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 */
    </style>
<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 */
.highlight .mh { color: #666666 } /* Literal.Number.Hex */
.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 */
.highlight .vm { color: #19177C } /* Name.Variable.Magic */
.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="p">,</span> <span class="n">transforms</span>
<span class="kn">from</span> <span class="nn">torch.utils.data</span> <span class="k">import</span> <span class="n">DataLoader</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">data_preproc</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span><span class="n">transforms</span><span class="o">.</span><span class="n">Resize</span><span class="p">(</span><span class="n">image_size</span><span class="p">),</span> <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">()])</span>
    
    <span class="n">dataset</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">root</span><span class="o">=</span><span class="n">data_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">data_preproc</span><span class="p">)</span>
    
    <span class="n">dataloader</span> <span class="o">=</span> <span class="n">DataLoader</span><span class="p">(</span><span class="n">dataset</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">dataloader</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">16</span>
<span class="n">img_size</span> <span class="o">=</span> <span class="mi">32</span>

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

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

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

<span class="c1"># plot the images in the batch, along with the corresponding labels</span>
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
<span class="n">plot_size</span><span class="o">=</span><span class="mi">16</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="n">min_val</span><span class="p">,</span> <span class="n">max_val</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="n">max_val</span><span class="o">-</span><span class="n">min_val</span><span class="p">)</span> <span class="o">+</span> <span class="n">min_val</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(-1.)
Max:  tensor(0.6784)
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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">from</span> <span class="nn">torch</span> <span class="k">import</span> <span class="n">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="k">def</span> <span class="nf">conv</span><span class="p">(</span><span class="n">input_depth</span><span class="p">,</span> <span class="n">output_depth</span><span class="p">,</span> <span class="n">kernel_size</span><span class="o">=</span><span class="mi">4</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="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">input_depth</span><span class="p">,</span> <span class="n">out_channels</span><span class="o">=</span><span class="n">output_depth</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">output_depth</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="c1"># class Discriminator(nn.Module):</span>

<span class="c1">#     def __init__(self, conv_dim):</span>
<span class="c1">#         &quot;&quot;&quot;</span>
<span class="c1">#         Initialize the Discriminator Module</span>
<span class="c1">#         :param conv_dim: The depth of the first convolutional layer</span>
<span class="c1">#         &quot;&quot;&quot;</span>
<span class="c1">#         super(Discriminator, self).__init__()</span>

<span class="c1">#         self.conv_dim = conv_dim</span>
        
<span class="c1">#         # 32*32*3 -&gt; 16*16*(conv_dim)</span>
<span class="c1">#         self.conv1 = conv(3, conv_dim, kernel_size=4, batch_norm=False)</span>
        
<span class="c1">#         # 16*16*(conv_dim) -&gt; 8*8*(conv_dim*2)</span>
<span class="c1">#         self.conv2 = conv(conv_dim, conv_dim*2, kernel_size=4, batch_norm=True)</span>
        
<span class="c1">#         # 8*8*(conv_dim*2) -&gt; 4*4*(conv_dim*4)</span>
<span class="c1">#         self.conv3 = conv(conv_dim*2, conv_dim*4, kernel_size=4, batch_norm=True)</span>
        
<span class="c1">#         # Final fc layer</span>
<span class="c1">#         self.fc = nn.Linear(conv_dim*4*4*4, 1)</span>
        

<span class="c1">#     def forward(self, x):</span>
<span class="c1">#         &quot;&quot;&quot;</span>
<span class="c1">#         Forward propagation of the neural network</span>
<span class="c1">#         :param x: The input to the neural network     </span>
<span class="c1">#         :return: Discriminator logits; the output of the neural network</span>
<span class="c1">#         &quot;&quot;&quot;</span>
<span class="c1">#         # define feedforward behavior</span>
        
<span class="c1">#         x = F.leaky_relu(self.conv1(x), 0.2)</span>
<span class="c1">#         x = F.leaky_relu(self.conv2(x), 0.2)</span>
<span class="c1">#         x = F.leaky_relu(self.conv3(x), 0.2)</span>
        
<span class="c1">#         # Resize the tensor for FC layers</span>
<span class="c1">#         x = x.view(-1, self.conv_dim*4*4*4)</span>
<span class="c1">#         x = self.fc(x)</span>
        
<span class="c1">#         #x = F.sigmoid(x)</span>
        
<span class="c1">#         return x</span>


<span class="c1"># &quot;&quot;&quot;</span>
<span class="c1"># DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="c1"># &quot;&quot;&quot;</span>
<span class="c1"># tests.test_discriminator(Discriminator)</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="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"># 32*32*3 -&gt; 16*16*(conv_dim)</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="n">kernel_size</span><span class="o">=</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"># 16*16*(conv_dim) -&gt; 8*8*(conv_dim*2)</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="n">kernel_size</span><span class="o">=</span><span class="mi">4</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="c1"># 8*8*(conv_dim*2) -&gt; 4*4*(conv_dim*4)</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="n">kernel_size</span><span class="o">=</span><span class="mi">4</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="c1"># 4*4*(conv_dim*4) -&gt; 2*2*(conv_dim*8)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv4</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">8</span><span class="p">,</span> <span class="n">kernel_size</span><span class="o">=</span><span class="mi">4</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="c1"># Final fc layer</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">fc</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">8</span><span class="o">*</span><span class="mi">2</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
        

    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Forward propagation of the neural network</span>
<span class="sd">        :param x: The input to the neural network     </span>
<span class="sd">        :return: Discriminator logits; the output of the neural network</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="c1"># 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="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="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="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">conv4</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"># Resize the tensor for FC layers</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">8</span><span class="o">*</span><span class="mi">2</span><span class="o">*</span><span class="mi">2</span><span class="p">)</span>
        <span class="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="c1">#x = F.sigmoid(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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<pre>Tests Passed
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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">input_depth</span><span class="p">,</span> <span class="n">output_depth</span><span class="p">,</span> <span class="n">kernel_size</span><span class="o">=</span><span class="mi">4</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="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
    
    <span class="n">transpose_conv_layer</span> <span class="o">=</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="o">=</span><span class="n">input_depth</span><span class="p">,</span> <span class="n">out_channels</span><span class="o">=</span><span class="n">output_depth</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">transpose_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">output_depth</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="c1"># class Generator(nn.Module):</span>
    
<span class="c1">#     def __init__(self, z_size, conv_dim):</span>
<span class="c1">#         &quot;&quot;&quot;</span>
<span class="c1">#         Initialize the Generator Module</span>
<span class="c1">#         :param z_size: The length of the input latent vector, z</span>
<span class="c1">#         :param conv_dim: The depth of the inputs to the *last* transpose convolutional layer</span>
<span class="c1">#         &quot;&quot;&quot;</span>
<span class="c1">#         super(Generator, self).__init__()</span>

<span class="c1">#         self.conv_dim = conv_dim</span>
        
<span class="c1">#         self.fc = nn.Linear(z_size, conv_dim*4*4*4)</span>
        
<span class="c1">#         self.t_conv1 = deconv(conv_dim*4, conv_dim*2, kernel_size=4, batch_norm=True)</span>
        
<span class="c1">#         self.t_conv2 = deconv(conv_dim*2, conv_dim, kernel_size=4, batch_norm=True)</span>
        
<span class="c1">#         self.t_conv3 = deconv(conv_dim, 3, kernel_size=4, batch_norm=False) #No Batchnorm for last layer</span>
        

<span class="c1">#     def forward(self, x):</span>
<span class="c1">#         &quot;&quot;&quot;</span>
<span class="c1">#         Forward propagation of the neural network</span>
<span class="c1">#         :param x: The input to the neural network     </span>
<span class="c1">#         :return: A 32x32x3 Tensor image as output</span>
<span class="c1">#         &quot;&quot;&quot;</span>
<span class="c1">#         # define feedforward behavior</span>
        
<span class="c1">#         x = self.fc(x)</span>
<span class="c1">#         #reshape x for convolutional layers</span>
<span class="c1">#         x = x.view(-1, self.conv_dim*4, 4, 4)</span>
        
<span class="c1">#         x = F.relu(self.t_conv1(x))</span>
<span class="c1">#         x = F.relu(self.t_conv2(x))</span>
        
<span class="c1">#         #Last layer uses tanh</span>
<span class="c1">#         x = F.tanh(self.t_conv3(x))</span>
        
<span class="c1">#         return x</span>

<span class="c1"># &quot;&quot;&quot;</span>
<span class="c1"># DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="c1"># &quot;&quot;&quot;</span>
<span class="c1"># tests.test_generator(Generator)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">class</span> <span class="nc">Generator</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
    
    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Initialize the Generator Module</span>
<span class="sd">        :param z_size: The length of the input latent vector, z</span>
<span class="sd">        :param conv_dim: The depth of the inputs to the *last* transpose convolutional layer</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">Generator</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>

        <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span> <span class="o">=</span> <span class="n">conv_dim</span>
        
        <span class="bp">self</span><span class="o">.</span><span class="n">fc</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">8</span><span class="o">*</span><span class="mi">2</span><span class="o">*</span><span class="mi">2</span><span class="p">)</span>
        
        <span class="bp">self</span><span class="o">.</span><span class="n">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">8</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="n">kernel_size</span><span class="o">=</span><span class="mi">4</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="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">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="n">kernel_size</span><span class="o">=</span><span class="mi">4</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="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="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">,</span> <span class="n">kernel_size</span><span class="o">=</span><span class="mi">4</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="bp">self</span><span class="o">.</span><span class="n">t_conv4</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="n">kernel_size</span><span class="o">=</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">#No Batchnorm for last layer</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="c1">#reshape x for convolutional layers</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">8</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
        
        <span class="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="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="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_conv3</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
        
        <span class="c1">#Last layer uses tanh</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_conv4</span><span class="p">(</span><span class="n">x</span><span class="p">))</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="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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<pre>Tests Passed
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<h2 id="Initialize-the-weights-of-your-networks">Initialize the weights of your networks<a class="anchor-link" href="#Initialize-the-weights-of-your-networks">&#182;</a></h2><p>To help your models converge, you should initialize the weights of the convolutional and linear layers in your model. From reading the <a href="https://arxiv.org/pdf/1511.06434.pdf">original DCGAN paper</a>, they say:</p>
<blockquote><p>All weights were initialized from a zero-centered Normal distribution with standard deviation 0.02.</p>
</blockquote>
<p>So, your next task will be to define a weight initialization function that does just this!</p>
<p>You can refer back to the lesson on weight initialization or even consult existing model code, such as that from <a href="https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/blob/master/models/networks.py">the <code>networks.py</code> file in CycleGAN Github repository</a> to help you complete this function.</p>
<h4 id="Exercise:-Complete-the-weight-initialization-function">Exercise: Complete the weight initialization function<a class="anchor-link" href="#Exercise:-Complete-the-weight-initialization-function">&#182;</a></h4><ul>
<li>This should initialize only <strong>convolutional</strong> and <strong>linear</strong> layers</li>
<li>Initialize the weights to a normal distribution, centered around 0, with a standard deviation of 0.02.</li>
<li>The bias terms, if they exist, may be left alone or set to 0.</li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">weights_init_normal</span><span class="p">(</span><span class="n">m</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Applies initial weights to certain layers in a model .</span>
<span class="sd">    The weights are taken from a normal distribution </span>
<span class="sd">    with mean = 0, std dev = 0.02.</span>
<span class="sd">    :param m: A module or layer in a network    </span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1"># classname will be something like:</span>
    <span class="c1"># `Conv`, `BatchNorm2d`, `Linear`, etc.</span>
    <span class="n">classname</span> <span class="o">=</span> <span class="n">m</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span>
    
    <span class="c1"># TODO: Apply initial weights to convolutional and linear layers</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">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">normal_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">)</span>
        <span class="c1"># We have disabled bias in our modules but the following code snippet is used to set bias</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">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">constant_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">)</span>
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<h2 id="Build-complete-network">Build complete network<a class="anchor-link" href="#Build-complete-network">&#182;</a></h2><p>Define your models' hyperparameters and instantiate the discriminator and generator from the classes defined above. Make sure you've passed in the correct input arguments.</p>

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

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

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

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

Generator(
  (fc): Linear(in_features=100, out_features=2048, bias=True)
  (t_conv1): Sequential(
    (0): ConvTranspose2d(512, 256, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (t_conv2): Sequential(
    (0): ConvTranspose2d(256, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (t_conv3): 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_conv4): Sequential(
    (0): ConvTranspose2d(64, 3, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
  )
)
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<h3 id="Training-on-GPU">Training on GPU<a class="anchor-link" href="#Training-on-GPU">&#182;</a></h3><p>Check if you can train on GPU. Here, we'll set this as a boolean variable <code>train_on_gpu</code>. Later, you'll be responsible for making sure that</p>
<blockquote><ul>
<li>Models,</li>
<li>Model inputs, and</li>
<li>Loss function arguments</li>
</ul>
</blockquote>
<p>Are moved to GPU, where appropriate.</p>

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

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

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Least squares loss has been shown to produce better results so I chose it</span>
<span class="c1"># LSGAN reference -&gt; https://arxiv.org/pdf/1611.04076.pdf</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">loss</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">mean</span><span class="p">((</span><span class="n">D_out</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">loss</span>

<span class="k">def</span> <span class="nf">fake_loss</span><span class="p">(</span><span class="n">D_out</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39;Calculates how close discriminator outputs are to being fake.</span>
<span class="sd">       param, D_out: discriminator logits</span>
<span class="sd">       return: fake loss&#39;&#39;&#39;</span>
    <span class="n">loss</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">D_out</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">loss</span>
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<h2 id="Optimizers">Optimizers<a class="anchor-link" href="#Optimizers">&#182;</a></h2><h4 id="Exercise:-Define-optimizers-for-your-Discriminator-(D)-and-Generator-(G)">Exercise: Define optimizers for your Discriminator (D) and Generator (G)<a class="anchor-link" href="#Exercise:-Define-optimizers-for-your-Discriminator-(D)-and-Generator-(G)">&#182;</a></h4><p>Define optimizers for your models with appropriate hyperparameters.</p>

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

<span class="n">learn_rate</span> <span class="o">=</span> <span class="mf">0.001</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">0.999</span> <span class="c1">#default value</span>
<span class="c1"># Create optimizers for the discriminator D and generator G</span>
<span class="n">d_optimizer</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">(</span><span class="n">D</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">learn_rate</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">learn_rate</span><span class="p">,</span> <span class="p">[</span><span class="n">beta1</span><span class="p">,</span> <span class="n">beta2</span><span class="p">])</span>
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<h2 id="Training">Training<a class="anchor-link" href="#Training">&#182;</a></h2><p>Training will involve alternating between training the discriminator and the generator. You'll use your functions <code>real_loss</code> and <code>fake_loss</code> to help you calculate the discriminator losses.</p>
<ul>
<li>You should train the discriminator by alternating on real and fake images</li>
<li>Then the generator, which tries to trick the discriminator and should have an opposing loss function</li>
</ul>
<h4 id="Saving-Samples">Saving Samples<a class="anchor-link" href="#Saving-Samples">&#182;</a></h4><p>You've been given some code to print out some loss statistics and save some generated "fake" samples.</p>

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

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

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

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

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

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

            <span class="n">batch_size</span> <span class="o">=</span> <span class="n">real_images</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
            <span class="n">real_images</span> <span class="o">=</span> <span class="n">scale</span><span class="p">(</span><span class="n">real_images</span><span class="p">)</span>
            
            <span class="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="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="c1"># Pass real images through disc &amp; calculate real loss</span>
            <span class="n">d_out_real</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">real_images</span><span class="p">)</span>
            <span class="n">d_real_loss</span> <span class="o">=</span> <span class="n">real_loss</span><span class="p">(</span><span class="n">d_out_real</span><span class="p">)</span>
            
            <span class="c1"># Generate fake img through latent vector z &amp; calculate fake loss</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_img</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_out_fake</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">fake_img</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_out_fake</span><span class="p">)</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="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_img</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_out_fake</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">fake_img</span><span class="p">)</span>
            
            <span class="n">g_loss</span> <span class="o">=</span> <span class="n">real_loss</span><span class="p">(</span><span class="n">d_out_fake</span><span class="p">)</span>
            <span class="n">g_loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
            <span class="n">g_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
            
            
            <span class="c1"># ===============================================</span>
            <span class="c1">#              END OF YOUR CODE</span>
            <span class="c1"># ===============================================</span>

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


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

    <span class="c1"># Save training generator samples</span>
    <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;train_samples.pkl&#39;</span><span class="p">,</span> <span class="s1">&#39;wb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
        <span class="n">pkl</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">samples</span><span class="p">,</span> <span class="n">f</span><span class="p">)</span>
    
    <span class="c1"># finally return losses</span>
    <span class="k">return</span> <span class="n">losses</span>
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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;[22]:</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">50</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> <span class="n">print_every</span><span class="o">=</span><span class="mi">500</span><span class="p">)</span>
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<pre>Epoch [    1/   50] | d_loss: 1.1819 | g_loss: 4.0737
Epoch [    1/   50] | d_loss: 0.7348 | g_loss: 1.3972
Epoch [    1/   50] | d_loss: 0.5987 | g_loss: 0.7552
Epoch [    1/   50] | d_loss: 0.4917 | g_loss: 0.5571
Epoch [    1/   50] | d_loss: 0.5019 | g_loss: 0.5399
Epoch [    1/   50] | d_loss: 0.4064 | g_loss: 0.5478
Epoch [    1/   50] | d_loss: 0.3142 | g_loss: 0.5478
Epoch [    1/   50] | d_loss: 0.4517 | g_loss: 0.7551
Epoch [    1/   50] | d_loss: 0.4085 | g_loss: 0.7184
Epoch [    1/   50] | d_loss: 0.4155 | g_loss: 0.3415
Epoch [    1/   50] | d_loss: 0.4496 | g_loss: 1.2192
Epoch [    1/   50] | d_loss: 0.3697 | g_loss: 0.3836
Epoch [    2/   50] | d_loss: 0.4525 | g_loss: 0.6267
Epoch [    2/   50] | d_loss: 0.4593 | g_loss: 1.3800
Epoch [    2/   50] | d_loss: 0.3825 | g_loss: 0.4408
Epoch [    2/   50] | d_loss: 0.2435 | g_loss: 0.4629
Epoch [    2/   50] | d_loss: 0.4439 | g_loss: 0.8543
Epoch [    2/   50] | d_loss: 0.2573 | g_loss: 0.4559
Epoch [    2/   50] | d_loss: 0.4704 | g_loss: 0.2658
Epoch [    2/   50] | d_loss: 0.2989 | g_loss: 0.4133
Epoch [    2/   50] | d_loss: 0.8170 | g_loss: 0.2403
Epoch [    2/   50] | d_loss: 0.3794 | g_loss: 0.6150
Epoch [    2/   50] | d_loss: 0.4076 | g_loss: 0.3781
Epoch [    2/   50] | d_loss: 0.3842 | g_loss: 0.3182
Epoch [    3/   50] | d_loss: 0.4290 | g_loss: 0.5965
Epoch [    3/   50] | d_loss: 0.2232 | g_loss: 0.4184
Epoch [    3/   50] | d_loss: 0.3107 | g_loss: 0.8232
Epoch [    3/   50] | d_loss: 0.3012 | g_loss: 0.9794
Epoch [    3/   50] | d_loss: 0.7329 | g_loss: 0.9282
Epoch [    3/   50] | d_loss: 0.3818 | g_loss: 0.5539
Epoch [    3/   50] | d_loss: 0.1269 | g_loss: 0.7856
Epoch [    3/   50] | d_loss: 0.1787 | g_loss: 0.3991
Epoch [    3/   50] | d_loss: 0.4093 | g_loss: 0.9002
Epoch [    3/   50] | d_loss: 0.2452 | g_loss: 0.9300
Epoch [    3/   50] | d_loss: 0.3269 | g_loss: 0.1522
Epoch [    3/   50] | d_loss: 0.5008 | g_loss: 0.8197
Epoch [    4/   50] | d_loss: 0.2400 | g_loss: 0.4223
Epoch [    4/   50] | d_loss: 0.3010 | g_loss: 0.8603
Epoch [    4/   50] | d_loss: 0.1538 | g_loss: 0.8052
Epoch [    4/   50] | d_loss: 0.1827 | g_loss: 0.6508
Epoch [    4/   50] | d_loss: 0.2609 | g_loss: 0.4090
Epoch [    4/   50] | d_loss: 0.2489 | g_loss: 0.6336
Epoch [    4/   50] | d_loss: 0.1551 | g_loss: 0.5230
Epoch [    4/   50] | d_loss: 0.6692 | g_loss: 0.2884
Epoch [    4/   50] | d_loss: 0.2915 | g_loss: 0.4225
Epoch [    4/   50] | d_loss: 0.1766 | g_loss: 0.5108
Epoch [    4/   50] | d_loss: 0.2177 | g_loss: 0.6214
Epoch [    4/   50] | d_loss: 0.2413 | g_loss: 0.8199
Epoch [    5/   50] | d_loss: 0.2098 | g_loss: 0.8068
Epoch [    5/   50] | d_loss: 0.3608 | g_loss: 0.3154
Epoch [    5/   50] | d_loss: 0.1595 | g_loss: 0.3201
Epoch [    5/   50] | d_loss: 0.3077 | g_loss: 0.6506
Epoch [    5/   50] | d_loss: 0.1944 | g_loss: 1.3167
Epoch [    5/   50] | d_loss: 0.1989 | g_loss: 0.4287
Epoch [    5/   50] | d_loss: 0.1996 | g_loss: 0.6177
Epoch [    5/   50] | d_loss: 0.2313 | g_loss: 1.0402
Epoch [    5/   50] | d_loss: 0.1822 | g_loss: 0.5105
Epoch [    5/   50] | d_loss: 0.3673 | g_loss: 0.4844
Epoch [    5/   50] | d_loss: 0.0998 | g_loss: 0.9814
Epoch [    5/   50] | d_loss: 0.2893 | g_loss: 0.6714
Epoch [    6/   50] | d_loss: 0.0744 | g_loss: 0.6189
Epoch [    6/   50] | d_loss: 0.2469 | g_loss: 0.8531
Epoch [    6/   50] | d_loss: 0.1614 | g_loss: 1.1852
Epoch [    6/   50] | d_loss: 0.1064 | g_loss: 1.2700
Epoch [    6/   50] | d_loss: 0.4061 | g_loss: 0.4299
Epoch [    6/   50] | d_loss: 0.2239 | g_loss: 1.2539
Epoch [    6/   50] | d_loss: 0.0998 | g_loss: 0.7591
Epoch [    6/   50] | d_loss: 0.3439 | g_loss: 0.7399
Epoch [    6/   50] | d_loss: 0.1479 | g_loss: 0.9486
Epoch [    6/   50] | d_loss: 0.3159 | g_loss: 0.8254
Epoch [    6/   50] | d_loss: 0.2862 | g_loss: 0.0732
Epoch [    6/   50] | d_loss: 0.2220 | g_loss: 0.8005
Epoch [    7/   50] | d_loss: 0.1587 | g_loss: 0.8458
Epoch [    7/   50] | d_loss: 0.2508 | g_loss: 0.7652
Epoch [    7/   50] | d_loss: 0.1957 | g_loss: 0.6144
Epoch [    7/   50] | d_loss: 0.1729 | g_loss: 0.7313
Epoch [    7/   50] | d_loss: 0.2652 | g_loss: 0.8990
Epoch [    7/   50] | d_loss: 0.0793 | g_loss: 0.9110
Epoch [    7/   50] | d_loss: 0.2603 | g_loss: 1.3078
Epoch [    7/   50] | d_loss: 0.1771 | g_loss: 0.6612
Epoch [    7/   50] | d_loss: 0.2149 | g_loss: 0.3388
Epoch [    7/   50] | d_loss: 0.0727 | g_loss: 0.7717
Epoch [    7/   50] | d_loss: 0.2455 | g_loss: 0.3407
Epoch [    7/   50] | d_loss: 0.1864 | g_loss: 0.5911
Epoch [    8/   50] | d_loss: 0.1571 | g_loss: 0.8343
Epoch [    8/   50] | d_loss: 0.1118 | g_loss: 1.0955
Epoch [    8/   50] | d_loss: 0.2714 | g_loss: 1.0287
Epoch [    8/   50] | d_loss: 0.0571 | g_loss: 0.4328
Epoch [    8/   50] | d_loss: 0.0622 | g_loss: 0.6038
Epoch [    8/   50] | d_loss: 0.3151 | g_loss: 0.4170
Epoch [    8/   50] | d_loss: 0.1520 | g_loss: 0.8451
Epoch [    8/   50] | d_loss: 0.1236 | g_loss: 0.3694
Epoch [    8/   50] | d_loss: 0.2143 | g_loss: 1.3740
Epoch [    8/   50] | d_loss: 0.5157 | g_loss: 1.5605
Epoch [    8/   50] | d_loss: 0.3725 | g_loss: 0.7747
Epoch [    8/   50] | d_loss: 0.1279 | g_loss: 0.5256
Epoch [    9/   50] | d_loss: 0.1807 | g_loss: 0.7903
Epoch [    9/   50] | d_loss: 0.6007 | g_loss: 0.5796
Epoch [    9/   50] | d_loss: 0.0763 | g_loss: 0.6605
Epoch [    9/   50] | d_loss: 0.3586 | g_loss: 0.5988
Epoch [    9/   50] | d_loss: 0.1776 | g_loss: 1.1730
Epoch [    9/   50] | d_loss: 0.1186 | g_loss: 0.7386
Epoch [    9/   50] | d_loss: 0.1437 | g_loss: 0.7863
Epoch [    9/   50] | d_loss: 0.1776 | g_loss: 1.2267
Epoch [    9/   50] | d_loss: 0.3432 | g_loss: 0.6808
Epoch [    9/   50] | d_loss: 0.3259 | g_loss: 0.5108
Epoch [    9/   50] | d_loss: 0.0951 | g_loss: 0.9984
Epoch [    9/   50] | d_loss: 0.2741 | g_loss: 0.8527
Epoch [   10/   50] | d_loss: 0.4158 | g_loss: 1.1455
Epoch [   10/   50] | d_loss: 0.0934 | g_loss: 0.8400
Epoch [   10/   50] | d_loss: 0.2557 | g_loss: 0.2910
Epoch [   10/   50] | d_loss: 0.2188 | g_loss: 0.4584
Epoch [   10/   50] | d_loss: 0.0667 | g_loss: 0.7996
Epoch [   10/   50] | d_loss: 0.2611 | g_loss: 0.6665
Epoch [   10/   50] | d_loss: 0.7222 | g_loss: 0.1045
Epoch [   10/   50] | d_loss: 0.0598 | g_loss: 0.8326
Epoch [   10/   50] | d_loss: 0.2476 | g_loss: 0.6799
Epoch [   10/   50] | d_loss: 0.2454 | g_loss: 0.7173
Epoch [   10/   50] | d_loss: 0.1704 | g_loss: 0.7460
Epoch [   10/   50] | d_loss: 0.3245 | g_loss: 1.2275
Epoch [   11/   50] | d_loss: 0.0929 | g_loss: 0.4628
Epoch [   11/   50] | d_loss: 0.1109 | g_loss: 1.3204
Epoch [   11/   50] | d_loss: 0.0644 | g_loss: 1.1709
Epoch [   11/   50] | d_loss: 0.2897 | g_loss: 1.1018
Epoch [   11/   50] | d_loss: 0.4334 | g_loss: 0.2708
Epoch [   11/   50] | d_loss: 0.2462 | g_loss: 0.6372
Epoch [   11/   50] | d_loss: 0.0593 | g_loss: 0.8026
Epoch [   11/   50] | d_loss: 0.1058 | g_loss: 0.6992
Epoch [   11/   50] | d_loss: 0.1364 | g_loss: 0.5949
Epoch [   11/   50] | d_loss: 0.1345 | g_loss: 0.5262
Epoch [   11/   50] | d_loss: 0.2229 | g_loss: 0.8613
Epoch [   11/   50] | d_loss: 0.0462 | g_loss: 1.2466
Epoch [   12/   50] | d_loss: 0.0658 | g_loss: 0.5162
Epoch [   12/   50] | d_loss: 0.3520 | g_loss: 0.6550
Epoch [   12/   50] | d_loss: 0.1337 | g_loss: 0.7653
Epoch [   12/   50] | d_loss: 0.1344 | g_loss: 0.8844
Epoch [   12/   50] | d_loss: 0.1440 | g_loss: 1.1855
Epoch [   12/   50] | d_loss: 0.0723 | g_loss: 0.9091
Epoch [   12/   50] | d_loss: 0.1449 | g_loss: 1.3889
Epoch [   12/   50] | d_loss: 0.0909 | g_loss: 0.5725
Epoch [   12/   50] | d_loss: 0.0368 | g_loss: 0.5055
Epoch [   12/   50] | d_loss: 0.3788 | g_loss: 1.1580
Epoch [   12/   50] | d_loss: 0.0502 | g_loss: 1.1169
Epoch [   12/   50] | d_loss: 0.0459 | g_loss: 1.0836
Epoch [   13/   50] | d_loss: 0.1028 | g_loss: 1.3850
Epoch [   13/   50] | d_loss: 0.0692 | g_loss: 0.8189
Epoch [   13/   50] | d_loss: 0.3517 | g_loss: 0.5835
Epoch [   13/   50] | d_loss: 0.1018 | g_loss: 0.5641
Epoch [   13/   50] | d_loss: 0.0751 | g_loss: 0.9106
Epoch [   13/   50] | d_loss: 0.2117 | g_loss: 1.2109
Epoch [   13/   50] | d_loss: 0.0833 | g_loss: 0.8203
Epoch [   13/   50] | d_loss: 0.1835 | g_loss: 0.7795
Epoch [   13/   50] | d_loss: 0.0730 | g_loss: 0.7264
Epoch [   13/   50] | d_loss: 0.0631 | g_loss: 1.1748
Epoch [   13/   50] | d_loss: 0.0447 | g_loss: 1.0189
Epoch [   13/   50] | d_loss: 0.0532 | g_loss: 0.6730
Epoch [   14/   50] | d_loss: 0.0534 | g_loss: 0.7295
Epoch [   14/   50] | d_loss: 0.1308 | g_loss: 1.1982
Epoch [   14/   50] | d_loss: 0.1112 | g_loss: 0.9359
Epoch [   14/   50] | d_loss: 0.1329 | g_loss: 0.9381
Epoch [   14/   50] | d_loss: 0.3424 | g_loss: 0.4506
Epoch [   14/   50] | d_loss: 0.1936 | g_loss: 1.2392
Epoch [   14/   50] | d_loss: 0.0824 | g_loss: 1.2990
Epoch [   14/   50] | d_loss: 0.1735 | g_loss: 0.8421
Epoch [   14/   50] | d_loss: 0.2725 | g_loss: 1.5960
Epoch [   14/   50] | d_loss: 0.1810 | g_loss: 0.5381
Epoch [   14/   50] | d_loss: 0.1504 | g_loss: 0.7130
Epoch [   14/   50] | d_loss: 0.1948 | g_loss: 1.0298
Epoch [   15/   50] | d_loss: 0.1494 | g_loss: 1.2316
Epoch [   15/   50] | d_loss: 0.0448 | g_loss: 0.4796
Epoch [   15/   50] | d_loss: 0.1492 | g_loss: 0.9796
Epoch [   15/   50] | d_loss: 0.0850 | g_loss: 0.5822
Epoch [   15/   50] | d_loss: 0.0477 | g_loss: 0.9552
Epoch [   15/   50] | d_loss: 0.0727 | g_loss: 0.6332
Epoch [   15/   50] | d_loss: 0.1570 | g_loss: 0.7457
Epoch [   15/   50] | d_loss: 0.2734 | g_loss: 0.5492
Epoch [   15/   50] | d_loss: 0.0929 | g_loss: 1.0942
Epoch [   15/   50] | d_loss: 0.1239 | g_loss: 0.8129
Epoch [   15/   50] | d_loss: 0.0784 | g_loss: 0.6377
Epoch [   15/   50] | d_loss: 0.1032 | g_loss: 0.5999
Epoch [   16/   50] | d_loss: 0.1570 | g_loss: 1.1634
Epoch [   16/   50] | d_loss: 0.1311 | g_loss: 0.8898
Epoch [   16/   50] | d_loss: 0.0815 | g_loss: 1.0514
Epoch [   16/   50] | d_loss: 0.2527 | g_loss: 0.5172
Epoch [   16/   50] | d_loss: 0.0661 | g_loss: 1.0886
Epoch [   16/   50] | d_loss: 0.0816 | g_loss: 0.5366
Epoch [   16/   50] | d_loss: 0.0468 | g_loss: 0.7943
Epoch [   16/   50] | d_loss: 0.2298 | g_loss: 0.4412
Epoch [   16/   50] | d_loss: 0.0857 | g_loss: 0.3699
Epoch [   16/   50] | d_loss: 0.0822 | g_loss: 0.9566
Epoch [   16/   50] | d_loss: 0.0655 | g_loss: 1.3527
Epoch [   16/   50] | d_loss: 0.1163 | g_loss: 0.7283
Epoch [   17/   50] | d_loss: 0.0982 | g_loss: 0.8441
Epoch [   17/   50] | d_loss: 0.1036 | g_loss: 0.5942
Epoch [   17/   50] | d_loss: 0.1055 | g_loss: 0.6476
Epoch [   17/   50] | d_loss: 0.2610 | g_loss: 1.2549
Epoch [   17/   50] | d_loss: 0.1041 | g_loss: 0.7884
Epoch [   17/   50] | d_loss: 0.0561 | g_loss: 0.4820
Epoch [   17/   50] | d_loss: 0.0889 | g_loss: 0.4453
Epoch [   17/   50] | d_loss: 0.0766 | g_loss: 0.7726
Epoch [   17/   50] | d_loss: 0.2836 | g_loss: 0.5600
Epoch [   17/   50] | d_loss: 0.1365 | g_loss: 0.6102
Epoch [   17/   50] | d_loss: 0.0382 | g_loss: 0.6931
Epoch [   17/   50] | d_loss: 0.3010 | g_loss: 0.7311
Epoch [   18/   50] | d_loss: 0.2517 | g_loss: 0.5615
Epoch [   18/   50] | d_loss: 0.0505 | g_loss: 0.7605
Epoch [   18/   50] | d_loss: 0.1250 | g_loss: 0.7026
Epoch [   18/   50] | d_loss: 0.0657 | g_loss: 0.7918
Epoch [   18/   50] | d_loss: 0.1278 | g_loss: 0.8805
Epoch [   18/   50] | d_loss: 0.1843 | g_loss: 0.9998
Epoch [   18/   50] | d_loss: 0.0576 | g_loss: 1.0348
Epoch [   18/   50] | d_loss: 0.2066 | g_loss: 0.6663
Epoch [   18/   50] | d_loss: 0.0616 | g_loss: 0.7852
Epoch [   18/   50] | d_loss: 0.1198 | g_loss: 0.8711
Epoch [   18/   50] | d_loss: 0.1377 | g_loss: 1.1980
Epoch [   18/   50] | d_loss: 0.0991 | g_loss: 0.9745
Epoch [   19/   50] | d_loss: 0.2724 | g_loss: 0.8642
Epoch [   19/   50] | d_loss: 0.1712 | g_loss: 0.6015
Epoch [   19/   50] | d_loss: 0.3416 | g_loss: 0.3330
Epoch [   19/   50] | d_loss: 0.0572 | g_loss: 0.7598
Epoch [   19/   50] | d_loss: 0.1977 | g_loss: 0.4644
Epoch [   19/   50] | d_loss: 0.0438 | g_loss: 0.7311
Epoch [   19/   50] | d_loss: 0.0334 | g_loss: 1.1177
Epoch [   19/   50] | d_loss: 0.0928 | g_loss: 1.0560
Epoch [   19/   50] | d_loss: 0.2159 | g_loss: 0.8172
Epoch [   19/   50] | d_loss: 0.1908 | g_loss: 0.7251
Epoch [   19/   50] | d_loss: 0.0832 | g_loss: 0.6752
Epoch [   19/   50] | d_loss: 0.2387 | g_loss: 1.1314
Epoch [   20/   50] | d_loss: 0.0773 | g_loss: 0.7918
Epoch [   20/   50] | d_loss: 0.0903 | g_loss: 0.8832
Epoch [   20/   50] | d_loss: 0.0622 | g_loss: 0.6539
Epoch [   20/   50] | d_loss: 0.0890 | g_loss: 1.2049
Epoch [   20/   50] | d_loss: 0.1012 | g_loss: 0.7128
Epoch [   20/   50] | d_loss: 0.2006 | g_loss: 1.3079
Epoch [   20/   50] | d_loss: 0.3229 | g_loss: 1.3231
Epoch [   20/   50] | d_loss: 0.1563 | g_loss: 2.0465
Epoch [   20/   50] | d_loss: 0.1233 | g_loss: 0.9109
Epoch [   20/   50] | d_loss: 0.1266 | g_loss: 0.7390
Epoch [   20/   50] | d_loss: 0.2125 | g_loss: 0.9407
Epoch [   20/   50] | d_loss: 0.1540 | g_loss: 0.6462
Epoch [   21/   50] | d_loss: 0.0966 | g_loss: 1.0143
Epoch [   21/   50] | d_loss: 0.2044 | g_loss: 0.6006
Epoch [   21/   50] | d_loss: 0.1399 | g_loss: 0.7544
Epoch [   21/   50] | d_loss: 0.0480 | g_loss: 1.0664
Epoch [   21/   50] | d_loss: 0.0695 | g_loss: 0.7744
Epoch [   21/   50] | d_loss: 0.0888 | g_loss: 1.0012
Epoch [   21/   50] | d_loss: 0.0651 | g_loss: 0.6514
Epoch [   21/   50] | d_loss: 0.0877 | g_loss: 0.5925
Epoch [   21/   50] | d_loss: 0.0541 | g_loss: 0.7665
Epoch [   21/   50] | d_loss: 0.1351 | g_loss: 0.4685
Epoch [   21/   50] | d_loss: 0.1862 | g_loss: 1.5703
Epoch [   21/   50] | d_loss: 0.0506 | g_loss: 1.0840
Epoch [   22/   50] | d_loss: 0.4343 | g_loss: 1.1639
Epoch [   22/   50] | d_loss: 0.0761 | g_loss: 0.7884
Epoch [   22/   50] | d_loss: 0.0418 | g_loss: 0.7755
Epoch [   22/   50] | d_loss: 0.0246 | g_loss: 0.7984
Epoch [   22/   50] | d_loss: 0.1028 | g_loss: 0.5085
Epoch [   22/   50] | d_loss: 0.1246 | g_loss: 0.5107
Epoch [   22/   50] | d_loss: 0.4154 | g_loss: 1.0216
Epoch [   22/   50] | d_loss: 0.1108 | g_loss: 0.5002
Epoch [   22/   50] | d_loss: 0.0829 | g_loss: 0.8620
Epoch [   22/   50] | d_loss: 0.2050 | g_loss: 0.5663
Epoch [   22/   50] | d_loss: 0.0697 | g_loss: 0.6597
Epoch [   22/   50] | d_loss: 0.1394 | g_loss: 0.5644
Epoch [   23/   50] | d_loss: 0.3412 | g_loss: 1.3191
Epoch [   23/   50] | d_loss: 0.0701 | g_loss: 1.0547
Epoch [   23/   50] | d_loss: 0.2481 | g_loss: 0.6392
Epoch [   23/   50] | d_loss: 0.0687 | g_loss: 0.9681
Epoch [   23/   50] | d_loss: 0.0780 | g_loss: 0.8139
Epoch [   23/   50] | d_loss: 0.1021 | g_loss: 1.2817
Epoch [   23/   50] | d_loss: 0.0562 | g_loss: 0.8715
Epoch [   23/   50] | d_loss: 0.1271 | g_loss: 0.8425
Epoch [   23/   50] | d_loss: 0.1167 | g_loss: 0.8615
Epoch [   23/   50] | d_loss: 0.3297 | g_loss: 0.3802
Epoch [   23/   50] | d_loss: 0.1705 | g_loss: 0.7979
Epoch [   23/   50] | d_loss: 0.1941 | g_loss: 0.9529
Epoch [   24/   50] | d_loss: 0.1302 | g_loss: 1.6257
Epoch [   24/   50] | d_loss: 0.0470 | g_loss: 1.5682
Epoch [   24/   50] | d_loss: 0.1311 | g_loss: 1.1266
Epoch [   24/   50] | d_loss: 0.2379 | g_loss: 0.6366
Epoch [   24/   50] | d_loss: 0.1882 | g_loss: 0.5536
Epoch [   24/   50] | d_loss: 0.0846 | g_loss: 0.7653
Epoch [   24/   50] | d_loss: 0.0470 | g_loss: 0.7714
Epoch [   24/   50] | d_loss: 0.3338 | g_loss: 1.2086
Epoch [   24/   50] | d_loss: 0.1226 | g_loss: 0.8374
Epoch [   24/   50] | d_loss: 0.2643 | g_loss: 1.3431
Epoch [   24/   50] | d_loss: 0.0953 | g_loss: 1.0289
Epoch [   24/   50] | d_loss: 0.0548 | g_loss: 0.5201
Epoch [   25/   50] | d_loss: 0.0851 | g_loss: 1.5288
Epoch [   25/   50] | d_loss: 0.0221 | g_loss: 0.8433
Epoch [   25/   50] | d_loss: 0.0519 | g_loss: 1.0098
Epoch [   25/   50] | d_loss: 0.0576 | g_loss: 0.8914
Epoch [   25/   50] | d_loss: 0.1163 | g_loss: 0.7172
Epoch [   25/   50] | d_loss: 0.0615 | g_loss: 0.9771
Epoch [   25/   50] | d_loss: 0.1348 | g_loss: 0.7381
Epoch [   25/   50] | d_loss: 0.1114 | g_loss: 0.4285
Epoch [   25/   50] | d_loss: 0.0490 | g_loss: 1.2441
Epoch [   25/   50] | d_loss: 0.0390 | g_loss: 1.1768
Epoch [   25/   50] | d_loss: 0.1245 | g_loss: 0.7488
Epoch [   25/   50] | d_loss: 0.0688 | g_loss: 1.1754
Epoch [   26/   50] | d_loss: 0.1021 | g_loss: 1.0452
Epoch [   26/   50] | d_loss: 0.0964 | g_loss: 0.8858
Epoch [   26/   50] | d_loss: 0.0366 | g_loss: 0.9877
Epoch [   26/   50] | d_loss: 0.0805 | g_loss: 0.8490
Epoch [   26/   50] | d_loss: 0.1149 | g_loss: 0.7484
Epoch [   26/   50] | d_loss: 0.1981 | g_loss: 0.8609
Epoch [   26/   50] | d_loss: 0.3875 | g_loss: 0.6898
Epoch [   26/   50] | d_loss: 0.1332 | g_loss: 1.5209
Epoch [   26/   50] | d_loss: 0.1272 | g_loss: 0.8860
Epoch [   26/   50] | d_loss: 0.1237 | g_loss: 0.4328
Epoch [   26/   50] | d_loss: 0.0685 | g_loss: 0.8104
Epoch [   26/   50] | d_loss: 0.1575 | g_loss: 0.5304
Epoch [   27/   50] | d_loss: 0.1233 | g_loss: 0.5872
Epoch [   27/   50] | d_loss: 0.1259 | g_loss: 0.4373
Epoch [   27/   50] | d_loss: 0.0895 | g_loss: 1.1770
Epoch [   27/   50] | d_loss: 0.0813 | g_loss: 0.9521
Epoch [   27/   50] | d_loss: 0.1896 | g_loss: 0.6023
Epoch [   27/   50] | d_loss: 0.0408 | g_loss: 0.8371
Epoch [   27/   50] | d_loss: 0.0568 | g_loss: 1.0670
Epoch [   27/   50] | d_loss: 0.2150 | g_loss: 0.6617
Epoch [   27/   50] | d_loss: 0.0728 | g_loss: 0.8695
Epoch [   27/   50] | d_loss: 0.0936 | g_loss: 0.6625
Epoch [   27/   50] | d_loss: 0.1006 | g_loss: 0.7553
Epoch [   27/   50] | d_loss: 0.0856 | g_loss: 0.8305
Epoch [   28/   50] | d_loss: 0.0363 | g_loss: 0.9195
Epoch [   28/   50] | d_loss: 0.1073 | g_loss: 0.5529
Epoch [   28/   50] | d_loss: 0.2104 | g_loss: 0.5547
Epoch [   28/   50] | d_loss: 0.1366 | g_loss: 0.5849
Epoch [   28/   50] | d_loss: 0.1945 | g_loss: 0.6176
Epoch [   28/   50] | d_loss: 0.0777 | g_loss: 0.9877
Epoch [   28/   50] | d_loss: 0.1488 | g_loss: 1.2387
Epoch [   28/   50] | d_loss: 0.1145 | g_loss: 1.5802
Epoch [   28/   50] | d_loss: 0.0594 | g_loss: 0.9699
Epoch [   28/   50] | d_loss: 0.0638 | g_loss: 0.6357
Epoch [   28/   50] | d_loss: 0.0378 | g_loss: 1.2037
Epoch [   28/   50] | d_loss: 0.0546 | g_loss: 1.0241
Epoch [   29/   50] | d_loss: 0.0248 | g_loss: 0.6932
Epoch [   29/   50] | d_loss: 0.0378 | g_loss: 0.6639
Epoch [   29/   50] | d_loss: 0.1179 | g_loss: 0.9141
Epoch [   29/   50] | d_loss: 0.0327 | g_loss: 0.4416
Epoch [   29/   50] | d_loss: 0.1217 | g_loss: 1.1431
Epoch [   29/   50] | d_loss: 0.0781 | g_loss: 1.0753
Epoch [   29/   50] | d_loss: 0.0721 | g_loss: 0.4876
Epoch [   29/   50] | d_loss: 0.1764 | g_loss: 0.8791
Epoch [   29/   50] | d_loss: 0.1583 | g_loss: 0.7995
Epoch [   29/   50] | d_loss: 0.1198 | g_loss: 1.2252
Epoch [   29/   50] | d_loss: 0.0724 | g_loss: 0.9911
Epoch [   29/   50] | d_loss: 0.0626 | g_loss: 1.0680
Epoch [   30/   50] | d_loss: 0.0741 | g_loss: 0.9216
Epoch [   30/   50] | d_loss: 0.1420 | g_loss: 0.5008
Epoch [   30/   50] | d_loss: 0.1213 | g_loss: 0.7103
Epoch [   30/   50] | d_loss: 0.1096 | g_loss: 1.9155
Epoch [   30/   50] | d_loss: 0.1781 | g_loss: 1.2043
Epoch [   30/   50] | d_loss: 0.1025 | g_loss: 0.7038
Epoch [   30/   50] | d_loss: 0.0585 | g_loss: 0.8814
Epoch [   30/   50] | d_loss: 0.0549 | g_loss: 0.9333
Epoch [   30/   50] | d_loss: 0.0368 | g_loss: 1.3635
Epoch [   30/   50] | d_loss: 0.0585 | g_loss: 0.7108
Epoch [   30/   50] | d_loss: 0.0343 | g_loss: 1.0798
Epoch [   30/   50] | d_loss: 0.1152 | g_loss: 1.0144
Epoch [   31/   50] | d_loss: 0.1814 | g_loss: 1.2402
Epoch [   31/   50] | d_loss: 0.0783 | g_loss: 1.0822
Epoch [   31/   50] | d_loss: 0.0655 | g_loss: 0.8549
Epoch [   31/   50] | d_loss: 0.0648 | g_loss: 0.9383
Epoch [   31/   50] | d_loss: 0.0883 | g_loss: 0.5834
Epoch [   31/   50] | d_loss: 0.0954 | g_loss: 0.5305
Epoch [   31/   50] | d_loss: 0.0286 | g_loss: 0.9799
Epoch [   31/   50] | d_loss: 0.1188 | g_loss: 1.1679
Epoch [   31/   50] | d_loss: 0.0301 | g_loss: 1.2161
Epoch [   31/   50] | d_loss: 0.0409 | g_loss: 1.0381
Epoch [   31/   50] | d_loss: 0.0495 | g_loss: 0.9329
Epoch [   31/   50] | d_loss: 0.0624 | g_loss: 1.2238
Epoch [   32/   50] | d_loss: 0.0508 | g_loss: 0.7970
Epoch [   32/   50] | d_loss: 0.0366 | g_loss: 0.9740
Epoch [   32/   50] | d_loss: 0.0376 | g_loss: 1.1697
Epoch [   32/   50] | d_loss: 0.0381 | g_loss: 0.6569
Epoch [   32/   50] | d_loss: 0.0425 | g_loss: 0.7678
Epoch [   32/   50] | d_loss: 0.1161 | g_loss: 0.9796
Epoch [   32/   50] | d_loss: 0.1008 | g_loss: 0.9266
Epoch [   32/   50] | d_loss: 0.0797 | g_loss: 1.2931
Epoch [   32/   50] | d_loss: 0.0501 | g_loss: 0.9696
Epoch [   32/   50] | d_loss: 0.0956 | g_loss: 0.6910
Epoch [   32/   50] | d_loss: 0.0686 | g_loss: 0.8872
Epoch [   32/   50] | d_loss: 0.0306 | g_loss: 0.7991
Epoch [   33/   50] | d_loss: 0.0735 | g_loss: 0.6358
Epoch [   33/   50] | d_loss: 0.1868 | g_loss: 0.9251
Epoch [   33/   50] | d_loss: 0.0337 | g_loss: 0.6664
Epoch [   33/   50] | d_loss: 0.0415 | g_loss: 0.7642
Epoch [   33/   50] | d_loss: 0.1357 | g_loss: 0.8589
Epoch [   33/   50] | d_loss: 0.0272 | g_loss: 1.0769
Epoch [   33/   50] | d_loss: 0.1118 | g_loss: 0.9897
Epoch [   33/   50] | d_loss: 0.0758 | g_loss: 0.9637
Epoch [   33/   50] | d_loss: 0.0492 | g_loss: 0.5653
Epoch [   33/   50] | d_loss: 0.0767 | g_loss: 1.4331
Epoch [   33/   50] | d_loss: 0.0795 | g_loss: 1.1522
Epoch [   33/   50] | d_loss: 0.0383 | g_loss: 0.5979
Epoch [   34/   50] | d_loss: 0.0862 | g_loss: 0.6718
Epoch [   34/   50] | d_loss: 0.0562 | g_loss: 1.2088
Epoch [   34/   50] | d_loss: 0.1980 | g_loss: 1.5028
Epoch [   34/   50] | d_loss: 0.0940 | g_loss: 1.0562
Epoch [   34/   50] | d_loss: 0.0709 | g_loss: 1.4047
Epoch [   34/   50] | d_loss: 0.0547 | g_loss: 0.7614
Epoch [   34/   50] | d_loss: 0.0551 | g_loss: 0.7380
Epoch [   34/   50] | d_loss: 0.0354 | g_loss: 1.0411
Epoch [   34/   50] | d_loss: 0.0393 | g_loss: 0.9573
Epoch [   34/   50] | d_loss: 0.0542 | g_loss: 1.1214
Epoch [   34/   50] | d_loss: 0.0680 | g_loss: 1.1429
Epoch [   34/   50] | d_loss: 0.0696 | g_loss: 0.7456
Epoch [   35/   50] | d_loss: 0.0570 | g_loss: 0.9347
Epoch [   35/   50] | d_loss: 0.2470 | g_loss: 0.3751
Epoch [   35/   50] | d_loss: 0.0422 | g_loss: 1.0228
Epoch [   35/   50] | d_loss: 0.1091 | g_loss: 0.5093
Epoch [   35/   50] | d_loss: 0.3054 | g_loss: 1.4084
Epoch [   35/   50] | d_loss: 0.0673 | g_loss: 1.3171
Epoch [   35/   50] | d_loss: 0.2627 | g_loss: 0.8513
Epoch [   35/   50] | d_loss: 0.0482 | g_loss: 0.8255
Epoch [   35/   50] | d_loss: 0.0404 | g_loss: 1.2604
Epoch [   35/   50] | d_loss: 0.0364 | g_loss: 0.9847
Epoch [   35/   50] | d_loss: 0.4115 | g_loss: 1.2349
Epoch [   35/   50] | d_loss: 0.1979 | g_loss: 0.9584
Epoch [   36/   50] | d_loss: 0.0883 | g_loss: 0.9966
Epoch [   36/   50] | d_loss: 0.0461 | g_loss: 0.8822
Epoch [   36/   50] | d_loss: 0.0336 | g_loss: 0.5470
Epoch [   36/   50] | d_loss: 0.0915 | g_loss: 0.9506
Epoch [   36/   50] | d_loss: 0.0422 | g_loss: 0.7545
Epoch [   36/   50] | d_loss: 0.0515 | g_loss: 0.5444
Epoch [   36/   50] | d_loss: 0.0996 | g_loss: 0.7511
Epoch [   36/   50] | d_loss: 0.0493 | g_loss: 1.1564
Epoch [   36/   50] | d_loss: 0.0949 | g_loss: 1.0134
Epoch [   36/   50] | d_loss: 0.1425 | g_loss: 0.6837
Epoch [   36/   50] | d_loss: 0.0280 | g_loss: 0.9999
Epoch [   36/   50] | d_loss: 0.0301 | g_loss: 0.6892
Epoch [   37/   50] | d_loss: 0.0977 | g_loss: 1.5500
Epoch [   37/   50] | d_loss: 0.0541 | g_loss: 0.8735
Epoch [   37/   50] | d_loss: 0.1429 | g_loss: 0.5462
Epoch [   37/   50] | d_loss: 0.0592 | g_loss: 0.9439
Epoch [   37/   50] | d_loss: 0.1022 | g_loss: 0.6213
Epoch [   37/   50] | d_loss: 0.0517 | g_loss: 1.0483
Epoch [   37/   50] | d_loss: 0.0372 | g_loss: 0.8958
Epoch [   37/   50] | d_loss: 0.1059 | g_loss: 0.5923
Epoch [   37/   50] | d_loss: 0.1136 | g_loss: 1.0421
Epoch [   37/   50] | d_loss: 0.0298 | g_loss: 0.8433
Epoch [   37/   50] | d_loss: 0.0585 | g_loss: 1.2735
Epoch [   37/   50] | d_loss: 0.1782 | g_loss: 0.9640
Epoch [   38/   50] | d_loss: 0.1116 | g_loss: 1.3877
Epoch [   38/   50] | d_loss: 0.0401 | g_loss: 1.0107
Epoch [   38/   50] | d_loss: 0.0942 | g_loss: 0.9612
Epoch [   38/   50] | d_loss: 0.0742 | g_loss: 1.0128
Epoch [   38/   50] | d_loss: 0.0777 | g_loss: 1.3824
Epoch [   38/   50] | d_loss: 0.0627 | g_loss: 0.7520
Epoch [   38/   50] | d_loss: 0.1555 | g_loss: 0.4259
Epoch [   38/   50] | d_loss: 0.0398 | g_loss: 0.8906
Epoch [   38/   50] | d_loss: 0.0499 | g_loss: 0.5175
Epoch [   38/   50] | d_loss: 0.4368 | g_loss: 0.3900
Epoch [   38/   50] | d_loss: 0.1295 | g_loss: 0.9336
Epoch [   38/   50] | d_loss: 0.0366 | g_loss: 1.0613
Epoch [   39/   50] | d_loss: 0.0675 | g_loss: 0.9121
Epoch [   39/   50] | d_loss: 0.1269 | g_loss: 0.9522
Epoch [   39/   50] | d_loss: 0.0525 | g_loss: 0.7509
Epoch [   39/   50] | d_loss: 0.0758 | g_loss: 0.5009
Epoch [   39/   50] | d_loss: 0.0622 | g_loss: 0.4512
Epoch [   39/   50] | d_loss: 0.0440 | g_loss: 1.0929
Epoch [   39/   50] | d_loss: 0.0596 | g_loss: 0.9281
Epoch [   39/   50] | d_loss: 0.0284 | g_loss: 1.2207
Epoch [   39/   50] | d_loss: 0.2411 | g_loss: 0.2867
Epoch [   39/   50] | d_loss: 0.0731 | g_loss: 0.7054
Epoch [   39/   50] | d_loss: 0.0585 | g_loss: 1.0325
Epoch [   39/   50] | d_loss: 0.0512 | g_loss: 0.8501
Epoch [   40/   50] | d_loss: 0.0578 | g_loss: 0.4401
Epoch [   40/   50] | d_loss: 0.2316 | g_loss: 0.5412
Epoch [   40/   50] | d_loss: 0.0740 | g_loss: 0.7785
Epoch [   40/   50] | d_loss: 0.0581 | g_loss: 1.1142
Epoch [   40/   50] | d_loss: 0.1385 | g_loss: 0.5922
Epoch [   40/   50] | d_loss: 0.0282 | g_loss: 0.7447
Epoch [   40/   50] | d_loss: 0.0354 | g_loss: 0.7885
Epoch [   40/   50] | d_loss: 0.0433 | g_loss: 0.8961
Epoch [   40/   50] | d_loss: 0.0848 | g_loss: 1.3848
Epoch [   40/   50] | d_loss: 0.0716 | g_loss: 0.7566
Epoch [   40/   50] | d_loss: 0.0655 | g_loss: 0.3331
Epoch [   40/   50] | d_loss: 0.1822 | g_loss: 0.7275
Epoch [   41/   50] | d_loss: 0.1029 | g_loss: 0.5351
Epoch [   41/   50] | d_loss: 0.0613 | g_loss: 1.1506
Epoch [   41/   50] | d_loss: 0.0707 | g_loss: 1.1504
Epoch [   41/   50] | d_loss: 0.1127 | g_loss: 0.9214
Epoch [   41/   50] | d_loss: 0.2119 | g_loss: 0.7527
Epoch [   41/   50] | d_loss: 0.0465 | g_loss: 1.4255
Epoch [   41/   50] | d_loss: 0.0373 | g_loss: 1.2849
Epoch [   41/   50] | d_loss: 0.1941 | g_loss: 0.7334
Epoch [   41/   50] | d_loss: 0.0427 | g_loss: 1.1167
Epoch [   41/   50] | d_loss: 0.0541 | g_loss: 0.9213
Epoch [   41/   50] | d_loss: 0.0767 | g_loss: 0.6903
Epoch [   41/   50] | d_loss: 0.0303 | g_loss: 1.3968
Epoch [   42/   50] | d_loss: 0.0916 | g_loss: 0.6181
Epoch [   42/   50] | d_loss: 0.1242 | g_loss: 0.5949
Epoch [   42/   50] | d_loss: 0.0909 | g_loss: 1.2835
Epoch [   42/   50] | d_loss: 0.0472 | g_loss: 1.0355
Epoch [   42/   50] | d_loss: 0.1423 | g_loss: 1.2335
Epoch [   42/   50] | d_loss: 0.0648 | g_loss: 0.7836
Epoch [   42/   50] | d_loss: 0.1621 | g_loss: 0.8923
Epoch [   42/   50] | d_loss: 0.0380 | g_loss: 0.8404
Epoch [   42/   50] | d_loss: 0.0656 | g_loss: 1.1703
Epoch [   42/   50] | d_loss: 0.1760 | g_loss: 1.3609
Epoch [   42/   50] | d_loss: 0.1024 | g_loss: 0.8234
Epoch [   42/   50] | d_loss: 0.0564 | g_loss: 0.3408
Epoch [   43/   50] | d_loss: 0.0329 | g_loss: 1.1638
Epoch [   43/   50] | d_loss: 0.0982 | g_loss: 0.6419
Epoch [   43/   50] | d_loss: 0.0388 | g_loss: 1.1614
Epoch [   43/   50] | d_loss: 0.0509 | g_loss: 0.8126
Epoch [   43/   50] | d_loss: 0.0876 | g_loss: 1.1614
Epoch [   43/   50] | d_loss: 0.0598 | g_loss: 0.6436
Epoch [   43/   50] | d_loss: 0.1614 | g_loss: 1.1004
Epoch [   43/   50] | d_loss: 0.1693 | g_loss: 1.3669
Epoch [   43/   50] | d_loss: 0.0824 | g_loss: 0.8135
Epoch [   43/   50] | d_loss: 0.1674 | g_loss: 1.6732
Epoch [   43/   50] | d_loss: 0.0966 | g_loss: 1.0803
Epoch [   43/   50] | d_loss: 0.0282 | g_loss: 0.7919
Epoch [   44/   50] | d_loss: 0.0286 | g_loss: 1.1358
Epoch [   44/   50] | d_loss: 0.0330 | g_loss: 0.9293
Epoch [   44/   50] | d_loss: 0.0353 | g_loss: 1.2658
Epoch [   44/   50] | d_loss: 0.2089 | g_loss: 1.2355
Epoch [   44/   50] | d_loss: 0.0776 | g_loss: 0.7196
Epoch [   44/   50] | d_loss: 0.3197 | g_loss: 0.5859
Epoch [   44/   50] | d_loss: 0.1546 | g_loss: 0.9410
Epoch [   44/   50] | d_loss: 0.0477 | g_loss: 0.6940
Epoch [   44/   50] | d_loss: 0.0712 | g_loss: 0.9568
Epoch [   44/   50] | d_loss: 0.0945 | g_loss: 1.2202
Epoch [   44/   50] | d_loss: 0.0794 | g_loss: 1.1865
Epoch [   44/   50] | d_loss: 0.2244 | g_loss: 0.6788
Epoch [   45/   50] | d_loss: 0.0276 | g_loss: 0.8158
Epoch [   45/   50] | d_loss: 0.0682 | g_loss: 1.1122
Epoch [   45/   50] | d_loss: 0.1028 | g_loss: 0.9248
Epoch [   45/   50] | d_loss: 0.1040 | g_loss: 0.6585
Epoch [   45/   50] | d_loss: 0.0502 | g_loss: 0.6539
Epoch [   45/   50] | d_loss: 0.4367 | g_loss: 1.1138
Epoch [   45/   50] | d_loss: 0.0273 | g_loss: 0.6737
Epoch [   45/   50] | d_loss: 0.1066 | g_loss: 1.1326
Epoch [   45/   50] | d_loss: 0.1614 | g_loss: 1.3444
Epoch [   45/   50] | d_loss: 0.0355 | g_loss: 1.2528
Epoch [   45/   50] | d_loss: 0.0926 | g_loss: 0.9688
Epoch [   45/   50] | d_loss: 0.0663 | g_loss: 1.0168
Epoch [   46/   50] | d_loss: 0.0954 | g_loss: 0.5706
Epoch [   46/   50] | d_loss: 0.0425 | g_loss: 0.8073
Epoch [   46/   50] | d_loss: 0.0721 | g_loss: 0.9911
Epoch [   46/   50] | d_loss: 0.1725 | g_loss: 0.7792
Epoch [   46/   50] | d_loss: 0.0743 | g_loss: 1.3191
Epoch [   46/   50] | d_loss: 0.0473 | g_loss: 0.8722
Epoch [   46/   50] | d_loss: 0.1216 | g_loss: 1.3248
Epoch [   46/   50] | d_loss: 0.0535 | g_loss: 1.1578
Epoch [   46/   50] | d_loss: 0.0857 | g_loss: 0.9949
Epoch [   46/   50] | d_loss: 0.0902 | g_loss: 1.0000
Epoch [   46/   50] | d_loss: 0.0723 | g_loss: 1.2710
Epoch [   46/   50] | d_loss: 0.0617 | g_loss: 1.5353
Epoch [   47/   50] | d_loss: 0.1150 | g_loss: 1.2651
Epoch [   47/   50] | d_loss: 0.0282 | g_loss: 0.5296
Epoch [   47/   50] | d_loss: 0.0485 | g_loss: 0.6765
Epoch [   47/   50] | d_loss: 0.0283 | g_loss: 0.7019
Epoch [   47/   50] | d_loss: 0.0939 | g_loss: 1.1783
Epoch [   47/   50] | d_loss: 0.0686 | g_loss: 1.1719
Epoch [   47/   50] | d_loss: 0.0622 | g_loss: 0.6497
Epoch [   47/   50] | d_loss: 0.0237 | g_loss: 1.2146
Epoch [   47/   50] | d_loss: 0.0462 | g_loss: 1.2053
Epoch [   47/   50] | d_loss: 0.0727 | g_loss: 0.9677
Epoch [   47/   50] | d_loss: 0.0491 | g_loss: 0.7910
Epoch [   47/   50] | d_loss: 0.0410 | g_loss: 0.9670
Epoch [   48/   50] | d_loss: 0.1658 | g_loss: 0.7566
Epoch [   48/   50] | d_loss: 0.0345 | g_loss: 0.9387
Epoch [   48/   50] | d_loss: 0.0252 | g_loss: 1.0891
Epoch [   48/   50] | d_loss: 0.1549 | g_loss: 0.6764
Epoch [   48/   50] | d_loss: 0.1253 | g_loss: 0.5434
Epoch [   48/   50] | d_loss: 0.2176 | g_loss: 1.8316
Epoch [   48/   50] | d_loss: 0.0519 | g_loss: 0.8194
Epoch [   48/   50] | d_loss: 0.2199 | g_loss: 0.8121
Epoch [   48/   50] | d_loss: 0.0977 | g_loss: 1.0481
Epoch [   48/   50] | d_loss: 0.0699 | g_loss: 1.3408
Epoch [   48/   50] | d_loss: 0.1795 | g_loss: 1.1939
Epoch [   48/   50] | d_loss: 0.0193 | g_loss: 0.8048
Epoch [   49/   50] | d_loss: 0.0941 | g_loss: 1.1553
Epoch [   49/   50] | d_loss: 0.0373 | g_loss: 1.2267
Epoch [   49/   50] | d_loss: 0.0232 | g_loss: 1.1205
Epoch [   49/   50] | d_loss: 0.0258 | g_loss: 0.6994
Epoch [   49/   50] | d_loss: 0.1216 | g_loss: 0.8222
Epoch [   49/   50] | d_loss: 0.1814 | g_loss: 0.9450
Epoch [   49/   50] | d_loss: 0.0287 | g_loss: 0.8222
Epoch [   49/   50] | d_loss: 0.0482 | g_loss: 0.8094
Epoch [   49/   50] | d_loss: 0.0959 | g_loss: 0.9068
Epoch [   49/   50] | d_loss: 0.0637 | g_loss: 1.0103
Epoch [   49/   50] | d_loss: 0.0198 | g_loss: 0.9342
Epoch [   49/   50] | d_loss: 0.2725 | g_loss: 1.1447
Epoch [   50/   50] | d_loss: 0.2082 | g_loss: 0.7420
Epoch [   50/   50] | d_loss: 0.1833 | g_loss: 0.6354
Epoch [   50/   50] | d_loss: 0.0791 | g_loss: 0.6799
Epoch [   50/   50] | d_loss: 0.0619 | g_loss: 1.1187
Epoch [   50/   50] | d_loss: 0.0176 | g_loss: 0.7437
Epoch [   50/   50] | d_loss: 0.0797 | g_loss: 0.9393
Epoch [   50/   50] | d_loss: 0.0815 | g_loss: 0.9280
Epoch [   50/   50] | d_loss: 0.0805 | g_loss: 0.4580
Epoch [   50/   50] | d_loss: 0.0689 | g_loss: 1.3235
Epoch [   50/   50] | d_loss: 0.0715 | g_loss: 0.7801
Epoch [   50/   50] | d_loss: 0.0591 | g_loss: 1.0334
Epoch [   50/   50] | d_loss: 0.0627 | g_loss: 0.7467
</pre>
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<h2 id="Training-loss">Training loss<a class="anchor-link" href="#Training-loss">&#182;</a></h2><p>Plot the training losses for the generator and discriminator, recorded after each epoch.</p>

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<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[23]:</div>
<div class="inner_cell">
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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>
</pre></div>

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    <div class="prompt output_prompt">Out[23]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>&lt;matplotlib.legend.Legend at 0x7fa4c6e75dd8&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>
As mentioned in the factors already. The result propagates the bias of the dataset. The dataset includes faces of mostly "White" celebrities and this bias is picked up while training and shows up the in the generated results.<br>
Training the model on a larger and varied dataset should certainly help with generation of diverse faces and add variety to individual facial features. Also, it seems the model performs slightly worse on generating side poses as compared to front view of faces which can be solved adding more side pose images to the training dataset.</p>
<p>My model contains around 4 convolution layers. Certainly adding more layers with help as the depth of convolutions increase, models can learn more features. This means training time will also increase considerably.</p>
<p>Adam is usually a good optimizer for most cases and a standard learning rate of around 0.001 or 0.0005 works well. The original DCGAN paper recommend a beta-1 value of 0.5 but I noticed the generated images improved with setting beta-1 to 0.1<br>
Higher epochs should help with learning although at one point the learning would stop as the generator and discriminator become really good at their individual tasks.</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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