model shows an interesting aspect of going deeper with a model. The training time is significantly increased with more params to train. From the plot, it can be seen to consistently perform better than the single layer RNN model. The validation set however shows a concerning fact. The spike around epoch 16 in the loss might signal that our model has not have converged well for a certain pattern and training it further might result in significant overfitting.</li>
<li><strong>model_4</strong>: The last model shows the use of bidirectional RNN's which can take a look at the input from both directions. It took them a bit longer to reach the other RNN model with similar architecture however it eventually exceeded it slightly. The validation set shows a similar, less apparent, result</li>
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<p><a id='final'></a></p>
<h3 id="(IMPLEMENTATION)-Final-Model">(IMPLEMENTATION) Final Model<a class="anchor-link" href="#(IMPLEMENTATION)-Final-Model">&#182;</a></h3><p>Now that you've tried out many sample models, use what you've learned to draft your own architecture!  While your final acoustic model should not be identical to any of the architectures explored above, you are welcome to merely combine the explored layers above into a deeper architecture.  It is <strong>NOT</strong> necessary to include new layer types that were not explored in the notebook.</p>
<p>However, if you would like some ideas for even more layer types, check out these ideas for some additional, optional extensions to your model:</p>
<ul>
<li>If you notice your model is overfitting to the training dataset, consider adding <strong>dropout</strong>!  To add dropout to <a href="https://faroit.github.io/keras-docs/1.0.2/layers/recurrent/">recurrent layers</a>, pay special attention to the <code>dropout_W</code> and <code>dropout_U</code> arguments.  This <a href="http://arxiv.org/abs/1512.05287">paper</a> may also provide some interesting theoretical background.</li>
<li>If you choose to include a convolutional layer in your model, you may get better results by working with <strong>dilated convolutions</strong>.  If you choose to use dilated convolutions, make sure that you are able to accurately calculate the length of the acoustic model's output in the <code>model.output_length</code> lambda function.  You can read more about dilated convolutions in Google's <a href="https://arxiv.org/abs/1609.03499">WaveNet paper</a>.  For an example of a speech-to-text system that makes use of dilated convolutions, check out this GitHub <a href="https://github.com/buriburisuri/speech-to-text-wavenet">repository</a>.  You can work with dilated convolutions <a href="https://keras.io/layers/convolutional/">in Keras</a> by paying special attention to the <code>padding</code> argument when you specify a convolutional layer.</li>
<li>If your model makes use of convolutional layers, why not also experiment with adding <strong>max pooling</strong>?  Check out <a href="https://arxiv.org/pdf/1701.02720.pdf">this paper</a> for example architecture that makes use of max pooling in an acoustic model.</li>
<li>So far, you have experimented with a single bidirectional RNN layer.  Consider stacking the bidirectional layers, to produce a <a href="https://www.cs.toronto.edu/~graves/asru_2013.pdf">deep bidirectional RNN</a>!</li>
</ul>
<p>All models that you specify in this repository should have <code>output_length</code> defined as an attribute.  This attribute is a lambda function that maps the (temporal) length of the input acoustic features to the (temporal) length of the output softmax layer.  This function is used in the computation of CTC loss; to see this, look at the <code>add_ctc_loss</code> function in <code>train_utils.py</code>.  To see where the <code>output_length</code> attribute is defined for the models in the code, take a look at the <code>sample_models.py</code> file.  You will notice this line of code within most models:</p>

<pre><code>model.output_length = lambda x: x</code></pre>
<p>The acoustic model that incorporates a convolutional layer (<code>cnn_rnn_model</code>) has a line that is a bit different:</p>

<pre><code>model.output_length = lambda x: cnn_output_length(
        x, kernel_size, conv_border_mode, conv_stride)</code></pre>
<p>In the case of models that use purely recurrent layers, the lambda function is the identity function, as the recurrent layers do not modify the (temporal) length of their input tensors.  However, convolutional layers are more complicated and require a specialized function (<code>cnn_output_length</code> in <code>sample_models.py</code>) to determine the temporal length of their output.</p>
<p>You will have to add the <code>output_length</code> attribute to your final model before running the code cell below.  Feel free to use the <code>cnn_output_length</code> function, if it suits your model.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># specify the model</span>
<span class="n">model_end</span> <span class="o">=</span> <span class="n">final_model</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="mi">161</span><span class="p">,</span> <span class="c1"># change to 13 if you would like to use MFCC features</span>
                        <span class="n">filters</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
                        <span class="n">kernel_size</span><span class="o">=</span><span class="mi">11</span><span class="p">,</span> 
                        <span class="n">conv_stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
                        <span class="n">conv_border_mode</span><span class="o">=</span><span class="s1">&#39;valid&#39;</span><span class="p">,</span>
                        <span class="n">units</span><span class="o">=</span><span class="mi">200</span><span class="p">)</span>
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<pre>/home/ubuntu/AIND-VUI-Capstone/sample_models.py:156: UserWarning: Update your `GRU` call to the Keras 2 API: `GRU(200, dropout=0.2, activation=&#34;relu&#34;, implementation=2, recurrent_dropout=0.2, return_sequences=True, name=&#34;rnn&#34;)`
  return_sequences=True, implementation=2, name=&#39;rnn&#39;, dropout_W=0.5, dropout_U=0.5),
/home/ubuntu/AIND-VUI-Capstone/sample_models.py:160: UserWarning: Update your `GRU` call to the Keras 2 API: `GRU(200, dropout=0.2, activation=&#34;relu&#34;, implementation=2, recurrent_dropout=0.2, return_sequences=True, name=&#34;rnn2&#34;)`
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
the_input (InputLayer)       (None, None, 161)         0         
_________________________________________________________________
conv1d (Conv1D)              (None, None, 200)         354400    
_________________________________________________________________
bn_conv_1d (BatchNormalizati (None, None, 200)         800       
_________________________________________________________________
bidirectional_6 (Bidirection (None, None, 400)         481200    
_________________________________________________________________
bn_birnn (BatchNormalization (None, None, 400)         1600      
_________________________________________________________________
bidirectional_7 (Bidirection (None, None, 400)         721200    
_________________________________________________________________
bn_birnn2 (BatchNormalizatio (None, None, 400)         1600      
_________________________________________________________________
time_distributed_5 (TimeDist (None, None, 29)          11629     
_________________________________________________________________
softmax (Activation)         (None, None, 29)          0         
=================================================================
Total params: 1,572,429
Trainable params: 1,570,429
Non-trainable params: 2,000
_________________________________________________________________
None
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<p>Please execute the code cell below to train the neural network you specified in <code>input_to_softmax</code>.  After the model has finished training, the model is <a href="https://keras.io/getting-started/faq/#how-can-i-save-a-keras-model">saved</a> in the HDF5 file <code>model_end.h5</code>.  The loss history is <a href="https://wiki.python.org/moin/UsingPickle">saved</a> in <code>model_end.pickle</code>.  You are welcome to tweak any of the optional parameters while calling the <code>train_model</code> function, but this is not required.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_model</span><span class="p">(</span><span class="n">input_to_softmax</span><span class="o">=</span><span class="n">model_end</span><span class="p">,</span> 
            <span class="n">pickle_path</span><span class="o">=</span><span class="s1">&#39;model_end.pickle&#39;</span><span class="p">,</span> 
            <span class="n">save_model_path</span><span class="o">=</span><span class="s1">&#39;model_end.h5&#39;</span><span class="p">,</span> 
            <span class="n">spectrogram</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span> <span class="c1"># change to False if you would like to use MFCC features</span>
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<pre>Epoch 1/20
106/106 [==============================] - 350s - loss: 245.1420 - val_loss: 222.5966
Epoch 2/20
106/106 [==============================] - 355s - loss: 201.6635 - val_loss: 181.3138
Epoch 3/20
106/106 [==============================] - 352s - loss: 169.4292 - val_loss: 148.5373
Epoch 4/20
106/106 [==============================] - 353s - loss: 151.4993 - val_loss: 137.8633
Epoch 5/20
106/106 [==============================] - 353s - loss: 138.8266 - val_loss: 129.1121
Epoch 6/20
106/106 [==============================] - 351s - loss: 130.1329 - val_loss: 122.5836
Epoch 7/20
106/106 [==============================] - 352s - loss: 123.0556 - val_loss: 122.1295
Epoch 8/20
106/106 [==============================] - 353s - loss: 117.1297 - val_loss: 115.6572
Epoch 9/20
106/106 [==============================] - 354s - loss: 111.9423 - val_loss: 112.8803
Epoch 10/20
106/106 [==============================] - 356s - loss: 107.5712 - val_loss: 109.7933
Epoch 11/20
106/106 [==============================] - 355s - loss: 103.7297 - val_loss: 107.7206
Epoch 12/20
106/106 [==============================] - 354s - loss: 100.4962 - val_loss: 107.5594
Epoch 13/20
106/106 [==============================] - 353s - loss: 97.2491 - val_loss: 104.7682
Epoch 14/20
106/106 [==============================] - 355s - loss: 93.8398 - val_loss: 104.5081
Epoch 15/20
106/106 [==============================] - 353s - loss: 90.9383 - val_loss: 104.9926
Epoch 16/20
106/106 [==============================] - 356s - loss: 88.7684 - val_loss: 103.1174
Epoch 17/20
106/106 [==============================] - 356s - loss: 86.8071 - val_loss: 100.8130
Epoch 18/20
106/106 [==============================] - 354s - loss: 83.9331 - val_loss: 101.0065
Epoch 19/20
106/106 [==============================] - 353s - loss: 82.2601 - val_loss: 100.5183
Epoch 20/20
106/106 [==============================] - 352s - loss: 80.1738 - val_loss: 100.3393
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<p><strong>Question 2:</strong> Describe your final model architecture and your reasoning at each step.</p>
<p><strong>Answer:</strong>
The model I built consists of a mixture of the previous models. The Convolutional layer in model_2 proved that it can significantly reduce the loss and it was also the most efficient, around 60s per epoch. This is the first layer of the model.</p>
<p>The second thing I learned from the previous models is that although unidirectional GRU's performed better than SimpleRNN's, they still had a problem with both loss and overfitting. The use of bidirectional RNN's reduced the loss. They still had a slight overfitting problem around the final epochs. For those reasons, our final model has two bidirectional RNN hidden layers after the convolutional layer. Each of those layers is followed by batch normalization to reduce training time.</p>
<p>The final layer is a time distributed dense layer, to find the more complex patterns.</p>
<p>The result is a promising start. The loss is reduced, and more importantly, the gap between training and validation is reduced which means that our model was successful in reducing the overfitting.</p>

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<h2 id="STEP-3:-Obtain-Predictions">STEP 3: Obtain Predictions<a class="anchor-link" href="#STEP-3:-Obtain-Predictions">&#182;</a></h2><p>We have written a function for you to decode the predictions of your acoustic model.  To use the function, please execute the code cell below.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">data_generator</span> <span class="k">import</span> <span class="n">AudioGenerator</span>
<span class="kn">from</span> <span class="nn">keras</span> <span class="k">import</span> <span class="n">backend</span> <span class="k">as</span> <span class="n">K</span>
<span class="kn">from</span> <span class="nn">utils</span> <span class="k">import</span> <span class="n">int_sequence_to_text</span>
<span class="kn">from</span> <span class="nn">IPython.display</span> <span class="k">import</span> <span class="n">Audio</span>

<span class="k">def</span> <span class="nf">get_predictions</span><span class="p">(</span><span class="n">index</span><span class="p">,</span> <span class="n">partition</span><span class="p">,</span> <span class="n">input_to_softmax</span><span class="p">,</span> <span class="n">model_path</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot; Print a model&#39;s decoded predictions</span>
<span class="sd">    Params:</span>
<span class="sd">        index (int): The example you would like to visualize</span>
<span class="sd">        partition (str): One of &#39;train&#39; or &#39;validation&#39;</span>
<span class="sd">        input_to_softmax (Model): The acoustic model</span>
<span class="sd">        model_path (str): Path to saved acoustic model&#39;s weights</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1"># load the train and test data</span>
    <span class="n">data_gen</span> <span class="o">=</span> <span class="n">AudioGenerator</span><span class="p">()</span>
    <span class="n">data_gen</span><span class="o">.</span><span class="n">load_train_data</span><span class="p">()</span>
    <span class="n">data_gen</span><span class="o">.</span><span class="n">load_validation_data</span><span class="p">()</span>
    
    <span class="c1"># obtain the true transcription and the audio features </span>
    <span class="k">if</span> <span class="n">partition</span> <span class="o">==</span> <span class="s1">&#39;validation&#39;</span><span class="p">:</span>
        <span class="n">transcr</span> <span class="o">=</span> <span class="n">data_gen</span><span class="o">.</span><span class="n">valid_texts</span><span class="p">[</span><span class="n">index</span><span class="p">]</span>
        <span class="n">audio_path</span> <span class="o">=</span> <span class="n">data_gen</span><span class="o">.</span><span class="n">valid_audio_paths</span><span class="p">[</span><span class="n">index</span><span class="p">]</span>
        <span class="n">data_point</span> <span class="o">=</span> <span class="n">data_gen</span><span class="o">.</span><span class="n">normalize</span><span class="p">(</span><span class="n">data_gen</span><span class="o">.</span><span class="n">featurize</span><span class="p">(</span><span class="n">audio_path</span><span class="p">))</span>
    <span class="k">elif</span> <span class="n">partition</span> <span class="o">==</span> <span class="s1">&#39;train&#39;</span><span class="p">:</span>
        <span class="n">transcr</span> <span class="o">=</span> <span class="n">data_gen</span><span class="o">.</span><span class="n">train_texts</span><span class="p">[</span><span class="n">index</span><span class="p">]</span>
        <span class="n">audio_path</span> <span class="o">=</span> <span class="n">data_gen</span><span class="o">.</span><span class="n">train_audio_paths</span><span class="p">[</span><span class="n">index</span><span class="p">]</span>
        <span class="n">data_point</span> <span class="o">=</span> <span class="n">data_gen</span><span class="o">.</span><span class="n">normalize</span><span class="p">(</span><span class="n">data_gen</span><span class="o">.</span><span class="n">featurize</span><span class="p">(</span><span class="n">audio_path</span><span class="p">))</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;Invalid partition!  Must be &quot;train&quot; or &quot;validation&quot;&#39;</span><span class="p">)</span>
        
    <span class="c1"># obtain and decode the acoustic model&#39;s predictions</span>
    <span class="n">input_to_softmax</span><span class="o">.</span><span class="n">load_weights</span><span class="p">(</span><span class="n">model_path</span><span class="p">)</span>
    <span class="n">prediction</span> <span class="o">=</span> <span class="n">input_to_softmax</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">expand_dims</span><span class="p">(</span><span class="n">data_point</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">))</span>
    <span class="n">output_length</span> <span class="o">=</span> <span class="p">[</span><span class="n">input_to_softmax</span><span class="o">.</span><span class="n">output_length</span><span class="p">(</span><span class="n">data_point</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="n">pred_ints</span> <span class="o">=</span> <span class="p">(</span><span class="n">K</span><span class="o">.</span><span class="n">eval</span><span class="p">(</span><span class="n">K</span><span class="o">.</span><span class="n">ctc_decode</span><span class="p">(</span>
                <span class="n">prediction</span><span class="p">,</span> <span class="n">output_length</span><span class="p">)[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">])</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">flatten</span><span class="p">()</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
    
    <span class="c1"># play the audio file, and display the true and predicted transcriptions</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;-&#39;</span><span class="o">*</span><span class="mi">80</span><span class="p">)</span>
    <span class="n">Audio</span><span class="p">(</span><span class="n">audio_path</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;True transcription:</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="n">transcr</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;-&#39;</span><span class="o">*</span><span class="mi">80</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Predicted transcription:</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span> <span class="o">+</span> <span class="s1">&#39;&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">int_sequence_to_text</span><span class="p">(</span><span class="n">pred_ints</span><span class="p">)))</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;-&#39;</span><span class="o">*</span><span class="mi">80</span><span class="p">)</span>
</pre></div>

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<p>Use the code cell below to obtain the transcription predicted by your final model for the first example in the training dataset.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">get_predictions</span><span class="p">(</span><span class="n">index</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> 
                <span class="n">partition</span><span class="o">=</span><span class="s1">&#39;train&#39;</span><span class="p">,</span>
                <span class="n">input_to_softmax</span><span class="o">=</span><span class="n">final_model</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="mi">161</span><span class="p">,</span> <span class="c1"># change to 13 if you would like to use MFCC features</span>
                        <span class="n">filters</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
                        <span class="n">kernel_size</span><span class="o">=</span><span class="mi">11</span><span class="p">,</span> 
                        <span class="n">conv_stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
                        <span class="n">conv_border_mode</span><span class="o">=</span><span class="s1">&#39;valid&#39;</span><span class="p">,</span>
                        <span class="n">units</span><span class="o">=</span><span class="mi">200</span><span class="p">),</span> 
                <span class="n">model_path</span><span class="o">=</span><span class="s1">&#39;./results/model_end.h5&#39;</span><span class="p">)</span>
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<pre>/home/ubuntu/AIND-VUI-Capstone/sample_models.py:156: UserWarning: Update your `GRU` call to the Keras 2 API: `GRU(200, dropout=0.2, activation=&#34;relu&#34;, implementation=2, recurrent_dropout=0.2, return_sequences=True, name=&#34;rnn&#34;)`
  return_sequences=True, implementation=2, name=&#39;rnn&#39;, dropout_W=0.5, dropout_U=0.5),
/home/ubuntu/AIND-VUI-Capstone/sample_models.py:160: UserWarning: Update your `GRU` call to the Keras 2 API: `GRU(200, dropout=0.2, activation=&#34;relu&#34;, implementation=2, recurrent_dropout=0.2, return_sequences=True, name=&#34;rnn2&#34;)`
  return_sequences=True, implementation=2, name=&#39;rnn2&#39;, dropout_W=0.5, dropout_U=0.5),
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
the_input (InputLayer)       (None, None, 161)         0         
_________________________________________________________________
conv1d (Conv1D)              (None, None, 200)         354400    
_________________________________________________________________
bn_conv_1d (BatchNormalizati (None, None, 200)         800       
_________________________________________________________________
bidirectional_16 (Bidirectio (None, None, 400)         481200    
_________________________________________________________________
bn_birnn (BatchNormalization (None, None, 400)         1600      
_________________________________________________________________
bidirectional_17 (Bidirectio (None, None, 400)         721200    
_________________________________________________________________
bn_birnn2 (BatchNormalizatio (None, None, 400)         1600      
_________________________________________________________________
time_distributed_10 (TimeDis (None, None, 29)          11629     
_________________________________________________________________
softmax (Activation)         (None, None, 29)          0         
=================================================================
Total params: 1,572,429
Trainable params: 1,570,429
Non-trainable params: 2,000
_________________________________________________________________
None
--------------------------------------------------------------------------------
True transcription:

the last two days of the voyage bartley found almost intolerable
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Predicted transcription:

the lastro das of the vwoge bartly fond omost in talerble
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<p>Use the next code cell to visualize the model's prediction for the first example in the validation dataset.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">get_predictions</span><span class="p">(</span><span class="n">index</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> 
                <span class="n">partition</span><span class="o">=</span><span class="s1">&#39;validation&#39;</span><span class="p">,</span>
                <span class="n">input_to_softmax</span><span class="o">=</span><span class="n">final_model</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="mi">161</span><span class="p">,</span> <span class="c1"># change to 13 if you would like to use MFCC features</span>
                        <span class="n">filters</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
                        <span class="n">kernel_size</span><span class="o">=</span><span class="mi">11</span><span class="p">,</span> 
                        <span class="n">conv_stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span>
                        <span class="n">conv_border_mode</span><span class="o">=</span><span class="s1">&#39;valid&#39;</span><span class="p">,</span>
                        <span class="n">units</span><span class="o">=</span><span class="mi">200</span><span class="p">),</span> 
                <span class="n">model_path</span><span class="o">=</span><span class="s1">&#39;./results/model_end.h5&#39;</span><span class="p">)</span>
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<pre>/home/ubuntu/AIND-VUI-Capstone/sample_models.py:156: UserWarning: Update your `GRU` call to the Keras 2 API: `GRU(200, dropout=0.2, activation=&#34;relu&#34;, implementation=2, recurrent_dropout=0.2, return_sequences=True, name=&#34;rnn&#34;)`
  return_sequences=True, implementation=2, name=&#39;rnn&#39;, dropout_W=0.5, dropout_U=0.5),
/home/ubuntu/AIND-VUI-Capstone/sample_models.py:160: UserWarning: Update your `GRU` call to the Keras 2 API: `GRU(200, dropout=0.2, activation=&#34;relu&#34;, implementation=2, recurrent_dropout=0.2, return_sequences=True, name=&#34;rnn2&#34;)`
  return_sequences=True, implementation=2, name=&#39;rnn2&#39;, dropout_W=0.5, dropout_U=0.5),
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<pre>_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
the_input (InputLayer)       (None, None, 161)         0         
_________________________________________________________________
conv1d (Conv1D)              (None, None, 200)         354400    
_________________________________________________________________
bn_conv_1d (BatchNormalizati (None, None, 200)         800       
_________________________________________________________________
bidirectional_18 (Bidirectio (None, None, 400)         481200    
_________________________________________________________________
bn_birnn (BatchNormalization (None, None, 400)         1600      
_________________________________________________________________
bidirectional_19 (Bidirectio (None, None, 400)         721200    
_________________________________________________________________
bn_birnn2 (BatchNormalizatio (None, None, 400)         1600      
_________________________________________________________________
time_distributed_11 (TimeDis (None, None, 29)          11629     
_________________________________________________________________
softmax (Activation)         (None, None, 29)          0         
=================================================================
Total params: 1,572,429
Trainable params: 1,570,429
Non-trainable params: 2,000
_________________________________________________________________
None
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True transcription:

out in the woods stood a nice little fir tree
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Predicted transcription:

ote no wadstot an mi se letal fircry
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<p>One standard way to improve the results of the decoder is to incorporate a language model.  We won't pursue this in the notebook, but you are welcome to do so as an <em>optional extension</em>.</p>
<p>If you are interested in creating models that provide improved transcriptions, you are encouraged to download <a href="http://www.openslr.org/12/">more data</a> and train bigger, deeper models.  But beware - the model will likely take a long while to train.  For instance, training this <a href="https://arxiv.org/pdf/1512.02595v1.pdf">state-of-the-art</a> model would take 3-6 weeks on a single GPU!</p>

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