dlnd_face_generation.html

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<title>dlnd_face_generation</title>

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

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

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

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

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

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

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<style type="text/css">
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<h1 id="Face-Generation">Face Generation<a class="anchor-link" href="#Face-Generation">&#182;</a></h1><p>In this project, you'll define and train a DCGAN on a dataset of faces. Your goal is to get a generator network to generate <em>new</em> images of faces that look as realistic as possible!</p>
<p>The project will be broken down into a series of tasks from <strong>loading in data to defining and training adversarial networks</strong>. At the end of the notebook, you'll be able to visualize the results of your trained Generator to see how it performs; your generated samples should look like fairly realistic faces with small amounts of noise.</p>
<h3 id="Get-the-Data">Get the Data<a class="anchor-link" href="#Get-the-Data">&#182;</a></h3><p>You'll be using the <a href="http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html">CelebFaces Attributes Dataset (CelebA)</a> to train your adversarial networks.</p>
<p>This dataset is more complex than the number datasets (like MNIST or SVHN) you've been working with, and so, you should prepare to define deeper networks and train them for a longer time to get good results. It is suggested that you utilize a GPU for training.</p>
<h3 id="Pre-processed-Data">Pre-processed Data<a class="anchor-link" href="#Pre-processed-Data">&#182;</a></h3><p>Since the project's main focus is on building the GANs, we've done <em>some</em> of the pre-processing for you. Each of the CelebA images has been cropped to remove parts of the image that don't include a face, then resized down to 64x64x3 NumPy images. Some sample data is show below.</p>
<p><img src='assets/processed_face_data.png' width=60% /></p>
<blockquote><p>If you are working locally, you can download this data <a href="https://s3.amazonaws.com/video.udacity-data.com/topher/2018/November/5be7eb6f_processed-celeba-small/processed-celeba-small.zip">by clicking here</a></p>
</blockquote>
<p>This is a zip file that you'll need to extract in the home directory of this notebook for further loading and processing. After extracting the data, you should be left with a directory of data <code>processed_celeba_small/</code></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># can comment out after executing</span>
<span class="o">!</span>unzip processed_celeba_small.zip
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<pre>Archive:  processed_celeba_small.zip
replace processed_celeba_small/.DS_Store? [y]es, [n]o, [A]ll, [N]one, [r]ename: ^C
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">data_dir</span> <span class="o">=</span> <span class="s1">&#39;processed_celeba_small/&#39;</span>

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<span class="kn">import</span> <span class="nn">pickle</span> <span class="k">as</span> <span class="nn">pkl</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">problem_unittests</span> <span class="k">as</span> <span class="nn">tests</span>
<span class="c1">#import helper</span>

<span class="o">%</span><span class="k">matplotlib</span> inline
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<h2 id="Visualize-the-CelebA-Data">Visualize the CelebA Data<a class="anchor-link" href="#Visualize-the-CelebA-Data">&#182;</a></h2><p>The <a href="http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html">CelebA</a> dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations, you'll only need the images. Note that these are color images with <a href="https://en.wikipedia.org/wiki/Channel_(digital_image">3 color channels (RGB)</a>#RGB_Images) each.</p>
<h3 id="Pre-process-and-Load-the-Data">Pre-process and Load the Data<a class="anchor-link" href="#Pre-process-and-Load-the-Data">&#182;</a></h3><p>Since the project's main focus is on building the GANs, we've done <em>some</em> of the pre-processing for you. Each of the CelebA images has been cropped to remove parts of the image that don't include a face, then resized down to 64x64x3 NumPy images. This <em>pre-processed</em> dataset is a smaller subset of the very large CelebA data.</p>
<blockquote><p>There are a few other steps that you'll need to <strong>transform</strong> this data and create a <strong>DataLoader</strong>.</p>
</blockquote>
<h4 id="Exercise:-Complete-the-following-get_dataloader-function,-such-that-it-satisfies-these-requirements:">Exercise: Complete the following <code>get_dataloader</code> function, such that it satisfies these requirements:<a class="anchor-link" href="#Exercise:-Complete-the-following-get_dataloader-function,-such-that-it-satisfies-these-requirements:">&#182;</a></h4><ul>
<li>Your images should be square, Tensor images of size <code>image_size x image_size</code> in the x and y dimension.</li>
<li>Your function should return a DataLoader that shuffles and batches these Tensor images.</li>
</ul>
<h4 id="ImageFolder">ImageFolder<a class="anchor-link" href="#ImageFolder">&#182;</a></h4><p>To create a dataset given a directory of images, it's recommended that you use PyTorch's <a href="https://pytorch.org/docs/stable/torchvision/datasets.html#imagefolder">ImageFolder</a> wrapper, with a root directory <code>processed_celeba_small/</code> and data transformation passed in.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># necessary imports</span>
<span class="kn">import</span> <span class="nn">os</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">from</span> <span class="nn">torchvision</span> <span class="k">import</span> <span class="n">datasets</span>
<span class="kn">from</span> <span class="nn">torchvision</span> <span class="k">import</span> <span class="n">transforms</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">get_dataloader</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">image_size</span><span class="p">,</span> <span class="n">data_dir</span><span class="o">=</span><span class="s1">&#39;processed_celeba_small/&#39;</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Batch the neural network data using DataLoader</span>
<span class="sd">    :param batch_size: The size of each batch; the number of images in a batch</span>
<span class="sd">    :param img_size: The square size of the image data (x, y)</span>
<span class="sd">    :param data_dir: Directory where image data is located</span>
<span class="sd">    :return: DataLoader with batched data</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1"># Resizeing images and transforming to tensors</span>
    <span class="n">transform</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span>
        <span class="n">transforms</span><span class="o">.</span><span class="n">Resize</span><span class="p">(</span><span class="n">image_size</span><span class="p">),</span>
        <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">()</span>
    <span class="p">])</span>    
    
    <span class="n">dataset</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">data_dir</span><span class="p">,</span> <span class="n">transform</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">DataLoader</span><span class="p">(</span><span class="n">dataset</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<h2 id="Create-a-DataLoader">Create a DataLoader<a class="anchor-link" href="#Create-a-DataLoader">&#182;</a></h2><h4 id="Exercise:-Create-a-DataLoader-celeba_train_loader-with-appropriate-hyperparameters.">Exercise: Create a DataLoader <code>celeba_train_loader</code> with appropriate hyperparameters.<a class="anchor-link" href="#Exercise:-Create-a-DataLoader-celeba_train_loader-with-appropriate-hyperparameters.">&#182;</a></h4><p>Call the above function and create a dataloader to view images.</p>
<ul>
<li>You can decide on any reasonable <code>batch_size</code> parameter</li>
<li>Your <code>image_size</code> <strong>must be</strong> <code>32</code>. Resizing the data to a smaller size will make for faster training, while still creating convincing images of faces!</li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Define function hyperparameters</span>
<span class="n">batch_size</span> <span class="o">=</span> <span class="mi">256</span>
<span class="n">img_size</span> <span class="o">=</span> <span class="mi">32</span>

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<span class="c1"># Call your function and get a dataloader</span>
<span class="n">celeba_train_loader</span> <span class="o">=</span> <span class="n">get_dataloader</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">img_size</span><span class="p">)</span>
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<p>Next, you can view some images! You should seen square images of somewhat-centered faces.</p>
<p>Note: You'll need to convert the Tensor images into a NumPy type and transpose the dimensions to correctly display an image, suggested <code>imshow</code> code is below, but it may not be perfect.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># helper display function</span>
<span class="k">def</span> <span class="nf">imshow</span><span class="p">(</span><span class="n">img</span><span class="p">):</span>
    <span class="n">npimg</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">npimg</span><span class="p">,</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">)))</span>

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<span class="c1"># obtain one batch of training images</span>
<span class="n">dataiter</span> <span class="o">=</span> <span class="nb">iter</span><span class="p">(</span><span class="n">celeba_train_loader</span><span class="p">)</span>
<span class="n">images</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">dataiter</span><span class="o">.</span><span class="n">next</span><span class="p">()</span> <span class="c1"># _ for no labels</span>

<span class="c1"># plot the images in the batch, along with the corresponding labels</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">20</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
<span class="n">plot_size</span><span class="o">=</span><span class="mi">20</span>
<span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">plot_size</span><span class="p">):</span>
    <span class="n">ax</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">2</span><span class="p">,</span> <span class="n">plot_size</span><span class="o">/</span><span class="mi">2</span><span class="p">,</span> <span class="n">idx</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">xticks</span><span class="o">=</span><span class="p">[],</span> <span class="n">yticks</span><span class="o">=</span><span class="p">[])</span>
    <span class="n">imshow</span><span class="p">(</span><span class="n">images</span><span class="p">[</span><span class="n">idx</span><span class="p">])</span>
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<h4 id="Exercise:-Pre-process-your-image-data-and-scale-it-to-a-pixel-range-of--1-to-1">Exercise: Pre-process your image data and scale it to a pixel range of -1 to 1<a class="anchor-link" href="#Exercise:-Pre-process-your-image-data-and-scale-it-to-a-pixel-range-of--1-to-1">&#182;</a></h4><p>You need to do a bit of pre-processing; you know that the output of a <code>tanh</code> activated generator will contain pixel values in a range from -1 to 1, and so, we need to rescale our training images to a range of -1 to 1. (Right now, they are in a range from 0-1.)</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Complete the scale function</span>
<span class="k">def</span> <span class="nf">scale</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">feature_range</span><span class="o">=</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">)):</span>
    <span class="sd">&#39;&#39;&#39; Scale takes in an image x and returns that image, scaled</span>
<span class="sd">       with a feature_range of pixel values from -1 to 1. </span>
<span class="sd">       This function assumes that the input x is already scaled from 0-1.&#39;&#39;&#39;</span>
    <span class="c1"># assume x is scaled to (0, 1)</span>
    <span class="c1"># scale to feature_range and return scaled x</span>
    
    <span class="k">return</span> <span class="n">x</span> <span class="o">*</span> <span class="p">(</span><span class="n">feature_range</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">feature_range</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">+</span> <span class="n">feature_range</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
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<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="c1"># check scaled range</span>
<span class="c1"># should be close to -1 to 1</span>
<span class="n">img</span> <span class="o">=</span> <span class="n">images</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="n">scaled_img</span> <span class="o">=</span> <span class="n">scale</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Min: &#39;</span><span class="p">,</span> <span class="n">scaled_img</span><span class="o">.</span><span class="n">min</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Max: &#39;</span><span class="p">,</span> <span class="n">scaled_img</span><span class="o">.</span><span class="n">max</span><span class="p">())</span>
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<pre>Min:  tensor(-0.7804)
Max:  tensor(1.)
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<h1 id="Define-the-Model">Define the Model<a class="anchor-link" href="#Define-the-Model">&#182;</a></h1><p>A GAN is comprised of two adversarial networks, a discriminator and a generator.</p>
<h2 id="Discriminator">Discriminator<a class="anchor-link" href="#Discriminator">&#182;</a></h2><p>Your first task will be to define the discriminator. This is a convolutional classifier like you've built before, only without any maxpooling layers. To deal with this complex data, it's suggested you use a deep network with <strong>normalization</strong>. You are also allowed to create any helper functions that may be useful.</p>
<h4 id="Exercise:-Complete-the-Discriminator-class">Exercise: Complete the Discriminator class<a class="anchor-link" href="#Exercise:-Complete-the-Discriminator-class">&#182;</a></h4><ul>
<li>The inputs to the discriminator are 32x32x3 tensor images</li>
<li>The output should be a single value that will indicate whether a given image is real or fake</li>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">torch.nn</span> <span class="k">as</span> <span class="nn">nn</span>
<span class="kn">import</span> <span class="nn">torch.nn.functional</span> <span class="k">as</span> <span class="nn">F</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Adding in helper functions from course work </span>

<span class="k">def</span> <span class="nf">conv</span><span class="p">(</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;Creates a convolutional layer, with optional batch normalization.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">conv_layer</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Conv2d</span><span class="p">(</span><span class="n">in_channels</span><span class="o">=</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="o">=</span><span class="n">out_channels</span><span class="p">,</span> 
                           <span class="n">kernel_size</span><span class="o">=</span><span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="n">stride</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="n">padding</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
    
    <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">conv_layer</span><span class="p">)</span>

    <span class="k">if</span> <span class="n">batch_norm</span><span class="p">:</span>
        <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">BatchNorm2d</span><span class="p">(</span><span class="n">out_channels</span><span class="p">))</span>
    <span class="k">return</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="o">*</span><span class="n">layers</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">class</span> <span class="nc">Discriminator</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">=</span><span class="mi">64</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Initialize the Discriminator Module</span>
<span class="sd">        :param conv_dim: The depth of the first convolutional layer</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">Discriminator</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>

        <span class="c1"># We will make a 5 layer descrimnator </span>
        <span class="c1"># It will go from a input depts of 3 -&gt; conv_dim*8</span>
        <span class="c1"># Using a kernel size of 4, stride of 2, and padding of 1</span>

        
        <span class="c1"># inputs: 3*32*32 </span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv1</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span> <span class="c1"># No Batch norm in the first layer</span>
        <span class="c1"># state size. (conv_dim) x 16 x 16</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv2</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="n">conv_dim</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
        <span class="c1"># state size. (conv_dim*2) x 8 x 8</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv3</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
        <span class="c1"># state size. (conv_dim*4) x 4 x 4</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv4</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">8</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
        <span class="c1"># state size. (conv_dim*8) x 2 x 2</span>
        
        <span class="c1"># The final linear layer, used for classification, no batch norn</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">linear_dim</span> <span class="o">=</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">8</span><span class="o">*</span><span class="mi">2</span><span class="o">*</span><span class="mi">2</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">fc</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">8</span><span class="o">*</span><span class="mi">2</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
        
        
    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Forward propagation of the neural network</span>
<span class="sd">        :param x: The input to the neural network     </span>
<span class="sd">        :return: Discriminator logits; the output of the neural network</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="c1"># We will apply relu on all layers except the last</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv1</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv2</span><span class="p">(</span><span class="n">out</span><span class="p">))</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv3</span><span class="p">(</span><span class="n">out</span><span class="p">))</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv4</span><span class="p">(</span><span class="n">out</span><span class="p">))</span>
        <span class="c1"># Flatten tensor </span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">linear_dim</span><span class="p">)</span>
        <span class="c1"># final classification layer</span>
        <span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>
        
        <span class="k">return</span> <span class="n">out</span>


<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_discriminator</span><span class="p">(</span><span class="n">Discriminator</span><span class="p">)</span>
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<h2 id="Generator">Generator<a class="anchor-link" href="#Generator">&#182;</a></h2><p>The generator should upsample an input and generate a <em>new</em> image of the same size as our training data <code>32x32x3</code>. This should be mostly transpose convolutional layers with normalization applied to the outputs.</p>
<h4 id="Exercise:-Complete-the-Generator-class">Exercise: Complete the Generator class<a class="anchor-link" href="#Exercise:-Complete-the-Generator-class">&#182;</a></h4><ul>
<li>The inputs to the generator are vectors of some length <code>z_size</code></li>
<li>The output should be a image of shape <code>32x32x3</code></li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># helper deconv function</span>
<span class="k">def</span> <span class="nf">deconv</span><span class="p">(</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;Creates a transpose convolutional layer, with optional batch normalization.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="c1"># append transpose conv layer</span>
    <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">ConvTranspose2d</span><span class="p">(</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">padding</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">False</span><span class="p">))</span>
    <span class="c1"># optional batch norm layer</span>
    <span class="k">if</span> <span class="n">batch_norm</span><span class="p">:</span>
        <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">BatchNorm2d</span><span class="p">(</span><span class="n">out_channels</span><span class="p">))</span>
    <span class="k">return</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="o">*</span><span class="n">layers</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">class</span> <span class="nc">Generator</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
    
    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Initialize the Generator Module</span>
<span class="sd">        :param z_size: The length of the input latent vector, z</span>
<span class="sd">        :param conv_dim: The depth of the inputs to the *last* transpose convolutional layer</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">Generator</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span> <span class="o">=</span> <span class="n">conv_dim</span>

        <span class="c1"># To generate the image will will first pass the input through a linear layer</span>
        <span class="c1"># this layer will scale up the input to conv_dim*8*2*2 (seen as the reverse of the descriminator a 2x2 image with</span>
        <span class="c1"># a depth of conv_dim*8</span>
        <span class="c1"># After that we will move through 4 transpose convolutions scaling up to 32*32*3</span>
        <span class="c1"># We will batch norm every transpose convolution except the last </span>
        
        <span class="bp">self</span><span class="o">.</span><span class="n">fc</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">8</span><span class="o">*</span><span class="mi">2</span><span class="o">*</span><span class="mi">2</span><span class="p">)</span>
        
        <span class="bp">self</span><span class="o">.</span><span class="n">tconv1</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">8</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">tconv2</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">tconv3</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">tconv4</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="c1"># final layer finishing w/ depth of 3 (RGB)</span>

        
    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Forward propagation of the neural network</span>
<span class="sd">        :param x: The input to the neural network     </span>
<span class="sd">        :return: A 32x32x3 Tensor image as output</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="c1"># Scale up features with linear layer</span>
        <span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
        <span class="c1"># reshame tensors to be correct dimentions: [batch_size, conv_dim*8, 2, 2]</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">8</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
        
        <span class="c1"># Passing through first 3 transpose conv and applying </span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tconv1</span><span class="p">(</span><span class="n">out</span><span class="p">))</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tconv2</span><span class="p">(</span><span class="n">out</span><span class="p">))</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tconv3</span><span class="p">(</span><span class="n">out</span><span class="p">))</span>
        
        <span class="c1"># final layer w/out bacth norm &amp; with tanh </span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tanh</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">tconv4</span><span class="p">(</span><span class="n">out</span><span class="p">))</span>

        
        <span class="k">return</span> <span class="n">out</span> 

<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_generator</span><span class="p">(</span><span class="n">Generator</span><span class="p">)</span>
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<h2 id="Initialize-the-weights-of-your-networks">Initialize the weights of your networks<a class="anchor-link" href="#Initialize-the-weights-of-your-networks">&#182;</a></h2><p>To help your models converge, you should initialize the weights of the convolutional and linear layers in your model. From reading the <a href="https://arxiv.org/pdf/1511.06434.pdf">original DCGAN paper</a>, they say:</p>
<blockquote><p>All weights were initialized from a zero-centered Normal distribution with standard deviation 0.02.</p>
</blockquote>
<p>So, your next task will be to define a weight initialization function that does just this!</p>
<p>You can refer back to the lesson on weight initialization or even consult existing model code, such as that from <a href="https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/blob/master/models/networks.py">the <code>networks.py</code> file in CycleGAN Github repository</a> to help you complete this function.</p>
<h4 id="Exercise:-Complete-the-weight-initialization-function">Exercise: Complete the weight initialization function<a class="anchor-link" href="#Exercise:-Complete-the-weight-initialization-function">&#182;</a></h4><ul>
<li>This should initialize only <strong>convolutional</strong> and <strong>linear</strong> layers</li>
<li>Initialize the weights to a normal distribution, centered around 0, with a standard deviation of 0.02.</li>
<li>The bias terms, if they exist, may be left alone or set to 0.</li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">weights_init_normal</span><span class="p">(</span><span class="n">m</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Applies initial weights to certain layers in a model .</span>
<span class="sd">    The weights are taken from a normal distribution </span>
<span class="sd">    with mean = 0, std dev = 0.02.</span>
<span class="sd">    :param m: A module or layer in a network    </span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1"># classname will be something like:</span>
    <span class="c1"># `Conv`, `BatchNorm2d`, `Linear`, etc.</span>
    <span class="n">classname</span> <span class="o">=</span> <span class="n">m</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span>
    <span class="k">if</span> <span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s2">&quot;Conv&quot;</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span> <span class="ow">or</span> <span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;Linear&#39;</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="p">:</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">normal_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">)</span>
    <span class="k">elif</span> <span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s2">&quot;BatchNorm2d&quot;</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="p">:</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">normal_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">)</span>
        <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">constant_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">)</span>
    
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<h2 id="Build-complete-network">Build complete network<a class="anchor-link" href="#Build-complete-network">&#182;</a></h2><p>Define your models' hyperparameters and instantiate the discriminator and generator from the classes defined above. Make sure you've passed in the correct input arguments.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">build_network</span><span class="p">(</span><span class="n">d_conv_dim</span><span class="p">,</span> <span class="n">g_conv_dim</span><span class="p">,</span> <span class="n">z_size</span><span class="p">):</span>
    <span class="c1"># define discriminator and generator</span>
    <span class="n">D</span> <span class="o">=</span> <span class="n">Discriminator</span><span class="p">(</span><span class="n">d_conv_dim</span><span class="p">)</span>
    <span class="n">G</span> <span class="o">=</span> <span class="n">Generator</span><span class="p">(</span><span class="n">z_size</span><span class="o">=</span><span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">=</span><span class="n">g_conv_dim</span><span class="p">)</span>

    <span class="c1"># initialize model weights</span>
    <span class="n">D</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">weights_init_normal</span><span class="p">)</span>
    <span class="n">G</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">weights_init_normal</span><span class="p">)</span>

    <span class="nb">print</span><span class="p">(</span><span class="n">D</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">()</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">G</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">D</span><span class="p">,</span> <span class="n">G</span>
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<h4 id="Exercise:-Define-model-hyperparameters">Exercise: Define model hyperparameters<a class="anchor-link" href="#Exercise:-Define-model-hyperparameters">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Define model hyperparams</span>
<span class="n">d_conv_dim</span> <span class="o">=</span> <span class="mi">64</span> 
<span class="n">g_conv_dim</span> <span class="o">=</span> <span class="mi">64</span>
<span class="n">z_size</span> <span class="o">=</span> <span class="mi">100</span>

<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">D</span><span class="p">,</span> <span class="n">G</span> <span class="o">=</span> <span class="n">build_network</span><span class="p">(</span><span class="n">d_conv_dim</span><span class="p">,</span> <span class="n">g_conv_dim</span><span class="p">,</span> <span class="n">z_size</span><span class="p">)</span>
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<pre>Discriminator(
  (conv1): Sequential(
    (0): Conv2d(3, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
  )
  (conv2): Sequential(
    (0): Conv2d(64, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (conv3): Sequential(
    (0): Conv2d(128, 256, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (conv4): Sequential(
    (0): Conv2d(256, 512, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (fc): Linear(in_features=2048, out_features=1, bias=True)
)

Generator(
  (fc): Linear(in_features=100, out_features=2048, bias=True)
  (tconv1): Sequential(
    (0): ConvTranspose2d(512, 256, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (tconv2): Sequential(
    (0): ConvTranspose2d(256, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (tconv3): Sequential(
    (0): ConvTranspose2d(128, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (tconv4): Sequential(
    (0): ConvTranspose2d(64, 3, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
  )
)
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<h3 id="Training-on-GPU">Training on GPU<a class="anchor-link" href="#Training-on-GPU">&#182;</a></h3><p>Check if you can train on GPU. Here, we'll set this as a boolean variable <code>train_on_gpu</code>. Later, you'll be responsible for making sure that</p>
<blockquote><ul>
<li>Models,</li>
<li>Model inputs, and</li>
<li>Loss function arguments</li>
</ul>
</blockquote>
<p>Are moved to GPU, where appropriate.</p>

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<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">torch</span>

<span class="c1"># Check for a GPU</span>
<span class="n">train_on_gpu</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">is_available</span><span class="p">()</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">train_on_gpu</span><span class="p">:</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;No GPU found. Please use a GPU to train your neural network.&#39;</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Training on GPU!&#39;</span><span class="p">)</span>
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<pre>Training on GPU!
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<h2 id="Discriminator-and-Generator-Losses">Discriminator and Generator Losses<a class="anchor-link" href="#Discriminator-and-Generator-Losses">&#182;</a></h2><p>Now we need to calculate the losses for both types of adversarial networks.</p>
<h3 id="Discriminator-Losses">Discriminator Losses<a class="anchor-link" href="#Discriminator-Losses">&#182;</a></h3><blockquote><ul>
<li>For the discriminator, the total loss is the sum of the losses for real and fake images, <code>d_loss = d_real_loss + d_fake_loss</code>. </li>
<li>Remember that we want the discriminator to output 1 for real images and 0 for fake images, so we need to set up the losses to reflect that.</li>
</ul>
</blockquote>
<h3 id="Generator-Loss">Generator Loss<a class="anchor-link" href="#Generator-Loss">&#182;</a></h3><p>The generator loss will look similar only with flipped labels. The generator's goal is to get the discriminator to <em>think</em> its generated images are <em>real</em>.</p>
<h4 id="Exercise:-Complete-real-and-fake-loss-functions">Exercise: Complete real and fake loss functions<a class="anchor-link" href="#Exercise:-Complete-real-and-fake-loss-functions">&#182;</a></h4><p><strong>You may choose to use either cross entropy or a least squares error loss to complete the following <code>real_loss</code> and <code>fake_loss</code> functions.</strong></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">real_loss</span><span class="p">(</span><span class="n">D_out</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39;Calculates how close discriminator outputs are to being real.</span>
<span class="sd">       param, D_out: discriminator logits</span>
<span class="sd">       return: real loss&#39;&#39;&#39;</span>
    <span class="n">batch_size</span> <span class="o">=</span> <span class="n">D_out</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">labels</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">batch_size</span><span class="p">)</span>
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
    <span class="n">criterion</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">BCEWithLogitsLoss</span><span class="p">()</span>
    <span class="n">loss</span> <span class="o">=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">D_out</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(),</span> <span class="n">labels</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">loss</span>

<span class="k">def</span> <span class="nf">fake_loss</span><span class="p">(</span><span class="n">D_out</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39;Calculates how close discriminator outputs are to being fake.</span>
<span class="sd">       param, D_out: discriminator logits</span>
<span class="sd">       return: fake loss&#39;&#39;&#39;</span>
    <span class="n">batch_size</span> <span class="o">=</span> <span class="n">D_out</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">labels</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">batch_size</span><span class="p">)</span> <span class="c1"># fake labels = 0</span>
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
    <span class="n">criterion</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">BCEWithLogitsLoss</span><span class="p">()</span>
    <span class="c1"># calculate loss</span>
    <span class="n">loss</span> <span class="o">=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">D_out</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(),</span> <span class="n">labels</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">loss</span>
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<h2 id="Optimizers">Optimizers<a class="anchor-link" href="#Optimizers">&#182;</a></h2><h4 id="Exercise:-Define-optimizers-for-your-Discriminator-(D)-and-Generator-(G)">Exercise: Define optimizers for your Discriminator (D) and Generator (G)<a class="anchor-link" href="#Exercise:-Define-optimizers-for-your-Discriminator-(D)-and-Generator-(G)">&#182;</a></h4><p>Define optimizers for your models with appropriate hyperparameters.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">torch.optim</span> <span class="k">as</span> <span class="nn">optim</span>

<span class="c1"># params</span>
<span class="n">lr</span> <span class="o">=</span> <span class="mf">0.0002</span>
<span class="n">beta1</span><span class="o">=</span><span class="mf">0.5</span>
<span class="n">beta2</span><span class="o">=</span><span class="mf">0.999</span> <span class="c1"># default value</span>


<span class="c1"># Create optimizers for the discriminator D and generator G</span>
<span class="n">d_optimizer</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">(</span><span class="n">D</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span><span class="p">,</span> <span class="p">[</span><span class="n">beta1</span><span class="p">,</span> <span class="n">beta2</span><span class="p">])</span>
<span class="n">g_optimizer</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span><span class="p">,</span> <span class="p">[</span><span class="n">beta1</span><span class="p">,</span> <span class="n">beta2</span><span class="p">])</span>
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<h2 id="Training">Training<a class="anchor-link" href="#Training">&#182;</a></h2><p>Training will involve alternating between training the discriminator and the generator. You'll use your functions <code>real_loss</code> and <code>fake_loss</code> to help you calculate the discriminator losses.</p>
<ul>
<li>You should train the discriminator by alternating on real and fake images</li>
<li>Then the generator, which tries to trick the discriminator and should have an opposing loss function</li>
</ul>
<h4 id="Saving-Samples">Saving Samples<a class="anchor-link" href="#Saving-Samples">&#182;</a></h4><p>You've been given some code to print out some loss statistics and save some generated "fake" samples.</p>

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<h4 id="Exercise:-Complete-the-training-function">Exercise: Complete the training function<a class="anchor-link" href="#Exercise:-Complete-the-training-function">&#182;</a></h4><p>Keep in mind that, if you've moved your models to GPU, you'll also have to move any model inputs to GPU.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="n">D</span><span class="p">,</span> <span class="n">G</span><span class="p">,</span> <span class="n">n_epochs</span><span class="p">,</span> <span class="n">print_every</span><span class="o">=</span><span class="mi">50</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39;Trains adversarial networks for some number of epochs</span>
<span class="sd">       param, D: the discriminator network</span>
<span class="sd">       param, G: the generator network</span>
<span class="sd">       param, n_epochs: number of epochs to train for</span>
<span class="sd">       param, print_every: when to print and record the models&#39; losses</span>
<span class="sd">       return: D and G losses&#39;&#39;&#39;</span>
    
    <span class="c1"># move models to GPU</span>
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">D</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
        <span class="n">G</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>

    <span class="c1"># keep track of loss and generated, &quot;fake&quot; samples</span>
    <span class="n">samples</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">losses</span> <span class="o">=</span> <span class="p">[]</span>

    <span class="c1"># Get some fixed data for sampling. These are images that are held</span>
    <span class="c1"># constant throughout training, and allow us to inspect the model&#39;s performance</span>
    <span class="n">sample_size</span><span class="o">=</span><span class="mi">16</span>
    <span class="n">fixed_z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">sample_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
    <span class="n">fixed_z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">fixed_z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
    <span class="c1"># move z to GPU if available</span>
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">fixed_z</span> <span class="o">=</span> <span class="n">fixed_z</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>

    <span class="c1"># epoch training loop</span>
    <span class="k">for</span> <span class="n">epoch</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_epochs</span><span class="p">):</span>

        <span class="c1"># batch training loop</span>
        <span class="k">for</span> <span class="n">batch_i</span><span class="p">,</span> <span class="p">(</span><span class="n">real_images</span><span class="p">,</span> <span class="n">_</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">celeba_train_loader</span><span class="p">):</span>

            <span class="n">batch_size</span> <span class="o">=</span> <span class="n">real_images</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
            <span class="n">real_images</span> <span class="o">=</span> <span class="n">scale</span><span class="p">(</span><span class="n">real_images</span><span class="p">)</span>

            <span class="c1"># ===============================================</span>
            <span class="c1">#         YOUR CODE HERE: TRAIN THE NETWORKS</span>
            <span class="c1"># ===============================================</span>
            
            <span class="n">d_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>

            <span class="c1"># 1. Train with real images</span>

            <span class="c1"># Compute the discriminator losses on real images </span>
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">real_images</span> <span class="o">=</span> <span class="n">real_images</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>

            <span class="n">D_real</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">real_images</span><span class="p">)</span>
            <span class="n">d_real_loss</span> <span class="o">=</span> <span class="n">real_loss</span><span class="p">(</span><span class="n">D_real</span><span class="p">)</span>

            <span class="c1"># 2. Train with fake images</span>

            <span class="c1"># Generate fake images</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
            <span class="c1"># move x to GPU, if available</span>
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">z</span> <span class="o">=</span> <span class="n">z</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
            <span class="n">fake_images</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">z</span><span class="p">)</span>

            <span class="c1"># Compute the discriminator losses on fake images            </span>
            <span class="n">D_fake</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">fake_images</span><span class="p">)</span>
            <span class="n">d_fake_loss</span> <span class="o">=</span> <span class="n">fake_loss</span><span class="p">(</span><span class="n">D_fake</span><span class="p">)</span>

            <span class="c1"># add up loss and perform backprop</span>
            <span class="n">d_loss</span> <span class="o">=</span> <span class="n">d_real_loss</span> <span class="o">+</span> <span class="n">d_fake_loss</span>
            <span class="n">d_loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
            <span class="n">d_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>

            <span class="c1"># 2. Train the generator with an adversarial loss</span>
            <span class="n">g_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
        
            <span class="c1"># 1. Train with fake images and flipped labels</span>

            <span class="c1"># Generate fake images</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">z</span> <span class="o">=</span> <span class="n">z</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
            <span class="n">fake_images</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">z</span><span class="p">)</span>

            <span class="c1"># Compute the discriminator losses on fake images </span>
            <span class="c1"># using flipped labels!</span>
            <span class="n">D_fake</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">fake_images</span><span class="p">)</span>
            <span class="n">g_loss</span> <span class="o">=</span> <span class="n">real_loss</span><span class="p">(</span><span class="n">D_fake</span><span class="p">)</span> <span class="c1"># use real loss to flip labels</span>

            <span class="c1"># perform backprop</span>
            <span class="n">g_loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
            <span class="n">g_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
            
            
            <span class="c1"># ===============================================</span>
            <span class="c1">#              END OF YOUR CODE</span>
            <span class="c1"># ===============================================</span>

            <span class="c1"># Print some loss stats</span>
            <span class="k">if</span> <span class="n">batch_i</span> <span class="o">%</span> <span class="n">print_every</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="c1"># append discriminator loss and generator loss</span>
                <span class="n">losses</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">d_loss</span><span class="o">.</span><span class="n">item</span><span class="p">(),</span> <span class="n">g_loss</span><span class="o">.</span><span class="n">item</span><span class="p">()))</span>
                <span class="c1"># print discriminator and generator loss</span>
                <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Epoch [</span><span class="si">{:5d}</span><span class="s1">/</span><span class="si">{:5d}</span><span class="s1">] | d_loss: </span><span class="si">{:6.4f}</span><span class="s1"> | g_loss: </span><span class="si">{:6.4f}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span>
                        <span class="n">epoch</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">n_epochs</span><span class="p">,</span> <span class="n">d_loss</span><span class="o">.</span><span class="n">item</span><span class="p">(),</span> <span class="n">g_loss</span><span class="o">.</span><span class="n">item</span><span class="p">()))</span>


        <span class="c1">## AFTER EACH EPOCH##    </span>
        <span class="c1"># this code assumes your generator is named G, feel free to change the name</span>
        <span class="c1"># generate and save sample, fake images</span>
        <span class="n">G</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span> <span class="c1"># for generating samples</span>
        <span class="n">samples_z</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">fixed_z</span><span class="p">)</span>
        <span class="n">samples</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">samples_z</span><span class="p">)</span>
        <span class="n">G</span><span class="o">.</span><span class="n">train</span><span class="p">()</span> <span class="c1"># back to training mode</span>

    <span class="c1"># Save training generator samples</span>
    <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;train_samples.pkl&#39;</span><span class="p">,</span> <span class="s1">&#39;wb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
        <span class="n">pkl</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">samples</span><span class="p">,</span> <span class="n">f</span><span class="p">)</span>
    
    <span class="c1"># finally return losses</span>
    <span class="k">return</span> <span class="n">losses</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Set your number of training epochs and train your GAN!</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[23]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># set number of epochs </span>
<span class="n">n_epochs</span> <span class="o">=</span> <span class="mi">30</span>


<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="c1"># call training function</span>
<span class="kn">from</span> <span class="nn">workspace_utils</span> <span class="k">import</span> <span class="n">active_session</span>
 
<span class="k">with</span> <span class="n">active_session</span><span class="p">():</span>
    <span class="n">losses</span> <span class="o">=</span> <span class="n">train</span><span class="p">(</span><span class="n">D</span><span class="p">,</span> <span class="n">G</span><span class="p">,</span> <span class="n">n_epochs</span><span class="o">=</span><span class="n">n_epochs</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

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


<div class="output_subarea output_stream output_stdout output_text">
<pre>Epoch [    1/   30] | d_loss: 1.4287 | g_loss: 2.6966
Epoch [    1/   30] | d_loss: 0.1425 | g_loss: 6.7971
Epoch [    1/   30] | d_loss: 0.7459 | g_loss: 6.1874
Epoch [    1/   30] | d_loss: 0.5512 | g_loss: 3.3710
Epoch [    1/   30] | d_loss: 0.5389 | g_loss: 3.0891
Epoch [    1/   30] | d_loss: 1.0104 | g_loss: 3.8736
Epoch [    1/   30] | d_loss: 0.6435 | g_loss: 3.9834
Epoch [    1/   30] | d_loss: 0.9629 | g_loss: 1.5833
Epoch [    2/   30] | d_loss: 1.2865 | g_loss: 4.1011
Epoch [    2/   30] | d_loss: 0.7289 | g_loss: 3.9192
Epoch [    2/   30] | d_loss: 0.6049 | g_loss: 3.7334
Epoch [    2/   30] | d_loss: 0.7960 | g_loss: 4.1155
Epoch [    2/   30] | d_loss: 0.6975 | g_loss: 3.1569
Epoch [    2/   30] | d_loss: 0.5656 | g_loss: 3.5009
Epoch [    2/   30] | d_loss: 0.6297 | g_loss: 2.7708
Epoch [    2/   30] | d_loss: 0.8878 | g_loss: 4.4990
Epoch [    3/   30] | d_loss: 1.0460 | g_loss: 5.0997
Epoch [    3/   30] | d_loss: 0.7226 | g_loss: 3.0871
Epoch [    3/   30] | d_loss: 0.9324 | g_loss: 5.5165
Epoch [    3/   30] | d_loss: 1.0817 | g_loss: 4.1483
Epoch [    3/   30] | d_loss: 0.6191 | g_loss: 2.1927
Epoch [    3/   30] | d_loss: 1.0561 | g_loss: 5.7195
Epoch [    3/   30] | d_loss: 0.5641 | g_loss: 2.2774
Epoch [    3/   30] | d_loss: 0.7336 | g_loss: 3.8954
Epoch [    4/   30] | d_loss: 1.1861 | g_loss: 4.8934
Epoch [    4/   30] | d_loss: 1.2917 | g_loss: 1.8125
Epoch [    4/   30] | d_loss: 0.7518 | g_loss: 4.1885
Epoch [    4/   30] | d_loss: 0.6566 | g_loss: 2.5286
Epoch [    4/   30] | d_loss: 0.4051 | g_loss: 2.8789
Epoch [    4/   30] | d_loss: 0.7713 | g_loss: 2.1204
Epoch [    4/   30] | d_loss: 0.8314 | g_loss: 1.5300
Epoch [    4/   30] | d_loss: 0.7927 | g_loss: 2.6203
Epoch [    5/   30] | d_loss: 0.7076 | g_loss: 2.1846
Epoch [    5/   30] | d_loss: 0.5402 | g_loss: 2.8965
Epoch [    5/   30] | d_loss: 0.5379 | g_loss: 2.7624
Epoch [    5/   30] | d_loss: 0.4516 | g_loss: 2.1572
Epoch [    5/   30] | d_loss: 0.6537 | g_loss: 2.3208
Epoch [    5/   30] | d_loss: 0.6584 | g_loss: 1.6888
Epoch [    5/   30] | d_loss: 0.7624 | g_loss: 3.0901
Epoch [    5/   30] | d_loss: 0.7496 | g_loss: 1.5124
Epoch [    6/   30] | d_loss: 0.6976 | g_loss: 1.8983
Epoch [    6/   30] | d_loss: 0.8904 | g_loss: 1.0152
Epoch [    6/   30] | d_loss: 0.8317 | g_loss: 2.1008
Epoch [    6/   30] | d_loss: 0.4793 | g_loss: 2.8940
Epoch [    6/   30] | d_loss: 0.8777 | g_loss: 1.2673
Epoch [    6/   30] | d_loss: 0.9389 | g_loss: 2.3267
Epoch [    6/   30] | d_loss: 0.6302 | g_loss: 2.1010
Epoch [    6/   30] | d_loss: 0.9073 | g_loss: 3.7242
Epoch [    7/   30] | d_loss: 1.2040 | g_loss: 4.5849
Epoch [    7/   30] | d_loss: 0.5608 | g_loss: 2.3061
Epoch [    7/   30] | d_loss: 0.5787 | g_loss: 2.3630
Epoch [    7/   30] | d_loss: 0.8308 | g_loss: 1.8624
Epoch [    7/   30] | d_loss: 0.7836 | g_loss: 2.0602
Epoch [    7/   30] | d_loss: 0.6493 | g_loss: 2.6549
Epoch [    7/   30] | d_loss: 0.6134 | g_loss: 2.2199
Epoch [    7/   30] | d_loss: 0.6240 | g_loss: 2.3158
Epoch [    8/   30] | d_loss: 0.7606 | g_loss: 3.7599
Epoch [    8/   30] | d_loss: 0.7087 | g_loss: 2.9242
Epoch [    8/   30] | d_loss: 0.5221 | g_loss: 4.0316
Epoch [    8/   30] | d_loss: 1.1007 | g_loss: 1.1969
Epoch [    8/   30] | d_loss: 0.7896 | g_loss: 3.2776
Epoch [    8/   30] | d_loss: 0.6268 | g_loss: 2.2031
Epoch [    8/   30] | d_loss: 0.8235 | g_loss: 2.8978
Epoch [    8/   30] | d_loss: 0.7692 | g_loss: 3.1851
Epoch [    9/   30] | d_loss: 0.6114 | g_loss: 3.3134
Epoch [    9/   30] | d_loss: 0.4604 | g_loss: 2.8527
Epoch [    9/   30] | d_loss: 0.6081 | g_loss: 1.5988
Epoch [    9/   30] | d_loss: 0.5220 | g_loss: 2.6009
Epoch [    9/   30] | d_loss: 0.7334 | g_loss: 1.7134
Epoch [    9/   30] | d_loss: 0.5342 | g_loss: 2.4043
Epoch [    9/   30] | d_loss: 0.5350 | g_loss: 2.1440
Epoch [    9/   30] | d_loss: 0.6021 | g_loss: 2.3611
Epoch [   10/   30] | d_loss: 0.5652 | g_loss: 2.4344
Epoch [   10/   30] | d_loss: 0.8302 | g_loss: 3.2248
Epoch [   10/   30] | d_loss: 1.1083 | g_loss: 1.2080
Epoch [   10/   30] | d_loss: 0.6131 | g_loss: 2.1949
Epoch [   10/   30] | d_loss: 1.6602 | g_loss: 1.0158
Epoch [   10/   30] | d_loss: 0.7148 | g_loss: 1.2984
Epoch [   10/   30] | d_loss: 0.6131 | g_loss: 1.9415
Epoch [   10/   30] | d_loss: 1.0640 | g_loss: 3.6400
Epoch [   11/   30] | d_loss: 0.6031 | g_loss: 2.2171
Epoch [   11/   30] | d_loss: 0.4666 | g_loss: 1.9704
Epoch [   11/   30] | d_loss: 0.8835 | g_loss: 1.3036
Epoch [   11/   30] | d_loss: 0.7315 | g_loss: 3.5656
Epoch [   11/   30] | d_loss: 0.4408 | g_loss: 2.3942
Epoch [   11/   30] | d_loss: 0.6057 | g_loss: 2.7155
Epoch [   11/   30] | d_loss: 0.6041 | g_loss: 2.8250
Epoch [   11/   30] | d_loss: 0.6365 | g_loss: 2.1255
Epoch [   12/   30] | d_loss: 0.5204 | g_loss: 3.0184
Epoch [   12/   30] | d_loss: 0.8636 | g_loss: 0.9741
Epoch [   12/   30] | d_loss: 0.5975 | g_loss: 3.2991
Epoch [   12/   30] | d_loss: 0.7539 | g_loss: 4.1866
Epoch [   12/   30] | d_loss: 0.5845 | g_loss: 1.7224
Epoch [   12/   30] | d_loss: 0.8015 | g_loss: 3.2772
Epoch [   12/   30] | d_loss: 0.5564 | g_loss: 1.6167
Epoch [   12/   30] | d_loss: 1.4243 | g_loss: 5.4196
Epoch [   13/   30] | d_loss: 1.2039 | g_loss: 4.5640
Epoch [   13/   30] | d_loss: 1.0167 | g_loss: 4.2873
Epoch [   13/   30] | d_loss: 0.3686 | g_loss: 2.3518
Epoch [   13/   30] | d_loss: 0.4029 | g_loss: 2.4634
Epoch [   13/   30] | d_loss: 0.7412 | g_loss: 1.2962
Epoch [   13/   30] | d_loss: 0.4603 | g_loss: 2.4954
Epoch [   13/   30] | d_loss: 0.8257 | g_loss: 5.0135
Epoch [   13/   30] | d_loss: 0.3034 | g_loss: 1.6187
Epoch [   14/   30] | d_loss: 0.3056 | g_loss: 2.9247
Epoch [   14/   30] | d_loss: 0.3944 | g_loss: 2.9260
Epoch [   14/   30] | d_loss: 0.4883 | g_loss: 2.8245
Epoch [   14/   30] | d_loss: 0.3895 | g_loss: 2.5231
Epoch [   14/   30] | d_loss: 0.4654 | g_loss: 1.5007
Epoch [   14/   30] | d_loss: 0.3930 | g_loss: 2.8122
Epoch [   14/   30] | d_loss: 0.6152 | g_loss: 3.6053
Epoch [   14/   30] | d_loss: 0.5961 | g_loss: 2.4772
Epoch [   15/   30] | d_loss: 0.4725 | g_loss: 2.9251
Epoch [   15/   30] | d_loss: 0.5236 | g_loss: 1.0131
Epoch [   15/   30] | d_loss: 0.6951 | g_loss: 1.8248
Epoch [   15/   30] | d_loss: 0.6055 | g_loss: 2.7284
Epoch [   15/   30] | d_loss: 0.4122 | g_loss: 2.3930
Epoch [   15/   30] | d_loss: 0.4472 | g_loss: 2.6374
Epoch [   15/   30] | d_loss: 0.5837 | g_loss: 2.6161
Epoch [   15/   30] | d_loss: 0.5646 | g_loss: 3.4258
Epoch [   16/   30] | d_loss: 0.3351 | g_loss: 1.6289
Epoch [   16/   30] | d_loss: 0.3609 | g_loss: 3.0865
Epoch [   16/   30] | d_loss: 0.5637 | g_loss: 4.6983
Epoch [   16/   30] | d_loss: 0.3233 | g_loss: 2.2909
Epoch [   16/   30] | d_loss: 0.4087 | g_loss: 2.3074
Epoch [   16/   30] | d_loss: 0.3959 | g_loss: 1.5805
Epoch [   16/   30] | d_loss: 0.5400 | g_loss: 1.4192
Epoch [   16/   30] | d_loss: 0.3957 | g_loss: 3.7631
Epoch [   17/   30] | d_loss: 1.2228 | g_loss: 6.4873
Epoch [   17/   30] | d_loss: 0.4304 | g_loss: 2.2026
Epoch [   17/   30] | d_loss: 0.8051 | g_loss: 1.5531
Epoch [   17/   30] | d_loss: 0.3148 | g_loss: 2.5487
Epoch [   17/   30] | d_loss: 0.3890 | g_loss: 2.7356
Epoch [   17/   30] | d_loss: 0.7680 | g_loss: 4.4814
Epoch [   17/   30] | d_loss: 1.3916 | g_loss: 0.9249
Epoch [   17/   30] | d_loss: 0.6175 | g_loss: 3.5430
Epoch [   18/   30] | d_loss: 0.3496 | g_loss: 2.4706
Epoch [   18/   30] | d_loss: 0.7816 | g_loss: 7.7688
Epoch [   18/   30] | d_loss: 0.9409 | g_loss: 1.0903
Epoch [   18/   30] | d_loss: 0.8915 | g_loss: 0.9699
Epoch [   18/   30] | d_loss: 0.6237 | g_loss: 5.1816
Epoch [   18/   30] | d_loss: 0.3345 | g_loss: 2.8878
Epoch [   18/   30] | d_loss: 0.4356 | g_loss: 1.2908
Epoch [   18/   30] | d_loss: 0.5968 | g_loss: 4.3795
Epoch [   19/   30] | d_loss: 0.3158 | g_loss: 2.8253
Epoch [   19/   30] | d_loss: 0.3814 | g_loss: 2.6336
Epoch [   19/   30] | d_loss: 0.6642 | g_loss: 1.6780
Epoch [   19/   30] | d_loss: 0.2737 | g_loss: 3.0428
Epoch [   19/   30] | d_loss: 1.5854 | g_loss: 0.4888
Epoch [   19/   30] | d_loss: 1.2313 | g_loss: 5.2511
Epoch [   19/   30] | d_loss: 0.3841 | g_loss: 2.1458
Epoch [   19/   30] | d_loss: 0.3879 | g_loss: 3.4196
Epoch [   20/   30] | d_loss: 0.4784 | g_loss: 1.3640
Epoch [   20/   30] | d_loss: 0.3449 | g_loss: 1.7991
Epoch [   20/   30] | d_loss: 0.5487 | g_loss: 3.2736
Epoch [   20/   30] | d_loss: 0.4291 | g_loss: 4.1663
Epoch [   20/   30] | d_loss: 1.2038 | g_loss: 6.7952
Epoch [   20/   30] | d_loss: 0.2514 | g_loss: 2.7803
Epoch [   20/   30] | d_loss: 0.5277 | g_loss: 2.4598
Epoch [   20/   30] | d_loss: 0.2590 | g_loss: 2.6583
Epoch [   21/   30] | d_loss: 0.4348 | g_loss: 3.0858
Epoch [   21/   30] | d_loss: 0.3505 | g_loss: 2.1359
Epoch [   21/   30] | d_loss: 0.2284 | g_loss: 4.6848
Epoch [   21/   30] | d_loss: 0.2615 | g_loss: 2.0545
Epoch [   21/   30] | d_loss: 0.3498 | g_loss: 4.1300
Epoch [   21/   30] | d_loss: 0.2175 | g_loss: 2.8948
Epoch [   21/   30] | d_loss: 0.2263 | g_loss: 2.1737
Epoch [   21/   30] | d_loss: 1.2750 | g_loss: 1.6849
Epoch [   22/   30] | d_loss: 0.5520 | g_loss: 4.1137
Epoch [   22/   30] | d_loss: 0.4989 | g_loss: 3.0597
Epoch [   22/   30] | d_loss: 0.3908 | g_loss: 3.1121
Epoch [   22/   30] | d_loss: 0.3410 | g_loss: 1.0620
Epoch [   22/   30] | d_loss: 0.1673 | g_loss: 4.2747
Epoch [   22/   30] | d_loss: 0.7921 | g_loss: 4.5423
Epoch [   22/   30] | d_loss: 0.2876 | g_loss: 2.4957
Epoch [   22/   30] | d_loss: 1.0296 | g_loss: 3.1073
Epoch [   23/   30] | d_loss: 0.9639 | g_loss: 5.6466
Epoch [   23/   30] | d_loss: 0.3210 | g_loss: 4.3384
Epoch [   23/   30] | d_loss: 0.1495 | g_loss: 4.0007
Epoch [   23/   30] | d_loss: 0.8056 | g_loss: 4.7987
Epoch [   23/   30] | d_loss: 0.1891 | g_loss: 4.2177
Epoch [   23/   30] | d_loss: 0.2076 | g_loss: 4.6238
Epoch [   23/   30] | d_loss: 0.1504 | g_loss: 5.1967
Epoch [   23/   30] | d_loss: 0.4338 | g_loss: 1.5274
Epoch [   24/   30] | d_loss: 0.1795 | g_loss: 3.6553
Epoch [   24/   30] | d_loss: 0.5204 | g_loss: 2.0987
Epoch [   24/   30] | d_loss: 0.2490 | g_loss: 2.6331
Epoch [   24/   30] | d_loss: 0.1950 | g_loss: 4.4165
Epoch [   24/   30] | d_loss: 0.1646 | g_loss: 3.0848
Epoch [   24/   30] | d_loss: 0.1845 | g_loss: 3.4111
Epoch [   24/   30] | d_loss: 0.3837 | g_loss: 4.0687
Epoch [   24/   30] | d_loss: 0.3012 | g_loss: 2.9067
Epoch [   25/   30] | d_loss: 0.2878 | g_loss: 4.2490
Epoch [   25/   30] | d_loss: 0.0713 | g_loss: 5.2638
Epoch [   25/   30] | d_loss: 0.4890 | g_loss: 3.9867
Epoch [   25/   30] | d_loss: 0.1690 | g_loss: 3.2909
Epoch [   25/   30] | d_loss: 0.3350 | g_loss: 3.0149
Epoch [   25/   30] | d_loss: 0.2939 | g_loss: 3.8318
Epoch [   25/   30] | d_loss: 0.3498 | g_loss: 2.2319
Epoch [   25/   30] | d_loss: 0.4655 | g_loss: 3.6205
Epoch [   26/   30] | d_loss: 0.4769 | g_loss: 2.3526
Epoch [   26/   30] | d_loss: 0.2213 | g_loss: 4.2936
Epoch [   26/   30] | d_loss: 0.1998 | g_loss: 3.4316
Epoch [   26/   30] | d_loss: 0.1810 | g_loss: 2.6018
Epoch [   26/   30] | d_loss: 0.5281 | g_loss: 7.2426
Epoch [   26/   30] | d_loss: 0.1370 | g_loss: 5.0099
Epoch [   26/   30] | d_loss: 0.5991 | g_loss: 4.4784
Epoch [   26/   30] | d_loss: 0.1850 | g_loss: 3.9751
Epoch [   27/   30] | d_loss: 0.3087 | g_loss: 5.7324
Epoch [   27/   30] | d_loss: 0.3638 | g_loss: 4.6586
Epoch [   27/   30] | d_loss: 0.1624 | g_loss: 3.4791
Epoch [   27/   30] | d_loss: 0.1072 | g_loss: 3.8657
Epoch [   27/   30] | d_loss: 0.3275 | g_loss: 4.1743
Epoch [   27/   30] | d_loss: 0.1644 | g_loss: 4.9012
Epoch [   27/   30] | d_loss: 0.6502 | g_loss: 1.8496
Epoch [   27/   30] | d_loss: 0.5558 | g_loss: 4.3035
Epoch [   28/   30] | d_loss: 0.1799 | g_loss: 4.5911
Epoch [   28/   30] | d_loss: 0.4813 | g_loss: 1.2362
Epoch [   28/   30] | d_loss: 0.2266 | g_loss: 2.7657
Epoch [   28/   30] | d_loss: 0.1941 | g_loss: 4.2865
Epoch [   28/   30] | d_loss: 1.1806 | g_loss: 0.2645
Epoch [   28/   30] | d_loss: 0.1599 | g_loss: 4.5140
Epoch [   28/   30] | d_loss: 0.2060 | g_loss: 3.1811
Epoch [   28/   30] | d_loss: 0.5011 | g_loss: 0.9536
Epoch [   29/   30] | d_loss: 0.8447 | g_loss: 3.4826
Epoch [   29/   30] | d_loss: 0.1696 | g_loss: 2.8488
Epoch [   29/   30] | d_loss: 0.3908 | g_loss: 1.2377
Epoch [   29/   30] | d_loss: 0.0798 | g_loss: 4.1998
Epoch [   29/   30] | d_loss: 0.5104 | g_loss: 3.1473
Epoch [   29/   30] | d_loss: 0.1021 | g_loss: 3.8939
Epoch [   29/   30] | d_loss: 0.2341 | g_loss: 3.8989
Epoch [   29/   30] | d_loss: 0.1236 | g_loss: 2.9963
Epoch [   30/   30] | d_loss: 0.3465 | g_loss: 4.9847
Epoch [   30/   30] | d_loss: 0.1148 | g_loss: 5.0906
Epoch [   30/   30] | d_loss: 0.1768 | g_loss: 3.2132
Epoch [   30/   30] | d_loss: 0.2368 | g_loss: 3.6295
Epoch [   30/   30] | d_loss: 0.5142 | g_loss: 4.9289
Epoch [   30/   30] | d_loss: 0.9655 | g_loss: 0.0880
Epoch [   30/   30] | d_loss: 0.3243 | g_loss: 2.3453
Epoch [   30/   30] | d_loss: 0.0699 | g_loss: 5.9062
</pre>
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<h2 id="Training-loss">Training loss<a class="anchor-link" href="#Training-loss">&#182;</a></h2><p>Plot the training losses for the generator and discriminator, recorded after each epoch.</p>

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<div class="prompt input_prompt">In&nbsp;[24]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
<span class="n">losses</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">losses</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">losses</span><span class="o">.</span><span class="n">T</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Discriminator&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">losses</span><span class="o">.</span><span class="n">T</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Generator&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Training Losses&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
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<pre>&lt;matplotlib.legend.Legend at 0x7f3e7b067fd0&gt;</pre>
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<h2 id="Generator-samples-from-training">Generator samples from training<a class="anchor-link" href="#Generator-samples-from-training">&#182;</a></h2><p>View samples of images from the generator, and answer a question about the strengths and weaknesses of your trained models.</p>

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<div class="prompt input_prompt">In&nbsp;[25]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># helper function for viewing a list of passed in sample images</span>
<span class="k">def</span> <span class="nf">view_samples</span><span class="p">(</span><span class="n">epoch</span><span class="p">,</span> <span class="n">samples</span><span class="p">):</span>
    <span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">16</span><span class="p">,</span><span class="mi">4</span><span class="p">),</span> <span class="n">nrows</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">ncols</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">sharey</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">sharex</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    <span class="k">for</span> <span class="n">ax</span><span class="p">,</span> <span class="n">img</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">axes</span><span class="o">.</span><span class="n">flatten</span><span class="p">(),</span> <span class="n">samples</span><span class="p">[</span><span class="n">epoch</span><span class="p">]):</span>
        <span class="n">img</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">detach</span><span class="p">()</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span>
        <span class="n">img</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">))</span>
        <span class="n">img</span> <span class="o">=</span> <span class="p">((</span><span class="n">img</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span><span class="o">*</span><span class="mi">255</span> <span class="o">/</span> <span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
        <span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set_visible</span><span class="p">(</span><span class="kc">False</span><span class="p">)</span>
        <span class="n">ax</span><span class="o">.</span><span class="n">yaxis</span><span class="o">.</span><span class="n">set_visible</span><span class="p">(</span><span class="kc">False</span><span class="p">)</span>
        <span class="n">im</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">32</span><span class="p">,</span><span class="mi">32</span><span class="p">,</span><span class="mi">3</span><span class="p">)))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Load samples from generator, taken while training</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;train_samples.pkl&#39;</span><span class="p">,</span> <span class="s1">&#39;rb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    <span class="n">samples</span> <span class="o">=</span> <span class="n">pkl</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
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<div class="prompt input_prompt">In&nbsp;[27]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">_</span> <span class="o">=</span> <span class="n">view_samples</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">samples</span><span class="p">)</span>
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<h3 id="Question:-What-do-you-notice-about-your-generated-samples-and-how-might-you-improve-this-model?">Question: What do you notice about your generated samples and how might you improve this model?<a class="anchor-link" href="#Question:-What-do-you-notice-about-your-generated-samples-and-how-might-you-improve-this-model?">&#182;</a></h3><p>When you answer this question, consider the following factors:</p>
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<li>The dataset is biased; it is made of "celebrity" faces that are mostly white</li>
<li>Model size; larger models have the opportunity to learn more features in a data feature space</li>
<li>Optimization strategy; optimizers and number of epochs affect your final result</li>
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<p><strong>Answer:</strong></p>
<p>From looking at the sample images we can see that most of them read at faces which is good, there are some odd artefacts and the expressions/facial feature seem to be repeating. We can see the mouth and eyes are a very similar in all the samples. The other main flaw is the quality of the images.</p>
<p>As mentioned above the data set is biased and we cans see this in the result, one way to improve the model would be to improve the data set, higher quality images, more images of more diverse people with respect to gender, age and ethnicity.
The model used to train was a relatively simple one and can definitely be improved with more layers, to produce larger images. Tuning the hyper parameters would also help.
Finally I would also train again using SDG optimizer for the discriminator, as well as training for much longer.</p>

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<h3 id="Submitting-This-Project">Submitting This Project<a class="anchor-link" href="#Submitting-This-Project">&#182;</a></h3><p>When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -&gt; "Download as". Include the "problem_unittests.py" files in your submission.</p>

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