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="c1"># !unzip processed_celeba_small.zip</span>
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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">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"># TODO: Implement function and return a dataloader</span>
    <span class="n">image_aug</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">CenterCrop</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="n">imagenet_data</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">data_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">image_aug</span><span class="p">)</span>
    <span class="n">data_loader</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">DataLoader</span><span class="p">(</span><span class="n">imagenet_data</span><span class="p">,</span>
                                          <span class="n">batch_size</span><span class="o">=</span><span class="n">batch_size</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span>
                                          <span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">data_loader</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">20</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="sd">&quot;&quot;&quot;</span>
<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="nb">min</span><span class="p">,</span> <span class="nb">max</span>  <span class="o">=</span> <span class="n">feature_range</span>
    <span class="n">x</span> <span class="o">=</span> <span class="n">x</span><span class="o">*</span><span class="p">(</span><span class="nb">max</span><span class="o">-</span><span class="nb">min</span><span class="p">)</span><span class="o">+</span><span class="nb">min</span>
    
    <span class="k">return</span> <span class="n">x</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(-0.9451)
Max:  tensor(0.9529)
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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"># helper conv function</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="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"># complete init function</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"># Define all convolutional layers</span>
        <span class="c1"># Should accept an RGB image as input and output a single value</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="n">batch_norm</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="c1"># x, y = 64 depth = 3</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="c1"># x, y = 32 depth = 64</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="c1"># x, y = 16 depth = 128</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">4</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">out</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sigmoid</span><span class="p">()</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">dropout</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Dropout</span><span class="p">(</span><span class="mf">0.5</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"># define feedforward behavior</span>
        <span class="c1"># define feedforward behavior</span>
        <span class="n">x</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="mf">0.2</span><span class="p">)</span>
        <span class="c1"># x = self.dropout(x)</span>
        <span class="n">x</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">x</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>
        <span class="c1"># x = self.dropout(x)</span>
        <span class="n">x</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">x</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>
        <span class="c1"># x = self.dropout(x)</span>
        
        <span class="n">x</span> <span class="o">=</span> <span class="n">x</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">4</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="p">)</span>
        
        <span class="n">x</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="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">dropout</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
        
        <span class="c1"># x = self.out(x)</span>
        
        <span class="k">return</span> <span class="n">x</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="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="c1"># complete init function</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="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">4</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="p">)</span>
        
        <span class="bp">self</span><span class="o">.</span><span class="n">t_conv1</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">t_conv2</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">t_conv3</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="bp">self</span><span class="o">.</span><span class="n">dropout</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Dropout</span><span class="p">(</span><span class="mf">0.5</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: A 32x32x3 Tensor image as output</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="c1"># define feedforward behavior</span>
        <span class="n">x</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="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">dropout</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
        
        <span class="n">x</span> <span class="o">=</span> <span class="n">x</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">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        
        <span class="n">x</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">t_conv1</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
        <span class="c1"># x = self.dropout(x)</span>
        <span class="n">x</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">t_conv2</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
        <span class="c1"># x = self.dropout(x)</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">F</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">t_conv3</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
        
        <span class="k">return</span> <span class="n">x</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="kn">from</span> <span class="nn">torch.nn</span> <span class="k">import</span> <span class="n">init</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="n">init_gain</span><span class="o">=</span><span class="mf">0.02</span>
    <span class="c1"># classname will be something like:</span>
    <span class="c1"># `Conv`, `BatchNorm2d`, `Linear`, etc.</span>
    <span class="c1"># TODO: Apply initial weights to convolutional and linear layers</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="c1"># print(classname)</span>
    <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="s1">&#39;weight&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="p">(</span><span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;Conv&#39;</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">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="n">init_gain</span><span class="p">)</span>
        <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="s1">&#39;bias&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="n">m</span><span class="o">.</span><span class="n">bias</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</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>
    <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="s1">&#39;BatchNorm2d&#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="c1"># BatchNorm Layer&#39;s weight is not a matrix; only normal distribution applies.</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="n">init_gain</span><span class="p">)</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">32</span>
<span class="n">g_conv_dim</span> <span class="o">=</span> <span class="mi">32</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, 32, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
  )
  (conv2): Sequential(
    (0): Conv2d(32, 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)
  )
  (conv3): 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)
  )
  (fc): Linear(in_features=2048, out_features=1, bias=True)
  (out): Sigmoid()
  (dropout): Dropout(p=0.5)
)

Generator(
  (fc): Linear(in_features=100, out_features=2048, bias=True)
  (t_conv1): 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)
  )
  (t_conv2): Sequential(
    (0): ConvTranspose2d(64, 32, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (t_conv3): Sequential(
    (0): ConvTranspose2d(32, 3, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
  )
  (dropout): Dropout(p=0.5)
)
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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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<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</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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<hr>
<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="kn">from</span> <span class="nn">random</span> <span class="k">import</span> <span class="n">randrange</span><span class="p">,</span> <span class="n">uniform</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="c1"># label smoothing</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="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="mf">0.7</span><span class="p">,</span> <span class="mf">1.2</span><span class="p">)</span>
    <span class="c1"># labels = torch.ones(batch_size) * 0.9</span>
    <span class="c1"># labels = torch.ones(batch_size) # real labels = 1</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="c1"># loss = torch.mean(-loss)</span>
    <span class="c1"># loss = torch.mean((D_out-1)**2)</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="c1"># labels = torch.zeros(batch_size) + 0.0 # fake labels = 0</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="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="mf">0.0</span><span class="p">,</span> <span class="mf">0.3</span><span class="p">)</span> <span class="c1"># fake labels = 0.3</span>
    <span class="c1"># print(labels)</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="c1"># loss = torch.mean(loss)</span>
    <span class="c1"># loss = torch.mean(D_out**2)</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">0.0005</span>
<span class="n">beta1</span><span class="o">=</span> <span class="mf">0.1</span>
<span class="n">beta2</span><span class="o">=</span> <span class="mf">0.99</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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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">if</span> <span class="mf">0.0005</span> <span class="o">&gt;</span> <span class="mf">0.001</span><span class="p">:</span>
    <span class="nb">print</span><span class="p">(</span><span class="kc">True</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"># D.train()</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="c1"># 1. Train the discriminator on real and fake images</span>
            
            <span class="n">d_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</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_out</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_out</span><span class="p">)</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="n">d_fake_out</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_out</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"># 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"># D.eval()</span>
            <span class="c1"># Compute the discriminator losses on fake images </span>
            <span class="c1"># using flipped labels!</span>
            <span class="n">g_fake_out</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">g_fake_out</span><span class="p">)</span> <span class="c1"># use real loss to flip labels</span>
            <span class="c1"># g_loss = torch.mean(g_fake_out**2)</span>
            <span class="c1"># D.train()</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="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">]---------------&#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="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>

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<p>Set your number of training epochs and train your GAN!</p>

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<div class="prompt input_prompt">In&nbsp;[23]:</div>
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<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">2</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="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>

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<pre>Epoch [    1/    2] | d_loss: 1.3745 | g_loss: 1.1990
Epoch [    1/    2] | d_loss: 1.0767 | g_loss: 1.6913
Epoch [    1/    2] | d_loss: 1.3325 | g_loss: 2.7247
Epoch [    1/    2] | d_loss: 1.4180 | g_loss: 4.3857
Epoch [    1/    2] | d_loss: 1.2693 | g_loss: 2.2416
Epoch [    1/    2] | d_loss: 1.3604 | g_loss: 1.8432
Epoch [    1/    2] | d_loss: 1.0685 | g_loss: 0.8227
Epoch [    1/    2] | d_loss: 1.1541 | g_loss: 1.3557
Epoch [    1/    2] | d_loss: 1.4202 | g_loss: 1.0962
Epoch [    1/    2] | d_loss: 1.1978 | g_loss: 0.8573
Epoch [    1/    2] | d_loss: 1.7056 | g_loss: 0.7590
Epoch [    1/    2] | d_loss: 1.1094 | g_loss: 1.9473
Epoch [    1/    2] | d_loss: 1.2082 | g_loss: 1.2869
Epoch [    1/    2] | d_loss: 1.4359 | g_loss: 1.4901
Epoch [    1/    2] | d_loss: 1.6255 | g_loss: 2.2729
Epoch [    1/    2] | d_loss: 1.7598 | g_loss: 1.1937
Epoch [    1/    2] | d_loss: 1.4591 | g_loss: 0.7360
Epoch [    1/    2] | d_loss: 1.3173 | g_loss: 1.6188
Epoch [    1/    2] | d_loss: 1.1512 | g_loss: 0.9567
Epoch [    1/    2] | d_loss: 1.3342 | g_loss: 0.9223
Epoch [    1/    2] | d_loss: 1.2550 | g_loss: 0.6613
Epoch [    1/    2] | d_loss: 1.0029 | g_loss: 0.7680
Epoch [    1/    2] | d_loss: 1.2297 | g_loss: 1.0750
Epoch [    1/    2] | d_loss: 1.3717 | g_loss: 1.0725
Epoch [    1/    2] | d_loss: 1.4551 | g_loss: 0.7059
Epoch [    1/    2] | d_loss: 1.2463 | g_loss: 1.0835
Epoch [    1/    2] | d_loss: 1.3793 | g_loss: 0.8578
Epoch [    1/    2] | d_loss: 1.3207 | g_loss: 1.3364
Epoch [    1/    2] | d_loss: 1.5140 | g_loss: 1.6030
Epoch [    1/    2] | d_loss: 1.0935 | g_loss: 1.0140
Epoch [    1/    2] | d_loss: 1.4815 | g_loss: 0.8224
Epoch [    1/    2] | d_loss: 1.2904 | g_loss: 0.7474
Epoch [    1/    2] | d_loss: 1.4002 | g_loss: 1.6420
Epoch [    1/    2] | d_loss: 1.2338 | g_loss: 1.1186
Epoch [    1/    2] | d_loss: 1.0368 | g_loss: 0.6395
Epoch [    1/    2] | d_loss: 1.5517 | g_loss: 0.8047
Epoch [    1/    2] | d_loss: 1.3355 | g_loss: 1.0293
Epoch [    1/    2] | d_loss: 1.3185 | g_loss: 1.1582
Epoch [    1/    2] | d_loss: 1.5309 | g_loss: 1.0596
Epoch [    1/    2] | d_loss: 1.3630 | g_loss: 1.0574
Epoch [    1/    2] | d_loss: 1.4201 | g_loss: 0.9303
Epoch [    1/    2] | d_loss: 1.4207 | g_loss: 1.3886
Epoch [    1/    2] | d_loss: 1.1532 | g_loss: 0.8147
Epoch [    1/    2] | d_loss: 1.2668 | g_loss: 1.1755
Epoch [    1/    2] | d_loss: 1.6530 | g_loss: 0.8258
Epoch [    1/    2] | d_loss: 1.1985 | g_loss: 0.8730
Epoch [    1/    2] | d_loss: 1.2029 | g_loss: 1.1122
Epoch [    1/    2] | d_loss: 1.1549 | g_loss: 1.5428
Epoch [    1/    2] | d_loss: 1.3328 | g_loss: 0.8734
Epoch [    1/    2] | d_loss: 1.4580 | g_loss: 0.8036
Epoch [    1/    2] | d_loss: 1.1862 | g_loss: 1.0602
Epoch [    1/    2] | d_loss: 1.1353 | g_loss: 1.1445
Epoch [    1/    2] | d_loss: 1.1501 | g_loss: 0.8108
Epoch [    1/    2] | d_loss: 1.2498 | g_loss: 0.6945
Epoch [    1/    2] | d_loss: 1.0280 | g_loss: 0.8035
Epoch [    1/    2] | d_loss: 1.3475 | g_loss: 1.0641
Epoch [    1/    2] | d_loss: 1.3006 | g_loss: 1.1010
Epoch [    1/    2] | d_loss: 1.3325 | g_loss: 0.9214
Epoch [    1/    2] | d_loss: 1.2756 | g_loss: 1.6782
Epoch [    1/    2] | d_loss: 0.9143 | g_loss: 1.5435
Epoch [    1/    2] | d_loss: 1.3755 | g_loss: 0.7103
Epoch [    1/    2] | d_loss: 1.5886 | g_loss: 0.2273
Epoch [    1/    2] | d_loss: 1.1985 | g_loss: 0.9057
Epoch [    1/    2] | d_loss: 1.4020 | g_loss: 1.1609
Epoch [    1/    2] | d_loss: 1.5822 | g_loss: 1.6106
Epoch [    1/    2] | d_loss: 1.0717 | g_loss: 0.7407
Epoch [    1/    2] | d_loss: 1.4248 | g_loss: 1.0281
Epoch [    1/    2] | d_loss: 1.2573 | g_loss: 1.1925
Epoch [    1/    2] | d_loss: 1.0658 | g_loss: 1.0124
Epoch [    1/    2] | d_loss: 1.1284 | g_loss: 1.0525
Epoch [    1/    2] | d_loss: 1.4191 | g_loss: 1.2700
Epoch [    1/    2] | d_loss: 1.1958 | g_loss: 1.5112
Epoch [    1/    2] | d_loss: 1.4958 | g_loss: 1.0860
Epoch [    1/    2] | d_loss: 0.8831 | g_loss: 0.7715
Epoch [    1/    2] | d_loss: 1.0806 | g_loss: 0.8051
Epoch [    1/    2] | d_loss: 1.0456 | g_loss: 0.9386
Epoch [    1/    2] | d_loss: 1.0447 | g_loss: 0.8005
Epoch [    1/    2] | d_loss: 1.5467 | g_loss: 0.6456
Epoch [    1/    2] | d_loss: 1.2668 | g_loss: 0.7612
Epoch [    1/    2] | d_loss: 1.1820 | g_loss: 1.3667
Epoch [    1/    2] | d_loss: 1.2989 | g_loss: 0.3188
Epoch [    1/    2] | d_loss: 1.0656 | g_loss: 0.9090
Epoch [    1/    2] | d_loss: 1.6599 | g_loss: 1.2030
Epoch [    1/    2] | d_loss: 1.3036 | g_loss: 1.0207
Epoch [    1/    2] | d_loss: 1.2533 | g_loss: 1.0348
Epoch [    1/    2] | d_loss: 1.3869 | g_loss: 0.8535
---------------Epoch [    1/    2]---------------
Epoch [    2/    2] | d_loss: 1.2527 | g_loss: 0.8478
Epoch [    2/    2] | d_loss: 1.2948 | g_loss: 1.3493
Epoch [    2/    2] | d_loss: 1.2806 | g_loss: 1.5106
Epoch [    2/    2] | d_loss: 0.8759 | g_loss: 0.6972
Epoch [    2/    2] | d_loss: 1.3522 | g_loss: 0.9151
Epoch [    2/    2] | d_loss: 1.3041 | g_loss: 1.3086
Epoch [    2/    2] | d_loss: 1.0603 | g_loss: 1.3671
Epoch [    2/    2] | d_loss: 1.3199 | g_loss: 1.4179
Epoch [    2/    2] | d_loss: 1.2482 | g_loss: 0.6307
Epoch [    2/    2] | d_loss: 1.5654 | g_loss: 1.2615
Epoch [    2/    2] | d_loss: 1.5462 | g_loss: 1.4267
Epoch [    2/    2] | d_loss: 1.3054 | g_loss: 0.6913
Epoch [    2/    2] | d_loss: 1.0767 | g_loss: 1.5455
Epoch [    2/    2] | d_loss: 1.3502 | g_loss: 0.9649
Epoch [    2/    2] | d_loss: 1.1773 | g_loss: 0.7654
Epoch [    2/    2] | d_loss: 1.1835 | g_loss: 0.8251
Epoch [    2/    2] | d_loss: 1.3483 | g_loss: 1.0148
Epoch [    2/    2] | d_loss: 1.1493 | g_loss: 0.7184
Epoch [    2/    2] | d_loss: 1.0798 | g_loss: 1.0536
Epoch [    2/    2] | d_loss: 1.1949 | g_loss: 0.9767
Epoch [    2/    2] | d_loss: 1.4199 | g_loss: 0.8378
Epoch [    2/    2] | d_loss: 0.9341 | g_loss: 0.8458
Epoch [    2/    2] | d_loss: 1.4681 | g_loss: 1.1780
Epoch [    2/    2] | d_loss: 1.0445 | g_loss: 0.7458
Epoch [    2/    2] | d_loss: 1.3006 | g_loss: 1.8486
Epoch [    2/    2] | d_loss: 1.3609 | g_loss: 1.4684
Epoch [    2/    2] | d_loss: 1.3481 | g_loss: 0.9478
Epoch [    2/    2] | d_loss: 1.3489 | g_loss: 1.7168
Epoch [    2/    2] | d_loss: 1.0761 | g_loss: 1.2611
Epoch [    2/    2] | d_loss: 0.9974 | g_loss: 1.4543
Epoch [    2/    2] | d_loss: 1.3376 | g_loss: 0.7860
Epoch [    2/    2] | d_loss: 1.0542 | g_loss: 0.9059
Epoch [    2/    2] | d_loss: 1.2532 | g_loss: 1.3609
Epoch [    2/    2] | d_loss: 1.3054 | g_loss: 1.3554
Epoch [    2/    2] | d_loss: 1.2281 | g_loss: 1.1519
Epoch [    2/    2] | d_loss: 1.5713 | g_loss: 0.9506
Epoch [    2/    2] | d_loss: 1.0971 | g_loss: 1.2167
Epoch [    2/    2] | d_loss: 1.3220 | g_loss: 2.1622
Epoch [    2/    2] | d_loss: 1.2112 | g_loss: 1.3000
Epoch [    2/    2] | d_loss: 1.2793 | g_loss: 0.5700
Epoch [    2/    2] | d_loss: 1.2318 | g_loss: 0.8795
Epoch [    2/    2] | d_loss: 1.2313 | g_loss: 1.3290
Epoch [    2/    2] | d_loss: 1.0740 | g_loss: 1.0653
Epoch [    2/    2] | d_loss: 1.3443 | g_loss: 0.8714
Epoch [    2/    2] | d_loss: 1.2299 | g_loss: 1.2036
Epoch [    2/    2] | d_loss: 1.3266 | g_loss: 1.2819
Epoch [    2/    2] | d_loss: 1.3460 | g_loss: 0.9691
Epoch [    2/    2] | d_loss: 1.1148 | g_loss: 1.1977
Epoch [    2/    2] | d_loss: 1.0051 | g_loss: 0.6582
Epoch [    2/    2] | d_loss: 0.9263 | g_loss: 1.1808
Epoch [    2/    2] | d_loss: 1.1271 | g_loss: 2.1888
Epoch [    2/    2] | d_loss: 1.5598 | g_loss: 0.6757
Epoch [    2/    2] | d_loss: 0.9330 | g_loss: 1.2021
Epoch [    2/    2] | d_loss: 1.2087 | g_loss: 0.9759
Epoch [    2/    2] | d_loss: 1.0370 | g_loss: 0.7389
Epoch [    2/    2] | d_loss: 1.2850 | g_loss: 1.1679
Epoch [    2/    2] | d_loss: 1.3885 | g_loss: 1.2403
Epoch [    2/    2] | d_loss: 1.6642 | g_loss: 1.0060
Epoch [    2/    2] | d_loss: 1.1581 | g_loss: 1.1270
Epoch [    2/    2] | d_loss: 0.9700 | g_loss: 0.9001
Epoch [    2/    2] | d_loss: 1.2886 | g_loss: 0.8462
Epoch [    2/    2] | d_loss: 1.2505 | g_loss: 1.2609
Epoch [    2/    2] | d_loss: 1.1035 | g_loss: 1.7791
Epoch [    2/    2] | d_loss: 1.1869 | g_loss: 1.1611
Epoch [    2/    2] | d_loss: 1.2771 | g_loss: 0.8748
Epoch [    2/    2] | d_loss: 1.1918 | g_loss: 1.0789
Epoch [    2/    2] | d_loss: 1.2283 | g_loss: 0.9125
Epoch [    2/    2] | d_loss: 0.9235 | g_loss: 0.9040
Epoch [    2/    2] | d_loss: 1.3772 | g_loss: 1.0962
Epoch [    2/    2] | d_loss: 1.0105 | g_loss: 1.6515
Epoch [    2/    2] | d_loss: 1.0970 | g_loss: 1.1108
Epoch [    2/    2] | d_loss: 1.0057 | g_loss: 0.7641
Epoch [    2/    2] | d_loss: 1.2008 | g_loss: 1.4295
Epoch [    2/    2] | d_loss: 1.3591 | g_loss: 1.5951
Epoch [    2/    2] | d_loss: 1.0368 | g_loss: 0.9509
Epoch [    2/    2] | d_loss: 1.2370 | g_loss: 1.7266
Epoch [    2/    2] | d_loss: 1.1311 | g_loss: 1.5283
Epoch [    2/    2] | d_loss: 1.0632 | g_loss: 1.3632
Epoch [    2/    2] | d_loss: 1.1546 | g_loss: 0.4200
Epoch [    2/    2] | d_loss: 1.3749 | g_loss: 1.5472
Epoch [    2/    2] | d_loss: 1.3035 | g_loss: 0.9801
Epoch [    2/    2] | d_loss: 1.1022 | g_loss: 1.6478
Epoch [    2/    2] | d_loss: 1.1165 | g_loss: 0.7664
Epoch [    2/    2] | d_loss: 1.1126 | g_loss: 1.4446
Epoch [    2/    2] | d_loss: 1.2290 | g_loss: 1.2022
Epoch [    2/    2] | d_loss: 1.2985 | g_loss: 1.7118
---------------Epoch [    2/    2]---------------
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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 0x7ff6a5b38ef0&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=" 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=" 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> 
I trained the model for 20 epochs nearly 1 hr of training with different optimizer and network size. an i got learning rate value from original DCGAN paper.</p>
<p>learning rate = 0.0002</p>
<p>trial 1
d_conv_dim = 32 g_conv_dim = 32 z_size = 100 epochs = 20</p>
<p>discriminator loss starts from 1.5 and slowly reduced to 0.5 generator loss starts from 2.0 and slowly decreases up to 5 epochs and the loss start increasing 3.5 after 20 epochs</p>
<p>trial 2
d_conv_dim = 64 g_conv_dim = 64 z_size = 100 epochs = 16</p>
<p>discriminator loss starts from 1.5 and slowly reduced to 0.73 at 16th epoch generator loss starts from 4.4 and slowly decreases up to 10 epochs to 0.50 and the loss goes zig-zag like sinusoidal between 2.2 to 1.3</p>
<p>trial 2
d_conv_dim = 128 g_conv_dim = 128 z_size = 100 epochs = 20</p>
<p>discriminator loss starts from 1.7 and slowly reduced to 0.62 at 20th epochs generator loss starts from 5.4 and slowly decreases to 0.3 up to 16 epochs and the loss goes zig-zag like sinusoidal between 2.9 to 1.1</p>
<p>trial 3
i changed the optimizer to SGD with momentum 0.5 d_conv_dim = 32 g_conv_dim = 32 z_size = 100 epochs = 10</p>
<p>discriminator loss and generator loss starts increasing 1.0 to 22.4224 and at end no image is generated. So i drop this.</p>
<p>So i think increasing the Conv dimension and reducing the epochs can produce the best result. even increasing the image size to 64 can produce more accurate image with little clarity</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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