dlnd_face_generation.html

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<title>dlnd_face_generation</title>

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

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

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

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

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

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

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

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># can comment out after executing</span>
<span class="c1">#!unzip processed_celeba_small.zip</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">data_dir</span> <span class="o">=</span> <span class="s1">&#39;processed_celeba_small/&#39;</span>

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

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

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># necessary imports</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">from</span> <span class="nn">torchvision</span> <span class="k">import</span> <span class="n">datasets</span>
<span class="kn">from</span> <span class="nn">torchvision</span> <span class="k">import</span> <span class="n">transforms</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">get_dataloader</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">image_size</span><span class="p">,</span> <span class="n">data_dir</span><span class="o">=</span><span class="s1">&#39;processed_celeba_small/&#39;</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Batch the neural network data using DataLoader</span>
<span class="sd">    :param batch_size: The size of each batch; the number of images in a batch</span>
<span class="sd">    :param img_size: The square size of the image data (x, y)</span>
<span class="sd">    :param data_dir: Directory where image data is located</span>
<span class="sd">    :return: DataLoader with batched data</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1"># TODO: Implement function and return a dataloader</span>
    <span class="c1"># resize and normalize the images</span>
    <span class="n">transform</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span><span class="n">transforms</span><span class="o">.</span><span class="n">Resize</span><span class="p">(</span><span class="n">image_size</span><span class="p">),</span> <span class="c1"># resize to 128x128</span>
                                    <span class="n">transforms</span><span class="o">.</span><span class="n">CenterCrop</span><span class="p">(</span><span class="n">image_size</span><span class="p">),</span>
                                    <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">()])</span>

    <span class="c1"># get training and test directories</span>
    <span class="n">image_path</span> <span class="o">=</span> <span class="s1">&#39;./&#39;</span> <span class="o">+</span> <span class="n">data_dir</span>
    
    <span class="c1"># define datasets using ImageFolder</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">image_path</span><span class="p">,</span> <span class="n">transform</span><span class="p">)</span>
    
    <span class="c1"># create and return DataLoaders</span>
    <span class="n">data_loader</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">DataLoader</span><span class="p">(</span><span class="n">dataset</span><span class="o">=</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">data_loader</span>
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<h2 id="Create-a-DataLoader">Create a DataLoader<a class="anchor-link" href="#Create-a-DataLoader">&#182;</a></h2><h4 id="Exercise:-Create-a-DataLoader-celeba_train_loader-with-appropriate-hyperparameters.">Exercise: Create a DataLoader <code>celeba_train_loader</code> with appropriate hyperparameters.<a class="anchor-link" href="#Exercise:-Create-a-DataLoader-celeba_train_loader-with-appropriate-hyperparameters.">&#182;</a></h4><p>Call the above function and create a dataloader to view images.</p>
<ul>
<li>You can decide on any reasonable <code>batch_size</code> parameter</li>
<li>Your <code>image_size</code> <strong>must be</strong> <code>32</code>. Resizing the data to a smaller size will make for faster training, while still creating convincing images of faces!</li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Define function hyperparameters</span>
<span class="n">batch_size</span> <span class="o">=</span> <span class="mi">128</span>
<span class="n">img_size</span> <span class="o">=</span> <span class="mi">32</span>

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

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

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

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

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Complete the scale function</span>
<span class="k">def</span> <span class="nf">scale</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">feature_range</span><span class="o">=</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">)):</span>
    <span class="sd">&#39;&#39;&#39; Scale takes in an image x and returns that image, scaled</span>
<span class="sd">       with a feature_range of pixel values from -1 to 1. </span>
<span class="sd">       This function assumes that the input x is already scaled from 0-1.&#39;&#39;&#39;</span>
    <span class="c1"># assume x is scaled to (0, 1)</span>
    <span class="c1"># scale to feature_range and return scaled x</span>
    
    <span class="nb">min</span><span class="p">,</span> <span class="nb">max</span> <span class="o">=</span> <span class="n">feature_range</span>
    <span class="n">x</span> <span class="o">=</span> <span class="n">x</span> <span class="o">*</span> <span class="p">(</span><span class="nb">max</span> <span class="o">-</span> <span class="nb">min</span><span class="p">)</span> <span class="o">+</span> <span class="nb">min</span>

    <span class="k">return</span> <span class="n">x</span>
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<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="c1"># check scaled range</span>
<span class="c1"># should be close to -1 to 1</span>
<span class="n">img</span> <span class="o">=</span> <span class="n">images</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="n">scaled_img</span> <span class="o">=</span> <span class="n">scale</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Min: &#39;</span><span class="p">,</span> <span class="n">scaled_img</span><span class="o">.</span><span class="n">min</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Max: &#39;</span><span class="p">,</span> <span class="n">scaled_img</span><span class="o">.</span><span class="n">max</span><span class="p">())</span>
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<pre>Min:  tensor(-0.8118)
Max:  tensor(0.9922)
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<h1 id="Define-the-Model">Define the Model<a class="anchor-link" href="#Define-the-Model">&#182;</a></h1><p>A GAN is comprised of two adversarial networks, a discriminator and a generator.</p>
<h2 id="Discriminator">Discriminator<a class="anchor-link" href="#Discriminator">&#182;</a></h2><p>Your first task will be to define the discriminator. This is a convolutional classifier like you've built before, only without any maxpooling layers. To deal with this complex data, it's suggested you use a deep network with <strong>normalization</strong>. You are also allowed to create any helper functions that may be useful.</p>
<h4 id="Exercise:-Complete-the-Discriminator-class">Exercise: Complete the Discriminator class<a class="anchor-link" href="#Exercise:-Complete-the-Discriminator-class">&#182;</a></h4><ul>
<li>The inputs to the discriminator are 32x32x3 tensor images</li>
<li>The output should be a single value that will indicate whether a given image is real or fake</li>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">torch.nn</span> <span class="k">as</span> <span class="nn">nn</span>
<span class="kn">import</span> <span class="nn">torch.nn.functional</span> <span class="k">as</span> <span class="nn">F</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># helper conv function</span>
<span class="k">def</span> <span class="nf">conv</span><span class="p">(</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;Creates a convolutional layer, with optional batch normalization.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">conv_layer</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Conv2d</span><span class="p">(</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="p">,</span> 
                           <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">padding</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
    
    <span class="c1"># append conv layer</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="c1"># append batchnorm layer</span>
        <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">BatchNorm2d</span><span class="p">(</span><span class="n">out_channels</span><span class="p">))</span>
     
    <span class="c1"># using Sequential container</span>
    <span class="k">return</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="o">*</span><span class="n">layers</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">class</span> <span class="nc">Discriminator</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>

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

        <span class="c1"># complete init function</span>
        <span class="c1"># complete init function</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span> <span class="o">=</span> <span class="n">conv_dim</span>
        
        <span class="c1"># define the layers</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv1</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="n">batch_norm</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span>
        
        <span class="c1"># second layer</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv2</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="n">conv_dim</span><span class="p">,</span> <span class="n">conv_dim</span> <span class="o">*</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        
        <span class="c1"># third layer</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv3</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="n">conv_dim</span> <span class="o">*</span> <span class="mi">2</span><span class="p">,</span> <span class="n">conv_dim</span> <span class="o">*</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        
        <span class="c1"># fourth layer</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv4</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="n">conv_dim</span> <span class="o">*</span> <span class="mi">4</span><span class="p">,</span> <span class="n">conv_dim</span> <span class="o">*</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        
        <span class="c1"># last fully connected 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">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv1</span><span class="p">(</span><span class="n">x</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv2</span><span class="p">(</span><span class="n">out</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv3</span><span class="p">(</span><span class="n">out</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv4</span><span class="p">(</span><span class="n">out</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>
        
        <span class="c1"># flatten the output</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">8</span><span class="o">*</span><span class="mi">2</span><span class="o">*</span><span class="mi">2</span><span class="p">)</span>
        
        <span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>
        
        <span class="k">return</span> <span class="n">out</span>


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

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># helper deconv function</span>
<span class="k">def</span> <span class="nf">deconv</span><span class="p">(</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;Creates a transposed-convolutional layer, with optional batch normalization.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1">## TODO: Complete this function</span>
    <span class="c1">## create a sequence of transpose + optional batch norm layers</span>
    <span class="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">convTran_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="p">,</span> <span class="n">out_channels</span><span class="p">,</span> 
                           <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">padding</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
    
    <span class="c1"># append conv layer</span>
    <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">convTran_layer</span><span class="p">)</span>

    <span class="k">if</span> <span class="n">batch_norm</span><span class="p">:</span>
        <span class="c1"># append batchnorm layer</span>
        <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">BatchNorm2d</span><span class="p">(</span><span class="n">out_channels</span><span class="p">))</span>
     
    <span class="c1"># using Sequential container</span>
    <span class="k">return</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="o">*</span><span class="n">layers</span><span class="p">)</span> 
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">class</span> <span class="nc">Generator</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
    
    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Initialize the Generator Module</span>
<span class="sd">        :param z_size: The length of the input latent vector, z</span>
<span class="sd">        :param conv_dim: The depth of the inputs to the *last* transpose convolutional layer</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">Generator</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>

        <span class="c1"># complete init function</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span> <span class="o">=</span> <span class="n">conv_dim</span>
        
        <span class="c1"># first, fully-connected 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">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="c1"># transpose conv layers</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">deconv1</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">8</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">deconv2</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">deconv3</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">deconv4</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>


    <span class="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="c1"># fully-connected + reshape </span>
        <span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">8</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> <span class="c1"># (batch_size, depth, 4, 4)</span>
        
        <span class="c1"># hidden transpose conv layers + relu</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deconv1</span><span class="p">(</span><span class="n">out</span><span class="p">))</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deconv2</span><span class="p">(</span><span class="n">out</span><span class="p">))</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">deconv3</span><span class="p">(</span><span class="n">out</span><span class="p">))</span>
        
        <span class="c1"># last layer + tanh activation</span>
        <span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">deconv4</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>
        <span class="n">out</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">tanh</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>
        
        <span class="k">return</span> <span class="n">out</span>

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

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">weights_init_normal</span><span class="p">(</span><span class="n">m</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Applies initial weights to certain layers in a model .</span>
<span class="sd">    The weights are taken from a normal distribution </span>
<span class="sd">    with mean = 0, std dev = 0.02.</span>
<span class="sd">    :param m: A module or layer in a network    </span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1"># classname will be something like:</span>
    <span class="c1"># `Conv`, `BatchNorm2d`, `Linear`, etc.</span>
    <span class="n">classname</span> <span class="o">=</span> <span class="n">m</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span>
    
    <span class="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">m</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">normal_</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"># The bias terms, if they exist, set to 0</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">m</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">zero_</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>
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<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)
  (deconv1): 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)
  )
  (deconv2): 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)
  )
  (deconv3): 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)
  )
  (deconv4): 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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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">torch</span>

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

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

    <span class="n">labels</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">batch_size</span><span class="p">)</span> <span class="o">*</span> <span class="mf">0.9</span> <span class="c1"># real labels = 1</span>
    <span class="c1"># move labels to GPU if available     </span>
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
    <span class="c1"># binary cross entropy with logits loss</span>
    <span class="n">criterion</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">BCEWithLogitsLoss</span><span class="p">()</span>
    <span class="c1"># calculate loss</span>
    <span class="n">loss</span> <span class="o">=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">D_out</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(),</span> <span class="n">labels</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">loss</span>

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

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

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

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

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

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

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

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

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

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

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

            <span class="c1"># ===============================================</span>
            <span class="c1">#         YOUR CODE HERE: TRAIN THE NETWORKS</span>
            <span class="c1"># ===============================================</span>
            
            <span class="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"># Compute the discriminator losses on real images </span>
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">real_images</span> <span class="o">=</span> <span class="n">real_images</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
        
            <span class="n">D_real</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">real_images</span><span class="p">)</span>
            <span class="n">d_real_loss</span> <span class="o">=</span> <span class="n">real_loss</span><span class="p">(</span><span class="n">D_real</span><span class="p">)</span>
        
            <span class="c1"># 2. Train with fake images</span>
        
            <span class="c1"># Generate fake images</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
            <span class="c1"># move x to GPU, if available</span>
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">z</span> <span class="o">=</span> <span class="n">z</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
            <span class="n">fake_images</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">z</span><span class="p">)</span>
        
            <span class="c1"># Compute the discriminator losses on fake images            </span>
            <span class="n">D_fake</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">fake_images</span><span class="p">)</span>
            <span class="n">d_fake_loss</span> <span class="o">=</span> <span class="n">fake_loss</span><span class="p">(</span><span class="n">D_fake</span><span class="p">)</span>
        
            <span class="c1"># add up loss and perform backprop</span>
            <span class="n">d_loss</span> <span class="o">=</span> <span class="n">d_real_loss</span> <span class="o">+</span> <span class="n">d_fake_loss</span>
            <span class="n">d_loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
            <span class="n">d_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
            
            <span class="c1"># 2. Train the generator with an adversarial loss</span>
            <span class="n">g_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
            
            <span class="c1"># Generate fake images</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">z</span> <span class="o">=</span> <span class="n">z</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
            <span class="n">fake_images</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">z</span><span class="p">)</span>
        
            <span class="c1"># Compute the discriminator losses on fake images </span>
            <span class="c1"># using flipped labels!</span>
            <span class="n">D_fake</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">fake_images</span><span class="p">)</span>
            <span class="n">g_loss</span> <span class="o">=</span> <span class="n">real_loss</span><span class="p">(</span><span class="n">D_fake</span><span class="p">)</span> <span class="c1"># use real loss to flip labels</span>
        
            <span class="c1"># perform backprop</span>
            <span class="n">g_loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
            <span class="n">g_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
            
            <span class="c1"># ===============================================</span>
            <span class="c1">#              END OF YOUR CODE</span>
            <span class="c1"># ===============================================</span>

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


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

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

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

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

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[20]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># set number of epochs </span>
<span class="n">n_epochs</span> <span class="o">=</span> <span class="mi">30</span>


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

    </div>
</div>
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<div class="output">


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


<div class="output_subarea output_stream output_stdout output_text">
<pre>Epoch [    1/   30] | d_loss: 1.4698 | g_loss: 1.1785
Epoch [    1/   30] | d_loss: 1.8950 | g_loss: 5.1740
Epoch [    1/   30] | d_loss: 0.6946 | g_loss: 2.7194
Epoch [    1/   30] | d_loss: 0.6917 | g_loss: 3.3802
Epoch [    1/   30] | d_loss: 0.7431 | g_loss: 2.6418
Epoch [    1/   30] | d_loss: 0.6165 | g_loss: 2.4816
Epoch [    1/   30] | d_loss: 0.9745 | g_loss: 1.0258
Epoch [    1/   30] | d_loss: 0.7233 | g_loss: 2.1427
Epoch [    1/   30] | d_loss: 0.7994 | g_loss: 3.3797
Epoch [    1/   30] | d_loss: 1.5038 | g_loss: 4.4430
Epoch [    1/   30] | d_loss: 0.9596 | g_loss: 2.3670
Epoch [    1/   30] | d_loss: 1.4518 | g_loss: 2.4776
Epoch [    1/   30] | d_loss: 0.6885 | g_loss: 1.9250
Epoch [    1/   30] | d_loss: 0.9668 | g_loss: 3.7770
Epoch [    1/   30] | d_loss: 0.8214 | g_loss: 2.7337
Epoch [    2/   30] | d_loss: 0.9709 | g_loss: 1.8010
Epoch [    2/   30] | d_loss: 0.9179 | g_loss: 2.5902
Epoch [    2/   30] | d_loss: 1.0566 | g_loss: 1.4870
Epoch [    2/   30] | d_loss: 1.1732 | g_loss: 1.0307
Epoch [    2/   30] | d_loss: 1.0080 | g_loss: 3.1032
Epoch [    2/   30] | d_loss: 0.9208 | g_loss: 2.0933
Epoch [    2/   30] | d_loss: 0.8635 | g_loss: 1.6468
Epoch [    2/   30] | d_loss: 0.7977 | g_loss: 2.1543
Epoch [    2/   30] | d_loss: 0.9599 | g_loss: 2.4116
Epoch [    2/   30] | d_loss: 1.1451 | g_loss: 2.0562
Epoch [    2/   30] | d_loss: 0.8601 | g_loss: 1.7969
Epoch [    2/   30] | d_loss: 0.9817 | g_loss: 1.5058
Epoch [    2/   30] | d_loss: 0.9296 | g_loss: 2.3130
Epoch [    2/   30] | d_loss: 0.9457 | g_loss: 1.5827
Epoch [    2/   30] | d_loss: 0.8827 | g_loss: 1.7210
Epoch [    3/   30] | d_loss: 0.9215 | g_loss: 2.2900
Epoch [    3/   30] | d_loss: 0.8584 | g_loss: 1.4821
Epoch [    3/   30] | d_loss: 1.0479 | g_loss: 3.0011
Epoch [    3/   30] | d_loss: 0.9481 | g_loss: 1.6583
Epoch [    3/   30] | d_loss: 0.8758 | g_loss: 2.1923
Epoch [    3/   30] | d_loss: 0.8997 | g_loss: 1.9795
Epoch [    3/   30] | d_loss: 1.0755 | g_loss: 1.5116
Epoch [    3/   30] | d_loss: 0.8166 | g_loss: 1.8448
Epoch [    3/   30] | d_loss: 0.9678 | g_loss: 1.7213
Epoch [    3/   30] | d_loss: 1.0320 | g_loss: 1.5058
Epoch [    3/   30] | d_loss: 0.8901 | g_loss: 1.3501
Epoch [    3/   30] | d_loss: 0.8746 | g_loss: 1.5287
Epoch [    3/   30] | d_loss: 0.9079 | g_loss: 1.9792
Epoch [    3/   30] | d_loss: 0.9698 | g_loss: 2.0453
Epoch [    3/   30] | d_loss: 0.9740 | g_loss: 1.5760
Epoch [    4/   30] | d_loss: 0.7405 | g_loss: 1.8903
Epoch [    4/   30] | d_loss: 0.8299 | g_loss: 1.7719
Epoch [    4/   30] | d_loss: 1.0452 | g_loss: 2.3398
Epoch [    4/   30] | d_loss: 0.9736 | g_loss: 2.1963
Epoch [    4/   30] | d_loss: 0.8177 | g_loss: 1.4585
Epoch [    4/   30] | d_loss: 0.9441 | g_loss: 2.4305
Epoch [    4/   30] | d_loss: 0.7925 | g_loss: 2.3339
Epoch [    4/   30] | d_loss: 0.8828 | g_loss: 1.8397
Epoch [    4/   30] | d_loss: 0.9414 | g_loss: 1.4070
Epoch [    4/   30] | d_loss: 1.1332 | g_loss: 2.6976
Epoch [    4/   30] | d_loss: 0.8742 | g_loss: 1.5450
Epoch [    4/   30] | d_loss: 0.8829 | g_loss: 1.0671
Epoch [    4/   30] | d_loss: 0.8194 | g_loss: 1.7808
Epoch [    4/   30] | d_loss: 1.0686 | g_loss: 1.7673
Epoch [    4/   30] | d_loss: 0.9202 | g_loss: 1.4023
Epoch [    5/   30] | d_loss: 1.0265 | g_loss: 2.5349
Epoch [    5/   30] | d_loss: 0.9863 | g_loss: 2.0533
Epoch [    5/   30] | d_loss: 0.9623 | g_loss: 2.2131
Epoch [    5/   30] | d_loss: 1.1617 | g_loss: 1.0398
Epoch [    5/   30] | d_loss: 0.8428 | g_loss: 1.2622
Epoch [    5/   30] | d_loss: 0.8850 | g_loss: 1.9289
Epoch [    5/   30] | d_loss: 0.7996 | g_loss: 1.5863
Epoch [    5/   30] | d_loss: 0.7975 | g_loss: 2.5573
Epoch [    5/   30] | d_loss: 0.7397 | g_loss: 1.7338
Epoch [    5/   30] | d_loss: 1.1850 | g_loss: 0.6370
Epoch [    5/   30] | d_loss: 1.1471 | g_loss: 0.8972
Epoch [    5/   30] | d_loss: 0.8902 | g_loss: 1.9814
Epoch [    5/   30] | d_loss: 0.8221 | g_loss: 1.7807
Epoch [    5/   30] | d_loss: 0.8807 | g_loss: 1.5126
Epoch [    5/   30] | d_loss: 1.0040 | g_loss: 1.5497
Epoch [    6/   30] | d_loss: 0.9143 | g_loss: 1.4498
Epoch [    6/   30] | d_loss: 0.9697 | g_loss: 1.5881
Epoch [    6/   30] | d_loss: 0.7700 | g_loss: 1.7109
Epoch [    6/   30] | d_loss: 0.9252 | g_loss: 1.3487
Epoch [    6/   30] | d_loss: 0.8181 | g_loss: 1.6099
Epoch [    6/   30] | d_loss: 0.9447 | g_loss: 2.0998
Epoch [    6/   30] | d_loss: 0.9975 | g_loss: 1.6012
Epoch [    6/   30] | d_loss: 0.8977 | g_loss: 1.4375
Epoch [    6/   30] | d_loss: 1.0982 | g_loss: 1.4766
Epoch [    6/   30] | d_loss: 1.2711 | g_loss: 1.2430
Epoch [    6/   30] | d_loss: 1.8470 | g_loss: 0.9992
Epoch [    6/   30] | d_loss: 0.8685 | g_loss: 1.0502
Epoch [    6/   30] | d_loss: 0.8902 | g_loss: 1.4306
Epoch [    6/   30] | d_loss: 1.0686 | g_loss: 2.4049
Epoch [    6/   30] | d_loss: 0.9843 | g_loss: 2.2239
Epoch [    7/   30] | d_loss: 0.8615 | g_loss: 1.4476
Epoch [    7/   30] | d_loss: 0.8967 | g_loss: 1.3855
Epoch [    7/   30] | d_loss: 1.0352 | g_loss: 2.1406
Epoch [    7/   30] | d_loss: 0.8223 | g_loss: 2.1659
Epoch [    7/   30] | d_loss: 0.8339 | g_loss: 2.2956
Epoch [    7/   30] | d_loss: 0.8715 | g_loss: 1.5437
Epoch [    7/   30] | d_loss: 0.9759 | g_loss: 1.5981
Epoch [    7/   30] | d_loss: 0.8245 | g_loss: 1.9664
Epoch [    7/   30] | d_loss: 1.0798 | g_loss: 2.0194
Epoch [    7/   30] | d_loss: 0.8696 | g_loss: 1.8476
Epoch [    7/   30] | d_loss: 0.8865 | g_loss: 1.8721
Epoch [    7/   30] | d_loss: 0.8755 | g_loss: 1.7869
Epoch [    7/   30] | d_loss: 1.0080 | g_loss: 2.5075
Epoch [    7/   30] | d_loss: 0.8807 | g_loss: 1.5631
Epoch [    7/   30] | d_loss: 0.8976 | g_loss: 1.7562
Epoch [    8/   30] | d_loss: 0.8385 | g_loss: 2.0913
Epoch [    8/   30] | d_loss: 0.8704 | g_loss: 2.4567
Epoch [    8/   30] | d_loss: 0.7698 | g_loss: 1.9500
Epoch [    8/   30] | d_loss: 1.1405 | g_loss: 1.3492
Epoch [    8/   30] | d_loss: 1.1449 | g_loss: 3.2141
Epoch [    8/   30] | d_loss: 1.0464 | g_loss: 2.4119
Epoch [    8/   30] | d_loss: 0.8329 | g_loss: 1.6099
Epoch [    8/   30] | d_loss: 0.9765 | g_loss: 1.2604
Epoch [    8/   30] | d_loss: 0.6047 | g_loss: 1.8246
Epoch [    8/   30] | d_loss: 0.7682 | g_loss: 1.5565
Epoch [    8/   30] | d_loss: 0.8602 | g_loss: 2.0388
Epoch [    8/   30] | d_loss: 1.1138 | g_loss: 0.8743
Epoch [    8/   30] | d_loss: 0.8383 | g_loss: 0.9135
Epoch [    8/   30] | d_loss: 0.9420 | g_loss: 1.9933
Epoch [    8/   30] | d_loss: 0.9059 | g_loss: 2.1564
Epoch [    9/   30] | d_loss: 0.9345 | g_loss: 1.9443
Epoch [    9/   30] | d_loss: 0.9309 | g_loss: 2.5594
Epoch [    9/   30] | d_loss: 0.9070 | g_loss: 1.4906
Epoch [    9/   30] | d_loss: 0.8332 | g_loss: 1.8086
Epoch [    9/   30] | d_loss: 1.1230 | g_loss: 2.3757
Epoch [    9/   30] | d_loss: 0.9355 | g_loss: 2.4067
Epoch [    9/   30] | d_loss: 0.8048 | g_loss: 1.9704
Epoch [    9/   30] | d_loss: 0.8889 | g_loss: 1.8185
Epoch [    9/   30] | d_loss: 0.9232 | g_loss: 1.6039
Epoch [    9/   30] | d_loss: 0.9610 | g_loss: 1.6199
Epoch [    9/   30] | d_loss: 1.1161 | g_loss: 2.2716
Epoch [    9/   30] | d_loss: 0.9433 | g_loss: 2.9775
Epoch [    9/   30] | d_loss: 0.9578 | g_loss: 2.1576
Epoch [    9/   30] | d_loss: 0.8939 | g_loss: 1.7456
Epoch [    9/   30] | d_loss: 0.8747 | g_loss: 2.4468
Epoch [   10/   30] | d_loss: 0.8485 | g_loss: 1.6574
Epoch [   10/   30] | d_loss: 0.9050 | g_loss: 2.7514
Epoch [   10/   30] | d_loss: 1.0990 | g_loss: 1.5812
Epoch [   10/   30] | d_loss: 0.7943 | g_loss: 2.0669
Epoch [   10/   30] | d_loss: 0.6906 | g_loss: 1.9444
Epoch [   10/   30] | d_loss: 0.8254 | g_loss: 1.2311
Epoch [   10/   30] | d_loss: 0.8581 | g_loss: 1.9114
Epoch [   10/   30] | d_loss: 0.7204 | g_loss: 1.7161
Epoch [   10/   30] | d_loss: 1.0765 | g_loss: 1.1725
Epoch [   10/   30] | d_loss: 0.9352 | g_loss: 2.9972
Epoch [   10/   30] | d_loss: 0.7309 | g_loss: 1.7158
Epoch [   10/   30] | d_loss: 0.9691 | g_loss: 1.7783
Epoch [   10/   30] | d_loss: 0.8536 | g_loss: 1.5421
Epoch [   10/   30] | d_loss: 0.9213 | g_loss: 1.5531
Epoch [   10/   30] | d_loss: 0.8954 | g_loss: 1.5409
Epoch [   11/   30] | d_loss: 0.9907 | g_loss: 1.7208
Epoch [   11/   30] | d_loss: 0.9829 | g_loss: 1.2800
Epoch [   11/   30] | d_loss: 0.7630 | g_loss: 1.9613
Epoch [   11/   30] | d_loss: 0.7179 | g_loss: 2.0438
Epoch [   11/   30] | d_loss: 0.6981 | g_loss: 2.1818
Epoch [   11/   30] | d_loss: 0.8555 | g_loss: 2.4907
Epoch [   11/   30] | d_loss: 1.0483 | g_loss: 1.6042
Epoch [   11/   30] | d_loss: 0.7554 | g_loss: 1.9119
Epoch [   11/   30] | d_loss: 0.7988 | g_loss: 2.2104
Epoch [   11/   30] | d_loss: 0.7468 | g_loss: 1.5949
Epoch [   11/   30] | d_loss: 0.7579 | g_loss: 2.5879
Epoch [   11/   30] | d_loss: 0.8196 | g_loss: 1.6475
Epoch [   11/   30] | d_loss: 0.7485 | g_loss: 1.7492
Epoch [   11/   30] | d_loss: 0.8194 | g_loss: 2.2980
Epoch [   11/   30] | d_loss: 0.8180 | g_loss: 1.0605
Epoch [   12/   30] | d_loss: 0.9154 | g_loss: 2.1702
Epoch [   12/   30] | d_loss: 0.8730 | g_loss: 2.2048
Epoch [   12/   30] | d_loss: 0.7453 | g_loss: 1.8414
Epoch [   12/   30] | d_loss: 0.6907 | g_loss: 1.8832
Epoch [   12/   30] | d_loss: 0.8567 | g_loss: 1.8968
Epoch [   12/   30] | d_loss: 0.7107 | g_loss: 2.8920
Epoch [   12/   30] | d_loss: 0.8209 | g_loss: 1.9692
Epoch [   12/   30] | d_loss: 0.9453 | g_loss: 1.4271
Epoch [   12/   30] | d_loss: 0.7927 | g_loss: 2.0560
Epoch [   12/   30] | d_loss: 0.6602 | g_loss: 1.8874
Epoch [   12/   30] | d_loss: 0.9814 | g_loss: 1.9784
Epoch [   12/   30] | d_loss: 0.7292 | g_loss: 1.8386
Epoch [   12/   30] | d_loss: 0.6452 | g_loss: 2.1675
Epoch [   12/   30] | d_loss: 0.9739 | g_loss: 2.2985
Epoch [   12/   30] | d_loss: 0.7427 | g_loss: 2.3128
Epoch [   13/   30] | d_loss: 0.8791 | g_loss: 0.9619
Epoch [   13/   30] | d_loss: 0.8727 | g_loss: 3.0529
Epoch [   13/   30] | d_loss: 0.9664 | g_loss: 2.8796
Epoch [   13/   30] | d_loss: 0.9862 | g_loss: 2.2085
Epoch [   13/   30] | d_loss: 0.9090 | g_loss: 0.8678
Epoch [   13/   30] | d_loss: 0.9656 | g_loss: 2.6502
Epoch [   13/   30] | d_loss: 0.6587 | g_loss: 2.2528
Epoch [   13/   30] | d_loss: 0.7612 | g_loss: 2.6134
Epoch [   13/   30] | d_loss: 1.5201 | g_loss: 1.4006
Epoch [   13/   30] | d_loss: 0.9831 | g_loss: 1.9333
Epoch [   13/   30] | d_loss: 0.8037 | g_loss: 2.8043
Epoch [   13/   30] | d_loss: 0.8145 | g_loss: 2.4358
Epoch [   13/   30] | d_loss: 0.6354 | g_loss: 1.9821
Epoch [   13/   30] | d_loss: 1.0315 | g_loss: 1.8159
Epoch [   13/   30] | d_loss: 0.7387 | g_loss: 1.9683
Epoch [   14/   30] | d_loss: 0.6525 | g_loss: 1.6299
Epoch [   14/   30] | d_loss: 0.9647 | g_loss: 2.7487
Epoch [   14/   30] | d_loss: 0.7417 | g_loss: 2.4903
Epoch [   14/   30] | d_loss: 0.5433 | g_loss: 2.5069
Epoch [   14/   30] | d_loss: 0.8965 | g_loss: 2.2083
Epoch [   14/   30] | d_loss: 0.9453 | g_loss: 1.7736
Epoch [   14/   30] | d_loss: 0.6861 | g_loss: 2.2748
Epoch [   14/   30] | d_loss: 0.7881 | g_loss: 2.9999
Epoch [   14/   30] | d_loss: 0.8849 | g_loss: 2.9950
Epoch [   14/   30] | d_loss: 0.6646 | g_loss: 2.5741
Epoch [   14/   30] | d_loss: 0.8093 | g_loss: 2.1279
Epoch [   14/   30] | d_loss: 0.8524 | g_loss: 2.1716
Epoch [   14/   30] | d_loss: 0.6802 | g_loss: 2.0703
Epoch [   14/   30] | d_loss: 0.6153 | g_loss: 2.1792
Epoch [   14/   30] | d_loss: 0.8486 | g_loss: 2.5720
Epoch [   15/   30] | d_loss: 0.6679 | g_loss: 2.0253
Epoch [   15/   30] | d_loss: 0.7314 | g_loss: 2.2534
Epoch [   15/   30] | d_loss: 0.7394 | g_loss: 1.6466
Epoch [   15/   30] | d_loss: 0.6806 | g_loss: 2.8647
Epoch [   15/   30] | d_loss: 0.7350 | g_loss: 1.8825
Epoch [   15/   30] | d_loss: 0.7694 | g_loss: 1.5638
Epoch [   15/   30] | d_loss: 0.6394 | g_loss: 2.3446
Epoch [   15/   30] | d_loss: 0.8407 | g_loss: 2.3960
Epoch [   15/   30] | d_loss: 0.6535 | g_loss: 2.4705
Epoch [   15/   30] | d_loss: 0.8699 | g_loss: 3.1327
Epoch [   15/   30] | d_loss: 0.6239 | g_loss: 1.1970
Epoch [   15/   30] | d_loss: 0.6502 | g_loss: 2.3649
Epoch [   15/   30] | d_loss: 1.3267 | g_loss: 3.1864
Epoch [   15/   30] | d_loss: 0.7617 | g_loss: 1.1106
Epoch [   15/   30] | d_loss: 0.6903 | g_loss: 1.7836
Epoch [   16/   30] | d_loss: 1.1235 | g_loss: 1.3417
Epoch [   16/   30] | d_loss: 0.4944 | g_loss: 2.6524
Epoch [   16/   30] | d_loss: 0.6884 | g_loss: 2.3265
Epoch [   16/   30] | d_loss: 0.6391 | g_loss: 2.1374
Epoch [   16/   30] | d_loss: 0.7961 | g_loss: 2.0913
Epoch [   16/   30] | d_loss: 0.6975 | g_loss: 3.2642
Epoch [   16/   30] | d_loss: 0.7129 | g_loss: 2.2652
Epoch [   16/   30] | d_loss: 0.8162 | g_loss: 2.0138
Epoch [   16/   30] | d_loss: 0.6229 | g_loss: 2.3778
Epoch [   16/   30] | d_loss: 0.6734 | g_loss: 2.4384
Epoch [   16/   30] | d_loss: 0.6576 | g_loss: 2.0210
Epoch [   16/   30] | d_loss: 0.7720 | g_loss: 1.9787
Epoch [   16/   30] | d_loss: 1.0057 | g_loss: 1.4925
Epoch [   16/   30] | d_loss: 0.7821 | g_loss: 1.5256
Epoch [   16/   30] | d_loss: 0.6956 | g_loss: 2.1498
Epoch [   17/   30] | d_loss: 0.8496 | g_loss: 2.8944
Epoch [   17/   30] | d_loss: 0.6882 | g_loss: 1.5980
Epoch [   17/   30] | d_loss: 0.7161 | g_loss: 2.6784
Epoch [   17/   30] | d_loss: 0.7652 | g_loss: 1.3452
Epoch [   17/   30] | d_loss: 0.7144 | g_loss: 1.3927
Epoch [   17/   30] | d_loss: 0.6743 | g_loss: 2.0398
Epoch [   17/   30] | d_loss: 0.7930 | g_loss: 2.2126
Epoch [   17/   30] | d_loss: 0.8012 | g_loss: 1.7241
Epoch [   17/   30] | d_loss: 0.6713 | g_loss: 3.0115
Epoch [   17/   30] | d_loss: 0.7623 | g_loss: 2.0236
Epoch [   17/   30] | d_loss: 1.0357 | g_loss: 1.0852
Epoch [   17/   30] | d_loss: 0.6494 | g_loss: 2.6548
Epoch [   17/   30] | d_loss: 0.6142 | g_loss: 1.6067
Epoch [   17/   30] | d_loss: 0.5688 | g_loss: 2.8062
Epoch [   17/   30] | d_loss: 0.9152 | g_loss: 1.4555
Epoch [   18/   30] | d_loss: 0.5961 | g_loss: 2.1684
Epoch [   18/   30] | d_loss: 0.6489 | g_loss: 2.1119
Epoch [   18/   30] | d_loss: 0.6594 | g_loss: 1.7291
Epoch [   18/   30] | d_loss: 0.6310 | g_loss: 1.9013
Epoch [   18/   30] | d_loss: 0.5407 | g_loss: 3.1199
Epoch [   18/   30] | d_loss: 0.5851 | g_loss: 3.0202
Epoch [   18/   30] | d_loss: 0.7568 | g_loss: 1.6911
Epoch [   18/   30] | d_loss: 1.4956 | g_loss: 1.0572
Epoch [   18/   30] | d_loss: 0.9164 | g_loss: 3.0744
Epoch [   18/   30] | d_loss: 0.5348 | g_loss: 2.2550
Epoch [   18/   30] | d_loss: 0.6233 | g_loss: 1.9595
Epoch [   18/   30] | d_loss: 0.7174 | g_loss: 2.2655
Epoch [   18/   30] | d_loss: 0.8488 | g_loss: 1.4670
Epoch [   18/   30] | d_loss: 0.6432 | g_loss: 2.2061
Epoch [   18/   30] | d_loss: 0.5381 | g_loss: 1.7410
Epoch [   19/   30] | d_loss: 0.4905 | g_loss: 1.9849
Epoch [   19/   30] | d_loss: 0.7116 | g_loss: 2.0552
Epoch [   19/   30] | d_loss: 0.6038 | g_loss: 2.4345
Epoch [   19/   30] | d_loss: 0.5420 | g_loss: 2.9336
Epoch [   19/   30] | d_loss: 0.4958 | g_loss: 2.4802
Epoch [   19/   30] | d_loss: 1.1815 | g_loss: 4.2488
Epoch [   19/   30] | d_loss: 0.8499 | g_loss: 1.4854
Epoch [   19/   30] | d_loss: 2.0992 | g_loss: 2.3442
Epoch [   19/   30] | d_loss: 0.5266 | g_loss: 2.3561
Epoch [   19/   30] | d_loss: 0.5961 | g_loss: 1.9492
Epoch [   19/   30] | d_loss: 0.6758 | g_loss: 2.4299
Epoch [   19/   30] | d_loss: 0.7152 | g_loss: 2.7303
Epoch [   19/   30] | d_loss: 1.0333 | g_loss: 1.2070
Epoch [   19/   30] | d_loss: 0.7271 | g_loss: 2.6709
Epoch [   19/   30] | d_loss: 0.6128 | g_loss: 1.5532
Epoch [   20/   30] | d_loss: 0.8109 | g_loss: 1.2328
Epoch [   20/   30] | d_loss: 0.7823 | g_loss: 1.4378
Epoch [   20/   30] | d_loss: 0.5674 | g_loss: 2.9168
Epoch [   20/   30] | d_loss: 0.7568 | g_loss: 1.9861
Epoch [   20/   30] | d_loss: 0.8444 | g_loss: 4.1269
Epoch [   20/   30] | d_loss: 0.6929 | g_loss: 3.8417
Epoch [   20/   30] | d_loss: 0.7461 | g_loss: 1.5578
Epoch [   20/   30] | d_loss: 0.5773 | g_loss: 2.6226
Epoch [   20/   30] | d_loss: 0.5903 | g_loss: 2.4063
Epoch [   20/   30] | d_loss: 0.6178 | g_loss: 2.6538
Epoch [   20/   30] | d_loss: 0.6544 | g_loss: 2.4335
Epoch [   20/   30] | d_loss: 0.7121 | g_loss: 1.7128
Epoch [   20/   30] | d_loss: 0.5332 | g_loss: 2.3567
Epoch [   20/   30] | d_loss: 0.5441 | g_loss: 3.5450
Epoch [   20/   30] | d_loss: 0.6697 | g_loss: 1.8745
Epoch [   21/   30] | d_loss: 0.5297 | g_loss: 2.3949
Epoch [   21/   30] | d_loss: 0.6858 | g_loss: 1.8395
Epoch [   21/   30] | d_loss: 0.5556 | g_loss: 1.5787
Epoch [   21/   30] | d_loss: 0.6189 | g_loss: 1.8587
Epoch [   21/   30] | d_loss: 0.6695 | g_loss: 3.1679
Epoch [   21/   30] | d_loss: 0.8433 | g_loss: 0.9612
Epoch [   21/   30] | d_loss: 0.6991 | g_loss: 2.3676
Epoch [   21/   30] | d_loss: 0.5987 | g_loss: 3.5887
Epoch [   21/   30] | d_loss: 0.7071 | g_loss: 1.9352
Epoch [   21/   30] | d_loss: 1.0422 | g_loss: 1.8059
Epoch [   21/   30] | d_loss: 0.6607 | g_loss: 2.4151
Epoch [   21/   30] | d_loss: 0.5967 | g_loss: 2.8954
Epoch [   21/   30] | d_loss: 0.5950 | g_loss: 2.2722
Epoch [   21/   30] | d_loss: 0.7494 | g_loss: 2.2158
Epoch [   21/   30] | d_loss: 0.6322 | g_loss: 3.2551
Epoch [   22/   30] | d_loss: 0.5092 | g_loss: 3.1619
Epoch [   22/   30] | d_loss: 0.9850 | g_loss: 2.9819
Epoch [   22/   30] | d_loss: 0.6461 | g_loss: 2.3702
Epoch [   22/   30] | d_loss: 0.5546 | g_loss: 2.4085
Epoch [   22/   30] | d_loss: 0.5784 | g_loss: 2.9134
Epoch [   22/   30] | d_loss: 0.5691 | g_loss: 2.8668
Epoch [   22/   30] | d_loss: 0.5647 | g_loss: 3.1221
Epoch [   22/   30] | d_loss: 0.6048 | g_loss: 2.3032
Epoch [   22/   30] | d_loss: 0.5537 | g_loss: 2.7462
Epoch [   22/   30] | d_loss: 0.8874 | g_loss: 1.9915
Epoch [   22/   30] | d_loss: 0.5126 | g_loss: 3.0103
Epoch [   22/   30] | d_loss: 0.7344 | g_loss: 2.4493
Epoch [   22/   30] | d_loss: 0.7071 | g_loss: 3.0357
Epoch [   22/   30] | d_loss: 0.6814 | g_loss: 2.8049
Epoch [   22/   30] | d_loss: 0.7252 | g_loss: 1.8144
Epoch [   23/   30] | d_loss: 0.6909 | g_loss: 2.5368
Epoch [   23/   30] | d_loss: 0.6472 | g_loss: 1.3504
Epoch [   23/   30] | d_loss: 0.4955 | g_loss: 2.6111
Epoch [   23/   30] | d_loss: 0.4560 | g_loss: 2.8824
Epoch [   23/   30] | d_loss: 0.8280 | g_loss: 1.2636
Epoch [   23/   30] | d_loss: 0.6680 | g_loss: 2.7462
Epoch [   23/   30] | d_loss: 0.8040 | g_loss: 2.8131
Epoch [   23/   30] | d_loss: 0.5588 | g_loss: 2.4003
Epoch [   23/   30] | d_loss: 0.5448 | g_loss: 2.9638
Epoch [   23/   30] | d_loss: 0.8580 | g_loss: 1.7791
Epoch [   23/   30] | d_loss: 0.4770 | g_loss: 2.4518
Epoch [   23/   30] | d_loss: 0.6718 | g_loss: 1.1140
Epoch [   23/   30] | d_loss: 0.5359 | g_loss: 3.0694
Epoch [   23/   30] | d_loss: 0.5465 | g_loss: 2.2689
Epoch [   23/   30] | d_loss: 0.5921 | g_loss: 4.1389
Epoch [   24/   30] | d_loss: 0.6146 | g_loss: 2.1624
Epoch [   24/   30] | d_loss: 0.5306 | g_loss: 2.4758
Epoch [   24/   30] | d_loss: 0.5764 | g_loss: 3.2768
Epoch [   24/   30] | d_loss: 1.2889 | g_loss: 4.4112
Epoch [   24/   30] | d_loss: 0.5348 | g_loss: 3.2028
Epoch [   24/   30] | d_loss: 0.9517 | g_loss: 2.9490
Epoch [   24/   30] | d_loss: 0.8618 | g_loss: 4.1981
Epoch [   24/   30] | d_loss: 0.6859 | g_loss: 2.1076
Epoch [   24/   30] | d_loss: 0.8432 | g_loss: 3.6729
Epoch [   24/   30] | d_loss: 0.5397 | g_loss: 3.5885
Epoch [   24/   30] | d_loss: 0.5745 | g_loss: 2.0819
Epoch [   24/   30] | d_loss: 0.4952 | g_loss: 3.1947
Epoch [   24/   30] | d_loss: 0.5248 | g_loss: 2.4421
Epoch [   24/   30] | d_loss: 0.8239 | g_loss: 1.6776
Epoch [   24/   30] | d_loss: 0.5771 | g_loss: 2.8638
Epoch [   25/   30] | d_loss: 0.7430 | g_loss: 2.4059
Epoch [   25/   30] | d_loss: 0.6450 | g_loss: 2.5165
Epoch [   25/   30] | d_loss: 0.5341 | g_loss: 2.2750
Epoch [   25/   30] | d_loss: 0.7948 | g_loss: 3.7045
Epoch [   25/   30] | d_loss: 0.4336 | g_loss: 2.7780
Epoch [   25/   30] | d_loss: 0.5012 | g_loss: 1.8026
Epoch [   25/   30] | d_loss: 0.5897 | g_loss: 2.5183
Epoch [   25/   30] | d_loss: 0.5689 | g_loss: 2.2989
Epoch [   25/   30] | d_loss: 0.6964 | g_loss: 1.9053
Epoch [   25/   30] | d_loss: 0.6816 | g_loss: 2.9370
Epoch [   25/   30] | d_loss: 0.7335 | g_loss: 2.0445
Epoch [   25/   30] | d_loss: 0.7653 | g_loss: 4.2181
Epoch [   25/   30] | d_loss: 0.4506 | g_loss: 2.0053
Epoch [   25/   30] | d_loss: 0.5769 | g_loss: 2.6021
Epoch [   25/   30] | d_loss: 0.5150 | g_loss: 3.8916
Epoch [   26/   30] | d_loss: 0.5610 | g_loss: 3.2660
Epoch [   26/   30] | d_loss: 0.4789 | g_loss: 2.6005
Epoch [   26/   30] | d_loss: 0.9607 | g_loss: 0.6245
Epoch [   26/   30] | d_loss: 0.4760 | g_loss: 2.4508
Epoch [   26/   30] | d_loss: 0.5057 | g_loss: 2.8111
Epoch [   26/   30] | d_loss: 0.4800 | g_loss: 4.5602
Epoch [   26/   30] | d_loss: 0.4568 | g_loss: 2.6849
Epoch [   26/   30] | d_loss: 0.4353 | g_loss: 3.3304
Epoch [   26/   30] | d_loss: 0.5041 | g_loss: 2.7982
Epoch [   26/   30] | d_loss: 0.4804 | g_loss: 2.0803
Epoch [   26/   30] | d_loss: 0.4865 | g_loss: 2.9036
Epoch [   26/   30] | d_loss: 0.5083 | g_loss: 2.4737
Epoch [   26/   30] | d_loss: 1.5320 | g_loss: 4.2553
Epoch [   26/   30] | d_loss: 0.4540 | g_loss: 3.5338
Epoch [   26/   30] | d_loss: 0.5801 | g_loss: 1.9847
Epoch [   27/   30] | d_loss: 0.5984 | g_loss: 1.8792
Epoch [   27/   30] | d_loss: 0.4849 | g_loss: 3.6687
Epoch [   27/   30] | d_loss: 0.4944 | g_loss: 3.6845
Epoch [   27/   30] | d_loss: 0.7571 | g_loss: 2.1481
Epoch [   27/   30] | d_loss: 0.4562 | g_loss: 3.5166
Epoch [   27/   30] | d_loss: 0.5877 | g_loss: 3.3160
Epoch [   27/   30] | d_loss: 0.5575 | g_loss: 3.0936
Epoch [   27/   30] | d_loss: 0.5912 | g_loss: 3.5202
Epoch [   27/   30] | d_loss: 1.3811 | g_loss: 4.4433
Epoch [   27/   30] | d_loss: 0.5504 | g_loss: 2.6123
Epoch [   27/   30] | d_loss: 0.5388 | g_loss: 4.1098
Epoch [   27/   30] | d_loss: 0.5782 | g_loss: 2.6020
Epoch [   27/   30] | d_loss: 0.8659 | g_loss: 1.2586
Epoch [   27/   30] | d_loss: 0.4736 | g_loss: 3.0762
Epoch [   27/   30] | d_loss: 0.4717 | g_loss: 3.1176
Epoch [   28/   30] | d_loss: 0.4285 | g_loss: 4.1634
Epoch [   28/   30] | d_loss: 1.1709 | g_loss: 3.4765
Epoch [   28/   30] | d_loss: 0.5869 | g_loss: 2.5733
Epoch [   28/   30] | d_loss: 0.4399 | g_loss: 3.4140
Epoch [   28/   30] | d_loss: 0.4894 | g_loss: 3.5307
Epoch [   28/   30] | d_loss: 0.4768 | g_loss: 4.1650
Epoch [   28/   30] | d_loss: 0.5810 | g_loss: 3.4445
Epoch [   28/   30] | d_loss: 0.4450 | g_loss: 2.4948
Epoch [   28/   30] | d_loss: 0.5111 | g_loss: 4.0581
Epoch [   28/   30] | d_loss: 0.4583 | g_loss: 3.8862
Epoch [   28/   30] | d_loss: 0.4289 | g_loss: 3.5484
Epoch [   28/   30] | d_loss: 0.4638 | g_loss: 2.4979
Epoch [   28/   30] | d_loss: 0.4892 | g_loss: 2.9506
Epoch [   28/   30] | d_loss: 1.6607 | g_loss: 7.0988
Epoch [   28/   30] | d_loss: 0.6983 | g_loss: 2.3378
Epoch [   29/   30] | d_loss: 0.7324 | g_loss: 3.6672
Epoch [   29/   30] | d_loss: 0.4644 | g_loss: 3.0838
Epoch [   29/   30] | d_loss: 0.5147 | g_loss: 2.4399
Epoch [   29/   30] | d_loss: 0.5229 | g_loss: 2.9722
Epoch [   29/   30] | d_loss: 0.5938 | g_loss: 3.1863
Epoch [   29/   30] | d_loss: 0.5531 | g_loss: 2.9669
Epoch [   29/   30] | d_loss: 0.4509 | g_loss: 3.4131
Epoch [   29/   30] | d_loss: 0.4572 | g_loss: 3.4451
Epoch [   29/   30] | d_loss: 0.6997 | g_loss: 2.1221
Epoch [   29/   30] | d_loss: 0.4518 | g_loss: 2.3035
Epoch [   29/   30] | d_loss: 0.5861 | g_loss: 1.6609
Epoch [   29/   30] | d_loss: 0.5561 | g_loss: 3.2760
Epoch [   29/   30] | d_loss: 0.4356 | g_loss: 3.9985
Epoch [   29/   30] | d_loss: 0.5141 | g_loss: 2.9125
Epoch [   29/   30] | d_loss: 0.5137 | g_loss: 3.1683
Epoch [   30/   30] | d_loss: 0.4521 | g_loss: 3.4633
Epoch [   30/   30] | d_loss: 0.4439 | g_loss: 3.4074
Epoch [   30/   30] | d_loss: 0.5663 | g_loss: 2.7672
Epoch [   30/   30] | d_loss: 0.4449 | g_loss: 3.1115
Epoch [   30/   30] | d_loss: 0.6704 | g_loss: 2.1116
Epoch [   30/   30] | d_loss: 0.4897 | g_loss: 3.0948
Epoch [   30/   30] | d_loss: 0.5339 | g_loss: 2.1338
Epoch [   30/   30] | d_loss: 0.4951 | g_loss: 2.4438
Epoch [   30/   30] | d_loss: 0.4240 | g_loss: 3.2526
Epoch [   30/   30] | d_loss: 0.4930 | g_loss: 3.1736
Epoch [   30/   30] | d_loss: 0.4810 | g_loss: 1.5427
Epoch [   30/   30] | d_loss: 0.4807 | g_loss: 2.9795
Epoch [   30/   30] | d_loss: 0.4306 | g_loss: 3.2394
Epoch [   30/   30] | d_loss: 0.5851 | g_loss: 2.6255
Epoch [   30/   30] | d_loss: 0.4809 | g_loss: 3.3806
</pre>
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<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<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;[21]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
<span class="n">losses</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">losses</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">losses</span><span class="o">.</span><span class="n">T</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Discriminator&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">losses</span><span class="o">.</span><span class="n">T</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Generator&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Training Losses&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
</pre></div>

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<pre>&lt;matplotlib.legend.Legend at 0x7fc734184ba8&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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Y49LIB7JpHeJxMZ5+o5Hfc0rvVTXV8hcLkPt8kA+H4Cx9ca9UuHa+KMtwHLI3Y83KMDlDSguzbcvgvMCXWKsRGnBHJg6mwPnZ6e+/kLBRX/y5/8TZt+eKLxYZConeY7csOuysItxms0+fyl2vzlDdzmaa6Iv/VRdh5wOMe5BLhnP1Z/6PdQR7i+SoV+HsJB/rvfEfL75PSec27TETYBEklcPMSY5sEV+WCo55QfCn9NgHZ6OH5UAaF0GDNLHEvKs3e/9wptPCDbd4fyPM8FzZrDA2JIt0rO5SnWJwdwCf/0Ax0ZePronq45livuwak+79KxHMdpChwnIQYa0rW1mYsTupoDs+33Vf8R5uQS81oOh9EanXBxKYz86I3y3nmt4wthV+29fqvrv7xSXUeZyinu7H4vyvO81o368qXyegYH7NW15qE+8P4u8ONeF3j/iutSPSuJefQFbrlwkPc8/i2OqGF8LptjctnGsRqsiejijLXYBhofv/uYYDZHtAS4zFZYG1/PtR5nJIQ5+lqAtW6Oapz+Gu70tiNpMplMJpPJZDKZTKatZF8kTSaTyWQymUwmk8m0lbZitTzfd0mzzc4t3RJOfDTG3NgyBk4xGcs96hWC4J6/Fg40ngBHg9sUiB5XYsu2RuDXGq6sC6/Z8sZ2NMyVHA3sGHw58Og8CpQPLF0Bd8w/+z/+qE0/goPX04+F5ZDEyYGu+Bvugrqm2lGg3rzy3JvF+p3+5lJl9WqM8iyFKSZ0zESU5QL4og93wRrYBrGfNBCmNQK6EYTvRpToXpg2ToKVRyxF1wbgYxiAtR4IC2HbKRiIGJjDPKfzFrBYYGJs48xEjecSn4mA/N2lfM+5tIlOm8RwbY2UpzMgDl6oMu8Aqxvtq16SGK50aPefPJEL6BGcAX0gQwGC/CaJMKkYLsbdZI2IdHspPgNyEsAB8VOln1zLBfP5MyFwn332izZ99lyuirOp2izR4hmwDVBoG9iRj0DTfbjC7g1QaHeoIPDdaG9dXn0gYidAUk+HKvODkT4/HApf6w1QzhifE+CJGyarNBkGOpMAIR3s6Z4f9x+16Vvk8sedZ+1nr881fjMQecjAzui/izmOFcAlusBYcjRAXuCyuwfE73ygcSuHC2OBdEzXxghc4h2qLCt33bh9T4GUeRibQmCC4QoO3RHmG8wxA9Spl6tdDnoa14YY4+hIuUDfzOEyWmHSSxrEykObrxjYOtM87Ad4p4wonfpaUdLxGHhzhnrHe+dwyuykate/+ju5Tc//keaiB6dqg5nbDRNZFZWbNDj8NTCy1ZLzgb9x/a1Y1ySo8xrHWuAGme5xbET9Ao98+vRxm/70W5+26T04MHvL9f3zheorBsZO53tUoyuAgidA+YaVxpX6CPOa/tTVX8nR9tUUzp8YZOYljsJgbi2Bmvtw8L5r3ZriFlhL1AWRb2CaQEw/vC+c9fvf+qhNn+xr3EmG6nejgea7tI+5L1EdOLrwb6ztgDM2C0A/hos18HaHOq0LuCtjvAkTHv/B/M9jRpjbPYwlDvNyhGctS611Z0shrw4YabojRrksC3fTOIk/+/Kz9vOLN/ru4GE9zXlwH+kO6jfC5M+5j8dAuphbGQmCR7RCfGeoUY9Fg7lWWAF7FblS3AORLjIeA0FzKYGCL1PVaQBWtfTQZ6+xLsXcOsV4NgeKG8A9uv41jmLZjqTJZDKZTCaTyWQymbaSfZE0mUwmk8lkMplMJtNW2tqG8HartsYWrCMqgK+mcRcYJFyl6PT35gvhETMEa84WQAmB0YCEcQ54RJXDZZTMVoNienDRdNw+xscecLAQEZ8ruGCFdPsELnT11a/a9M9++MM2/dE9uWOlwL2yAq6lBEAZgNrfjUtk4SJ3WawDFC/hHpUlCJaNAKWljyDEcOzyQrrMgRcGvjYEQjFM4YpGnACfR8ChEiBYty52aGquAySSmGKKZ6Y9XTO+UZm/hpMncdYboBpT4CczYNQ+g71+DQbAJliV5Tuv+U3lB55LB+v8HgBLGkyEOGTIX+3rPfeBuY7gDtaDO+gnH8i576OPhJSNDg71rL7SMdDPCugX6yxshpwwBNrkvxvz8NEHB4fKy/GB0vfglvf8b3/epn/15edt+vxMKM4VnAaXxFyJfoEvjx2x0N0gyoHnu364LvdDMMenwKhO+3JS3d9THfWAiKdw1YyRV7pC01WbDsUecMqogoMn+mOM/tA9XT+rB3Trpz/7ZZs+u9FYcnmjQMl0D/Xhnj2bYvzA2IMh2XVPhYyd7Anre36mow8TOG/7NRE2OIjXO0Ii69otlk3e8TohnHgjINRRwHEPbr1dpR/vaf44ORB29fCxjkw4OPexTmugXKsMzn1zjX234xRxbro4z3DEZAIktYc6onPz1TWDmKsQumhHBea1Cn9bxAheP1edXrySk+S3P/mO7hntph6LonQXb9fPv7jQ+8ywDii/xq0bJqjO9/A/cGMcIDB6H+PkIdwbf/vpt9r0pz/4Hfytxvay1P2LpiK9BGsV1imd0Wmni3M+FVFwXeG66LMjOIjOhmqPF9fq42Os1zwGTEfb5xrM3/ATvzvVVe2yxg26plMrj52g7kbAzh/t7+NzvTNdPTsoixCO4ezvPALm4xofKCFd8W9PVPkJHeOVrwp4e8UyRFeo0S54FKvM391mowiIbl/vvZzrPveP1Q9ejzW2L7g2381JLFesVu7yy/URijfPPlf+cEQuxVrw6Ejv0Ef5R1hbhzii1enr/VO4s6ZdHfNJsC7ysAwIN44zoS+t1p8XOKrj4fjdRlq3a12GnXNuMdH6pFyqj1QLpUOsRVPkpcN1Pc478BjRdMZwBYgysHEg7f1kO5Imk8lkMplMJpPJZNpK9kXSZDKZTCaTyWQymUxbaSt2sna1WzXb5j7cuMKa6CccGJ225M8ub9r0L5/J6W9yoaDjFffGwSqGCYKzEt1hUFugfR4Qgttg6AHeFDvQbgWco9oI4Aw8A+6kdDdKkS8PjmtffC4nyecvnrbpTz5WugaGVgI5rFdwwwt2g0TmXuxeputgxlks7K/Gdn/tC2WoUUZ+Rfc5lYWPptQF9vP0QOjbANjoHpwkhwhquw+8p5fCkarBLOoN9zsgH8DEki5cSGFIlg1VX69x71++ESLhLd/tQEyMl26BGd0QCSmgDPJie1TgfeQFziUNxZGmwLLneul4TyjU5OZlmy5TYB6J0g+OhQ8+fKxg9AfHcm0dHujzuAensK/BdSJ2vlt0B2yNh38P0HcDfO5lao89OOQdn57o3kC24h6Q1EDY+f2Z6vp8LGwvQd7DWHW9KhDwt9pNPdb12vHTOedyIPo99IX9Pb1zH0hZmqDs0Ac8urChIZfE7TawZ/ymyLEXGGIQEptbj18P76n8I+DBX70WjvjlMwWRPr/QUYYa/b5f6Z2uccTh1UvNGyVcCh9/R2jn6EQI0rVTnWZwrivp0uzt6vfT2lUNRhTB7dcDUlYl+jzNgXjizMY9oFbfR2D40xP1tSGwq6wEDg6sboNoxnydF/rbqmkbEY5s0JF0OtD9FjP1hWPgcw8OhGCfXchd+epS9TidqV7o8j5ZwLEyBbaH8vjiXOPW7+Y6nhDBYfoulZWVe3G1HieuML4vud6AQyVdx3nEJkcw8hTO3XQ4DzEnPn2i4wOffF8I7wjurGGoPpYvVBa3dwwKOM9/zXxUbyC3WOfg/RjIvsYRkw6OpBwdqz1eT4G2PheSt8LfekDmljcah5dTHvO5YzXZjbE+y5a07Yc7KsbSUU/pmEcvgLZGWFxEOB5ChNUD0s15zgN2ziMTfjNvemgXFXBHv0Z0Ah45ynEUqaTrssq2BHdd4VgY22/MIx44FtSle3kfeOQb1XuW74ZtLYrCvXm9do09P5d7bLnQs48xPw5HcGrFujREv4uBfgZdvU+KtSOdWvkdhK6tdHx1jF5xW44YP2h5XOO7To1jU+VSfadYKD2+liP6Ei6sRGG5OuERvBhjT7/Uu05StZkM91xgvf++sh1Jk8lkMplMJpPJZDJtJfsiaTKZTCaTyWQymUymrbQV2lqWlZtMp80fYjsY28QM0DmG49vnfyvc8+alAomGQAt6DEwOayQfn1dANHykQ3wnDoCm3aYSbOUT45rD1WkFh7ElEJUlsAGPW8lAJBLgSGWmdzoD4vVtBBNOe9o2v74WAkQK0t8RguUHkesN1xhN+FroQ7qB8WCLP1a6WsHpEihshI31UUfv/2BPSMAh0KUetvn7QNx6QDq6sFQLm2syB8ssOF85IBlkuui+O+oiSPsJkIQVAndfMXC2yoZVseHdifa7QXYAfaIj5p2qds5rqqwK4eBGhAaoW4mg4CkQ9JOhXM4enioQ88GR0t19uYYGCAzvNp4lvGcDSyUi3IwPDAQdABumE/MGjshg1kB32O97COJ9el9urksgYNdwepsAqSpQeQGc1kq0pWy1G3dBV9euatzvOkMEUz4Q0jZE+ceo0wDOjBv4Wgk0Cs3Pq+gcB/wSGNyGqSmPGyDtN22ajrsnI7WXtCPs7f6+MNRXr4Qpvjp73aa/eivktcR4ewEU+c0bXUOH4BTjSh+4Y84gzkSMyt0gys455zX8Uj5VW+kPlKcUaFruq/3RrfjJY+HC905U7z3geRWjVWMMKhCYe+M16crnE5VbX+ShkYAA23D/rSLdO4Zjaj9g+avN3sA9++0EDtvIVlFo7qvhPgtTaXdzLVx2jvlnD66Zd6mirN35ZF1/F0vlaYnxs0I5e8A3uT4J8DmMyV0P7u0fnKiuP/mujr7sj1SOEVw7vRroYUS8dv15WcLBd4XxoKLLLhxckd+SbQe4XUVXfow9XbSZ+/d19OHllZDDJfITY85Z4JhAtgBqe4fyPc+lDUIastFhzOxj3TDC2JuO1ACDDtY5uD7kehXIMaMG0KXa+cRS0cCxjvEbB1UfbcSjez+QY64rShz5KeDmWnDeJEIJ+25Msy6I6T5L714ce+JzMScUq93UY1EU7vJ6PfbfAPHs4XhUL4WzLr6PdLFW8XFcLSJODFw5iFHvOFoShu92bSWWHAQ46ta0AR5VyTCWVIjaUC0RRQJ9rYLTNqNkBGhfJdD08muK39uYCDCGox8Q1a8MbTWZTCaTyWQymUwm065lXyRNJpPJZDKZTCaTybSVtnNtrUqXNe5cZSiMrA60fXu7Be2cc1ev5bB0A9fWwUh/e9iHAyH4gxDb5ytEd643Ap3DDQ/ub76n/MQNstWBM2XP6Zl+D4E7C6BDXSA6Ez3/aiq0Jl8iyPNCGG86k8Pkq5dypWWg3o+OhSzN4Ui5gNNb+XV71b+h4jBwDw7XTnunHzxuP7/86d+26Xwi5ChjwGAPrnEMYg6cuANnwi6C3aYIQs/gqUkM91diEyW2/Bvn3BDXViWRLjLBwLTAaUUdBLhPhd49BrobXQmjOr4AEgk0bgLk4PVE19wAfcrpLuzv5vea2nluVazxi4lTOR90hUsVJdA09J0UGMYhglyPRmqXXThD+kB0CiAyGw6AdPgEHukBNambOvOBwNfAbIjsEXEs4NaYZ+qDS6d0RfdoYICHR3A83YejL5zN2O9WKzgDY4jMgPfcqWqhKwncpxPgOj7xNqCEoOc2XGVroo9EVT29G1Fkusg5IG5ViUDIQINaogZoDdt5hP7dwzs9fqS2mXSBFwFPzUr0u4XQ1qtLpWe//KJNnz6U22UE9C7sAFOiU3exG3fBuqpcMV/nnXhZhOMTOdDiCvnowTlwD67EMcbVGoGl0QVdgf6Tsw2wDxa8DwqjcfnccDUnFg2UrsQYyD5LvLoH9+jgUG6uMesXg8MEfW260jwI8svNEDg7xxgbBhuHDO5MZVm5y5v12DMGGrhacW7GOqSkw6nuQ/zVR1s/PdFRgu9975M2fXRw2KYDIpGc21BPAVDRuu2HQBZ9OHnWcG7WLdjVXYn1VEHDVw4gdLcGjo1TBe5wX+83L4UiRignj0cG6t30R89zLmqOTXB8S+GqmoChjmtgilhb0HU83HBY/RrU3NsovFYl6pFRAdzGka7myECAuqUxKJ5ZuncjjlXJYyD4nOMe2oOPebvk2rkLLBTIa9wlzql0XgOfvkMVReEu3l41ab1PZ6BGFyXAUFFfydcc8wl5dI5HRdBgQvr/AAAgAElEQVTvPNYv8lNuHJ3S57z/7ZEAj30U5ZwvUakg9MNa5Z/0tVbpBUTBMR4WWJtz3YLvJsyjvxGKoH5XcuN71fvKdiRNJpPJZDKZTCaTybSV7IukyWQymUwmk8lkMpm20lZoa1WUbtkgqjECms/hTLSAK2KxFO55jG3aB0/k7ncEl84D4KcRsgYqxy3n2rKdFkJh8rG2dTPgW3GzhR8Cq9wHNtDfF9bngC1MiKscyQEy7iH49Y34m5dnQnrp3nnzRq6tL54rMPcjBFJPB8rD5QwBl/3doDvdTuB+93fW+NT97z1sP/9fusr4j/7oZ206XwhzdT4cXIE7+D7czIAxOSBY/aFQiQHcOSPgqhGwAaIj4S2QQ3yA/CQctny4oNF/qgIWFQHBOgCq0YtVLx+cCKO4QTDuV2+vlQfgJa+neto1EILFjlwiPc9zcVMHhwgcftQXlt0/Ero8Cf6mTadAursd1V0CXIlOjgVw3sBHWQORcTVRZKCr3t9HJYoNN1D+HfpdDtQNOGsJd8cq59/CMbECopIrndBtGv0rglPrHLxXQXfBcns3s/dRVVduvlzePqT9vJOor9Fp0wPrtOkSCbdA1gV4O1KudIWuAe/Q+ZNOsGwPtw6utUcU/d1IDH+tpKPeXlfjXnlPzq4ruNhdXWk+uUEQ85s3CHBfa4xNhrpnB66DRaK6q9xuULqqqtxssW6zHQSwjrtil2bncCnFHJMEuqaf0P0YDps+8UQga4QVGeiaXB0RVbo0NmVBB+6agekxdvnoxxsIOjhb4mA9uqf7OM6C/v52pHqcvwGyDrdeD+6jRMXcjuqxqGp3MV2PMcsNbBUO3XSoBHbmo3B7COj+yamw1d9++q02/fCe1hYpMDy/IJJI1B4YHtp3feu+C1fgwgE1BIrLdkf8lv13k9TEGIOxpEY9cq3SRyD3TqQxfB7B5Z5YPVy171J17VzelCNRe7q2Ejct6GaM90lw9IXYZIBx2Eea2O4GM4j+WGNeqZiH27ImFs1xGtfWWHfTabNANAG6nX+drSfxdYf249c4roRjFnSiDYEJe7tZ5riyKN31+frIUYRy7sCRleVCk/wKjvAdjB0B1oge17FwcOUREtr2+4zcgDazsaRpshPguwaWVhtlSJNUL1adenBwTYHFhoH6dYbIAjWOhCT46lBgfErxrmmoeo98pfN8e0TZdiRNJpPJZDKZTCaTybSV7IukyWQymUwmk8lkMpm20paurZVbzdb4SQYHqBDbtIMenLz2tK17H8hRDxheCoaiqunapvtnibazZ0DZrm+ExcwQALqA89QtKeCDsbzp6B5JLoRmrye3vM5I73FvX1vox3AdvJkrj31EHF6gPBD7111dCMF6eSM8st9T2cQI5F2V9Fe7O3X7qfu9P/iOc865CzwjOvndNn2YnLXpv/qjf9umr1HOCyBoVU91FBdEJYFQhnBqBQqbxsT26LgKvKNpb6ClXIB7hz2hF6sM6EWFoPNAsJIICAewjWGkd1rO9a4hsEZvT+1hDuxoQXc1tF+3o0C9QeC5vf11OXYGep8hbMBOv6cg15Nf/nGbDhFcPOgiUDLc5PIMQXOBFEdAl/wEqA8DGMNh0gOCVt72d+A/VQV0C5hNUWk8IKRcoy5CoLUVcOUMY0kNdDqBO2Y0VLoCLlsAACXekle76Y9lVbnJfNE8A/g1Ao57cLRmkOmATtdwByW+RSS1BuZSotwr4nnAX4hgEXN1DXK5QTZvIHD4HP0+wG+XdOnu+irbgwc6+vBwJiRwUgh9fDNW21ytMN7X+rwLjDbFwFHku0Einec5rzmq8eTpB+3Hp/vHbfrF8xdtuoJbd5po7klwNCAIicnBRZBugWDKfP42TBdOvDIR1dvx1nPE6+iMCpyVSCCdYhmwnrhpSHdD9es+xpvhQGPV+aXqa4Xg3QXQ+xCIV1bthqWrnGu9oOnCWtMBE2VIfLCPvH56X/X+O9/9uE1/+OS0TacR3gH4vod49Q6Yfg0H9QrjVNUc86gwrm64haP8qwAoMsZpOvF6tAXGuMfTJHSCDYBi9kdwxh5P2nS4hIM48OlFvpt6rF3tiiaPxJL5PqzHiuNUHL4zHWIc8TDIeXifAOXo40jVRiB5lLtf//2oBFUBZBJ/54Of5Pjt4K7tMK444K81jymgj2+M25WuZ95zoNYrvGvG++OY2p2qdu52WRIB9fcwqOVAPD1PbtEbWDCy5yOvXsTx9t04K9cznAY31i4YLG6R2hBzaVRjfcTjM1iLBiXw2+jd+HyA+3iYNysea+BxIg4xWEfNV/rbBVxes19jnWM7kiaTyWQymUwmk8lk2kr2RdJkMplMJpPJZDKZTFtpO9fWqm6DYaZwP+zuC09JCro7apt4OtF2+/VS6RBOmjOgS4g/7hZ0csSWfwGXogWcvwJsyScN/uFjS3eJew9HQkmfAFtl0NX5SpjN//3Hf96mxxM6xQo/GCGwcLovRBZxuTcQvgxbzBFQOpp/3aW8unBRuXaZPQ3lQvsfj1Ruj//xR2362z050v6r/+dZm/7yi4s2nRQqo25X7wzSeQMR8YDlcPt/A5UEQhE1zpsekMyQLlwpnOKAYVZAaMkkdIZqsxEQuKrSewRw0AxGcC0DljAb6po5CVYE562Xu0HpQs+5o+b1EvALDAp+79GHbfr1SMjgLLtp00Q5czrIISo1XflqtFF/YwgBFkLMY8POrEGw6DQJJzailCECRC9KIeglrwd+EgJLyYHPsQkMD+DYDBQ0QBlkC7qWKZ/DGI35DlXXKne6JTLgOMuwQl3TfY4ooe8B9UY/gqG18z18jgDNFVzp4lhumwGdXZtxu9hwlGQAZ7pB6pmThVCoi2uN91eXcjOdT5WvYVcOxEdDHWW4WuhowAJtJqhQ73guHTHLYDcone/7rpOsy/3+sYKy7x/stekQz16hHjuw2fM7yusqUzkugXJtuGrSRTDHIIQC2GhXPrHy23b37mtrYnU+MW/lsQIOT4TQBz5Xsa8B2UqBl4fh38+Xc86N+up3MZy/wx3VY+00JnolxyZdw/ylGG8/fSSc9Q9+/ztt+lsPhTpHmAcd7rMRxz6jW2zxzus3LJjbcZUYLPcJgK3SvXMDydQNCzgEJ3RmDrBWQYYDNJp+R215f0/j0BRrtBrzxqre0ULHeW17rMt3I9osoQWOTZVgeKOIx23g3om6YNsg3k38kv2Erp10xb21/ixR5z6xXGCwMeaEJZw2qw0bUFwPB9EaSDWWVC7D59Wca3m8K11/0a6SaDf1GPie63fX/b5caB2QA3+nmzPXhQ5rAh/rFtaj43oG4xSWkRtrlA1W1LEe3d+7pt7ARHneA/XL4zm8BK2Tcysd2fl9ocZRrxLzclXo8w4cwbuhrungy8miMLTVZDKZTCaTyWQymUw7ln2RNJlMJpPJZDKZTCbTVtoKbQ2CwA331u5yJTCUi7M3bZqIaVkIYwIluOE6SAc9fqsNI6CHdCMExpMQB0KA2xyBzJN0vc3NQOs5MjNBXn701ZdtusI1s5muOT8T5nkxF5q1Ak7QHcqB7+hAOGEZCyP9rd/6rTYdw3FrCQQ39neE7lRLl09/6pxzLumpPPec8LJodNWmvQ9URy/OhA1cXAFv7qu+Bgx6ijrK4HAVFHDfg0Ndf8MmT39bNOhfBSe6MdxQq4nc4Xynug47wMeAPNRwfYxCIRI0HouIyJbE7XSfE3y+AD6TARVbLXaDfHjOOa/BEOZwvpvBYWyUCg2M0P7KG6GtNfA5oq0BsAnWY4z+WBO5hMsrsStSIXXjQEjHuwBojw/kZIX6LYCYzedE2oW6XI/VZqsSDtAYk+gwfXIo5PCzF5d6LtCOfSAf33uksvzLL166u5LneS2OU6D90Q0zhLNbUcBNF4j8siQSibEXeFW2UrmUFbE29lnVQR+Yer8rfNxrcLcciM4SDn48DvDyjerli9ev2/TnX2neGN+o/xZojwXqcYG2NodT6wJ9rQ9k3QeKHKItr4LdoOZB4LtB407e6QsJTkINcJ19taEK7xD1dc34WgjvL14L4Z3OVBaBB0R7gKMEqC8kXQqsDcR6G0idbYE4Vg7s6gYu1jdT9bvJRO1xCfdjotZ7I5VHPNBxksSHSznG+xBo4dE9uZwOE92n3lE9Oie3Rx9INLGzABPFAZxnP3pyr00POqqAJfpjDjwxSOlkStdL4MooU7rr0rUzb45+lI6O9QxWTnSZTq3ANoF8xrHeqcT44QVEZIE1ws20B5fZo67mnLNQ4wCdljfcMe9SnnNBc++Cx2Sw7K1wRGuFIyigsl1Bx1IgxwEc3hOUY54R4+Z6BhhzCIy2UhvwbjFWlLmP+Txg31xozKww9gZYIxdYZxXMO9oRnc/53iTHE4yfRNA5VoQJWdC7k+97rtu4ISNogCuB8fvAOmMeeSLCCkS4rImNbjDibap2XP/hNjzBg+t5TdZ898kL9l0cZ8OaZIG1aIY+my0xZsDROZtrHuBRLK5tPKyTI3w36kYaMxIg+VFGZ+Lt69F2JE0mk8lkMplMJpPJtJXsi6TJZDKZTCaTyWQymbbSdq6tZemmN2v8cQm8LEMA1BocWwZ3oeUKW8C0uMIWc5wCRUo6+Fxb1TlwNzoAukB/WyG45my63vodwj2M9wiBj6UIdB7BtXUGhDXH9nFvIDQunwgVXK10n7dvhXP8+M/+tE3//n/0vTb90ZNvtekYWEIv2Y1LZLmYupu/+3fr5+0jeO4CW+NAJfZnQiieJLr+cKB6GSbAA4C5vBoDpQOiEwIdvn8oFPgQWHAYA9fI1vefAv19cyYE7BqoTLEEztoDcgskdRCrnLux8nK0L3Sq3xOWQzfCGtjJAQJQM2jvfKF8TmIECL5DBZ5zo6aZenRLBAJ42NP7fHiidlaNhWivxkCk+ghYS3dUOGz6Uzj6ddBP6WwLLKYCAnXrPhYkcPhEud1cCzE9f/68TZ9dCYl0QJD88N3vfXktR+EcGAmN5SI8N0CG99D3//F3Hrbp//z3f9Cm/6c/+Ym7K9VO1NNsrDadAfFEcbk5xi+6YV8B77640ni0wHg0o2U1xucE6OMAjrf76D8nhwr0fNQ4U3vAYGYz4qwq/69eCAM+Q/16cN3b6+o5QQ+B72uNBxdz4ZTRtd5jOheSnyMPNbCyEHPIIIGr3x0qiEK3f3/t1lqUyocP58ARMMh6JWfX0VDIK7G/JCbSrHxfXuidr69UvyOgvQ9OdX8v4fwLjLVF4vXvUyCsl0BYL66VngFdrkuMpWiovVB5WaBeylgYb+0T/QOSf6DyeHAiJ9QA2DXH4TtV7Vx5uy7AmEL0swvU/NE9HV/ZizRnzC7UH5cXGj+jgcbkVU/jznKItUgN1AwuviECr9e+xoqivHX71GtUdPAFvpgtgEfSWRdcfQb8tsYaKZvxWBJYPtR7zPaeqg0M0ZZfXqv9nr964XaiGk0K81EcY87GkaQcfQBDrLsBdp9iyRli7l8QP13AlRgoYdgDcol1nguIdK/r1/8aJHU61rg+u8aaE0jzCnW0WgCDhJMnaeIYdcfx3KGPd9HVegx8j3vW9fZun+8j3/dcr7POYz7FPwDR7tBNF229REXmcGMn9h2O1GdjtPUIR658nAfwsYjw3LuPLZXN8ZMS61UP/eX6WkcWLt8qfQOEtcJxpQht0/HYSoXjDshL0tUYEwLRDeC+79XEseH0i+N+7yvbkTSZTCaTyWQymUwm01ayL5Imk8lkMplMJpPJZNpKW6GtdV27vNnKnuXagh325eZHt68JtmZdBjYLyIufws0NLlgxtsk9H05wKQJdF0I/sxLb83hUtlhv/y8ZYBa4X3osR7gq0nusiOvqckdGIgTq0qF7JZwv6UJ5CUTiL//iz9r00VDIWJxqP92Lhffcpaq8cNPna7SxvAB2yYiqxF8WeJ9CqMCjE5X/CsFrz97qPc881d1iAecp2G+NzoX/fnJ62KZPR8TR1k11DOzrC5Tn1VSoQgAsyMczUzh7wbDKnQDRncBBa29Pz+oN9QfEKAKU2Qj5PUF+3sZ047s7+c65bpOXAnnqAHHodtWePvj4cZt+9uzHbXp6pTq6GKq8zr+Ui3GW654hgxPj80dPHrXpk3vC0boIUH0bV7eAS9jNhTDbn/zor5XHL4U8jTrqhB2gYT3UaRfOzKf799v0BAjYZCzkMk6Uhz2kU6Bk3z1UezzqCxW8S9VV7RYNRrRC4GG6Ms6X6o9v354pjb6zoK0kxqDEo1sgcBYG4J4B9UmE+tC5uACOPl6u0bRhctJ+tgJenSOg9hC4+v4hyhCOmL6ve09nqq8VsOjOWO30xUzt9GqiMqg3nK7hDIzA2X60m/4YBoE7ajD9CvhTDFT65FTl5eHIxP0TlUsEtGiR6ppJKhwwwWtezYRGLae6/jUc/Y6PdH9SdUVzhGGFZ95g7Dq/EUs2Ba5PIrWHIwAHh5pDE1/90Sf6CAfX1URj7BCfnxwLF+0PMQGDnst3hNLVnnNV8341+lSMOk3wPvsDjbEh8M0IeFkJDO8KOPqrc7V1OnwmhdIHKJfjU5VLr6fyrZuCyZHfFdDfm7HmyrcXQiLHQB9z2E56QMG7wFNhsO0qHi3CP/SBCrpQ+el26faNefy13JvvVJ6OfIRwGp+vyEeizDEGjXE0IICjcV8mwy670rvNVxhL0S5jsMYnR5oTj+6pP7Ie/Qa7L+aIGgCc9dVzzYmvX5+36YJ9AZ2zxhLfJ89aEL/V5yncoztAcXtwZN0f6ZoI7br03o15/qbyfd91e+tnTifAg7HmjrGGy4CHToDp54gQweNn7gwOp6nGr9G+KrufKp1i8Rhj/VFhcCqb70kFyvniHMc9nr9q01cYsxM4PSfIS44pKwZW70rVRYb5vAaq2ie6zDEGR73ca+WzrLY/MmA7kiaTyWQymUwmk8lk2kr2RdJkMplMJpPJZDKZTFtpK7Q1CAM33FujOzVQhqNjoZmRh23fXN9Tz+fEq7QduwLikK+E7pRwJvKAZjEIaQmnVudrmzZJGVBz/fnhvhBWIlWrCnl8JXfBai5cKMc2eAUHrRjOsiGCXwdwWOrj82yh9/v5n/5Vm/6D3/6gTZ+eyiVyudiNK53nahc26Fk10fuAXHI1nG9vyLOgyA8PVI4LOKV+BUffG6CiPaASw6Ecb+e5EKyfnancax/I1GiN9HSBcEaREBUYn20ENCftl3R0v85QL5L2hBAUnt77nIFfQ+U9RKRvD+6vCdrSCLjT0ZXQhbuU52oXNTgFfSjp8NmHA2YNJGMFR9YpEKjZc7lqTn3hUP1EZTQEWsoAyZ9/9lmbrtCvnzxRm04afHw6F9J19krIR4Cx4eBI/eLirTCe52/VT6dXyq8D+ngPY9IJcLAYjpGH+8BWe8KrenCu+/CTj5S3GMjWHap2dRswPPIxJAOdZ+DnJTByH+NtL1WdHgA39OBEV9MhF3XgeUSXVNfdgdIecNXbIOVvzlR3U/QXH3jVvYcq/9pT35mM1dfPz1W/40uhqtdAxgpPrZzjqiuVLzoA15gr6BIc1MRf706+57m0mVsSHnuA+/bH94S2BmONXynw9wlQ3Rs4+o1x3GK+erezHh0YQRq76UzP2kDpmt+S6Ti9wPhNJ8YO+sUKc1yJB43ncKmsdZ+kYPvS+DHs4/hCX9ccHan/phzQGCUd9X6nqoW01kD3PDge0vn34aN7bfrkQPXLvM6AsI6BNK/gKumtdP0+xtvZCsczZsIco0TIeNwEjC/gtr6Yajy8vFE7mi3VjpbAU/2YQd2R7gDrI44OK8/lQu9XwxWYaHwfcyjHoSmw+jtV7Vzd2LZmcA0m3ncfqH3AdSHQ4riruogwB9xM9c43GJM9HOVIcXRrvlQ9ziZwAO5qHgob/HSKa+dwSy7hbDzYV95X6AthojmO812IVUKdsQ3q/lzqgfTdwClHgda9nK/yXwOJfB8Fge+G/XU5TiK9Q4Q8dXCkbo42zXpf4ljUEn1jCufZBJEjzt9oTtobqt6Pj7V23d/T8bOErrzN+bprHDu4PNNaJceRjV5fY51D21xknPPV1nwgumFMZ3e4O2Nd6mEc8rDuC3kGEMeh6nL7IwO2I2kymUwmk8lkMplMpq201Y6kc54LmkPLKWLohNj26eCbcIFf0Xs4iMpfrpmDusQvU9iFrPFrS86YRkscmsYvEowV129+kdnDDtTBnn4B+ttfYhcSBg78NTeGOUOB53v4BaDGN3ofMRW7B/pFqDvHgfsb/er8ix/9ok0H34aZz/FufjmvisrN367fdekQUwyGRRliSpUL7MDhF7HeCgfYsVsRID5NBwV5OtCvN8c4kP/mWmYrszF2pfHDyOnJ+lffEgYSOYw15p/r16MX+PX94ka/QvWxw/vqWu33yb7y/tGJfkHsYrdngV+5OoiTFeAXOQ9GKRF+Wer1tuxm76naOVc1/SR0jOekcunDvCnAxqiPGFHevn5xvVnqPUu8wwp9+dnVV2365EB9qd9H+7nUbmZ1qntGe+vdqRqGKvt7iKcHk43RBXbMENTp1V9rNz9A/MNXl2pH1zf69a+T4hfoj7Rj0CllfnCwr1/3nzwUvXD/8Xfb9DjbjZmA5+RzRbOYknEu4ZBSB2rHb2+0IzjBTkP3o+/rbxET7lefq+5m2EVIQXT4j1QHaQyDERgxhN31r6geYnPdLFTnK/TTAxjyVOgKz/5OsUFfvNY4nHT1C+3LC+V3NFJbi0EF1BiHS5gMLWAg08XYVnxN7K/fVFVVu2UTQ64XYxcD49gxDDd8/EJeYy67Rny4FxeaJxgDdIF5aJnp8y5iho1AI3QTjuGI+9gY5WUwJoo6up9fKI9j7Bwxzt7bG8RKw6/fEYxnRn2QSjCXI53kMN52Q/66rrmdv317ATmMu5XfdEjGjQ6wy/4A49TxQONXiR3BF1+ofX8F0qOA8V/lcW0BU8EhdoJTjU0l6agK8ewaM7IKuxgr7BBxrRL7MESsYWD1hQxAxiBK+ql2YLiD/PjkQZvubfjroMywcz0a6T4BdpPK3SxznHPOVc1cmGExMcJu8skx5gOsY/t9xLWFSc2L56rTq4L0Eo3RVKbfui8a50hDgqtLle8x4pDeBi+sfK5t1acT7I5yh/McBk4vfy5Dngyx0Q+6qqRPHmkt9vBIZZCXmhMY/5npAdo7NrhcVuyI9AgC1x2tn5n2NN91uDuJMSLHTvEUdMXllXYHATy6/ROVRVbqha5AO5UZDCcxVsboV2kf5E0zVuSgYvr72HnEXFqWIEQQt/n1uZ5/daX39kELJozHfqz38DDGMFYvyaYQ/aDCOr30tzejsx1Jk8lkMplMJpPJZDJtJfsiaTKZTCaTyWQymUymrbQVc+d5zsXNNmkJpI8oaQycYg+xZ5aIg5bDhIfhbzwPGB7MB6pc29MekIAS27ohDsz6wHuGDd5zbw8mGz0dHv8CmE9YsziArXp4ToTn4CA5aam4pvMLTHiArsyxPf0SeO3BvranO8D57lJlVbtpE8eRsfS8XPmul6rHMbbDOwuV1ykOdY+wVX/yROWbL3X9EYIwHeKgeN+pTs+AQH98Tyjb4d76b0vQP8t9Yag3N8I8crQ1Il37I6EFjIsUg60ZXwh/SIeIo4R4jD4bLc6XM35lgvbTrXf1e03t6gZp5cH4EM9OYE7U6wqR6gFNPwxVLj4QZQ+mOo/vP2nTl8As9g/VXgcDlTXNhohgBQ1ywYPenaFwnQCmL/Mb9ftvfSiMqprTYEcI0D3E+yJO/On3hBcFiNN0da6/7Y7UNp/+9sf6/IHK4NnfKq7mXaqua5c3Jl4FDFWyhfI3mwgbfY74ml8CtVoBzXryAKYnwGKnM/W1OWJNxcB/QcW4Lg3FQtVT1ZjgpDShAgZZL1QXxUD12O8Ib3v8QCjQfCak/WBf17g5DJ/QTuYw1PKB5dC8pNtRG1sCMUri3fTHMs/d1et1jM8ABikfP5AZyz7mHren9PQMZgo8GgDE04MpWIJ5NseY7BN3rNgGVBYjxERLGtOiRaCBNYZzWQexWWcYZMIR2gWwrxB1EQOLZqw6mkUkMIjqwSQvgGFJjesz4ITejsw9nNPxAB/uI12gYI8PEOcSmOYSiCFjs8boVHtDzX2Tufp4GMCgDfNjjFiMNeZHGv+5TvM54haGGPtTYMCLQm3zCIZj12PlfXWDIy/AA99c6QhJhPb1wWPFEO709B411jwpFkkRxo3ya4yjfnPVrm7m9o0Y0jju4ZYwWsEaZoTYtx7Mg6YwOzo50RGIvT31r8tzjWXHffWfrg8EHH2pQD0WDY5fwwBvAMOzKAQWjbVQMlJ+Bx2llzgq5OE4y+xCc/hipLLZg/FLmcGQBu16H9hv3FGZ5W8wL9+hPD9wacNOn9yDaeYSxy7QB+eIZ1ni+EAF9HaPa5uHWlvM0B54jGt/qDFzCDM6H+NqDSz2tv48jMdDoK19rKmrinisnsMY2UMcZ/EKfgdSvRwcqN4rtB8e5PCQ3wjzIOvRhxHR+8p2JE0mk8lkMplMJpPJtJXsi6TJZDKZTCaTyWQymbbSVmir72qX1M22KgzTekA+UsT3YvzHFAhlAAeowNG1Dc6T2I+tgWtU2OINA93Hh7Nqgi3hfhOzajTQtWlH28GH9+Si93KKGGR4TlESmwW+hZiDHnBHUKuuvhIKATLMFUB0VjEcROESWfR35Ernea5q0GG/h4JGTMkg0vvHMNkdYGt8AHen1VD1uA88gHEns1z41vIadVcJnfn0vlCbbz8WkjhosK55pcycDoQKzOC8mgAVyOHcuLen608PhQGEcFstM6EgFXDpDvjtCLAA6C3nATtJ0ID7iNt2l/Jc7eLGdXdZIV4p0I4a6T5Q4SGcSff31DBPhnD0Qz/1QiFYR6cqxyHKdA+4W12jnwDjKct1/cUJUDfgc0mgvNx7qGsyoImj/g/a9NN0GxsAACAASURBVPSV0M76qd7p4CEcAlEGkyu5YL56rbpO8d73EPcyxfv92eeKk3mXqp3nigZnBJHiQri2Joi99/GHes8E7fJqLGTNC+GUi/I9Bk46G6ss9oFNDoFJJcDU6Bi4alyM6b64f4DYsEBuPeBt3VD1+PSD+236sKf3Oz9XvqL7etfBkTDqSaX7c+wvgNtlleYBOuAW/m7cBYuicOdNvNNrOFE/gDNk/yPFRk0wxmaYHw/3hTd1MZfNEG93BWfIAuMLpkQXdzFWw7GRmL7X9I0ICG0PODMRxF5X+SoxZ+Ub6LqeH8EtkHEyU2DvYahnDRGrzWMsYOTBq949JtypPOe8Ju9E8FNgu/sD4H0YXzoHeoek+0mbvg/MdQKU87DU9QFca0dd4MVYIoU4S5EBa+sU6/x45B1rzl8oNzhD1sBfP0I8zCVcaUPH+JJqYDHWegPgjiHGpAUGtMwH0ozxv3C7Q5RvxXHKAYmeAS1+cqRxb4j6ZXoPcQM9rHtDHkP6ALH60AeyTOPaCnEBM6Tj5hhCmatuEzyn36P1K8Y3feqOgeXyXUOk61pzRQXnfh6FyRhzEGi2h2NBQyDon+W7qUffD1zcW79T0kOb7ynfA7iuB6nKi+7eJ3C95rgWMQIF3qc/+FD3R7mH6AMeHPJLINBVk6YTc4hICBXi0zJChEOfHsD1OoAjq8MRHj/EOhpuyTkcfUtHLBZ5j5V3HvfgkZf3le1Imkwmk8lkMplMJpNpK9kXSZPJZDKZTCaTyWQybaXt0FbPuX6DLQRgWFKwF304r2L32OXADVe1tpiribZ+GZw3K2mHiS1ebOf72GJOcM3RQA9+1Fl/fgJ8sQOs9OmhcJ3Xr4QYMDC7z6wkcFDbCHINtzZGawZ2VAGzzIEGDT8U4jV4LAcpOr3dqTznqgZRreD0SCQlAtbQxU73EvhCjt8hjuCEliPbeaw6WgDdmU2B3uE9Hx4Jjzt6KBTzNniqv4C7FNDpDx4LHzscCBe6AlqcEXub6/NBR+jK4Fh/WwFXrtAePOA67EAEO4iKJbtyba2dqxfrp5ZAHHLgKQvgqb09vVsX7zkEjnX6QKh35Qs3JF8VA3GLIyEfdEibjIX2wYjVlbd4HpCPAPhe2FPeBwkC+PI3L0/Ylf9EboGOjo5wep5enSlftVx5K3CAD+7rnvsnakslgkH/1U/+zu1CVV27VeMQN4Fz4hjI00ksdOfkVPk72VN9XV/rPQsgLDVQGA/Yz73R4zZ9DGy0C/QxjoFSwWnOb7DvTqxrVwwij3HFw9+V6Ed0UjyCI2uK/lUjWPaiRHDnjlwHE0w080z1Xq4wVqGu02g346rne+3RjjrX884vldcHpwg+nqOM0Ly7HQSPxxmSDo54FF3gnnAV93GNB+Q3jYke4kjCbF2mRPBioGsRHQXhHpoRpiOmDofgCON9hH5EV3UPwb0P4LBN588Rot0XsO2eXWsMv0t5zmudjkPMgz7mbEcXWji7dogCH+odjuFunWNtU+B4iE98EH12BUfjFVBMDwuTarUeNzgGF3OMscBQ9+BQXfLoQx/oHY4ZRSXaA6732Y94FKjCXBkAI0feQrQZOqjfpTzntfMwHW4LvNsenOf3+nQP130GaIt+Hzgp6t0LVb5xqr7mYRy4vFLdFQXWtOi/5XyNJNZYexRwGw0Tup1rfq59rkSI1sJpuaLDKND4mi6gymMO11Yf9Z7dqN+VeNYBXG+/0vT/G8vzPZc2a7R5pP4V+HQ7Ba6PI0YjOPV7PvuXyiJE3XF+5HecGk6p46kQ5SWQ9WrDSXvd3hhZIgvYH7HmwRgQYFxJ8a5Jl+OnrimxjlqhvirMuQU+rzlmAGGl8/ko3f4olu1Imkwmk8lkMplMJpNpK9kXSZPJZDKZTCaTyWQybaWt0NbQ991B46x2hSC1AbZmQae6LrbhT4FAeSBEAmwHj1fCuooFEA1gUjG2YEM4ce0BBzpJ9dyHDZK3DwxyL9Q2MZ3K7neV/vmVcJJX58/b9A2cDnMEsp+uEPwaRGAN4HGFbe79I7kRfvSd31YeHgrVW6xUxnepynlu0VR9AETJQzlHwI985LuC89TFQlvmPWzV7yVAPsBsTYFHLGcKNB4DCz7cU+EN9oSBZdP1NXlFDEDIUwSEIz3RPSK4cS4v4GqJZ4ZgUj3gkQka8wqITgBymc7ENIPMgQCX/m7czMqqdpMmMPwKKEMHz5tlwMt8IQv7PQW8TjwEzgbK5QHtiICOVyhrBzyiWAmLcUBqHeqsalwX53AVC1fAOeAMGsM9sgLG4sMdDU3K1QvVaZbr/tkSDnkYY4Zw2usA/SuAz3/5mZxarybbB+p9H9V17VZNOU6AodxM9A4ncFEcwcE1ADY9GOl9rhEcegW3z8M9jTspEPAoUNso4aJc1ECgFmpX0W19hO8+guCASi5Qbr1E43qQAsfGuybA8Hy0wQxBsYsl8Ff0UwaALoDIlggWne/IXdBzfotJEZueTNT+CjiNBjjq4AO9i9B/ibyysYfgxT2Uu1+iDkAMhrRTxU1vn0T/0xh4Zo78+hgDN8Y9zP8wMXQRnlPTYTXHkZCQ9ai8Hx8IBe0N9CJE8pZwOLxL+Z5zSXP0o8acWLC+WLgFXGvxPnT09nHcYPPICuoCqGix1OcruMbThRNUsCsahLIE/l2jL1RYqyQYSwM4ggZwZPci4a8RjgUVKHPes4KDfQ33yADHf9hPY7SZQR8LpjtU7YQbZsTygbwXwMu7wLg1GzhHgtcLWNcoL8ey1hiXY+20XGCexRqUx7WKZmziCFVtYOQa4yM4HjvWI9bIPsYhGGa7IuMxEKCSxD+RLrEumOOdDnAkgajpX3/+yt2VPM93UTNXh3AyXQDzXs4xTtFVH52wQ0ReVeQwNbiIdRpwzkDfBK5MV/wCyPqiOd6G4cNlOPLWw9oj8NEW0C8SjqtoLyCh3Qp4dbHCOh31VSPN4aPC+MCjgQdwwH1f2Y6kyWQymUwmk8lkMpm2kn2RNJlMJpPJZDKZTCbTVtoObQ0CdzRcIw8zojhAGYizxGAvRgj6eQzHuScI9Hk5E8JBimwBt68MeEkNx6I+3uQeMNpRE5R6GArVOHBwCFzpHt/uaav3HlDNM2CAb6+BdgJnfY6v5GdjoUzTpRDONNa+8tFTBT1/si+klsiMX+8GpauqukUBWEck00I4nHaw3R9OVe/zFVBV4IPdBAgWAlET/ZxNhSUkcDk7uieEL0YdLOr19UQFSuzTL4FbeKUQklEinOHgUMhc6KtOQw8YNZiHAg6TAVkT4l7ABkogKBF+oxnACewuVdXOzZu8EPFcgB0/R985DFDOh3LE7U3ftOkIqKoHJ1gGsg0y4kp0hcOYAAStylQWeb7OTzEH/gOXvxSB0wM45FWB3qnCcwK003KhNri6UXoxUVubLehsBgQIeNHrnwpl/+M/+Rtdv9oVoly58WQ9TlzfqGwncIQjyshf/yLgR1GqMa7zWOkKaBwJwxKIYQXcswaylgNz9YGcxo3jaoD2H8BdsAQCPwHy3MU80AmF0PT6DKKNgOZAkTMElOaLhECZ6GhXA23NgW9lZLzuUL7vu26DZsM40OVzvcPsQs66PWBaLuNYQ4RUl9QVMEjidkAG/ZB9893utD7aUhCty6LXUb9becCZS/WjimMA2h0/38DhgGmXGz9Zw6USOCERx6NTIdgV6no209ESzv93Kc+51iuXwcLjAHgZETHgpBXmRA8Oth74yACYWg3kMqhifK4HgE7cCCrvgcmr6qaPo+96JfFj3APOkElAlI8uu+rrxHs99OsMc6WHtukyOEOibeRYa3Hu7mGNcJfynHNRMzYM0bZylPkMecpZj4C9a7rNpiqjGmu1GutejtXEXCOsXbo8qgGkO2vcsDcQRL4UMeoUZY4jDjXWdL7j2gM4a/U1/ZcdFc8qC80hfOyjE63XPlLAAfe//slfu7uS53suauaNFN8XZm/lHjsNdBStkwDdxlohpHu+j/UE+viS2CquL+EGDpNbF4LlLzfw1/Vzs4xjHZ3q9R2li6N4RFs5+AQbzv+IHIE5N8d3I2LnxZJ5oPM63gPrq5N9OLW/p2xH0mQymUwmk8lkMplMW8m+SJpMJpPJZDKZTCaTaStth7aGvjs8WiMCN3ACXAI56iCI5gbyAbwqBBcyAH4z7APdQQDOGzhrreZAK7ANj1jJrgdcY9Y4GSE2r1sBK7g5F9YXpsBSauX3kHgLnGhdqi3gXy6FL01h6BaIbHU5EJFRqq3tCRzwYD7lxjIyvFvVztWNqyYxjwhIag5crAfkN1iiMIA3z1FeIRDAoKPyOp8CPcQ7P7kvzDROVXjLTOjCLFsXJFGgCtv6FdCDq9cKAD7oqQKOToRL9cFCB8B1CuBCC6J6wFvo8kXk0weiE6Oug/72qMD7yPOcuzUDnBBjYhDcFVzp0C9KoBUl+mYA/MIn+4B+7cMhjkHPq1o4VLGAAzCCK7eBb9GNMjg0M/h2CIc6sj4VcVa6s+aq67zU50VFZ1kEiJ6pz14CH3vthLa+BpYZdLYP1PteqmtXNWU0XiDfufLn10Td3h3IPoSrZoSgwkWtckzQLhnAeHqFvjlROQ4O2Td1n7pY9zc6Q3aHwlNHo+s2Pb5S+uZa6R6OOAxSBY4OgYJ7me4/cKrHLvqvDxdhEDquYqBv5HO1gAvmHSqMAndyb11eHjj+5Us5GC6meP89vbMDAuehrumC7tMSFaiT77E9AHWCu7EDQjpBQO2q6Q+EC5OYqJ3SS2LvNZFMBCvHeFgBystXGGNCOBZ6aqcRkEsfLOZkrvZYzdH3q90gyp7vu/i2r2Ps6PcwsbNtAb0t0B/Z5gIstejw6Sd6f9KhHsuCrovADWugbK65T0mnYqLIsdpFB3NykvKdiP7RkRVHEzAO17h/gbaWecrXFE6l0yUCo6MP0kX2LhUEvtsbrZHtIRytZ3B/ToG8LiPlabXSeFhWOhKS+JrLawaSh+t3jbabhxzDiT1jLgECfdtOFjONB3TdTLtYr20QwZwf9WmNMbNi3WEe8OliTSzZx5EIuLBncJUexMr76FCY613K83wXNGuBDuYYL9Y8PZ5ozedXquuwVr0sGP0BR2h4pivwdD37YIlxYIW1pk8cHF3Jb/DaAnNThjpNE6CyA46r73YCrrG+LlAXBfD+Muc6R59ndBEGuouq3jh21u3rWMz7ynYkTSaTyWQymUwmk8m0leyLpMlkMplMJpPJZDKZttJWTEEQhm6/cXsc3gjBWsEJsQZalM3ggIRt9QT7qH1kwYezWYz0EC6UJayvpghkvsL2PJ03J02g6xs4g/q1kMmqgMNnjuKgNRMQzm4otIFuo6sbOCkB5crg/Pn44eM2vXfytE1HgRCnt1NgfuPdBFx2Xu3qxgquWBFJQfknQGtO9KdHQHG+AFK1AOpcMBj5SyEiF5najAdsFISMe/P5izYdIk7xary+fw0UqhMBSwF6Oh0LR7x8o/ot4Qocf3LcplMGfgWmVAVfg5g5IipI4/MQgXDjajeurXVVu1WDEQfoLyu01xLvkDvguXMVOgMMV8BWQmAZNR3EGJQZDnULutWhz6YD9Zled41NzG9UR5NK6QXwp37JPq16zBlNuECwd1g9L2ZKT/D5BDgnxwwPFO3kDVBMBJNPtxsu31ue77mowYV9vPNyiQDoG0Gm6Z5KNBCYTUdjUwQMssJvh95YiGMO7Ll7LBfpvXvqJ3lG/HVdBwGQ5zBWeu9ArsAMWF+sVI90tcyAxtEZ0mfwdIxPKfBLonErtFkyXsQM6Vx3l/J9z3U76z7g4YzCwYNHbfrkQGNWTUdatOmAtKH3bsSRhqwkEulUy7j3FcaEq4vzNn3rbky6bcWg3KijEFgljBFpFLoRPD3LiT7qAXzXUVdjw7AnbC1Cu8rgXlyv3l2/dynf91zaYNcBnBg7XeCLcE704q+pF6DIYYA+SAtVtF06fJaYl4sCfQNtIEQFd5rxYwmEOAcOR8fp1QpzaA/rIp/1jmMQdDxWzl2B8i9Q7yvgxyvUdYbxLEmAi0a76Y+B77tBvwlkj36RdDTYD/bVHzPiiznaHM5NhRh3PLjKezzSBey7Rh9gPyFKGLA9NGOTj/XRCq7mMRygEyxKoi4mMDZCzCceuGvmK8fxFzrP5zhWQMvZBI2gN9pr08dHWCjeoTzfd1GDDseJ6iuK1IamV0JbY7wDj7x5mAc7RFvhouyxP6J951hPFBgs6cgfcE5q+mEXx984yFYYP8qS8xSOAekvnY++XmMsr+D2XWR02ybmivUg5tma4zlcuwepubaaTCaTyWQymUwmk2nHsi+SJpPJZDKZTCaTyWTaSluxWn4Quu7gwDnn3OGhMKc3Z2/bdFDS6YgBTbGVG2ordwEUqRsCcwXtQKfUCvfHLTcCphbY8q8aPzpiVym2snM4v23GTAY24gsF8TsHbboOhW/lmcogwz33u7omPvlI1+P+8xousjdCKpaLdweU/k3l+Z5LGgc6H9veZC+WM+CLl6qvs4zIINBeoJ8BnNrouHszA9qKrfo5cNYu6m4EnKLK1ukQKN/eocp2AJQvAFZ5PRHGPJ9+2aZTuI0djbStXwbAi3I4p9Ghjo6scPYKPLq/wkETCPBdqnKeWza4Rg0nrwQoVDdRW59nRKTgbDyBU+hCmHWQApOLhNTU+bsdCCMgOsux3FevX6p+JwdrrO7srfC6HG1kNJBLKFErh3bnwTUtB9qxypTHOVyUV3AzWwFXmdW655fP1H+XM10zvxZ264W7qccwCN3hQeP2CZfY6xuVYVGpHgviSh0gr3BqDZHmOJzBAXOxQn8EH9k/gKsmoqFnaGNhuO5jMfpdBTy21xWCtED78kIEv64wThNDBRJYAc8jAEfnvBjur+EUKJlPWzoEi653U491VbusGfs2sEME0U76mj+urn/Vppc4HhIBEY+I9tKlEYhj6TY4uTbpAZO6eHvZpldzlV3R9N8F+kK1RL3woWBuAzpAIi8rtJGcaDquJ+ZZ412TocaeCM8imkUk0O1menSe81pc2ge2WiwwdgCxLblyIE6Mz0lTZ3CzX8yE5NEZs9pwv6XrNTIK9+xosC67FHUR45jAHGV4fan+yKDrSRfrHKyXXAmnfLhE0hV4jqMtKyCiSyClRYl1V6nxudfbjRt2UZbu8mY93oWsIlg7P4dbdQfnGxZzzP0MKg+j3AhriLLgfIOyWOr+OeetDlzQceSnWK7La7nhDIp1Rc6jD8rjDGurpEvkFqgm2myBZ5YOERh4zohjCVxmo1jl1AFSOzgU5nq38lzQHOdI4Sga9LRuK3y982ShuujGnAfxHQHv2YEbcw4Ef7HSXJmVOL6HzpxxXYJ6n9/moXo3wloDPy7o7kz3/frd416GdWmGdsIjfSsg7pzuMMS4nG7JcJ+Nsa5+X9mOpMlkMplMJpPJZDKZtpJ9kTSZTCaTyWQymUwm01baCm2tnXN5g8Qd7AlBiyptH+fYPg+B+oWetnXpPhcgnWMbOKErGsIlR0CUQvAKMWzkGNC6aAKvp6lQqzjVtSkwW4ctYyJFg77c5HI4rL55LjxgAgSuB0Ti6MOHeiegXEWl/HjA1t5eC4XYFRLpnHO3t6afaDFWWbyEo2AxBhZzrXd7BhewCfbe94BEgBR145nu04db3LRUWV/DDXgKx9FHo3UdnJwq6K0/1D32e2qPez7qH054v3zxpk3//DPhlvlD3bPfVV5KoAouAnoHRMGHUxeI0o1AteWOGKyqrt2ywW4O4dq6DyfEAbBwrxQGcfr4gzY9O1PA9BncJhPEpa2Ah/rA1IjLxHCrG0RqJ/Pxa92/QawGCG7fHQhR6eFzH06DDNK+4XLGANzAXHHJRvDlJND9X33xRZv+0TPlcQTErj9UWUY7QiJ932sRnC6tNoG8L5fqF2kK1AxoDd1ca6Bjy6Xq/ersrE0XQJ17QJSWcAacT/W3xBarxiW5S0QHZw2ur4QFTYBtdoF0bSCsQHE2kHLgxLOZUN858MwNR1vMCRWcCaua5bobt8+yKt14snb8fXAsB8MxXIM7vlD76ymClQO1inL0WYyBmAZdjb7mo51UBfFL3T/EfJZ01KbLxok3wj1KlGFN/BhIZga36pJ9U1l0JTCtouLgqHQKBHqAdF1zjIHTIN4jjXfjhu252kXN80foFyuMR69eqx8djuicjEqqgMPB/XWJdj+eqk1HCcY+jLHTOXBS9NmFg0t2va7rOep8vgCHGaqsahwPWcKlfH4Nl3iggmnw7vl0OiX6ByRwoWuWyO8K713yXd1uVDvn8qY/JCmwbOCeGZDQNz7c/hdC0BdjjTWBx/UZjlkBMSzp9jnRuvDmXHj5DG7gHSCaUYOQJjgy4OMoVtxRHwlRL3kmB+7rt0p3+rp3yGNnJR1qgWcSx0abdTjeRSfneP9Ul/R2hLZ6zt029X5Xzxgea229uFDZLm/UN1dYlEUZnIvhwhp0UBZ0PoXLcLCxoNAot5iq/fDoR9H0Kx8sen+EdQXWPCHnL9w7W6FeMH/VdGpF3RFzJVJbIe90i6VbcHqgNfDDJ1obvq9sR9JkMplMJpPJZDKZTFvJvkiaTCaTyWQymUwmk2krbYW2BkHg+nvr7dkZkKMAqCipIbqzhUCgAvdu6zWaIsLI0fkMjF7Ruk4Pi+mCBeQg7q0/HwBRGw6BVZRCDMpC95gB7+o90Lbv85fK2K/OXrbpxVxb6x9/95M2/YNPvt+mv7yRM2R/X9zgWzh7hdjOTvxdoTstKeAGD4G0TVSeXaCMk+dCK1YL4DTAHUBEuhCIWxLrninfB658DFDdh4PWyUh5u3e4Dox+8kiOUmkqPKAColOkqv+9E5XzwVIY0bMLpesz5ffjY6EjCX5nqdEgq5j4K16JRndo42G8I3tBJ3PhCYIK13CiOx8DQYNT2wVwmdG9p216uBLmugdUg8RWif61QLDkPNf9u3DC/fR3f69NBw3G4flE1+BmBgRulgudoqtohXzVDLxL9JRptIewFjKUwfWQ5MoEaKXLOK7spj/Wdd0GHe8dqL32hir08ULttYv3WXjKa4V+5MX62zcv5JB7PdF9DvaF7BfA3egKNx2rTlcbQdLXGE1npWtD4GOzQkhXGervphmxN411Icb4KEVfg0Pe1VLtYVag/wZwI8YkUsMNj0hPVXMOuUPVlSubQObJnsrCx5j5Em7Fi4XeZx8/6bIdbxjPOqZ1zxrOtjnGQbdi31Aa5ujObzC/AM/kLUocSQngopxvoF5wdwSaxbjoGy6JffXBwz2haoNDuqDDSRJtIAVSW4U7qkcnF+EkYWHBBReY9dVCfSSGM2mFtrgiEgo3VbrWBnBpzOhijJovcJykWtKheN2Waizp4r3jNh3pMZvHiZCvHOhfmWsOKZJ3jzELrJFAMbu5g2sr2tU12sDNpcpvieMMdynP81zYuJaHcHaezoD/Mlh7pnJ59kpuuicHcOqPtT4oFhrjKq45MVnmNMbEcZ4Aa6HBkeqp3xzh8YBw+1jz0r2z8tDX6E6KYxDXb/Ue/a7mFh4v8+HKW9N5nnN0pfxO4FD76mc6HvLjL3V06E7l+a5qjm0EOLZz8PB+m74Z69nLSm13gfbH43JBjXnoWmXkPJY7UGyUhY+6wdDnhj21jduxskYd5TwehLyU7IPAaSt0KvY7n9g/olVwNAyQX5x4aV2BnXMuGao9JKnaputqXfC+sh1Jk8lkMplMJpPJZDJtJfsiaTKZTCaTyWQymUymrbQV2hrFiXvwwcfOOefewvEwCYWx1UCtfKCtICtcBGu3CHvDEVkYOBnV2M9nEGsPTnN0NaJDXddbb4VHFZztMqEUEQK2lw6IyoAIp/L4Fi5f/y97bxIrW7bmd63dRx9x2tvfvNnna+q5SmUZBggshDFDhMTAEkMkj2DAgAkT5gyQGCBGjG0hSwgjIQZgl21hU/WeVOV6XfbN7e+5p4129wxin/3/BXXTlZHvhJ6U+v6TXBk3zo69V/OtFbF+6//NL+XAtz8WlvPHH/xhW/7g4f22vPoCDnietpJTJAh2cN/0kSj2JuX7znV6688B0eZmIjVcAZRzCefAAAnQu8AQh6nqqA+n0ADoyBAoYYeZlYHSxXC6y2b628vuus0GS7VdDCc6j8leiTwB4Rzsa8t+CSRvgQS2Ra5r9hJVTsXkvHQRxusOjptRh26pu0Fb61pVFwGbuAIilYJpCvG70flSz/lWKLxsvBTmsciR2NfjGISbGPpxH+5zdS50qbxCOV/fT+EhCTNIUrI7UVftFQ6AgqDfZXAtK4B55MDhfLB8fvJm5zZm+g5C9bEM6PIg3g1KV9drx0/nnOtgQNYVXJEvL9ryGNhwsGS76JqLU+E9Z3AL7AINChG3u7Do3XDoxbGFqVM7XjUY2OxSDoGDQM7JCWJwBdTtChh/CtfSyZ6wID9m4nL97QJI4HJJJ0WML8QqDxVC9Cyod/P7aRTH7n7jeHfY0ZhaIL49w/yxmuoZOl3MgyCofY8Ornp945lRLOGinK00Tio4ZhN/zafre2PC7VXO8ylwesQs7mMe8IC80qWwQttVuEk6Fh69/XZbPjy63ZZfwUm6QP1VSALv7+rEgOdcEF4j+FhXYP6aInZcLvScI/T7GFhbsVJfz3EkJ4LzbEaXSDi594BTjgaKTQHuJ2qwRYQrl8KtuaKjNWJmDifegrgd/Hd9ILQVYi/XdyXmh2IJ/BgOqcVMdzeDs+sh+sNNynPqjxXaKMS9HsCVN0e/P4FTK/HX6SWOWwAnjQeKq3P8bZxqvN+N9J4+jhWEERz8y/U1K+CLXk4kk6gkj3jAhRTrrxJsbY527+DeidnWcJv34doaYW2ToE0/P/uyLf/qM5VvWl7T12ocS+gONN/cevBBW87gpFpc6CgBSFW3gpN4gUneg6t7BcfXEHXNGJfgSF3MOm0ccpdY/La6xAAAIABJREFUQ3k8MoAYQHfxwhF71/s9xJISRxZqZrcAUh1HnBTQjnDuDRCrPGS1GKAvf1fZjqTJZDKZTCaTyWQymbaSfZE0mUwmk8lkMplMJtNW2gpt9fzQRf21g1UyEdaJnKduBqzBT+iApPfAsNN52GrFTqtLgB9lwClyJnvFVjH3rWcl8KFme/r1me53PFRiUDoETg6B6U20TX0OXOoxkEgP+OI77wjRuXdLLq8wMHWuq4qKwSnRmbCogdRu1zzfWXXlXLZcf+aTr7SVPhUF4F4u9MzFBRCpGAleS9RXCFc+YDEZ2uXyVBgcHV+XwD/GA7hHBqrrk6/XCeO/gSPp3kS43wiOkSUwrnmKpMmFkJMI2GqfLo6o/xBJmQvi1XRUC4B1hcT58BvNjn6uqZ3nygZFmQL1u04y7pxzoDycDwczr9CzHe2rHReZXr+cqb06+8Ad4TLmwfHt1ReftOWXf/bbtpwCsyybui4jXa8XCqXowcVx9O7Dttx/IIyFDpQpMEwm62ZSaOI6l+C3p3CLjYGYJUBUfOCl1Y4a0vOcCxscOwXSdHKheuv3VZ4cINE8nADrDG6EQNm6QFU6cMxcAjONE8QmsJVVpH4VwpGyH60RoKuFxuBqphgLwtJNgQ6dPH+Kz9H1RnvCGomRz6bAyha66BXwsaIABoY5gThlCDc+huSbVBBEbri/TtAdDVSHJ1/I3fu3j5UsexggZuLoRUwsONZ7goqoGfo67mExVTyfIcH8EljwFFjXqkl2n3KOBTZLBCsGdt0FAhZjnmfy6wJjJ4zU70b7OgZysKfyGK/PgGUua+H2AdcUyW5clH3nXNzUQUpXaMaCWp99eqlxdJSoXvZ6cELE/NGJdJ0c64mTl4q3cSjUvAcn5w4d7EvVkT9f1/sCbpR0aCzqFf4OeGSKcYSE5kPgpp0RFng4NhGjTy2AXA6xplvB9Xqecf4VSvfu3/iZrv8P/7G7Kfm+7/pNH2Hi9h6OpniIC1mt9zyBq/vFlfrAcKCYNRyrXTyMkxdPFeO8V5qAD0OekxDamhzdbctl4wxeA7/1sRYuPPRHjrVE7RLAgbM71udExFax5Ong+E+KWDqA23yecs5lTMacU+0ostbOuWx97SpC3EOc6sGheO/uvbb86lLHOirEVR5/C4Dvr+ZaH1ycKO4kTuO6P0TcSXWdFV2qF+v7XWFtSyf/Cl+ICq5hgLbyCMBoonIO5jXAUb+QLs64lxjtHsNlP+rh+sCEo4H69XeV7UiaTCaTyWQymUwmk2kr2RdJk8lkMplMJpPJZDJtpe3YSc9zXuOUOTlUkta9A20rX372WVtOBkJVYmzrRvj+2gHyGiPRdgQ0zU31t9OZkINToDtpRicyuKK5NY6zNxDOWsEtL4Ab1SDWlm4WCwc7PdV2dwqnw0f3hLN+9NGHbXlvqOsUQJaGSFgaBsQr4HTLtKLxblCBsqjd9Gy9DY5admGgLfvjEfbGddvufIok6XhLApw0gUPiHaB0j4Hb0arz3kTb6vt7QKbQNnFn3Y4hkuoGcKl69VpYXb4QasS+0O2rLQYhsFz2Fzh2VkAn6PToMdkrHM/YdB5wicrfIfKRrz+0WBJ50VtKH0nfgaTMS923H8C1dSSX4cXL1ypf6Zl7dNydCh2uvxBGcr+jceIdIPF9g175QJjzmsm6dY91BSwk0/XobEanvYwJ2OG4lhVqx2dfid/OF7pOF06oXoEEzcBIaloi3rCukcDFTLFpOtZ9nAMhusrUwJMh71WvM75EcNlL4Oj36qna6/yl2vH+g7fa8uCW+kbiqVzsr+9zUBzjKVRXl6e69tnjL/T6K8XvH//4HV0b8fZiqvdcXqo+nj4X+ne1QEJpODKWAZAwuB3WeL1c0Sb45hQEoRsN13NeNwSifK62e/FCY8q/pcA6R9/qwcXPgw9nidm6Zh8Fgk/0czTWnNfr6jrdWONqVq/reoXrZRjf9A336YaNGE/nwGrjdamL8y97uK/xRGuEGnE4xD0MOooVYahyJ9qNi7KrlYzcQ8yscHShBiJ2cqX2HcVaKxwTK4yw/sGU0cURi+WcaBrWDbdv6frHumaFNqsarL+HdVOGfr64Qpufqg8urzRXRpizJhO1UacHdHmFvgEcOkHnzNEfPTjuRuApb73/blv+gz/8A7crXX9iBJSRuLYDyhkic/t8rnp5cg53fqx7u5ho9waKjZMx1sPPPm3L0zPF2HCqfhJgkFVN//bRFikcbl9jvp0jNvRvaRzdfl/r0m4Mh+8E7q/AWXHiZeMLQQHXaw//MkO2guVSfWB/iIXiDcrzahc0a64aaLXLsG7DkuTgWGuY82fCjGeXGgO9nv42QX/txFoXRlgPLy80J1Ur9eO9kZ6519PYrOOqubbWk8vszccLUqxXfTjDJ/v6/G4H617E4RXWBTnmuBAZDSq9xQWIq11g+FFf8y+dpL+rbEfSZDKZTCaTyWQymUxbyb5Imkwmk8lkMplMJpNpK22FtgZh4MZ76y38oq/voEdvC7348uOP23IPScTjlJggkAgiWCH22OmSCWexg0Tb0PFAW/7ncKfsADfsNbhCBw5vnQES/E60lT28r9dPpy/a8hPiHHAq7RzLnXVyG85bB8IclkhmO8EzVUxUWgqp8ODaWPs7Qncq56prV9ax6jPpa6u70wOaiaTnr4BN1mB0RiNdp7tAY8B97BhOrRmQiP4+3P1COAYWTLy6fk9YCwMIC33+hw+09T8cPmrLPrDJs3OhcUvgIsGSCIfKJX5nCeAySsTLw/VLOPkFvt4fDbdP8Prd5LXoZYqhE4OV2QeW1HfAWQcas/6+2iWF01+4FC6zhPNmjCTH0UjPdvjR+2357Le/1jUr3c810lrWcFaG42znju4rPBBe5SFhe75AH6n0t7mD8yTGzhWSwD8/kWtm3kMCYTiblXCfoytt4e0G3alr58oG0V0B78uATi2BjV6kih23fOE0faDzQaJnThE/w476wO27+tvVa9Xd7DVwoKuXbbkDPNFrxgadck/PhLM+/0pOpZdLYUGHcKAsga6/OlG8PVkK+3p+Kozq2YVc9BbAkguiakCRU2B1Dtizq3cTVz3fd0njzD1NFWsWBdxxGW+HcGNEG6VA3SIkMScruuHcB8Qt7AFZU/d2U7hdz4GML/11+6Vwg1zRHRb9xetguQCXbt6LT7dJVHOvC5dsoK1JF87YBTD8AO0FxK7CePeDXY3H2hXX/QXHbbqYm5ddPdxipfr8+LHG5oO7ip8PJkg6j7mB8/0EcXh+qfcsTzUGQxyrGN8VQhk1rosZMciVHJWnVxqD83O9nmAMHgGPHCCul3AzdXBS92KgvnBULuBIzzhMh+njCdcaO5of69rVjSO+B+S7i4FUoP/VOCYxnes9T17qOMS7D7XOS7DOCWI9T+9IcbJXvteWqxdfqXyu9sjh7NlrkNY6U79bYnwnmLMmt4RwHnz0oC1HcD6vkcie20Ye2qXAcxeYQzOsc3BKwJ0D+w2wjn14qCNKNyvP+Q2a7CHWODgYcwqIUEfDwzttebr6EtfE0QCMAWaaGO1rfvSAflZwQPbhmlrSGbn5b16ofi7mwpIXcDxO8J1mcgy3Zrit+/huVCMVRI0H93gUDOhyvsEr41gfxu8QWQ8SuP5+V9mOpMlkMplMJpPJZDKZtpJ9kTSZTCaTyWQymUwm01baCm31Pc91m23Y2tcW7PGhEoCOgYomlbCYGFgn8RcawTlszdIJzk+4na2t2QkSpo4S3U8f29DXLm8VEoomSLAb93ADQJCuYA4VRcJSCrjSrYB1LYBhTuD+tQ9EhDjH1RlcRuGu5pMH4tb9Dcpzvkvq9X0FSB7skGQ6hDPkDPhxb6Rnu+VUjwNsmedorxzOWgXwjwx41ekVHKyATA+Azl6jUfz8fk/XG/eFIQz6uq8UbqYLYD8liY+CCWGlAK6tDi5qERKme+zXuE4At95oR4iyV1cubpzASiR7hlGuO+qpDm/tCSkL4Cg4At6TvAYChWTSHtqr01E5BBIR3BLq3Y1/1Jajue5tlq3xjhUS2YOkc9Gx0FYv0dhZANFZwNVyCUeyChjq+VLj65snQsO8SH3mYKI6OINbqoMbYVHC6c5HULhB1VXdjhOOlxwI5hUe9BVwz0M45fWBiNGVr4JbcoaYNezq/f276tNlCkwNSY4LOKimDZqzuNR9XV7pvko4Y0/gbOd31aemqM7iTLH3ZKbrnF4IB3p9onKGPuDDkTFD3MoX+oAwwpEIoEQ3qtq5osGRL17oGQJ08AmevwKiVABdXqCNwpzOhBhreH+GYLYRaXzMp3ADrLrAuBvnTx/YagDH0DDhFXW9gpwtiivg2CFcTvsjjbXhSM6XIVxLC8SwnH0QxyBCHg+B++xNyvc812scGw9i3bc/Bu65ejNa/eq10Plfffm4LY9/KpfSIdYcZaq/7SDeeT09WwZnxtVjXb/CeZ7ecF2niyu4Ps80pgqgzX2MlyFiYAfrIjS1Kzg/wuIzQ8NfAok8LxRL9KnOdbDYe/BIztCj/sTtSnXj2O3TgR1zYgVmE2F/A+V8einU/usTOd5G6NMhxmBU6fkTJJJPgodtOa2F8pfIZB8EzboMk3gOtDvAXD15KGzTwTE0w7I+cG9eq+Q4vsFYyr7MmHR6pTqYISYPcWTsON7q68R3luf01QBkt4sxP1a47zyj27++F0Qx8HLirAHiKmJWhbnED9U5Ak9rCHaUCkcp8nL9/lXBoyr6M2KlfbR1wLkJ68wK/avEfF4z3uK7SQYHd4d4HnR4jI4u73o7Tpd9Z9mOpMlkMplMJpPJZDKZtpJ9kTSZTCaTyWQymUwm01baai86ihJ3587bf+X1uw8/bMt/9z/9+7/7XZn+iv7+37u5a+2/+xP39/7Rz2/ugqbvrv/6H97YpR4d9tz//J//0Y1dby25v7n/4N+64Wv/cOR534P/+Bb9+Cc/dj//uY3H34dush0nk333n/zH/9mNXc/0+9GD9z50//3//k9+37dh+h314Y9/6v7E4urvRf/tP7i5uNrrD90f/62/fWPXM928bEfSZDKZTCaTyWQymUxbyatxePqvfbPnnTjnvt7d7Zj+DXqrruujv/5tf72sHX+vsnb8Ycja8Ycha8cfhqwdfxiydvxhyNrxh6Hv1I5bfZE0mUwmk8lkMplMJpPJ0FaTyWQymUwmk8lkMm0l+yJpMplMJpPJZDKZTKatZF8kTSaTyWQymUwmk8m0leyLpMlkMplMJpPJZDKZtpJ9kTSZTCaTyWQymUwm01ayL5Imk8lkMplMJpPJZNpK9kXSZDKZTCaTyWQymUxbyb5Imkwmk8lkMplMJpNpK9kXSZPJZDKZTCaTyWQybSX7ImkymUwmk8lkMplMpq1kXyRNJpPJZDKZTCaTybSV7IukyWQymUwmk8lkMpm2kn2RNJlMJpPJZDKZTCbTVrIvkiaTyWQymUwmk8lk2kr2RdJkMplMJpPJZDKZTFvJvkiaTCaTyWQymUwmk2kr2RdJk8lkMplMJpPJZDJtpXCbNx8eHtaPHj3a0a2Y/k36xS9+8bqu66ObuJa14+9P1o4/DFk7/jBk7fjDkLXjD0PWjj8MWTv+MPRd23GrL5KPHj1yP//5z7//XZm+tzzP+/qmrmXt+PuTteMPQ9aOPwxZO/4wZO34w5C14w9D1o4/DH3Xdtzqi+T04tL90//1H6//p75oXz8aipDN5i/bcjo91wdF/bbcHdzR68NhW/bCQB/mFSqWdVuuS72+nF225dVi1ZYrz2vLRZWv72txhdfKtjw/P23Lz796rnufZ225P57ofkNV2WqVqnyl63cj1UfPU3kV6HOfnS/b8tlCzzQ5eqS/ffCW24XOL6/cP/o//k/nnHNRpGeIC7Xp9ORZW85merZe0G3LnY7KVan6ujp7pfLJSVv2Cj0nmerZVG13MZ235WWma3bizvp+A9V/iestVrpGifbNSrR1rfcXTn2qdOovvUnSlt9/5722vO+P2/LXp+rXf/bLT9ry09O8LQ+OftKWf/Yf/kduF1rM5+4X//JPnXPOjfZ1f2yLx08+a8v/2//yD9ryL/7sL9ry8mrWln2MnX4nassd9PteqNbrJBizteo0xli+tTdqy0f76/HuVXpvlqsP1mhTh3tZrPT6+VxjZ5mrznFJ52PceZHatKwxHl3VloMobsuDvYO2/MGH77flvSPFgZvU9ONfuf/r3/uxc865YYjnWepeT2Pd618+V9z7V3O9/4XXa8uvUBd1pesEkdolxiisI9W15+k9K7RNL1J/CDvrv726VGzguAvRFyLEwwBtWtXoa6HqvwoQHXCdpKPn6wd6/63b+2354dsas+lQ73+dYuz7HbcLffP4qfsv/qv/xjnnXODr2UJPbfTFk6/a8pcff9qWczynQ79cpap/r9Trnq828jk/OrVBhblysVy98fU4XrdpgvsdDAdteYL5+WKu2Dxfagyyv4QYdz7GVF3p3ivEjy7fg7FZpKqzHPfr4fop5oeb1IuTV+6/+5/+B+ecc8Oh+sqHjx625f09xAK0S43yJea1L75+0ZYvEL9qPM9wpHofD7Ve8hDjlleaexZTrV3qZl6cz9VfLmaK689efK6/y9VffMznF7n6wIuXWgudvDxry0Wme49Hiuudvtox7Ks/pGdTPQdC+2Sg+jvc33O70GI2cz//5/+suSfNAfMrxc8/+8W/asv/z5/8i7b8zWO1V4ax4zBOEsZDxK/Q01xZR28+PbZcqu96GBujpk5DvBb4ukaI+Jk59Ys0U7svlioXheJBWqkBSrxeca5ETHaByhHHNdYCMcZvb6A+e5N6/Mmv3H/5d9brqQrz1FWhfvb1pdpohjkRYd8Fhf42QAzqJ2g7tFcY6PpRV+/p9DSveIH61airsRSP1nVxdaY1tUMdHuC9p2caX69eaEyvcrVRgjkxQNmv9aydoa6pnuncxXzRlrMM7Y73DLAumIy2nx/tjKTJZDKZTCaTyWQymbaSfZE0mUwmk8lkMplMJtNW2gpt9X3PJb31Fu+gIzQhroS81J42TEts/Xu+9phXC6EFfqlyuhQGEQPdCbtCH+KecIrKAw7ldA9+ra3nXoPY+SEw1Lk+s8iEeezt65l6D3WNfAF87JXQEiK3/gZ+gO/noeogTrRlfOu2MIDwSs/N7ebp2Wu3C3le7QJvvcU9cMCfrrStXlxpuz1CLwmdkIxyqbudnepez0+EhURAKMKOMAAHjKmX6PUYOEEO/PQaFwmAtgbAPzzgFmWpts6Ac8yB5eROn5OV2vpfADNOT4XoDt663ZZ/+vBWWx7f1znkP/3X37Tlkws90+mJrnOT8gPfdcfrzwki1fNyKtzwy1/9ui0/eyxcuc6At6Hu9nsdvK7P6qB/T4AJ9fGmvNA4IZ0Y+8B0svV7Bj0g0hMhXQH6Qg20YwXUbR8Y+RlQaH5+XuoG5qn6bBdjsIMYswBaeDFVX54vjtvyIfDmm5RX1S5uUPo81r0Sz10UqsNFrXohDniulxENN3GdPtqxg7ruA0uqUC8nZ0LTeSSgaLC9AqhMRNwS7d/BmO0AEcrQpgURVlwnihU/KzzrxUJjNn0GHDhU+4aI59Na1/F7xEhvTkEUuNGdZn4CXr44FXZ1dXmOPxBq1QUON8V8UKf6W07WnGMiYEn9QM+5CnX9Gkc/GFcnTUPdOhQevAcUfa+vPp+iD372XEdYrhZCKHPMp0EInBVVHgPP8z2i8cCr0Wdq9Duf84O/m9/Bw9B3e3vrmPTewwft6wcT9Scf/TVF3Ikx3x+MVHfBW+j3qP8kVn+NOD8i9p1caF5enCv2ZaU+K7gO5+gLB12N6XSiNVTxSvPRN080J7x8qc/xYsXnXl/3WMTAHWMg1anGY+np3oltJjgKE2I9GNRAR29SvnN+d32/da01wckrPfNv/vwv2/I5MMQafb3GfguP1mx0ahzJSHDco9vFfIZbC7Eu4hgYNf17E1/EOghrage8P0t0X4wTBZ4jy7EG9xSfePynqolp4/gP7tHDvWEouxJrrZtU7TlX+et76U+0Ll/NcTTjnDgv6gvHOvhsYc36xfoEx5wiYswkfvH+bKXYt6hVp2Ezj4P8dXvA5A8HwLlXOKrTATYcIJb6xI8x7vAcw44+LEdbh3iOJfssvqsh3LgF5tbvKtuRNJlMJpPJZDKZTCbTVrIvkiaTyWQymUwmk8lk2krboa2B53rj9fZpHGkbtwB64SJujevlqyttlwYVnOgKbDGXArKSgZCy7kjOcSsPbo8rYG0l8J4BkJ5m+7+CY9P0DFvZodCD6FiIHXGaDLhO2CHaoOsMxsJYfEf3WTjIesQ5dU0vAcK2FCazygmo3Zx8z7lB8/nVSpjv/BWcfuEWGI+EExTAIMpM2/rLlXCsQVfPM0jUdskAblc+sORCnwUizHkhYZA10hGg/TfcAvmTiA/sCNjMNAMCV6k8X+lD51MhvcsFHPiWen2vI1fPdz98R6+//6O2/GwqPOz5jB5aN6wGM6ng3nVyqnb87AuhO7MzoMuo6GFPYyAButTDbe8Duzocqx1HQFRj9OMaeEkMV7RBfz3G+l1hHgkczAK8TrwtBTo1nmms7QMtmc+EiJyf63UnGsylsA4siNJxnMIhdnGpfu0QY25SpefctKm7YKA6LFPguejfKZFXvJ4DYdlgS+F05wOBiuC0GBHBwmP2Mr1eAJe5docESen2JoiBYPQD9Is9dKo6RR8BsjjL1TencLhMEcN9YF0L3PBLIPkJYrjrIvbsqB2dVzsvbO7d12efZ4qxRO1jtMX8Ss9Z4viAz1tF7I1j/cPdkRDG/Yni7RJOjs+ISeGS+w1W/rN35UjaA9Y4v9AcdA5UdW9P71k4xG8clQiBkful4jBp1hB9swCOHiIOlegnJeJWBYfam1Qche6tB4fOOedGQOmKXM+wxFjoE9nEMxOPHE2AjgOfizt6fzfRZ6Ubrpq6t+UKx0kwHube+t4iONnOY/W7ulJfe71QX3v5/GlbPjtVoIwH6kfBAM8HTL4ENki0s5rr3gMe80F7FXAynsIB+KblNXFljvn7l7/+s7b8Ephrkes+ilL3x/5aYt3AEJvApZzrH8Y7h7XLQW/8xteDpp2Cmog4MO+AYwHO2IhptVN7TYEpFnw/7r3CZ1WIwxniZ85xh2VZALTSy3e0LxV4zjXfO9Ie+vEJ5v4FnN8RY3kcgrG0DoDdE7PmOS64/KdgPwse70LnGPBvm+np7btaBw6Bs+Yz3S+Mk929B3rP2YXWHiWOIoU83oX+4COW8hgCzyh56Nd8C3H0Zbl9O9qOpMlkMplMJpPJZDKZtpJ9kTSZTCaTyWQymUwm01baCm11delc3uASJdAxoBq0+EwvgEEiCW6yh8TSQON8T2hpt6ct3hJbs4tzOWvNkHB3ND7UdXpAVBsEpUKKzpLJkYFtRHDbiuEI61VCWohBVkCwXIyEpUgm7AOd7cClLwNS2gEu28+Ba053k3DZq0oXrNbugdMXT9rXSyAmfbh30k2vrOj2pe320RjJiRNhGx0gaAGS9vqOLquqI68guqpbiBo3vA2/RY9l4DRgTnIffa2EexXcELt9lcd7arvLqdCCVYUE3EAhOnDKenf/blt+O5LL6wsklv8f3Q3Kk7tbBoTl9VPhOmcv5K5Ywl1wAOfVYVdjYwT+43Ck9xzvq01vHah8+5Zca2FY6EIwj3FfdRpd9wc6xeH3rJIOdXA0LJ1Qq+FYWMgoFXq3vFI86MKRlKjzGbCuNKVzHjBXYGs18JaOvxtEufZql/rrtgmAc3tAi6ql7m+VIJYxRADjiYG5Ei1NUC+9PdXpBEieh7HUC9TWNRJg57N1O2ZA4CeI5T0gyse3FZs7QIEYD1dIuv7shVxzvwbqP4XrctBHWwADPDvXe7pztKMvt9QgEuZ2k/Kcc9fNtwJWukKCcCavL4BgeRgPXWC4MWLsGO344V3Fl4/eU3mEep8CjVoWb7flGm6uk2auun2sa9BV9ZuvvtDfnWDuxRx3hoTX6RLulThv4EV6P51+PcTkCAhfgXEXAbfjcYaI8f8GFfh+m1w8wNGbCvc66ODIBtB9OiryuEEc0vVS5WFf82YXiGztsY30WYdHcgw/e6D2fXW+7t8ZEL/ZXP089vU5z55qfI36it84PeAKHAMpcWSgAhMZwCE5AGrt10Dp8H4PUHWJmTzNdoO21q5uj3B889mX7etPvhTOW2FOLMFshohNHpxwOTcMgKYfYh15fAicEXOYTydWH30dyG9QrD+rIpaPvyswl62Ic/KYAN7TwdqZLugVYk8EdrrCoOLxo3KJfo14W3O+Cphz4OZUOefmzXi4eqI+//pM67Yi1fNwDeHBYdVH/PSRH4HHcHzgv/0BjoHQfhVximuUybFi3KN763F665a+x8A42F3CZX+Y3NH94jvI2am+I1zge0+d6t5X+D5C3N4D8hqh/9D110OdoTu673Pww3YkTSaTyWQymUwmk8m0leyLpMlkMplMJpPJZDKZttJWaGtd5S6frVE5GLs5D99HCyR+9jxgndiyjYA7MmGqx4TmkbZdZ0sl0KVD3949Oc1Fnm6ogDPjsnEEXQFlZJLrIZJWd2IhsTEQMP9Y1TQ80PuJEJ6fCRehu2AyUd10I2AO2GIugdgNR3pPD7jojarKXdUkXc+WQGx7QqqIKNcbQKnK3Z7aMWFyZJ+OY3g9YQJlOE/FREfQH9A7w8ZJqoIdJJ02HbDDGEhGEsHlDCxsAnxsuRJzkJfie2pgySeXcMADA9RFO3aJ4oIMTpho+kbltWNvnumezoFB5AskyQVS1QdO3QWCRhfWg32Nh4cPhL4d3RYONaAbZkCkBsg4ktAHjbtciWS4NXDamo5kDg6IpEqBn6yAts57QrlyoHHTpermknEA3RrE4UZMqoDhDeAefdO6bppdVWbOAAAgAElEQVQBf9tDXHgBnGWRq6Ndok8TEQ6ALzKZcgTUKeDrGLP7cFc+vgssFXhPVF67tqrtjvqqn/07ct0e76vMz68K9c3zS7Xds6+ft+XHSJ7+lx+/aMufnQtVnQHxyoDIBujvvQTOkx295yble55LGnz/YqZ+uVoAwWICb9xrhXhLRLyP2PEeXMX//X/7o7b8zjtC6rtAKGu0Vwl2qQQCfZ1DO4oZM1U+hGvp+Dcf6xoncvikC2i6BGsNp8HOQM+RASEsMPDqgAnNGR+AnnlEtnfkvltXrs7XMSNlsvIAeC76bk18DsM3wFxJCpdzBufKsgSqiDaK0Kb7cOgdD9U2d26tncRXcG1dYp6av/eoLX/wNz5sy//k//4Xbflf/rN/3pbPz+XwPUf89Hyij4g3DsdTeIRlwykT/Q7HZdJy48DKjakuK5fO1ijk05eKKcsVxh1QaR/1HHUxjuB02elg7djVmLp9gGMCQ8WaDtYiXoz68rG+ROfwGsw0Q1/IcSxsWdA1Fv2L/Q7tQvy7xDxfAT8mRp0i1UKACYJrhxyILJ1jeZ2bVFHW7nVzzOvVhfriYp5vvKe9D6CtPB/lA2EtOM3iGMJkqDXHGE7mA4w1up0nXY3HQ3w3uH9/jbZ2uhjfiI2DrpDXJMbRH7j8pqnef/ZC8+OTz9WXTy41D64yOGOXbAvvDSXnaLqMEObqaPu4ajuSJpPJZDKZTCaTyWTaSvZF0mQymUwmk8lkMplMW2krtNWraxc1W+s1ks7CLMhV2GMPKrh0rYT6ZCQSsfXcGQrlzBa6PugyN9kTJtXtCPXx8bl+SdRmjfnRxXB8W9cIe/rMANv9yUYST33+Xl/b126kLfEU7oWvXgpzPbsQEhn3tW0+whZ2FGiLfgmModffjQtWXZSuuFhvlVfArkIkhndMSgpUOASr4gN3cAVf533rOX3ir0BKiETQBYzJVoMGXWCCY27NE6H1gc348KDyKqIgQLCBla3weg/3ntRw7p0y0TPQUU/lGIhRL9kR2lrXLZM5vxRq9uqxnFpTtO8QfS5B2yXo4BP0+9vAvsdIUN2L9DwR3I2ZrDrCe0LiPQ3bR5ewmk5i+DtXEX8mFsWMyOgEwKJH+4o3r1/BpRNUYwb0LgoZt9R2BdxwI5/o3c3Jq52LGuwmWSDJOBHWhZ75FI+fA4EL6c5Gh14kPT+Am+7dnur6R/cVEz94515b3h8JwRkiPnSa64RApIlC+RiPNcc60Kki1fu7ofraHpr03p7u/QGSeP/Jrz9py58+V/teAIlMMTEFHtGn3SSyr51zecMIlcCSOAZrJKL2mZgeYyDHXNkFvvnTR/tt+dGx6uIA8SWEk2YNDK+K9Z4aca1ukoiHCTFFHMd48FZb7uEe3W8+bYt0F/T6mpNT4J8V0Gw6I3rEy3HEoAaeV3ucT5hFezft6Opax2xwlCYDKpqWdBCGszFiE4FNkMOuBBq4qnXNCu6ZNSomAZbNcUWeMWzm0DHG6ABHePo4pjGBq/38Z+qbTz/9qi3PTniUQ+0YRLp+gLMnXv3m/sM+HnAuRjuyfJMq8sy9blzpz18J1c3gBF3lRJdR/1x0gvvrY+Law3qug/kUhpyOlCDrxUPvIIrqXWcUQPuXG+7OPIMB92NmIkA2AeLzXgGXTlyfRzxWPFqEOOmziYiR4h7S5crtQkVRu7NX62dazjB/4F4r1IuPudzhmArXmUs4TQfgfwdosBHWHHtY2/QQk4d9jYcjHAMYNG3gw3U7QBAIO8JZeyPF9Q7WWeyb40jXroH3zq50jOmy4lh787kdhtIQZc9/c5t+V9mOpMlkMplMJpPJZDKZtpJ9kTSZTCaTyWQymUwm01baCm2tysKtLtcueiW2felymPT38H5twRKdmZ7LiW+IBLsFkLIS26ujid7ThWtZAFzDwaUxWzB5/Pqao31tHydI/LvhTloQn3MQ8Ae8P8G29nCh+8r3heh8+RgOS6+FvC4mev/evq7Th3OdtyMXrKqq3HK+rqOQSB8wDB8ocO2IsABPKfl+OOsBnwvg0BvCFS2AO2dd4vobzw8EKq6vb6B9LQJuUAGhIV6Uo0/VQIHYvzaszYAHJl0ki54pEW5GTHs5a8spEkeHTshB4O8G3XHOuaJJXPz8tRwtT+FQ18G4q30knQeuNES73NvXM/ThTsZk4XTDDOPoja8HcH4MIjr6Ne8hOQ3kw4fdbQVEuQbeU5Xf4roJLJeuvONDxaTwhWKPR84VGCkdTNO5EK8qR8buG5TnyWX1HAjc+Vz1+Q0i9Zw2f0AGg0pxp7+RLFsXfe9QGN5H7wph/dEHcsA+ggNhghjL5Mu+a65ZqQ7pxOjYdnQnxfsruNJyCHpwj06Aund7+vxoX/3u+GMlGP/Nk5O2/ORUjnYFEnz739Z/fkdVrnZZgz9nodrCC1D29dlduD5yDi2BXR0fad56644cdPvAkj3MZxXckumA7BCHPeJ2Da7q470+xzrG956P/lIKY3vy9Ju2PF8oNhZO8fMSiHiKdq+AYOWoA5945LfE7XpnYbV2dYOkVU5tt8rYplhDYI7JcX8x3ewDYIhA1rIcbQQ8kfMQk6oT/ffQZl7TZkRJK7p6goj1ceToCIj04G2ts6IvP9ffppjz0Tc25004Q8Ix2o+4vsDxFxwzqcvdrHOKsnSvGwfzRar5u8bCxQPrF+IZKrweYc0xAsrfwTgicspk93TG5nqG6GFNB+CmXrwa7tNEEBE/2S/KnC7CGF+Mt3h/xAUu2jHEc/AgB9daOdDWrNCYKHc0IKuqctMGmy02jiioHMY8WoU/3kA24fKK+aCLgBiWcFZFP97vIisAHfk9fdcISyDoTVV0cDwriTGv9VXu4DhACNf8Ekczxrk+dP9I7x+8VLvEl8CMub7iETHEoQ0HbNRl9T2ODNiOpMlkMplMJpPJZDKZtpJ9kTSZTCaTyWQymUwm01baDm0tCrc6XTvkBUjcGcG1jFvvEfaYFwu5SqZAsA7hfJXDTW60hyTLcDUKgE1WwN0yYCfczu9115gWcQMfuE4F10liNpUHhIDkBfFMOOQNRyO8X+9ZTbX1/cnrx235HPfbiQ/acv9A29bBjtzMnHMtrRslwBeBnmzgJngez2MiW7qgAsVBG3lA43wm3cbrRBQ8IHEeXFDDxhXOc0iGy88HrkYHLyaLLtGQBfCWGm69PhigEq6e/T7Q5akwreVcbnBRBowX7m5Rtpvfa2pXuaJe96PHX3/Rvp7V6nMRkkMX6HMR2vT4UH1uBOQ6Ap66gTSRjas3ODm8J37j+1vUGX3BhcTu0NeQQLhGu9cbGDPGNfpmDEfnPuLTwUCvX5wLdyox1iJgZSACN9ygb1rXn361hDsrnucUKNjCI7oNd1bU6bsT4al/+LN32vJHjx615cM7ijtDJOAO6WrKMcas19eJszeOA/DfgU6p223gOhXeU6H+ywyYfA3nyY7a/c6e2nT6AC7dcJjOgOicwOku3JHZp+ec85t66eLZIpC0Y6CJeaRnnl8IkU8Qpz64f7st79/WPOgnQqNcoj7txSpXIY8nAP0iGt24VNO52vfpnIyYAUxstKe+c/dIc9/j5zgCALw67MDt/FLvma6AhQYqO/QlunAHiBWOCNsNqqoqlzbHF8qSR3j0gZ0ejlUUwnxLoOYZYmOMeaWAMzuPPXCWiLkuQT/24Bztk+FrLpljLt1wtUQszTO4xGOO63bUp0ZHwqjPL3Qk59p12znnAtRNiGMFMZzP6bIebMztiBvFbtywq6pq3fTnVxr/PpFI1CHRTw/4Zg9u5zwykBAtJkaM8UU3VY+uvFi7ljx+07jFFkD66fJb5BqPy7n63RJZAzIg4hsxG3E9YAzAPNPFenDO4z+opxDPnQIX5fGym1RdO3dNnNJ5P0af8xEvvJCYJuYSzGVdoLAdHu9CHU0GRFuJd9OdHGt0HHO6Nrj2mLUAzxThO0hIp3q3wUK/qei6OAo0GuCoX6BjODTY7tXE59VGbK4a332+jxm27UiaTCaTyWQymUwmk2kr2RdJk8lkMplMJpPJZDJtpa3QVs95Lmi2uGO4C/nY7idawS3mVapt+KQjFCboCZEJiAMCQYs6cCqjMyATstLNE0l5r5Pp1o4ogbajcyCsG0atRGHxDwXdtpDk2a+EuY6Q1PRiJgQrSOQuuFwhwT1c+sZDbVW77lbNs4U85zd1HQdE17QfnmELPNzYytdVKuIE2D6vN3ARbJkDs/D4GwYdprCHHwZCbYQuCAPxcjqGMem5rlfj4hWcugo66oFOqPGsAZFePHiAZ62QuLgGapJ6QGlitOkNqiort5qucYrZqdxIc6AwTHxcwB1uiDE1gNtslKgfx0RbgeVUQJFKuuyWQK0qOsf91UTbPokbjLWcbn5sF/xPDfaC7wcx5mIgOmNgkPFQsSEGXrIA4kW6ZADsJPR3w9LVtefKbH3tla9nOwXpNy3U5+Zw6MuBkQ2AJf/0p++25Q8fyY1xf4jnqYSE1kvVV5ag/wBdzYG7ew1yyrYr0QAknuucbQfOteZ4xFhGW9QY727FPqi4fXusNr1cqS+/mutvr5a6Zp7u5siA5/kuaZDTbqBx1Af+FA5U/0u4i18BwYqBVh/cVtt1PLWvh8T0dKMmouSjb1Q+0Swmhm/cPoGMbqDjdOasGZv1Obdwj/tfnbXlc6CgDq6PKRwLl0AuC8yJcUz8FrEd89JGtvcbVF1VLlus4+oKKDYxbqKidaZ2nE31DAH6QGegNU/cAe4GrJC4G/KYu/4QCB/apkQcbF1u6b7I2Ihxt8BajE6lPeDSAVyBQ7goM65vuHRzOmfTAd3dmPOJ0v3/Vl43pbqWQ3CeKl5w/bdB46dEOVUkQpkAK+wkaq8uxg+dWim6rHI+o9Nv22SIBwUnS1y8gznOwzglrjyDO7uPTAslYm+EWBLBrbYDhJW0Y475PCM+7X/Lg//O8lqMm1hpB/2v5FoUd8spO0ScHMB9dwj73Ye3NE738B2nB8fw3qFeD0O4rMLx9fp+IxyJCuDaWoLLXwDvj9HWNfpAye9VOELUG2A9E3GNQDfitugC4rIJ4nypa9I9+7vKdiRNJpPJZDKZTCaTybSV7IukyWQymUwmk8lkMpm20nbspO85r0HfokjbtFWNMhzMKo9YlC7TgcNp0tXWbwUeaiOnKDGIgg5Wwgc3ErjSfbXhUktijUiQTQyTTqVMVIs/3dhuruG21aHTHRyT9sZy2ouQyXQB19A58JnVQp/bT4CB3aA8T4gqMSe6g1XAIP2eMGMfLRMSy/GJthKBwzY53VSBKBFX4P3Qlc5rt9vp2IntfiLHG0wkt+nJ3ODlDURa70noLOqER1Z9IFhAd4orObhWQAWCIV25bk5lnrnzF0+az5YTYgfPPFvqXjO0aSfRuBsAXerETECPjgyUbcNNjFgSGPAK6Ixf0fF1/XoN7K2EOy9xaaLIG2g6uC82L5s0wHjsAVEZj9SOYfhct7UCSwYkLMBV6/luXFvr2rm0cUBMM9Xta7ginsFpsQQmOOypHT94/2Fb/vChksf30e3LhWJK4VQvGd1ZgasyrnqIj2FT8TX6RYV/r1K8lzgiXZQRPwu4rRJ/JaZeAFUtUE8hkMM9BN8+5pN+omddFLtpR8/zXRw2aCvmvnKFBOV4P7G6YqlnHvZ1r4cHmj9cAKdrXIkxy31LYmk6iTtgmV4Tvyq0hfsWpDxCG/l4phHmteOh5or0UvNzDsQuBp4Xw16wxvywYqxCTAqA21crxbybVFUVbjpdJ7L3yGhniGOlPnuxYCdVuTNSO3bpeo2Gz+C2eXIqLDg9hws5bmHvltxUD24JKe5er8uAzQb4nHKJRUyqduwgvh2N5KwbearzBMcdqpXul1NCgKVkBCSSaCuZ1w1nyGBHaGtVu3TVuKAivm+6oKqesw1UWEoiZChAOzKDQAjMMmaZcQDXpJtqDOTUbxqbRpvRhgM23W4Vx0pWM9DEgFgsnWXZRriXKOf94ngXnjWJmPieR4p2047OuXbpxkwQrEM6O3vgrEOM30Gi12/jiMGkr7p463ivLe8hM8UYYzmGuzGP+LlI32uu18Z+oH/v9PTvFTDyGvdYZHDwJYKNBu7gOYZ9HeUYYpzOFrrOKqNTOuL5hpO3HiP5HtuLtiNpMplMJpPJZDKZTKatZF8kTSaTyWQymUwmk8m0lbZGW12TnNUbA0ldaas7g6PjMtXW+xzZLwddoCrAXDzyr7WwmAwJqom4OTiuVk4In89Esc2euJdhmxjX8IjPkd4DiFABCdjI1Q1sIwx1TeI6ww7cXMfahp6ez3UduG+FevvO3Myc51zQJGGls24B16kCbolZqXruAPfswM0sBDpVABHhlrwHXMmh7uhux6SxTJxdNvirx/rfQLrYvkCXmWQY14uIUOLnlLyEu3AsFGEAd6xA9JarSyWBXWVw7Ju+bMthtN0w+66qaueWzdjo99SHFj5d1YAJoi16HSAXSM4bEC1mMmmwD3Tr82PiEd+CDgNdKq+rosLY3Wg74JEbiCXHAhCkzSze+kj8bScURnIEB9c+kJbTKfFafBLqj8mgb1KVc+6aaH8BzPubpcoLxIgy1L3euauY8v5dPVsnwjgC6lMB/dzAiOFG6JB0nPilB7fYrKnfyGnsehuJ44FI5XB9roheok9hLBdwjw4wn6zQf324tiLcbzhsl4jzBdBgB0zrJuX7vov76/qYoc5XGY5goJ5TzD3LXLHj7X0hht2YSCRjI+PaBmOo93AsIfYGdOFugl+dIX4zZqKc+Rgjoe43QlvTFXgKF9YpnEJLoHcduCcSy1zi/SvElR5dZP3dxNW6qlvkscS65RLo6Ukhl+xeomceHciFnuj29IzHHoDwYq68An766rXmlfmlEp3XX33Wlt+6I3z90YfvOeecm8CBu9tRX4uAl0eBPj8ttA6p4cDdRTtGXV0nB97MXPcbQ4pO8ODkPBLAdOfmkZMblB8Ebtjgur2R1quL+VVbztEWJZBfLi2SnvoZ3cATZCuIEFc7GOMxglOOeavEcQ+OsTBc13tREzVH/9erLoczZwbHWa43Ely7wEPVXN9inUmHWl7TAxIZYjwGnNuL3axXPU8x3oNTc0U3cP+vHp9xzrkA2PAAseMQTt/3D9Q3DvdUPjoU5to/UEz24WgcAOsP0R+ucVUPx798uMOG6Ee89wrxpoK7eAfu8RWOPkz21CNuH2u9Spx1ulTcKhgHcESGxwe7yfZx1XYkTSaTyWQymUwmk8m0leyLpMlkMplMJpPJZDKZttJ2e5ie71zjoFYSRwCPWQB5ObvS9jy38id7YgN72KomAlRlwK7gHOiQPLXwkFAbiGxJVKBBr7yA2926HB0giWdumHpuJIzVvUQhkSIgt1DY0X3tAzt5cS7UxQPeEiPJbS/ZTcJl54R8ruDCtoHwwrWWuPIQ+FECdMYDBlHC2bZictMIdVQSS0XbwG0zgENa3VyHbqDVRqJe4DRA84gK0Cm0DolBInEzcLgcrmgdbPeP4JS1AjJd0GVrCXQTbX2TqqvSZau1u2B6LvwpBMISoJ6ZBHfDfQ59zkedEjjy+HrE9+BdLDITMNupwXQ4RjdMdh3dO9GniPIRF8G4JuFXAXv3gFENgK4cYjw+efJaf1wQE8KYWAgDu0mVzrlFgxhegGi6RKBawt2xizF4H66tPdRzvkL/KxHXQtVjAmfhki6riFleDRQWKNE1jl75wOeAd/lApGtgiks6tRLH8oHDw8W6Bka9gckBXa6A8QRArbuovwpIT5nRP/Hm5HmeSxo07OpEY36J54xj9aclUXigsA8eyo1z0Cc69eZx5xNFRQzaSGROm0wgte2Ux2vQfRfHBDwcMUkzYmwaj30m7o4Vkw6AFp6cXOhP4Vg4Rl8uas4naruU64JqN+1YVJW7aFywV3AKdhgLw77WMGGscpfHIYZCzXO4hl6cCFtdZBrX0zlwYfSHW7dv6zqp1kgvH3/VluPuuv2Cu2+3r/lIhp5g3eQhxi4WcP7MidIB5wR654VwIK/ejDJ6WD1VOdl4OqgDq/N2s58RhYE7apBEH8+2QgL4ArFmgRg77gofTFCPdCCveCYGCGXNoyw4G+BtHNvRW3yMn/j6KNbGZMr1CeIk3sK1UIn69GKeldJzp1iX8UhKt4u1PGL1HK7LFebHJOZ6fDfj0Tnn/Ot65BE1PGeF+ipTHMXCe/pjzQe3Jpr7j481ThO8XnfRplhT+XDPDnFML2STNX2jRNtyXnM+4iqX+YjfFcYXs0gkmNfGcI09xPcqrmNnS43xBVxhfcwJnR6w28rQVpPJZDKZTCaTyWQy7Vj2RdJkMplMJpPJZDKZTFtpS7TVOe8aIQTu4MfaXiUiNV0o4Xc30evpVMl8r0JhAyXQAuKnAbyqmMg+j4WC0AktqPX+axfQGtvRMVzmCuAx/mqDzVOZzpdATujoRlShYDJlYBGdDhAYoCY53GozODX1bmvL/UZV165sttA3kmKnRExVh6AEXQeoWQ3kaAmcIEc7RuhiFRPFRvwNA7hGkeJVuK82H1X7vEdcgSgl8UgiD8A5cmzrZ3iO3HtzAvYVrtkL4OAFFDeE+2wNtC/fkftuuly4r3755845504v5ETXw2eHwMViOKVGcJZjIvlVDvyGznHoKD6TEAPpiYCjEYut8fzXSHUNDtXfIGLwXqAdATFqXhwDrwCCvUG9IWaEwHj7cMesSFoD9fHhRJfDhfImFXi+GzRJjkvU/+xS/XWOMTiiQyCef7kQ9nYCjNuDS2MIhLGMhB72EJsme8J7BgN9Vgyn3zBo7hd9iih4Chfcqwu9nuVwMK3g5FkBsQdGVQNd7iOGsxMUqDMHrH4At8U+2n21I3dBV9eubrDZJ08191WI7wg1Ll3QORFj8Er18uqlcGofOLqHYx0eLTPhqulHqGti3zhOkmXrvy0rjh30EfBzNWJ8WsKNEkdb6q7mjRQIcYD5n8dTshUSZDPpOd5zhb5BHKvakdtnWZbu/HKNn6boT5PhflvuTDQ3E/30I47f87a8msJ9GHhZjphVYO5bAr+czU7acgK0dDYVPn3xcj02x0ChB/HdtjxHn38917h/+vSbtnx2qvvtoI8EYO94JGHTMhtINVzeN+YB783vr7zdjEfPc+7ahJSYps+5bMNuls7RenU61RjMCv0tKHo3SmDlztjk6/q1w/p2oy4whzXrpYquqli3LOca0xdzxYAl4vB8BsdOzFkF+gBdtenU6uOI2ADY5BxruoxrZmLPOzqJ5TnPeU19VUQ/EacWOSZI1NfhnsbLwZ7m+yDW6yeXmJ8qYffLlWLZeKGH0+zoXAd9vfQxlq+bCUeiPB/fk0J9BypKOLLXPJLCZ8WYwneE2le79BBjj8dC7E/29XynC30uQfMAcZ7H676rbEfSZDKZTCaTyWQymUxbyb5Imkwmk8lkMplMJpNpK22FttZ15ZZNUuohEJ0KyFE6U/LL1SUwI+3qutPPlaz9y9VXbZkJOw9uH7blw8P7bZmJ0cOBtnVDuL8xCX3l1vcb9ZkYFy6GFVFVXJuJRmthC1WtreEUCYSvzuTEVs/1enekB2dicFpMpgs9Bx2WArcbVqB2tcsbbNErNpgn3R4QAh8umSUdGOHKuwRCkcNFscL1wwjoEtwe4x6S/IYx3s+Eqes6DbpwkQQGWeIzczjRTlMhn9MLvb6CW54HXDdK6HCp51sAYwa57IZj9Q0m9ab7aeDvBsHK88y9eLZGk4hFFWjHhDhxB7gyEiVPkfB66YDx4LZpSpwkTIgrhGLv7rGuj6TyTB7vN4gwjcEKoCgB+xrQjoKJeoHi5sDePCRsp7tyhWT0Afp199sSmgNny5bq17MXz9/07t9ZpfPctHnuGfCqWaZYEyBeDI+EK6Na3LPXake3FKJT85gA/qfGc/b7ev3RIyFxlac2HTuhQVG/qXf07RkcIF89f9GWv/jicVvO0RfCDXxOgyoGZkOXZsaDwwmQbdRZBHa0Dzysh7nldEGo5+a0WqXu419/7pxz7uSZXIAj1NHySnVUwEly0sWxB19zz1dfftmWLzPhlIOOnv9geNCW95Gsur+v+kqIoCG5dd04+nIMzmZqi7MlnBuBTl9MNd+tLvR66RAzKz43nHV5nmIDVQMKSwdgYIkljwnUu0KUPVfV6/rqwcWy31P/d0BSr4AbFhcag0WF4w1wbc2/5TjJcqbyq9NnbfnJ61dtOaIjPdH/5n7uYt2UITZeneoe//zjX7XlX34qtPUK2BsTl9cpEWk6SX5bW+A4QArUGnNRBdfKTcju5lRVlVvO1/NZBFSaruuOjpZ4zxDtzqQBjF90bc1TzZtzuO/uDzROJ0PMNx6PgaC+mjbN0M7TuerwbKY2uphiLUYUttbndDHWoz6Od3Xo4os5F4ubGu1LpLTA2gnLNVfvyEW5drXLm7WAx8/AOp4rrP5Ydd7t6JnzHMfugIfySM7JV8LIuVy/hXXevUf4bgLEPYzVTt5qfc0Cc1yR6oIp1jkLtO8Cc0KO2OsC1XmC7wU8qpPnwLexvgvh+NqJeawBfYau3uX23ztsR9JkMplMJpPJZDKZTFvJvkiaTCaTyWQymUwmk2krbYW2llXtZsv1FuuQyBycgy5fC6k6nwrJuDNQUt3RWO5nOZzlXlzqb08+hePrc+Ei9+8eteXDCthJDHyNyXevt5axXRvCaTIHCuUBvUyRPPT1S2Far85VvgDOWsDma4TP76yETlwthP0SyauRyXQFh7BFuhuXyKquXdagMK0Lr3MuhmOXA5ZT5nAHm8IxCohSB869ATjI2aWe8xVc4dILPRuxuqM7at+9CVwiG9TGw2cWwGkWQBCvgF1dzoW2FqX+tgs302FXeGYHCbULYoZnwrEvXz3V+7sP23IFJzaiwR7cLm9SVVm62eUadUk2kAVgrnD7GiCJdqvUqbcAACAASURBVAWXswr3F49UF0xgfHGq+j1ZaZw+OVX5EO376NGDtnxwBCSsvTaw5BROh6nGCPE5OtTNp4oZXeA6t+4oxvTgOJcA/+Tn+nSO5Vto2LxgwnCgozeowvPcaeOiN6VxdA/IJsZmBJvb5yvdU4Wxdhsx9sGR0McacSoDuuTBQXQOZD9Zqp/0++oPobceJ0WmtphmcpFc1bqXEfD+yoPLMfCqmsQS3erg8prP9Kwvz9XvDvaEbIcR0OWRntXD/dTe7tDW3366Rlvp8swxmPM50Y79RM/ws5/8rC3HqJjPX37dls8u4eQZCYP8EebHP0zu6T0jON5u4KHrNlgsVT9fPte1/+I3X+nzH2vuA1XmxhPFjNuHKheIK8tS7eXzSALqJs2J+GFeRlytkQy9rnZzZMAPfNcfrWNlgnaJ4YibYYzkc83Zz2ZAl9V13TzH/LTQnHR+pus8e605JsX8UWa6ZhdHL8aJ2vTVqzVKnQGTy1FXn37+SVv+83/95/ocxEMPrsDnz3Uvi4XGXTzC8QjMj0EX7uhYU/GYEY8n1Jh/vGo3+xl1LafSDpBvOhR7U332Cu0yRt+dDJCknsctgJP6dN7EuJ7iOUMgskO4kId0vG3Q0jnWMxcYm5c4tpPh+MwQbr0V7FNTHOtgNoESyHGIY0YgLjccXLlmDsBm+1iDxeRcb1B1rSMOAe6pzLnm141zruSxogwoeJYBbUVbRAOV55jvv3mltcgU4/3Oba1t7t7B2qmpoiLTZ67mqrcFjgmc4rjD+RXmO8zV3UR/2x+qbxK9x9cIl+JZZxi/XOjEMeOq3v99TM1tR9JkMplMJpPJZDKZTFvJvkiaTCaTyWQymUwmk2krbYW2VqVz13RRniIhMpJZn50Js3n5RIjMO0O5G81H+tvPn2rL+C++EU6xAtZ551h/+/SV8Lk/eCSU7d6xtpUne0xcvf6uTIwoy4VULRdI/DvVff3y179uy8++EdKzLHRf4762tTtATg4Gqo8UuIQH5MOH6xu3pL0QCdlzMnk3qdoVTQJbz8cWP5FgIFVEJZfACWI8ZwanspMZnC7hPJWmetBOLLS0QtLxWQaMBsjLXhQ2dw53QXzmdAEkeI4EvjkwD1zv9XP1uyiCy1oP6NAQLpVwWbu8Uh/MFuqbPjCDHLhIEuwK+ahbl7XqWxIru5KOXUyOC+wv1t++fqFn++xEaPqSuCOQqn3gspdATh9/I6fOCojs/vEaucyBBTFJ+2ql/nX5Wm36+KViQ45nmuwTxRVaOQIWfTxWG/XwrB20yyBROQdOmfTh6BvvBqVzge/KyRoZK8+ZYBjYSqXYFAH160W67/FEOOv7Dx+15S6xZ2KjeD329Fm9SA1yiaTnnUSxab9BqSo4xa2AXQ3Hut4EWBndkoOeMLkA7noVHC4rIF7zMzmhLuYavxmTNSMhPJsrQycrc93DTaquKpc3yFK+QCJwxPQKqF+KJN+zXGPzsy++ass9uK2+RKLxC+DgnUjXeX2lMXNxqbHc7ct9N4aT4GK2vt+XTzVXf/xbuOyibu/clVth3BXuh9Do5kDQI7hhu1j9NFvJebLGeHc4tuDhaIWPebDy4c5e7QZRruvaFc0818MKKUCMDdmO4AFnV5q/Li/VFpcXwFlRX3Go+DU4eLstJ8BZX53qKEWN8bMHd8rR4RpfHww07jyMzdNTjZcnH8updQl3xxju+wu4k8YhxqmHIyxct6i4gT3XPMIDR0q6MXvFLttx/fkZ8NAYyeiHh3q26bnGSwhslGg656rsW6YDrhsQYl2KYwAuVduMcTyjTNd/sAJ6eTXTvVc84hCprTPsCRUVy8Dq4axfYR0VoN17PcRhNGSM8RshztM1vBtvn8j+u8hztXB44NpsIwc31wQxIs/gIr3COA0wtwJL7mBN2xuoHT20QZ5rjJ+8UCzj0bDDO+u5mM638yViA+I0To45D2uSw0PE7CEcd7Fmzwq4Z8/1rDmQ4xXip7fhkq379SMeA9mebbUdSZPJZDKZTCaTyWQybaXtdiRd7RbXP8kgjxXTAH3+TN+0T0+RUwk/XVwg39hnOFwa3VG+yOmpvul/daVfUgaRfhH77W+1U+jjlwfurPWaXycqmB/U+EVldqXy55/pl79f/vLTtvzkRL8m8mfuxOneZ2favfnRIz3HW4eqpxz3wLQtPg69RjywHO7mF571Mfl1vfjMBYWG5GYocwhluPFLmA395gv9on3FnGT4VSvEzxYPuNuHn32ZJmgFo5N6b/1Lke/zV031iwVcLC7xI/cVcjt+9VS/OL7GYWceNO469bs//uittrx/oLZgbsHlVNccRTK6KDwcCt9RPtCqrt2i6fcZdrgH+LUtRj7UBLtXMcqnr9WOv/5cY2DJn1/x6+cA+Sjvj0UFBCEMJZCLbv6lTEL+aLRu9y5+OS86+DUMphSsw0v8Ivj4mfraAXYAepHaYtBVnf/NP/qDttw51nhkXs1eV7/4ZRgHBxP8KtnRPd+ofM8FjdFXJ4aBA0wT4p52Lnr4BfkY+a1u78HUCP37BeLwHJtxKXZV7h/easvRGLnHKvWTS+xqrI7WfZ2GHgnGehRpTKfIlfcasfTVa9ErBXYSD0d6jjsYd8doiwV2Rxcr5LnDLkyCevJgzJKV38NN4DvI9z03aKiESzx/AcO1FXYxFjBZAMDg/uKTL9ryaF8x5YMff9CWr77QrtInn/ymLSeIme/dksnSbRWdh3g7a8zdzp+rXZjrsnegz1+ukDf5Su//5LMnbfn1JXawYWg2Gegza+S5Yy7grGKOPt0vzR+YL5j5f29SeZa754/XffNyoPngAcy8hgloJMxJveO9tnyJHQgas0TYuSlgdsfX56XaIAbpMpro+mPk7b37/nquGu0rHowOdI8HdzW+3b7IhWqhMX22VJvGodZZNXajQpgskg7azCnJ3JEwkmGeUFAV+Y52JKuqcstmrXdxqXYcDdUv+2PsCMN0hfkKF3Ma3CCPNSiWKdaoZyCljkdqjwN47iV4ZPZ1v9ktrTGXBugXG4YqOc1jYPCDeLMgOchxVOqZujGMnWBE1sP86NBeBdYzzDs5Gm71deK7y/Nc2Hw+d9o2Rz8MdrBsCbAlvAB9OEdff4HvA6MBDdA0fwQIQjHzt2JuG8z0+ge31nRB4bEfaR00ZY5IXBsh0H36uSis4b7G8tEtGJph3Rsjf/gc+VFr0B0VcjSTdwzxP+n3AK9sR9JkMplMJpPJZDKZTFvJvkiaTCaTyWQymUwmk2krbbcX7QfONXnmOgNte3/+iTCbX30uLKfE9moPuU/u3BNn8xEQmbQAGvWRDp7zsPePH95ty68+/kvdGgwNPOQ08huTnXwqVKDEodjVDCjuN8pd+d77j9py5et1L9C9cOv7y1SISAnkMkR+RVcRd9R3+Axb7rU8DJyrdmO24znl2omYOAi77Q7IQtLVM89PhC599ULlGXCo2+9+2JaXwOeY9+fhrTtteQBEeNCH4QKMJsr8Oo8Q0BIgBiG6cuhg+jFUhU4mapcEOUN7QL0uXgG1dsgBVQsv8oETFJdq92oIBCgUPuSXu2nHoqjcydm6/04G6mdIi+n6AED6GLMdmJukMB8ZJKqX2/sy1+gABxr0VKcfvqU8mlenQs2nU+WNuzgRVpRP1581GckAx4tVP8Oe0K1+othw95bupQC+eO9IyNZtoHxXM+WjBBm2kW8K5KzrEWOJ1AcTYJ6XwKNuUr7vuaQxr7k1UL18M1d9hp76Ygdj5PYEeTRhFPXqif52hAo4nOj6VarrPDoWwhghJ+98qbZZLpDz73zd75cwS4kSVegAOFaO/rUPg5A5MMwEGH8fuSAvnyv2JshRON7IiYq8qTDq6QN9DFEuiBXdoGpXu6IxF8mBmq9y5pFErkSgfkTpuh3d635f9TIBmnYf4z2+pTFw91Djp8D5hJqYL2JZ2hijEVXtAzu/e09x+hlyC374s5+25dfnGmunFyoHiM9nwKK7OL6RoG8uEVc59RGbJE7J+H+TqsrSzc7XcbVEHtUzGqjdAh65pzrvjlQ+2lcezwWMd06XKp+91nxzNoWhB44nHNxXjH33Ryrf2VO8GzfzYg4TlyRSvH/4QOupjzA//79/+qdtmeZIQ2DyM6yRfJh1BVhzOWCWdN5hHyDmStOpAGZ7N62iMfUZjjRnDYdqoxAmiVyjdjA5FCkQXjxcgWfzYCqEZYMrV8CYwaUGyPsY8jhTE5IjjNcoQD5xjwYzMNKDSQ5zajNfNIlFTHEbeSxdQVMyPghzZOtlGt8V2W5MzFxdt/2lBtpaAtNkV2Te2QD9zGPsxVG4EOZjXhdoK+ro4FDjIZ0hly1yUQ+Ru3lwuP6eQlOj3rnWDxMYIs1xHCADuv8CuZIvcVTFBzLvoW8cYG6tmL8SMYFH6jZQZ3QO/3t877AdSZPJZDKZTCaTyWQybSX7ImkymUwmk8lkMplMpq20FdoaxLEb31s7kl5h+/Mvv/jXbfk53Eu7QEFS5HEEVed+8p6wnK+fCoshKpGn2hJ++kTOjL2RtmwHR8ISwoH2aesGpyiQIzJDDr0EjlUP7wsVmQLz+OiR3NHOZ0j6gnxzH70l9O79e3r/GJjQ1ydCg+bABlZwPmSexmWxI7TV911y7UAJ7LICikxHrEEfeaTw08PbcHMbnqsuqlrPMEauuE4kNG0PLn69RNgJUwPlyKWVNs6MUVftTMykA2Sx6sOhEdv3D4+EJ1wE6lNVISTj/sMHbfn2MawOmU+sJ7RghvyVwUxtPQZCSPzhJlXVtVs1bm01wRX0p7iHvt5B/kFgkL2+nnMIhHUK9LDTU73vIS9jFKit7z0Q2nF1rkE+uxK6UfhF83dwgYPbZxduq4e3hCAlA13v3m2NL+LPkz31tbf7QuDHA7icIZdXAewk7BIBVh10YDX88YXa+iYVxbG79/Yag+sgB9ZnyLE7n+u+O079bIj2HQ+Ry/Yd9eOwK7wqieFCCze3BDlGCyBoc+CsZN+LZjx6K70WIBdVAHR8iLpNMr2+/77uMUacqDHup2dArZALDsafLoHjawHXwRzOqUMg2577HrZ030FlWbiz6TrXZQFcr4ArJUiwjbvgCYOHcOi7e6S+Gzj1h3v76qMP9oWZHt8S8nsIF0WY77rZTBjrbLWOZfOVXnv3J3KHfXBfDuQ95vuFW/XbBxr3YcH+gnxuufos0dl0hZy/le6B+UZD9E3ibOWO0Nbaea5qclrWwOQWU8X9V7XWOQc9Ve7RgZxdj9F2EebK2Vxx5DmOhzx/pef3gXofPxR2fjjWOOlifZA36xKvUl3R4fLOfWG2/87f+Xfb8gWeaVW9+ejHZ3B2jXo8NsR8xcgLDKfK0CPOqrcHyClZuh2hrZ5zXtN39u4B3Ue/jJCrt7+nMRUBMw4QP2Pc9yJV/d9BrtzQR15GOLv2YNX6ban6/Cb+h6jbPvJeLjG31+A5S9h9jofAZtEWec6jOnQ/Bn6MtQrz8+aZyhnWSwHus2Bwu0l5ztVNP6pxryVzSgIPxpLATQbMFc08tXqdDvK3DrQWOpxo/I6QxzErdJ3lhdaR4xFw98m6v1W43xHy+sYOjrhwW+1MNdaGIc7kYF3Me+n3VQc9xIYn+J702XO53OcbeeNVUdxRzL6Hi7LtSJpMJpPJZDKZTCaTaSvZF0mTyWQymUwmk8lkMm2lrdBWzwtcJ1ljbRcXwjQ/+0bbqAu4DoVI8LoCi1Qm2iYfAQn40bHcxFyt7d5lqvf7ia4fw0mq0ydCQYe69T3AJMnV2IIfwXEtxHbzBfCTg32hl+/AzbRkotqlcL/xvq5TAR0Nz4Fv1bqhsAAuAiula0e9m5bvea4TruuIiexTYBshXBeZPPgAycIPD1R3t6ZIJg1UMQCKGsEdKwY6XAGhSOEwVQNBKZo+UAL9o2sZuoIbAE2swTmMkfz6DjAAD9dJIvUdn+6+wDl6HeFjZSHkME/1nhLpXonO3qQ857mwYeLKFKwMsOFO8uYky3g0twdM7hiYGvto1AH201UddVFfOepiMRWm1QHa6F+3ARCLkL9nwUH3OEYCcLiWsV9EHb0/juCaqys6r1KfypH8l2RWH+juZKzxTsfCl6e7QVuTTuwevb92VRwBYb0/ftqWP5/JhZVt1wXKNgQ+1xsiBqF+a6BmPpDBEC6FKZwqVzXjOWJCw2YV6FMOrnge+v8QWHLuCdfJmUTaE87KpNvxRG1RArtOUyF5dO/08cfpHKg+0Na7exq/nzzRPPa7qq4qlzWfWcHt1oNFIkhwFwaq/yOgve+9Jwzvo7ffacvdgerCg6unHyKuRkDfgKOViH055rBV44A8GMAdFnU11LTm3n5b9/X8NZD5R8JfP0Sy7AAYar6RyF338smncny/gBvhbEY3SNVlgHnD7YZsXV+6iX0lHBoLH26/Q8w9OAKw6mnOHiKhe4JjHdFYsaYGBjmAk/VgT209RruHdAwHjpw2dbSxfgB6ORrp8//mjz5qy/O/LWfIZ59+1pa/eaZxUad0JAUOBwS+ph0ksUnglyHurQDOGtW7QiK9duxFHnBTuFseAWVcXApXdqnWtAnO2wzg8ur6SCTPyQTrpQTrj8pnHSFWEg9t2qxGXcX4zAAxO8lZn4jTiKs9YJs41eE8rq0wjnjMygFlj3FswcOaMQCCXe8INXe13ForYJc1siDwdZ4k2sc5ug8eqa0THA/Jcd/xRPW7N1J5EKtNV4VeDzyN8eE9rZ2i5jgNr91BMI0wTw2AxB5cvG7L5wO4s2JBcwDktoMMFatSDfz8mY4JeuhrNZq3QgD10L6Rt/3+ou1Imkwmk8lkMplMJpNpK9kXSZPJZDKZTCaTyWQybaXt0Fbfd2GyxoLOVtqCnaXALYCwTi+1BT69EhaWr4A7DoQZhTGwxhLbynCYDLAl7/tAP4EfVHCUrVy3+a/+rgZWQddHJqYnX1XD7aqAY1MJhNPBMTEE8jGdAyniljFwjgQIcEikd7WbxNnOec5rEKEaSFsOTK1fq13o7hijHjtA6fyu6i7Ds4XAunw4YJLyyIH/5mi7EvezapCPJMYfAgmhg1cX+FOQvBnfq0O2hYoVEJFiCXwJSFoUCEXYSJYN1MJDO+Y7cjPzPOfCxv2UXSsDHhwEaqMig2MXygnxC+CLHrAQH65oXki8GG59S6EVGZw36QRXNknSS/A0IRLZe8D9EvSpGLhdjbYmNsh+6jnhWNVKjVfjfiO4og37cGrtqfzxF0K8nk7pSHlzCnzfjZqE0gUw6CHqIvSBFldwkMv4bETNdH3WLxM6Vx7GHdrjAq6eJbDCCOhw2XS4mj9FlmijHKgMkXbgfgUcBWuM5SAlpgU3WTxrUTGW6LnTTNe5AO4dYX54/+07bfmf/uXn7qZU17UrG/SwAl6WeKqXFEPH99TWtwaaE98Gyng4gmM2+mgU43VgSfVK15wB/3XoMxXnsGbMJB19PrrRhrtyZx/oFlDcdE9jPc+RvB6W2UWpuXqF+XRxKZfCz1/KXTDE/LtE3yTCFgSq15vW9SfilIxbIb4tzoQ++qijGP31DIMwwxopgFPooKvyBEdoAgysqgQ6W6geWXd1ur63UaI2yi/V/nSh7491JOVv/dEftOXPgEGepvqcAuOx4HGbWO0SYIyncNz1Qia7B/4JLLPaEdm6vvb6vvpA5MdHGv+TQzmAH6JNqwXWoss3I/IeXKG9DeT6zShhhn6f08kZsfJ6fUmn58BD/MSRoy6Q1wxO+d1EHzpPiZerT+U80oTkAFmttusiJhRYJCU9ZC5A25U7cqd3nnNBM8ay7M1u2FwALXE0w8frezjydHRbru5BT/2eDq4djM0Kfffl15+05Qh9YDAW+l81KHUNHL7XhXs83K39ITDXie7x/tv6/ADxNsJxpSBUTHr99Mu27GrNa97G+lZ1tkJcjfG9LfANbTWZTCaTyWQymUwm045lXyRNJpPJZDKZTCaTybSVtkJbq9pzy2K9nT67EDaxONNWd4Et9hL2gi9PiWHc0kWBp+ZImgxzQddBws4ukVPgTaUPnAIOXWGTqDUG/lTChSyrgS14QDWBWxIHi4hH0iEPiZVdTMc+3ft0quSlGZCxXg8IIRCCGjjMjcp3zsXr5wgKoBqwPi2BtjgggGVKvE91ERPnqN+MBfs10UNc3qne6xR9aQHXsAaFqTNiekBCVvh8OMUleA/dLj3gZiVwWuKfRHpK8DfFCtgP3Oo8IE5lLqTBT3eDKNe1kN5el7gD+hwwxcgJm1ihMvIrJFwGAhfBaTHE+wOMRzr0zdA3VleKDyEsx8ryGm0Fhokx7eW6ng/sPAbGVgO9YHL5GqhkBQSmXAn/qMAaFUCwokh9fHap1y/O4FhY7Abd8erKdRp8bQzk+nZfz/wl0M8az7yaAlGaqf47SFRco/6ZCJsES5UTBdY1u8DUez04cjbYbQpk0Uc8puNvAIfRCO0Y0NEQfcqP0AfQT4pS8bNeof9i7K82XKg17uiQ+jaSk9+k6tq5solTMCV2NeJCRGdDJIS+3xd6twf3cKSkdiHdGzEefeDrmVN70DV1o60RH66dqUEpuvIK89RC8bgPt9EO2i4EiltXmCty/a23BMp+qdcPh8B44Zz88gJjlk7p6Pscyzcpz3ntkYEIyFcG3HFWCuElmlkCq5sDidwb6287OM7T7avc+f/aO5MmSZLzPHusuWdVZS3dXb1Mz6YZAIJIygYQadRFOukk/Sv9JfEi001GgKAAgsAAPQt6el9qyapcYw8dMirfp8xmDJ1kpdGs7XtPbtnZkRG+fO5R/vj7JWr3EAhaiTF2ea4jRcsLxfY7d+6urhdrjM6B9I9fvFyXdycaI3uHcmH/4P6Ddbn/60frcg4n6aTUM/V7OO4A119vpmetMiDoROx4soRs5Q2qqiq3bJyA93flmHkInLUKNd8VPIKCvtXGvXpY37YQU4j2Voh9BdoxyzFvcYGL6xfN/Jjh+AbnXh/rzzZiaQf3kiNm0x0/wzyw4Jok0W+liBkejjJ4iMO9lvrpEjHW+xe4fb6TaufKJqOAj/FPN9IKz8wQS6S8hJM2zXcHexoDXTh688zT7K3cjZMpHMa7OJbGTt3ELA+xqwcMdlZiDp8Jqe4iHrQG6pttYLFhHy9KTn1gb+dA/xdzy7U1OPsDXNYrrJ3Cf8E6x3YkTSaTyWQymUwmk8m0kexF0mQymUwmk8lkMplMG2kjtLX0PHfRIGC/O5XD2hIIR2sIdzi4UX2bnK3LeQiMClvslSeEIwrkPuawnV/RxQ8OmyXeieMACZcbZ8IMtpsJkdFcyG07BhILDLJmMme6isJ5Ka9UB+1IuE4Cl7M5EBGfjqPAaAPiH1tK1Ot5ngubZ42A3s5P1UbzseqlD8dOkKXXEhJHcPiK4DLmAbsiyuXR5W2i30qBHdd4/nWL0ZG1JuYEHAtI1QD9xffh3FsR0QUGCIc8IoTEtJapsKYSfdBf6volHCa9eDvt6Pue6zZoRW8Hrl5grWZAK1pwUVzA0HEWEZkDttrSmArRvmSU2EczIL8JYgL7mBwOmUAYWE4CHA6JyyNHVzxiLHAeZZJntFeF8VUCZ02A5UxRvkCdTRE34r7q+CbludoF9eo340Ax4v6h4tFvlLfd5UhKPoXLa1KirYF4RnQ4Ba5UwwGwAnaTvNB1opZw6BEQoKRBHusCfR6xqybmRLdmxIN2jP9bEYfDOMUxhWqpMZ7P4YjpATnEkYElxkEPceNwKNfKm1bVYGgVeLiQDpWYcQcD9aceHFlDT30uADofAC8LY6DOPscDUTNgYJjbglzj9CreLeHwGs5073NgVzt7SugdwumwQD3TybxEvMlSxXiiql6l/j7a1T32xqqoEx53yNnJ3Fbk+b5rN5gtETgMr2vOkKVTv0wr4vU4bjFRnff3sbbZQxwcYE4CzpjNVHfTZwoEINbcuMENH3373fqz8zmOpywQGzEeP/uPf7kuH97VkaPDERA/Xz9E10dicjGOxdRtzPMdfb64xA2jHdPldtywa1evj634GI+TudY5L06EB89OhQ0PYXVZ+XCRxtzjMYMA1jw+FnE8SpCjA8Vw4ewC6U4aHLnCHJsg3pc4ihW1Mb7BrnewXov7qGfgiyXmtRSxJMAaCabXrgCKG8RoXyC4ebWdAVmvWtI551xIh2oebUNbFGi7BVysz881jnZP9P7CQc7jahHWq5M5slTMhLl2a631lwv1q8uTZ83NoC9kinXLmb77/Ks/rcsh8OrdO3KWHdyl07Aw7ajDDAWaz+8c6zvlr7FGwyQdwv2Vru1ZbWiryWQymUwmk8lkMpm2LHuRNJlMJpPJZDKZTCbTRtoIbS3K2p1ernCJt79Xou69gZAnJq1+Ayym6ghbmSOh+Qh4aImt8RLb8N612wRixwTkwCyvIZTNlm0QyvXI84Xx1NccNYERtbltTnc4bA3TWQ0IjAMKkQBNSudAz3qqjxwuiTlQyWG8UfNsIN8F9aqdQiQMjiPhVaeTt+ty1hLmwu3wClvgdAUk8uLFSGKOx0lnwkPTBfBBuKgtUe1XrlIFnR6JOMIZscDnBdrumqtYQKdQ973fIYpShGhHfB7gdxMglHO4j+7U7Bw3Jz/wXNxf1VcGNDNH/YdATxZzuJCFwp66GdzB6HQJPJKOdh7qtwb/kgGlIpIXtoVcXDnN+cAwfLhIVgnqfAEnZvQ7j1mQHRBiOu5muA7wT7rszuC+RtPlkxN9Psc1u1tCW52rnCtX2Iuf6bfvjpCcuKffHgNPyeEEmNffjzqVQIAK/u2QznET1EWt9thtw2ESLr5tf1WPZSzEMYPT4eJSGE89Vxv199QWOyO5p3bxOxXG7HyR4HPgY4gl1YKuhsDt0U+PBsJZ7w+BFt6kPM+55sgCpgDnI463gcB1uypHwMgrn3gV5idg9zlca3HawiWXwixdF/PgteMTGOMNTXpYyQAAHnJJREFU4k+kKl3oGuPvnq/LR/tCH1tDoVNE/Gr0zZL3CPQxY5J0OEbSsbzfg2PzDLgdnnVLJJ0LfM8NOqt1BlHGoqW1R4p1S4oYWyJmBZXWGdfWMDyeASfNCM9PV94caGu51Lzpw2X+1VcvnHPOPUVMm8OtusSRgRbm/PlS3zl++KGuPVMf+PhA4+VsoXs57KoPVBGOIWTff2yhyoWRjpcY11t0Nb+KSacvX60/f3midenbF+frclirLg4w9x219TzDNtYz6NOuAL6P+Y7YN52jd+BWHGA9XDRu4/xuAoZ5huMjARDOHo4ApKhbHkMp4OJbVzwuhmNhuJclHfoDzv/4GN+nE/tNynfOxU1crejqjnXDMvv+YLBA3Y3nGo/nF+oDfh9xEliyh7obf6P+Mz4Dag9kvYc1vbtYxYEC9RxgPesFuq8e6v/r7/Q7j76V0/K9TxR7790R5jrcx1ER9KmjkY4h3IHb9q+f6rljuKN38B0fRxLfVbYjaTKZTCaTyWQymUymjWQvkiaTyWQymUwmk8lk2kgbsZN5mrvXzdarhyTTvUBbqn6XTnzAN/376/LzM22dHt4Rchr7SPILBK0GGkinJh/b/xFQOSYqbscrPCzoalu7mmk7eAG3wBCOVYH7fuctErRVoO3gFrewPSFpOfCSHLhKt63vZJnurQQW0oLT3o2rQax8JGJnMu8EboxL3FOHyXGReNexzCTxYLwyuI+lQBgjOHEtmfR5IhTmyv01uRBaQ8w4z4Howq2wgIsjbv2a+xwxj+sOhLrfhEmx8awd4I7JVJjDDBhze2dzVOBdVNfOlQ2SNp4Jt6Aj3rDHJOJwgkM9Z3ALLNDWJZy8Crjc1mCUM7igXnMZBlpZAzMNG+zcv4YZM1EzED+0aZqpLwRw+yRSfQ2NpzMk/l7G57hEjFkA85wAtboEKrZ3IIT/JlVXGvctuKfuIPHwh8eKnxePn+k/A6NyKcpwS0zpYoeE4sUMqPME2CTqfYYxOwGC3/ZXsclv6/+lF3CQxVgI2vqdJfAn4nYjONTVOLKQA112bSKRer4gVAwr4QI6cJpb9luaowYDHI+4QXlO6aFzuHLHcEIOMU8RAz0FRjbFmBqB+gsjfc7YOJ3omeM25tMWEVnEO8xnvQZPTHtwXwQ+d/oK7t1/fLIu33oo1Crqqz5LjKkSHCoxuTk48iUcel2BZOtgl7uxrs9E6iUdpm9Qnue5+Aqbgyt0G1hjgeTmKdYQNd1I6UyewrE9hdvpXNeMPLhLx0DT4WQewu3TRaqX2XSFaE4uXq8/S+bA8gdab7RGQlJjjKnHX365Lp+O5Wr5Fz/9Ka6j+7r3QDHp9YVQ2N89+mZdnuJ4k99VeyVw0Ey2xCgXReHO365+/zdPv1t//gb4oI8jE6Ou1lslHd6BrdZA03uITRGPFRDxh7s0XcVTINBprfGWN8h0AGzTRYiZnKdmcJhHHUYYO0sez0HsTYBjV1j/ZOjvFY4JZPh+QufagHF4O0exfM9z3WatP89/4L0Aa74M81QSqo0myKAwmWo8BmdyYeUzz/Gdxy/lsvrNMx3rOz1Tv3/4SCjqTz596Jxz7gyxdJ6oje4f61jH/p7G43Bfa4y3T+TQ/IffakzNXwnH7o/UZ+/dFc7a6mu8/+xHQtYXeH/6+pWeezlTPbVbm7932I6kyWQymUwmk8lkMpk2kr1Imkwmk8lkMplMJpNpI23m2poX7vT5aov38+OP15/v3Bbm0gYO980bYQ1PsHX6i18oAedP/su/W5dvH8odLIEboQ+3QGJqTPxKt74CDk5evfrdGs6NviekqgMspwVXNgdXJdrDgWxwIVCBOqBDHhDOlPgBsAHUfF0Rs8RvbSnjcu1qlzdJhunSlQPhWGbALehch4TLMP9zBerL76m98pnwgATOgO4HHFe7O0J3PGB+aVN3TCLvwdl3D65TIfCPAqgGk+d6wDnoUkWH3hLtlc3hrDtHX9oTSka6d77Ufe4Bx7h5reoxBloTdVSHVfn9mGIBxC6DE1qORMU5cLQQ9Y4h7tIL4eh0R00X+nwOjHl3d4VetYe6xw4cIH2M7wiOvynuZQYXwxj4d43nqCr1X+Rrd6Wn5yYm5xBjWr6uSWfiZKG+fLOq106ljHXdjvr/8S2hmY+ew+UPeGSCuDdPgVRlwApRjxXQuMsT1emTM2E8wQslYj6+LRTmVnflghrFqtwcY224J5fUQVdjxDlh/Au6Ub4SFkSUsYDbaApMKIZbbIFEzx4GYauDuhwdrMt1yPu5QdW1qxo0LcZ80AHSF/vAIzEeX4wTlNUvR0eaqwLElOlUbZEuMSD39LszuBT22+rTHDNlgxFPwYhfXAKlxHzXey7cMYYFYdRWOcOxhpQu0cB1Ty7V7nPgZgg9144PeBiD9IWsy+3EVc85FzRBI+Lao6U+V3WABgLhZfxywO14TKJELF0shSj7mM+KBRYISJJeOrXdzlDrrp1mfjqii/ae7iUcHa3LB3RoBHYejoTpnf9BY2oR6Pm++Kufr8sffijk9cc40nT85bfr8v/+P3+3LlelnODvBHqO509fuG0oz3L38tkqrrz8Sr8RwEV5tKO5Z7HQWEu5zgAOSP91LIUcQo0rcKxlCvyUDv4ncIu95nzqVvGhivSbM9xXgOMpLSCIJY6ELOFUWmJtmeGYD9d0afH944trtBTlDDHZQ5zzve2sV51zLmjuLMJzJjzCxHkQax4i9eO5vt8ZKzbC49Zd4nhGiWt6OM4TxTwOpjHzdKx2qhuX191Doar7xxqvxz/68bo8aOt6+3BRHl/qeo++07GCy7nw9eGJ7msBR+d7x3qXunMozPU///u76/Iujgg9PQWCi/XCu8p2JE0mk8lkMplMJpPJtJHsRdJkMplMJpPJZDKZTBtpI7S1ds5dbfw++OTe+vO/GAljev1GiNKfzrXtWwJ/eYqkmI9eCHPZ2wEiGwl9K2GVSrdNkpIetvMruI+mV05oTKgei0OIgE96IS0gATHQnJSWd8AMHLb7C/Cv0zM5PM3gUrjT03bzAowEE7/Xbjtun87zXN2gEzWeOerBBRVuXyXcyRLcUwiHxHYtXKyYCtdJWV0hsCdgpgUdV+HE1YO7YqdBnQrgizXc8socSecdncr4txK1uw/3Tp9oMXDlAs9aok8V6IMp8Ei6v/pAZLdFfNR17dKm33cPlNB9v6fyN9/Koa6Ce+p+V4jdHhBeYpBpDufNpfALIlgV6tox8TqS48Z94NCNG14C58bWENhIR+3vAaehQ3C9pPudEBVXw1kWmGUEx06v4r2jDwKTCbtI0NxRH5wst5Q423OuvEq43IHjMe4VFJvrDoG2LoDxAIWnGeYSfXTCJNOINRn6Q5AqNjkkgPdj9auscaSMh4r9+3AIZtLza7hUqmvkGL/LsVDNRUuITgj3U7LjERK5p+TN4HaYAf16DVfj8bMztw3VrnZV0+/acNPtws2QRwnmeJ7TTM/5x7eaH2/fAfZd6xm6OIYxGGmuLHDe4AS48jfAiL1ULfL87WqOPpmr/oNS9fbRHT1H71BtXSGoXU41z1+81XWI5Dk4687RH1PMM0vMpzWOO8wrHjfAd7b1d3DPOe8KbcURAFerHcsMTsHo60SrQ7S1zz5KN0yMwflc/X5Gd/QEbu97t1XeFTYXN+jwvY5infNVnqC9dm/rGouJcOUe4vf/+O8/W5f/6ck/69b76gMnpebcuFB93IPL68+R9Pzv/+5/rcuffP6JfnegtcOfHt8c5pqmqXv89XfOOeeWOGJ0fKDf8+GsS9xzQbR1qc97XC9W6t8ZEH9izEXNNRXanVwsPr9aipRw/3XAR3s9xekQnxeYk/kcOeZ2OpbnXPMgPgWYBytgpAXnXIzB2BGL3c561fNqFzZ496AFV3cwqSDnXYG15QxrsotU/yG6xBoOdbS/LyS01VGf9jA29iPF5D2sUYdw8D8arBxUP/jJp+vPbj9QuUZYSeAMX7R1LwfHGt+PHj9fl1+MFctPpzjeh/l0OFC/fvhAbq4f7euZAnUlt/NK9/DmEpP+P3zt3kW2I2kymUwmk8lkMplMpo1kL5Imk8lkMplMJpPJZNpIG6Gtnue7uEFqjjrY3t0VQjE7155tCdw0XsB1EWjLi6dIsvxQ266dPeFVdEIrcMt+DIdPJL4PsMV7ldS8iIF0YcueKGNFF1YwXRVwywrWciUQIb+nez8/ETr1FO5co57qrAIS4AOF9VrEYbb1nl+7usEviAFfc8yMgNb4QIuAyCB/tEsStSNdvQI4Q1bAKYpT4VBXTofOOZfBbTIj3tNZ9QefmDMxDGCYMNtyCw+JVgfC6rpw6w3oWubpOhX6L6gm14XLVuiBDwiRFBjOk+GW/l4T+L4b9Vdj78ABw8Dz5ws4CMMlMgFO7Hk/kNi7pjMhUGDkq43hY+e3NR77x6rruNVFedWObItrGDnaHKSqq+kUhwcsgcYFTGyNPkurPbr4doE1zVEfKWJVB+O62FLi7NqrXdEkm19WxL+RuBzjaBex9/VEGGSBfrZE8uMAScx3gJdPz4XS7aOODuHwSBTTwX10OFphNy0kaW8BN21jHFdoiwKoah3pelWLbroag104jPrEDIFRZcDAIiSppxvhH06FBoUnwKFvUCu3z9V9+fjtgAacsBAOW+x/Kn99Ljz04xO55j4kkkfEEwm4u12Nq3uHQhh30I9fnmlOiuNVXd8fKEH2Xldz7+3bQL3QdmkK18MJ5vC5xg4AKVdizvcx/4ZdYL+YUDJgk0UCNB4xP/Y3Wr5soNr5DWbLoyw++lbcwtyDuM+TL17FOZ6xAxgi4hfnvhQOzBFcVjslx7jqOipW45AzTVFoHM3gUtnD3P7mVE6qIdxZDz4X2no/FVe/WKqfpsDhbn+kfvLZ8Qfr8oMDxZIe0MqXvxcyF398f10W/PqvV13LkbwbwbW4pZiVL7luAIaKuXICVHICVLfVU13U6N8VxyYWIy3Est2RxjJOebikOaqQo7/0+lpfM2aUXHPBZZ+Os9UPYLY+WGsfxwFSrEsD9DX2Ja57qzaP82xHvudcO6qb3wC2C1dzP8W94vjT4tqaXt/JMXayNo4D4FhBBYy5hTQLXEMc9tWmR0PFzd3d1Zxb4pjX8o2OGS1Sfb6Ay2/gA3PFsZ12rN+MgUIf9tWX29dO46ndfdRHgHu/ta9+1enJ1bz9UvPPu8p2JE0mk8lkMplMJpPJtJHsRdJkMplMJpPJZDKZTBtpIzYkCn13a9SgdEgcn2fajn07FdZ5eSZsooS7Ywwk8rsLIY4vzrSVu3co1MYLtK2ewH0vm2t7uEZi4wD46RVVlYXY7sf7MxO2eyVc5rhlD7S1BPKQ0ckT1oFfPpVz7Wyh+7p9oGdaTPSsAZJBtyJtj3shGMKbVO2ca3CwMiBmo3IIbLgg+lipXIMZrMFvRcDdSAOevhY2MHmhtisTuL/ClczDdfysbH5H1/OAjeRIVj6Zqx2XmRyu7n/y4bp8cEtOVgUcXysgEn4OBBpIVe8Ayc11O84viIuiDpDA9iYV+J4bNJmQyxDo+ImQxYtE/T6i0+KF6igfIfHugBbFSAoOrK0CIlMCeU1TtWMAWzKYQK4xsHoJBzmgJREyO3vXHO+I1gA5RrvUeL4K/bFGcucceFUA3MnzdA8JxnWA5+4NNSZuXqvfScDzXkPEndCx27vqf4+fynUxh7tg0ddA6XaRuBrY09dfI05dauzfuaXrH30o7KwFV9akQakWpfpagITPCeaEAihUkWs8DgK11637wufKtvDM0ANKhra4nKiv7SFWTYGjX6Adn73W77bvCre7SXnOudY6lsNBN8PRAEx+OfBXDy6vKVw9T5CU+gFiFh0Sz87VB9yJ6mV0LHRpB+66Ua14NAxWiF0ClNQjXn2hcfdsBmfdmebtBHXeQ1/b3YPjLBDpKeaZLMUcCuvFs6meg7hd5KuegvgHkPx/pXzPd614Fb8L9KEaSC5x+RCIbY02LeCeWdSqU7pRRyDwx+jTE8S+fbhHJsDuH51+tS6/bnC0EjEjKYgia+6dvlG/uJhpvfbh/Tu6mVLz871b+ry3KyTzt18LT/3lL+W2OkUM2+upbk4n6j+vXir29LcUVz3nXNT0uxjjq+BRGszZDv2ygKuqjzlmhvVfD47wHpx7p8Blk6m+v9fhPAv3VaC2nQY5jfD7GdDH6aXGCF3VHRBpn8cHgF37cGf1ED8CHEmYYi22xDr5WgyjkTbuM4i2NR49123w28sMGRkyrLcCHEHxVEeTnKg93GlxTALTkxsvNZ89xxGIdgWXe9TvrKtA8OKpjiEETZwKgA2PhnJhHaD905meaZYprs5z3UuFvsljZ72ern8I536Hfj3BUYn5XHXzdgL0PVX9nU5hgfuOsh1Jk8lkMplMJpPJZDJtJHuRNJlMJpPJZDKZTCbTRtoIbe21W+6vf/yRc865bltbreNncsRLgbZGwJKGSyE68Y7wTbqW/eKrJ+vyaCSUa38EbDLQtms91dZscaHt2/xSW8JXTqR1TOdX3dfZG20l+7G2qVtwNGqFcB4F5pDA+ekUCNIffq/niOmYCIelBbazO/hdYgYF8L8bV4OFVkCLXAH0AZhgBkfLIoIjGZBXD26QIZBUDzjFTi60NwTvmF8KowHZ67o7QqPixnWwBk5SAhE6fyms4GKq9vdi3Usf7nch6tkLVM90+cqBe7UioA0D3WQBxinJhZh5cPkKr2Wjvjl5nrfGoouZ7vV0DFSYOAscUadLjbs5nXLh8NWiozERcISNHAja+Fxj3wMC1IKDbTdatWPRB77YBcIBzLuC426ARMRxB+MFz1chQbTvq72KQs8a1up3ERCsEM7J19x6gZgNO3DovUF5nu/8q4Tt6CoZXP4i/M3v4MGDdbn88o/r8hx9YO8O6ivUfe/sCa/JP1Wb/r9/fqT7GWjcDe4Jazs6OtZ3Oqu+lMPRMEfS7+kbOYO++frpupwC37t7LIR2p6vfLDHuKrRdnbNMp1Y415UYd4nQpMUSzqbXHDRvWA0KeW0ctdSOAWMpy6jHAK68YziWvkXi6s/uCTnuLoDCPlYMmr1WuY2E6VmuOHB+dfQC/Z/I2AKI8hzHB2rgt8dAbg/uq4/0gTXmcCDESQKXLfV8r94ihs+ATAP/9GFN6JXbmR89z7m4idnEBDNgq3RUD2r1vxpuiTXciv0K8xawwmSp8TBHWyfAIx9PVdfjDhB8II9XaN/enrDtfTpjpxpr56+ExJ6ev1mXd2P9/rMn3+r7wDMf/khJ1Rfnmrf/4f/+cl0O9rXm+dlnP12X7x/r/w5/rvXV/LXu4Sbl+55rN9hopyV0r0Q7OsxTNdrFQ59zwLJnqHMfiexbQ7iUIx7VcIGf8VgW1o4+vl81cYDOxjlRc8SuBY57hEDm2x3OG8CugXA6HPfIELfnWA8ui+9fF/hcC4Bm9Uv6NN+cfOe5buOYnBHp59Eq4LYObuzLVHVe1VqHeGjTCN+/C+fVGMeTZkD8b/eFd9/ewzEBzNeD5ghgd6j3mA6OA1aoq3Kpd5DJVNde1jqOsZyp371+ozi5g34dYG3cwXGqyOOz6vmWWCef4QjeHEfD3lW2I2kymUwmk8lkMplMpo1kL5Imk8lkMplMJpPJZNpIG6GtrShwHx2tsJvJ68frz988F7rkA2s8uKXt1RevhL11Qm3xPhtrW3cGR79bR9qC/ZuOUK5RR3vYg1jb/OlQn5fAGfPGebKCA2UJ/Km/r236AAnVAySbXTIzOlCcKRDZ3wDLfQ5H1v/0gdCwIdDK8TnQgkpb4lkh1KVw4DxvULVTSuSyENYQ9ICtwj2zBKK8QBLc7kDb7USjAqCcBVDgblf9oXsAZCjU9edjIXGTifrDlYueD9TwAtvxxDmrvtr3g4fCrtpIYLsode2SjmRVhbJ+K24BmQMqOAR+e3apvlwDO4lCchc3KM+5oEFUxr7uNQSqMbojhIjJl6fAv2eZynmpPpeCQfMTJHSGCW0AXLub6x+WwPACOJv1dlboRtzSWKvbwG+BtvqRvhPhGnQmLDBemFC6zuAKSyQNTo+9HWGe2ULXuUbJ0DHS29bf3XzngtWz1ojIbTjLFYirbbj87R8LF58Dk/PhlFu2gGvXGrOHt4VjfX6i5PWXl0LNTv5JdT3ZUYxrd5pYBkT8FO5wb57LxbEDTOw/fKpk5R988lD/gITLS7RdPdd/rjAGS1DGBKoq4NtlW/3xaCS0794HH7ltyPecazfHFDJ2FfTXuK85oHAaXzMkrp5d6PmncN99dS7nzaM9td3wQGP2CNioByy4CoCEYn7cb3CsErjr+Ez3cgln9B2gca0Wjq3s6l4Gu6rzOld/zDCHTANd6NWpMK3TqeInyFnno03pRlhvKaw651xwNe6BDFZI5l1XbGDEHSZ6BwLIBPA5Pj+D+20K/PpyCqwfeOR3rzQ/ct5qd1ZxdTHVvMbjJjv7apc25qwjpzjdvyVn39/+9nfrcgXs/G//239dlxMcc3lyqmTrnx/fW5fvHsEdHa7eR3CwX378mZP+p7sp+b7vOt1OU6YLPzByOlqnqufKx7EO4MqXwL5hGu9CuITv4hhVZ8DjNPp+DVfzNuKU3+CaGbMDcCxwXQEL+xDz4zVE15ELV7FEnz0j2prp+ouKN0wulpkOEJ/dlo7w+M61mjr1MOhDHEHp7gDxxHqiHuv7BYJKu0PcUxUTwnn2wR31jVkf7vRwyy3wf/0B2qOZr3lsallonRXiqEGEY1MP7mLN09K7w+X49bq8gwm1AIrM8VgC3c04b2J9VQyF0Q5HiuEp3sneVbYjaTKZTCaTyWQymUymjWQvkiaTyWQymUwmk8lk2kgboa2ec67VYCmTsVCGWSWcIkyxZa9dfRcCD30LBOrpd0I1kiM5HJ2fIKk8EmSGHW3HBl1tCUfcVY+AvjVb+AVc/nIkPq5xDQ8XSZywoAyI4wzus8+eCzV68uztutyJhRod3paLWg+8WYWqnwEhLJEwvZ9snhj0nVS7dVbZDAlePbhURUA+MiAcNVywZjM9A53Kcmy3V0ggHSI5q98DalKhTeFw2AEe6V9hzECKii6w3IHqLT4QHuCjD2bAu+oEiMpC11kAbymA2HV6QkRjJLJ3PpPwAnFKaU24nXasqnrtuJosgLDA2bBDF1S0I5MsL+HItkRdMIl4WQFpBhrUiYGJ76GOkESbjret3mpseAHRaeAnQHFaIGtKJJEuMZZpFFcjMfglUFU60e3sK8Yc3BLuOHshxC5Gm87R39Nyczezd1LtOT9f/aYP1LzGeCGOWHmKL6NPH67L50/knp3AMbKN/hqiTT1g+i04bLbOUb+nwA0vVY/9/VW/IrZdp0CYY+Fwtw41vo8OhNAGbWBlyHJNbDBHnKwCxGH0kxlw9AR4cwL0/eHx3XX5s/u33Dbke/7aHZK5uaMQDp8gxDqx4lQrUrvnSCQ/BrJ/inZ8cSLktDVS/bZ6QK1SuhTCybGr/uMPV+20wBybpjgyApSugotjCLy9g7kih5NqmsEZGgjcyViI12u4ndOEtQUHxAIOl3RpDreUAN1VtauTVV8vgcMh97qr6bKLWOaAAxIfDBBTeHwixt/yKzpTTzXW2g5xAHgtycOocbjuZcDhgSNWWnK5vQ+1Jul4WJ90Fb9rHLfxR/pOjMTvH98RIh78rcb+3oGODPjAHUdDYa4Bjxrt0iL1JuWtj9lUBVxHUc88rpDinjximphXskLjYQmEdIl1VBfrjBbiY4QjCYx3AdadQbCq9whHuEqsgwogr3RhB216HW2Fu7CHfpdiPl1inUlnYiqO1O453ZsRb6NwS2hr7bm4XF27jTgSYw6IK91TB+3r+lhPtvF5TeQVx9jQLjFc2iscv0pnqsclEP8SA/IqVmaoK59OqnCP7+3geNAQDvc9lQOM+7Sn2D+t4HiPeaboaG7JA6zlMbe2d9Svb919uC7vw435XWU7kiaTyWQymUwmk8lk2kj2ImkymUwmk8lkMplMpo3kcWv6z+mLL76of/WrX23xdkw/JM/z/rGu6y9u4lrWjv92snZ8P2Tt+H7I2vH9kLXj+yFrx/dD1o7vh961HW1H0mQymUwmk8lkMplMG2mjHUnP806cc0/+7BdN29AHdV0f/vmv/XlZO/6bytrx/ZC14/sha8f3Q9aO74esHd8PWTu+H3qndtzoRdJkMplMJpPJZDKZTCZDW00mk8lkMplMJpPJtJHsRdJkMplMJpPJZDKZTBvJXiRNJpPJZDKZTCaTybSR7EXSZDKZTCaTyWQymUwbyV4kTSaTyWQymUwmk8m0kexF0mQymUwmk8lkMplMG8leJE0mk8lkMplMJpPJtJHsRdJkMplMJpPJZDKZTBvJXiRNJpPJZDKZTCaTybSR/j95egTsYn/4lAAAAABJRU5ErkJggg==
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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> (Write your answer in this cell)</p>
<p>About 70% of the faces created are recognizable as human faces. I believe that perhaps the addition of another layer and more epochs to train will have yielded more recognizable faces.</p>
<p>Making the model larger is a good idea to increase the quality of the faces shown. An increase in the depth of the conv_dim I suspect will make for a much better result. Also, the diversity of some of the faces (having glasses, hats, etc) definitely affected the training of the models. I do think that it shouldn't have an adverse effect as it should train on various types of images to make it more realistic.</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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