dlnd_face_generation.html

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<title>dlnd_face_generation</title>

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

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

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

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

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

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

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

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># can comment out after executing</span>
<span class="o">!</span>unzip processed_celeba_small.zip
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<pre>unzip:  cannot find or open processed_celeba_small.zip, processed_celeba_small.zip.zip or processed_celeba_small.zip.ZIP.
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">data_dir</span> <span class="o">=</span> <span class="s1">&#39;processed_celeba_small/&#39;</span>

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

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

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># necessary imports</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">from</span> <span class="nn">torchvision</span> <span class="k">import</span> <span class="n">datasets</span>
<span class="kn">from</span> <span class="nn">torchvision</span> <span class="k">import</span> <span class="n">transforms</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">get_dataloader</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">image_size</span><span class="p">,</span> <span class="n">data_dir</span><span class="o">=</span><span class="s1">&#39;processed_celeba_small/&#39;</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Batch the neural network data using DataLoader</span>
<span class="sd">    :param batch_size: The size of each batch; the number of images in a batch</span>
<span class="sd">    :param img_size: The square size of the image data (x, y)</span>
<span class="sd">    :param data_dir: Directory where image data is located</span>
<span class="sd">    :return: DataLoader with batched data</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1"># TODO: Implement function and return a dataloader</span>
    <span class="n">image_transforms</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span><span class="n">transforms</span><span class="o">.</span><span class="n">Resize</span><span class="p">(</span><span class="n">image_size</span><span class="p">),</span> 
                                    <span class="n">transforms</span><span class="o">.</span><span class="n">CenterCrop</span><span class="p">(</span><span class="n">image_size</span><span class="p">),</span> 
                                    <span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">()])</span>
    <span class="n">data_set</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">data_dir</span><span class="p">,</span> <span class="n">transform</span><span class="o">=</span><span class="n">image_transforms</span><span class="p">)</span>
    <span class="n">data_loader</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">DataLoader</span><span class="p">(</span><span class="n">data_set</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">32</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(-1.)
Max:  tensor(0.7412)
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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="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"># first layer, no batch_norm</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="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="bp">self</span><span class="o">.</span><span class="n">fc</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
        

    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Forward propagation of the neural network</span>
<span class="sd">        :param x: The input to the neural network     </span>
<span class="sd">        :return: Discriminator logits; the output of the neural network</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="c1"># define feedforward behavior</span>
        
        <span class="n">x</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv1</span><span class="p">(</span><span class="n">x</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv2</span><span class="p">(</span><span class="n">x</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv3</span><span class="p">(</span><span class="n">x</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>

        <span class="n">x</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="p">)</span>

        <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
        
        <span class="k">return</span> <span class="n">x</span>


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

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">deconv</span><span class="p">(</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;Creates a transposed-convolutional layer, with optional batch normalization.</span>
<span class="sd">    &quot;&quot;&quot;</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">transpose_conv_layer</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">ConvTranspose2d</span><span class="p">(</span><span class="n">in_channels</span><span class="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 transpose convolutional layer</span>
    <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">transpose_conv_layer</span><span class="p">)</span>
    
    <span class="k">if</span> <span class="n">batch_norm</span><span class="p">:</span>
        <span class="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="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">4</span><span class="o">*</span><span class="mi">4</span><span class="o">*</span><span class="mi">4</span><span class="p">)</span>

        <span class="c1"># transpose conv layers</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">t_conv1</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">t_conv2</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">t_conv3</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
        

    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Forward propagation of the neural network</span>
<span class="sd">        :param x: The input to the neural network     </span>
<span class="sd">        :return: A 32x32x3 Tensor image as output</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="c1"># define feedforward behavior</span>
        <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span> <span class="c1"># (batch_size, depth, 4, 4)</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">t_conv1</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">t_conv2</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
        
        <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">t_conv3</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">tanh</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
        <span class="k">return</span> <span class="n">x</span>

<span class="sd">&quot;&quot;&quot;</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="kn">from</span> <span class="nn">torch.nn</span> <span class="k">import</span> <span class="n">init</span>

<span class="k">def</span> <span class="nf">weights_init_normal</span><span class="p">(</span><span class="n">m</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Applies initial weights to certain layers in a model .</span>
<span class="sd">    The weights are taken from a normal distribution </span>
<span class="sd">    with mean = 0, std dev = 0.02.</span>
<span class="sd">    :param m: A module or layer in a network    </span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="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="n">init_gain</span> <span class="o">=</span> <span class="mf">0.02</span>
    <span class="c1"># TODO: Apply initial weights to convolutional and linear layers</span>
    <span class="c1"># Code taken from networks.py file in CycleGAN Github repository </span>
    <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="s1">&#39;weight&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="p">(</span><span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;Conv&#39;</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span> <span class="ow">or</span> <span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;Linear&#39;</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="p">):</span>
            <span class="n">init</span><span class="o">.</span><span class="n">normal_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="n">init_gain</span><span class="p">)</span>
            <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="s1">&#39;bias&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="n">m</span><span class="o">.</span><span class="n">bias</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
                <span class="n">init</span><span class="o">.</span><span class="n">constant_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">)</span>
    <span class="k">elif</span> <span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;BatchNorm2d&#39;</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="p">:</span>  <span class="c1"># BatchNorm Layer&#39;s weight is not a matrix; only normal distribution applies.</span>
            <span class="n">init</span><span class="o">.</span><span class="n">normal_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">,</span> <span class="n">init_gain</span><span class="p">)</span>
            <span class="n">init</span><span class="o">.</span><span class="n">constant_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">)</span> 
    
    
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<h2 id="Build-complete-network">Build complete network<a class="anchor-link" href="#Build-complete-network">&#182;</a></h2><p>Define your models' hyperparameters and instantiate the discriminator and generator from the classes defined above. Make sure you've passed in the correct input arguments.</p>

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<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</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">32</span>
<span class="n">g_conv_dim</span> <span class="o">=</span> <span class="mi">32</span>
<span class="n">z_size</span> <span class="o">=</span> <span class="mi">100</span>

<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">D</span><span class="p">,</span> <span class="n">G</span> <span class="o">=</span> <span class="n">build_network</span><span class="p">(</span><span class="n">d_conv_dim</span><span class="p">,</span> <span class="n">g_conv_dim</span><span class="p">,</span> <span class="n">z_size</span><span class="p">)</span>
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<pre>Discriminator(
  (conv1): Sequential(
    (0): Conv2d(3, 32, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
  )
  (conv2): Sequential(
    (0): Conv2d(32, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (conv3): Sequential(
    (0): Conv2d(64, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (fc): Linear(in_features=2048, out_features=1, bias=True)
)

Generator(
  (fc): Linear(in_features=100, out_features=2048, bias=True)
  (t_conv1): Sequential(
    (0): ConvTranspose2d(128, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (t_conv2): Sequential(
    (0): ConvTranspose2d(64, 32, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (t_conv3): Sequential(
    (0): ConvTranspose2d(32, 3, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
  )
)
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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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<h2 id="Discriminator-and-Generator-Losses">Discriminator and Generator Losses<a class="anchor-link" href="#Discriminator-and-Generator-Losses">&#182;</a></h2><p>Now we need to calculate the losses for both types of adversarial networks.</p>
<h3 id="Discriminator-Losses">Discriminator Losses<a class="anchor-link" href="#Discriminator-Losses">&#182;</a></h3><blockquote><ul>
<li>For the discriminator, the total loss is the sum of the losses for real and fake images, <code>d_loss = d_real_loss + d_fake_loss</code>. </li>
<li>Remember that we want the discriminator to output 1 for real images and 0 for fake images, so we need to set up the losses to reflect that.</li>
</ul>
</blockquote>
<h3 id="Generator-Loss">Generator Loss<a class="anchor-link" href="#Generator-Loss">&#182;</a></h3><p>The generator loss will look similar only with flipped labels. The generator's goal is to get the discriminator to <em>think</em> its generated images are <em>real</em>.</p>
<h4 id="Exercise:-Complete-real-and-fake-loss-functions">Exercise: Complete real and fake loss functions<a class="anchor-link" href="#Exercise:-Complete-real-and-fake-loss-functions">&#182;</a></h4><p><strong>You may choose to use either cross entropy or a least squares error loss to complete the following <code>real_loss</code> and <code>fake_loss</code> functions.</strong></p>

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

<span class="k">def</span> <span class="nf">real_loss</span><span class="p">(</span><span class="n">D_out</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39;Calculates how close discriminator outputs are to being real.</span>
<span class="sd">       param, D_out: discriminator logits</span>
<span class="sd">       return: real loss&#39;&#39;&#39;</span>
    <span class="n">batch_size</span> <span class="o">=</span> <span class="n">D_out</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">labels</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">batch_size</span><span class="p">)</span> <span class="o">*</span>  <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="mf">0.7</span><span class="p">,</span><span class="mf">1.05</span><span class="p">)</span> <span class="c1"># label smoothing </span>
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
    <span class="n">criterion</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">BCEWithLogitsLoss</span><span class="p">()</span>
    <span class="n">loss</span> <span class="o">=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">D_out</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(),</span> <span class="n">labels</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">loss</span>

<span class="k">def</span> <span class="nf">fake_loss</span><span class="p">(</span><span class="n">D_out</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39;Calculates how close discriminator outputs are to being fake.</span>
<span class="sd">       param, D_out: discriminator logits</span>
<span class="sd">       return: fake loss&#39;&#39;&#39;</span>
    <span class="n">batch_size</span> <span class="o">=</span> <span class="n">D_out</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">labels</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">batch_size</span><span class="p">)</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span><span class="mf">0.35</span><span class="p">)</span>
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
    <span class="n">criterion</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">BCEWithLogitsLoss</span><span class="p">()</span>
    <span class="n">loss</span> <span class="o">=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">D_out</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(),</span> <span class="n">labels</span><span class="p">)</span> 
    <span class="k">return</span> <span class="n">loss</span>
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<h2 id="Optimizers">Optimizers<a class="anchor-link" href="#Optimizers">&#182;</a></h2><h4 id="Exercise:-Define-optimizers-for-your-Discriminator-(D)-and-Generator-(G)">Exercise: Define optimizers for your Discriminator (D) and Generator (G)<a class="anchor-link" href="#Exercise:-Define-optimizers-for-your-Discriminator-(D)-and-Generator-(G)">&#182;</a></h4><p>Define optimizers for your models with appropriate hyperparameters.</p>

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

<span class="c1"># parameters taken directly from DCGAN paper in the assignment </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 and generator</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="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="n">z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">z</span> <span class="o">=</span> <span class="n">z</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
            
            <span class="n">fake_images</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">z</span><span class="p">)</span>
            <span class="n">D_fake</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="n">d_loss</span> <span class="o">=</span> <span class="n">d_real_loss</span> <span class="o">+</span> <span class="n">d_fake_loss</span>
            <span class="n">d_loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
            <span class="n">d_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>

            <span class="c1"># 2. Train the generator with an adversarial loss</span>
            <span class="n">g_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
            
            <span class="n">z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">z</span> <span class="o">=</span> <span class="n">z</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
            
            <span class="n">fake_images</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">z</span><span class="p">)</span>
            <span class="n">D_fake</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="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;[21]:</div>
<div class="inner_cell">
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># set number of epochs </span>
<span class="n">n_epochs</span> <span class="o">=</span> <span class="mi">10</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>
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    <div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Epoch [    1/   10] | d_loss: 1.2678 | g_loss: 0.9246
Epoch [    1/   10] | d_loss: 0.4066 | g_loss: 3.0303
Epoch [    1/   10] | d_loss: 0.3463 | g_loss: 3.6230
Epoch [    1/   10] | d_loss: 0.7510 | g_loss: 2.2199
Epoch [    1/   10] | d_loss: 1.0820 | g_loss: 2.6453
Epoch [    1/   10] | d_loss: 0.8641 | g_loss: 1.7200
Epoch [    1/   10] | d_loss: 0.4731 | g_loss: 2.4129
Epoch [    1/   10] | d_loss: 0.8035 | g_loss: 2.5367
Epoch [    1/   10] | d_loss: 0.8018 | g_loss: 2.1384
Epoch [    1/   10] | d_loss: 1.1427 | g_loss: 2.5015
Epoch [    1/   10] | d_loss: 1.3028 | g_loss: 1.9352
Epoch [    1/   10] | d_loss: 0.9036 | g_loss: 2.4863
Epoch [    1/   10] | d_loss: 0.8076 | g_loss: 0.9899
Epoch [    1/   10] | d_loss: 0.7579 | g_loss: 1.4733
Epoch [    1/   10] | d_loss: 1.1025 | g_loss: 2.2748
Epoch [    1/   10] | d_loss: 1.0385 | g_loss: 1.5898
Epoch [    1/   10] | d_loss: 1.0108 | g_loss: 1.0029
Epoch [    1/   10] | d_loss: 0.9887 | g_loss: 2.1093
Epoch [    1/   10] | d_loss: 1.0585 | g_loss: 1.3705
Epoch [    1/   10] | d_loss: 1.0139 | g_loss: 1.4829
Epoch [    1/   10] | d_loss: 1.2857 | g_loss: 0.8230
Epoch [    1/   10] | d_loss: 1.0279 | g_loss: 1.5098
Epoch [    1/   10] | d_loss: 1.1163 | g_loss: 1.5503
Epoch [    1/   10] | d_loss: 1.1857 | g_loss: 1.4569
Epoch [    1/   10] | d_loss: 1.3020 | g_loss: 0.9233
Epoch [    1/   10] | d_loss: 1.2003 | g_loss: 1.0737
Epoch [    1/   10] | d_loss: 1.0013 | g_loss: 1.5149
Epoch [    1/   10] | d_loss: 1.1473 | g_loss: 0.7903
Epoch [    1/   10] | d_loss: 1.1901 | g_loss: 1.0956
Epoch [    1/   10] | d_loss: 1.1829 | g_loss: 0.9849
Epoch [    1/   10] | d_loss: 1.1705 | g_loss: 1.1290
Epoch [    1/   10] | d_loss: 1.0306 | g_loss: 1.4243
Epoch [    1/   10] | d_loss: 1.4603 | g_loss: 0.6889
Epoch [    1/   10] | d_loss: 1.4630 | g_loss: 2.3193
Epoch [    1/   10] | d_loss: 1.2888 | g_loss: 1.2635
Epoch [    1/   10] | d_loss: 1.2287 | g_loss: 1.1767
Epoch [    1/   10] | d_loss: 0.9460 | g_loss: 1.8262
Epoch [    1/   10] | d_loss: 0.9701 | g_loss: 1.1467
Epoch [    1/   10] | d_loss: 1.1270 | g_loss: 1.6041
Epoch [    1/   10] | d_loss: 1.2799 | g_loss: 0.8857
Epoch [    1/   10] | d_loss: 1.1419 | g_loss: 0.7270
Epoch [    1/   10] | d_loss: 1.3838 | g_loss: 1.0005
Epoch [    1/   10] | d_loss: 0.9639 | g_loss: 1.3356
Epoch [    1/   10] | d_loss: 1.3735 | g_loss: 0.7654
Epoch [    1/   10] | d_loss: 1.0290 | g_loss: 1.5347
Epoch [    1/   10] | d_loss: 1.0874 | g_loss: 1.4622
Epoch [    1/   10] | d_loss: 1.2760 | g_loss: 1.1929
Epoch [    1/   10] | d_loss: 0.9778 | g_loss: 1.1624
Epoch [    1/   10] | d_loss: 1.0802 | g_loss: 1.2716
Epoch [    1/   10] | d_loss: 1.2227 | g_loss: 1.2463
Epoch [    1/   10] | d_loss: 1.1629 | g_loss: 1.3105
Epoch [    1/   10] | d_loss: 0.9608 | g_loss: 1.3797
Epoch [    1/   10] | d_loss: 1.2497 | g_loss: 1.1693
Epoch [    1/   10] | d_loss: 1.3182 | g_loss: 0.9065
Epoch [    1/   10] | d_loss: 1.0466 | g_loss: 0.7739
Epoch [    1/   10] | d_loss: 1.6897 | g_loss: 1.6087
Epoch [    1/   10] | d_loss: 1.3497 | g_loss: 1.0996
Epoch [    2/   10] | d_loss: 1.1990 | g_loss: 0.7386
Epoch [    2/   10] | d_loss: 1.2374 | g_loss: 1.0352
Epoch [    2/   10] | d_loss: 1.3119 | g_loss: 1.6561
Epoch [    2/   10] | d_loss: 1.2202 | g_loss: 0.8852
Epoch [    2/   10] | d_loss: 1.2090 | g_loss: 0.8931
Epoch [    2/   10] | d_loss: 0.7825 | g_loss: 0.9961
Epoch [    2/   10] | d_loss: 1.2083 | g_loss: 1.2701
Epoch [    2/   10] | d_loss: 1.0956 | g_loss: 1.2115
Epoch [    2/   10] | d_loss: 1.1021 | g_loss: 1.2702
Epoch [    2/   10] | d_loss: 1.1073 | g_loss: 1.0498
Epoch [    2/   10] | d_loss: 1.1592 | g_loss: 0.7690
Epoch [    2/   10] | d_loss: 1.0991 | g_loss: 0.8971
Epoch [    2/   10] | d_loss: 1.0117 | g_loss: 0.7798
Epoch [    2/   10] | d_loss: 1.1280 | g_loss: 1.2064
Epoch [    2/   10] | d_loss: 1.1218 | g_loss: 1.2396
Epoch [    2/   10] | d_loss: 0.8879 | g_loss: 1.4870
Epoch [    2/   10] | d_loss: 1.1523 | g_loss: 1.5844
Epoch [    2/   10] | d_loss: 1.1488 | g_loss: 1.1614
Epoch [    2/   10] | d_loss: 1.1542 | g_loss: 1.2580
Epoch [    2/   10] | d_loss: 1.2271 | g_loss: 0.9004
Epoch [    2/   10] | d_loss: 1.0847 | g_loss: 0.9904
Epoch [    2/   10] | d_loss: 1.0693 | g_loss: 1.4615
Epoch [    2/   10] | d_loss: 1.2147 | g_loss: 1.2079
Epoch [    2/   10] | d_loss: 1.3206 | g_loss: 0.8294
Epoch [    2/   10] | d_loss: 1.8621 | g_loss: 0.6587
Epoch [    2/   10] | d_loss: 1.1595 | g_loss: 1.1592
Epoch [    2/   10] | d_loss: 1.4473 | g_loss: 0.7521
Epoch [    2/   10] | d_loss: 1.2294 | g_loss: 1.1313
Epoch [    2/   10] | d_loss: 1.1415 | g_loss: 1.6979
Epoch [    2/   10] | d_loss: 1.0251 | g_loss: 1.1673
Epoch [    2/   10] | d_loss: 1.0729 | g_loss: 1.1977
Epoch [    2/   10] | d_loss: 1.1832 | g_loss: 1.7482
Epoch [    2/   10] | d_loss: 1.1984 | g_loss: 1.2943
Epoch [    2/   10] | d_loss: 1.2009 | g_loss: 1.4472
Epoch [    2/   10] | d_loss: 0.9245 | g_loss: 2.0063
Epoch [    2/   10] | d_loss: 1.3039 | g_loss: 1.0736
Epoch [    2/   10] | d_loss: 0.9466 | g_loss: 1.4110
Epoch [    2/   10] | d_loss: 1.0448 | g_loss: 1.3453
Epoch [    2/   10] | d_loss: 0.8174 | g_loss: 1.0011
Epoch [    2/   10] | d_loss: 1.1185 | g_loss: 0.9294
Epoch [    2/   10] | d_loss: 0.8209 | g_loss: 1.3514
Epoch [    2/   10] | d_loss: 1.1380 | g_loss: 1.2588
Epoch [    2/   10] | d_loss: 1.3100 | g_loss: 1.3552
Epoch [    2/   10] | d_loss: 1.0552 | g_loss: 0.9294
Epoch [    2/   10] | d_loss: 1.2077 | g_loss: 1.3302
Epoch [    2/   10] | d_loss: 1.0033 | g_loss: 1.0591
Epoch [    2/   10] | d_loss: 0.9826 | g_loss: 1.4256
Epoch [    2/   10] | d_loss: 1.0282 | g_loss: 0.8010
Epoch [    2/   10] | d_loss: 1.1611 | g_loss: 1.3232
Epoch [    2/   10] | d_loss: 1.0606 | g_loss: 1.6992
Epoch [    2/   10] | d_loss: 1.1724 | g_loss: 1.1471
Epoch [    2/   10] | d_loss: 0.9943 | g_loss: 1.9096
Epoch [    2/   10] | d_loss: 1.1794 | g_loss: 1.5163
Epoch [    2/   10] | d_loss: 1.3409 | g_loss: 1.3394
Epoch [    2/   10] | d_loss: 1.2205 | g_loss: 1.3750
Epoch [    2/   10] | d_loss: 1.0358 | g_loss: 1.9329
Epoch [    2/   10] | d_loss: 1.0591 | g_loss: 1.1984
Epoch [    3/   10] | d_loss: 1.0446 | g_loss: 1.1790
Epoch [    3/   10] | d_loss: 0.9909 | g_loss: 0.7827
Epoch [    3/   10] | d_loss: 1.0445 | g_loss: 0.9761
Epoch [    3/   10] | d_loss: 1.2304 | g_loss: 1.3048
Epoch [    3/   10] | d_loss: 0.9447 | g_loss: 1.0157
Epoch [    3/   10] | d_loss: 1.1366 | g_loss: 1.2525
Epoch [    3/   10] | d_loss: 1.0167 | g_loss: 1.3347
Epoch [    3/   10] | d_loss: 1.0692 | g_loss: 0.9990
Epoch [    3/   10] | d_loss: 1.0959 | g_loss: 1.1841
Epoch [    3/   10] | d_loss: 0.6477 | g_loss: 1.7943
Epoch [    3/   10] | d_loss: 1.0112 | g_loss: 1.2282
Epoch [    3/   10] | d_loss: 1.1040 | g_loss: 1.3971
Epoch [    3/   10] | d_loss: 0.6773 | g_loss: 1.0335
Epoch [    3/   10] | d_loss: 1.1360 | g_loss: 1.7226
Epoch [    3/   10] | d_loss: 1.1364 | g_loss: 2.2697
Epoch [    3/   10] | d_loss: 1.1428 | g_loss: 1.1902
Epoch [    3/   10] | d_loss: 1.1672 | g_loss: 1.1410
Epoch [    3/   10] | d_loss: 1.0633 | g_loss: 1.2181
Epoch [    3/   10] | d_loss: 1.1889 | g_loss: 1.8471
Epoch [    3/   10] | d_loss: 1.2343 | g_loss: 1.2243
Epoch [    3/   10] | d_loss: 1.2098 | g_loss: 1.7327
Epoch [    3/   10] | d_loss: 0.9578 | g_loss: 1.3428
Epoch [    3/   10] | d_loss: 0.9136 | g_loss: 1.3316
Epoch [    3/   10] | d_loss: 1.2326 | g_loss: 1.3626
Epoch [    3/   10] | d_loss: 0.9539 | g_loss: 0.9720
Epoch [    3/   10] | d_loss: 1.0919 | g_loss: 1.2316
Epoch [    3/   10] | d_loss: 1.0490 | g_loss: 1.1711
Epoch [    3/   10] | d_loss: 1.3153 | g_loss: 1.5352
Epoch [    3/   10] | d_loss: 1.1405 | g_loss: 0.6642
Epoch [    3/   10] | d_loss: 1.0223 | g_loss: 1.1404
Epoch [    3/   10] | d_loss: 1.2225 | g_loss: 0.9559
Epoch [    3/   10] | d_loss: 1.0467 | g_loss: 1.3920
Epoch [    3/   10] | d_loss: 1.1203 | g_loss: 1.2835
Epoch [    3/   10] | d_loss: 1.1131 | g_loss: 1.7478
Epoch [    3/   10] | d_loss: 1.2358 | g_loss: 1.1496
Epoch [    3/   10] | d_loss: 0.8782 | g_loss: 1.8228
Epoch [    3/   10] | d_loss: 0.7014 | g_loss: 1.6002
Epoch [    3/   10] | d_loss: 1.0781 | g_loss: 1.5245
Epoch [    3/   10] | d_loss: 1.0543 | g_loss: 1.0255
Epoch [    3/   10] | d_loss: 1.0535 | g_loss: 1.1569
Epoch [    3/   10] | d_loss: 1.1294 | g_loss: 1.3413
Epoch [    3/   10] | d_loss: 1.1399 | g_loss: 0.7288
Epoch [    3/   10] | d_loss: 0.9151 | g_loss: 1.1333
Epoch [    3/   10] | d_loss: 1.3716 | g_loss: 1.2365
Epoch [    3/   10] | d_loss: 1.0496 | g_loss: 1.3952
Epoch [    3/   10] | d_loss: 1.3308 | g_loss: 1.1075
Epoch [    3/   10] | d_loss: 0.8406 | g_loss: 1.4162
Epoch [    3/   10] | d_loss: 0.9725 | g_loss: 1.3542
Epoch [    3/   10] | d_loss: 0.9347 | g_loss: 1.0654
Epoch [    3/   10] | d_loss: 1.1849 | g_loss: 1.0723
Epoch [    3/   10] | d_loss: 0.9624 | g_loss: 0.8865
Epoch [    3/   10] | d_loss: 1.0189 | g_loss: 1.0592
Epoch [    3/   10] | d_loss: 1.1043 | g_loss: 1.4964
Epoch [    3/   10] | d_loss: 1.0563 | g_loss: 1.1820
Epoch [    3/   10] | d_loss: 1.0558 | g_loss: 1.1389
Epoch [    3/   10] | d_loss: 1.0771 | g_loss: 1.0799
Epoch [    3/   10] | d_loss: 0.7732 | g_loss: 0.7888
Epoch [    4/   10] | d_loss: 1.0663 | g_loss: 1.5529
Epoch [    4/   10] | d_loss: 0.8031 | g_loss: 1.1526
Epoch [    4/   10] | d_loss: 1.2282 | g_loss: 1.5755
Epoch [    4/   10] | d_loss: 1.0645 | g_loss: 1.5319
Epoch [    4/   10] | d_loss: 1.6009 | g_loss: 1.2010
Epoch [    4/   10] | d_loss: 1.0910 | g_loss: 1.0236
Epoch [    4/   10] | d_loss: 0.9018 | g_loss: 1.5865
Epoch [    4/   10] | d_loss: 0.9742 | g_loss: 1.6028
Epoch [    4/   10] | d_loss: 1.0920 | g_loss: 0.9553
Epoch [    4/   10] | d_loss: 0.9906 | g_loss: 0.7905
Epoch [    4/   10] | d_loss: 1.6280 | g_loss: 1.5523
Epoch [    4/   10] | d_loss: 0.9559 | g_loss: 1.3141
Epoch [    4/   10] | d_loss: 1.5548 | g_loss: 2.0179
Epoch [    4/   10] | d_loss: 1.3417 | g_loss: 1.4848
Epoch [    4/   10] | d_loss: 0.9617 | g_loss: 1.7579
Epoch [    4/   10] | d_loss: 1.0234 | g_loss: 1.1646
Epoch [    4/   10] | d_loss: 1.3499 | g_loss: 1.2200
Epoch [    4/   10] | d_loss: 1.0077 | g_loss: 1.3070
Epoch [    4/   10] | d_loss: 1.2325 | g_loss: 1.2306
Epoch [    4/   10] | d_loss: 1.0303 | g_loss: 1.2406
Epoch [    4/   10] | d_loss: 0.9789 | g_loss: 1.1153
Epoch [    4/   10] | d_loss: 1.6883 | g_loss: 1.1196
Epoch [    4/   10] | d_loss: 0.8948 | g_loss: 1.2034
Epoch [    4/   10] | d_loss: 1.0631 | g_loss: 1.3348
Epoch [    4/   10] | d_loss: 1.0201 | g_loss: 1.4570
Epoch [    4/   10] | d_loss: 1.1711 | g_loss: 1.3742
Epoch [    4/   10] | d_loss: 1.1729 | g_loss: 1.5106
Epoch [    4/   10] | d_loss: 0.9596 | g_loss: 1.1475
Epoch [    4/   10] | d_loss: 1.1284 | g_loss: 1.4568
Epoch [    4/   10] | d_loss: 1.0664 | g_loss: 1.5024
Epoch [    4/   10] | d_loss: 1.0950 | g_loss: 1.0967
Epoch [    4/   10] | d_loss: 0.8123 | g_loss: 1.4964
Epoch [    4/   10] | d_loss: 1.1723 | g_loss: 0.7811
Epoch [    4/   10] | d_loss: 1.3580 | g_loss: 1.6247
Epoch [    4/   10] | d_loss: 1.0002 | g_loss: 0.7819
Epoch [    4/   10] | d_loss: 1.0075 | g_loss: 1.2937
Epoch [    4/   10] | d_loss: 0.9217 | g_loss: 2.0743
Epoch [    4/   10] | d_loss: 1.2003 | g_loss: 1.4672
Epoch [    4/   10] | d_loss: 1.0222 | g_loss: 1.4700
Epoch [    4/   10] | d_loss: 1.1203 | g_loss: 1.5661
Epoch [    4/   10] | d_loss: 0.9863 | g_loss: 1.1215
Epoch [    4/   10] | d_loss: 0.7546 | g_loss: 1.2761
Epoch [    4/   10] | d_loss: 0.9191 | g_loss: 1.7874
Epoch [    4/   10] | d_loss: 1.0354 | g_loss: 1.2136
Epoch [    4/   10] | d_loss: 0.5763 | g_loss: 1.1841
Epoch [    4/   10] | d_loss: 0.9181 | g_loss: 1.1927
Epoch [    4/   10] | d_loss: 1.2024 | g_loss: 1.8441
Epoch [    4/   10] | d_loss: 1.0594 | g_loss: 1.0677
Epoch [    4/   10] | d_loss: 1.1898 | g_loss: 1.2417
Epoch [    4/   10] | d_loss: 1.0282 | g_loss: 1.2238
Epoch [    4/   10] | d_loss: 0.7137 | g_loss: 1.5708
Epoch [    4/   10] | d_loss: 0.8332 | g_loss: 1.1883
Epoch [    4/   10] | d_loss: 1.2059 | g_loss: 1.0886
Epoch [    4/   10] | d_loss: 0.8850 | g_loss: 1.7174
Epoch [    4/   10] | d_loss: 0.9850 | g_loss: 1.0969
Epoch [    4/   10] | d_loss: 0.8966 | g_loss: 0.9846
Epoch [    4/   10] | d_loss: 0.9028 | g_loss: 1.1777
Epoch [    5/   10] | d_loss: 1.2489 | g_loss: 1.2909
Epoch [    5/   10] | d_loss: 1.1125 | g_loss: 1.0876
Epoch [    5/   10] | d_loss: 0.7899 | g_loss: 1.4400
Epoch [    5/   10] | d_loss: 0.9140 | g_loss: 1.9513
Epoch [    5/   10] | d_loss: 1.0526 | g_loss: 1.1275
Epoch [    5/   10] | d_loss: 1.0373 | g_loss: 2.0038
Epoch [    5/   10] | d_loss: 0.8274 | g_loss: 1.3947
Epoch [    5/   10] | d_loss: 0.9382 | g_loss: 2.1718
Epoch [    5/   10] | d_loss: 0.9328 | g_loss: 1.0055
Epoch [    5/   10] | d_loss: 0.6888 | g_loss: 1.8307
Epoch [    5/   10] | d_loss: 0.5239 | g_loss: 1.4237
Epoch [    5/   10] | d_loss: 1.0860 | g_loss: 1.6529
Epoch [    5/   10] | d_loss: 0.8134 | g_loss: 1.8940
Epoch [    5/   10] | d_loss: 1.3066 | g_loss: 2.7566
Epoch [    5/   10] | d_loss: 0.7831 | g_loss: 1.8718
Epoch [    5/   10] | d_loss: 1.0452 | g_loss: 0.8371
Epoch [    5/   10] | d_loss: 1.3068 | g_loss: 1.5235
Epoch [    5/   10] | d_loss: 1.0334 | g_loss: 1.1186
Epoch [    5/   10] | d_loss: 1.2734 | g_loss: 1.4273
Epoch [    5/   10] | d_loss: 0.9438 | g_loss: 0.9513
Epoch [    5/   10] | d_loss: 0.9572 | g_loss: 0.9351
Epoch [    5/   10] | d_loss: 0.8710 | g_loss: 1.1791
Epoch [    5/   10] | d_loss: 0.8330 | g_loss: 1.9211
Epoch [    5/   10] | d_loss: 0.8592 | g_loss: 2.1499
Epoch [    5/   10] | d_loss: 1.0011 | g_loss: 1.1507
Epoch [    5/   10] | d_loss: 0.8383 | g_loss: 1.3680
Epoch [    5/   10] | d_loss: 0.8461 | g_loss: 1.0898
Epoch [    5/   10] | d_loss: 0.8903 | g_loss: 1.1605
Epoch [    5/   10] | d_loss: 1.2809 | g_loss: 1.5789
Epoch [    5/   10] | d_loss: 1.4055 | g_loss: 0.6915
Epoch [    5/   10] | d_loss: 1.0851 | g_loss: 1.3591
Epoch [    5/   10] | d_loss: 0.9843 | g_loss: 1.3693
Epoch [    5/   10] | d_loss: 1.1549 | g_loss: 1.6723
Epoch [    5/   10] | d_loss: 0.9079 | g_loss: 0.9842
Epoch [    5/   10] | d_loss: 0.9689 | g_loss: 1.6882
Epoch [    5/   10] | d_loss: 0.8121 | g_loss: 1.7893
Epoch [    5/   10] | d_loss: 0.9449 | g_loss: 1.2733
Epoch [    5/   10] | d_loss: 0.7643 | g_loss: 1.8130
Epoch [    5/   10] | d_loss: 0.8952 | g_loss: 2.0476
Epoch [    5/   10] | d_loss: 0.9793 | g_loss: 3.1098
Epoch [    5/   10] | d_loss: 1.0229 | g_loss: 2.0029
Epoch [    5/   10] | d_loss: 0.9074 | g_loss: 1.6014
Epoch [    5/   10] | d_loss: 1.0933 | g_loss: 1.9748
Epoch [    5/   10] | d_loss: 0.9766 | g_loss: 1.9500
Epoch [    5/   10] | d_loss: 0.7993 | g_loss: 1.0532
Epoch [    5/   10] | d_loss: 0.8073 | g_loss: 1.8917
Epoch [    5/   10] | d_loss: 1.1362 | g_loss: 0.8929
Epoch [    5/   10] | d_loss: 0.8608 | g_loss: 1.2583
Epoch [    5/   10] | d_loss: 0.9217 | g_loss: 1.6042
Epoch [    5/   10] | d_loss: 0.8116 | g_loss: 2.0578
Epoch [    5/   10] | d_loss: 0.9321 | g_loss: 2.1372
Epoch [    5/   10] | d_loss: 0.8828 | g_loss: 1.4176
Epoch [    5/   10] | d_loss: 1.0051 | g_loss: 1.6519
Epoch [    5/   10] | d_loss: 1.0888 | g_loss: 2.0448
Epoch [    5/   10] | d_loss: 0.6739 | g_loss: 1.6886
Epoch [    5/   10] | d_loss: 0.9423 | g_loss: 1.0596
Epoch [    5/   10] | d_loss: 0.9257 | g_loss: 2.2435
Epoch [    6/   10] | d_loss: 1.0797 | g_loss: 1.5290
Epoch [    6/   10] | d_loss: 0.9498 | g_loss: 1.6073
Epoch [    6/   10] | d_loss: 1.2224 | g_loss: 0.8815
Epoch [    6/   10] | d_loss: 1.1498 | g_loss: 1.8597
Epoch [    6/   10] | d_loss: 0.8269 | g_loss: 1.3849
Epoch [    6/   10] | d_loss: 0.7504 | g_loss: 1.6326
Epoch [    6/   10] | d_loss: 0.8592 | g_loss: 1.6555
Epoch [    6/   10] | d_loss: 0.6797 | g_loss: 1.3256
Epoch [    6/   10] | d_loss: 0.8772 | g_loss: 1.5870
Epoch [    6/   10] | d_loss: 0.9058 | g_loss: 1.6217
Epoch [    6/   10] | d_loss: 0.9985 | g_loss: 1.7432
Epoch [    6/   10] | d_loss: 0.9535 | g_loss: 1.3984
Epoch [    6/   10] | d_loss: 0.7421 | g_loss: 1.2465
Epoch [    6/   10] | d_loss: 1.5452 | g_loss: 0.9143
Epoch [    6/   10] | d_loss: 0.6878 | g_loss: 1.4565
Epoch [    6/   10] | d_loss: 0.8128 | g_loss: 1.3414
Epoch [    6/   10] | d_loss: 1.3846 | g_loss: 1.2089
Epoch [    6/   10] | d_loss: 1.0770 | g_loss: 1.3348
Epoch [    6/   10] | d_loss: 0.8343 | g_loss: 1.0411
Epoch [    6/   10] | d_loss: 0.8782 | g_loss: 1.3785
Epoch [    6/   10] | d_loss: 1.1747 | g_loss: 1.2391
Epoch [    6/   10] | d_loss: 0.9020 | g_loss: 2.2626
Epoch [    6/   10] | d_loss: 1.3743 | g_loss: 1.7117
Epoch [    6/   10] | d_loss: 0.8960 | g_loss: 1.6793
Epoch [    6/   10] | d_loss: 1.0364 | g_loss: 1.3826
Epoch [    6/   10] | d_loss: 0.6766 | g_loss: 1.5835
Epoch [    6/   10] | d_loss: 1.1201 | g_loss: 1.4891
Epoch [    6/   10] | d_loss: 0.9420 | g_loss: 2.3544
Epoch [    6/   10] | d_loss: 0.9295 | g_loss: 2.2191
Epoch [    6/   10] | d_loss: 0.9367 | g_loss: 1.1741
Epoch [    6/   10] | d_loss: 1.0678 | g_loss: 2.2360
Epoch [    6/   10] | d_loss: 0.7865 | g_loss: 1.8651
Epoch [    6/   10] | d_loss: 0.7456 | g_loss: 1.6748
Epoch [    6/   10] | d_loss: 0.6877 | g_loss: 1.1814
Epoch [    6/   10] | d_loss: 0.3560 | g_loss: 1.8322
Epoch [    6/   10] | d_loss: 0.8674 | g_loss: 1.3155
Epoch [    6/   10] | d_loss: 1.2474 | g_loss: 1.1493
Epoch [    6/   10] | d_loss: 0.8658 | g_loss: 1.2255
Epoch [    6/   10] | d_loss: 0.9295 | g_loss: 2.3097
Epoch [    6/   10] | d_loss: 1.0780 | g_loss: 2.0721
Epoch [    6/   10] | d_loss: 0.9660 | g_loss: 1.4660
Epoch [    6/   10] | d_loss: 0.7842 | g_loss: 1.7807
Epoch [    6/   10] | d_loss: 1.3441 | g_loss: 1.2154
Epoch [    6/   10] | d_loss: 0.9086 | g_loss: 1.5906
Epoch [    6/   10] | d_loss: 1.0733 | g_loss: 1.2473
Epoch [    6/   10] | d_loss: 0.8667 | g_loss: 1.1747
Epoch [    6/   10] | d_loss: 0.6743 | g_loss: 1.1635
Epoch [    6/   10] | d_loss: 0.6016 | g_loss: 1.2532
Epoch [    6/   10] | d_loss: 0.6778 | g_loss: 1.6770
Epoch [    6/   10] | d_loss: 0.6964 | g_loss: 1.4147
Epoch [    6/   10] | d_loss: 0.8879 | g_loss: 1.1162
Epoch [    6/   10] | d_loss: 0.9277 | g_loss: 1.1150
Epoch [    6/   10] | d_loss: 0.8272 | g_loss: 1.6084
Epoch [    6/   10] | d_loss: 0.9620 | g_loss: 1.1511
Epoch [    6/   10] | d_loss: 0.7136 | g_loss: 1.9530
Epoch [    6/   10] | d_loss: 0.8939 | g_loss: 1.4517
Epoch [    6/   10] | d_loss: 0.8514 | g_loss: 1.5137
Epoch [    7/   10] | d_loss: 0.9950 | g_loss: 1.7085
Epoch [    7/   10] | d_loss: 0.9287 | g_loss: 2.1773
Epoch [    7/   10] | d_loss: 0.7813 | g_loss: 1.8661
Epoch [    7/   10] | d_loss: 1.1107 | g_loss: 0.6544
Epoch [    7/   10] | d_loss: 0.8498 | g_loss: 1.8624
Epoch [    7/   10] | d_loss: 0.8897 | g_loss: 1.8839
Epoch [    7/   10] | d_loss: 1.0700 | g_loss: 1.1354
Epoch [    7/   10] | d_loss: 0.7729 | g_loss: 1.5638
Epoch [    7/   10] | d_loss: 0.8050 | g_loss: 2.0349
Epoch [    7/   10] | d_loss: 0.8528 | g_loss: 2.1058
Epoch [    7/   10] | d_loss: 0.9546 | g_loss: 1.7568
Epoch [    7/   10] | d_loss: 0.5409 | g_loss: 1.3425
Epoch [    7/   10] | d_loss: 1.0023 | g_loss: 1.8573
Epoch [    7/   10] | d_loss: 0.9340 | g_loss: 1.4199
Epoch [    7/   10] | d_loss: 0.6562 | g_loss: 1.5254
Epoch [    7/   10] | d_loss: 0.8498 | g_loss: 1.3551
Epoch [    7/   10] | d_loss: 0.6525 | g_loss: 1.6529
Epoch [    7/   10] | d_loss: 0.7617 | g_loss: 1.3288
Epoch [    7/   10] | d_loss: 0.8005 | g_loss: 1.9091
Epoch [    7/   10] | d_loss: 1.0216 | g_loss: 1.5208
Epoch [    7/   10] | d_loss: 0.9260 | g_loss: 2.0798
Epoch [    7/   10] | d_loss: 0.8988 | g_loss: 1.8071
Epoch [    7/   10] | d_loss: 0.7422 | g_loss: 1.5049
Epoch [    7/   10] | d_loss: 1.0057 | g_loss: 1.6525
Epoch [    7/   10] | d_loss: 0.8553 | g_loss: 1.6432
Epoch [    7/   10] | d_loss: 0.8638 | g_loss: 1.2550
Epoch [    7/   10] | d_loss: 0.7366 | g_loss: 1.4042
Epoch [    7/   10] | d_loss: 1.0356 | g_loss: 1.7033
Epoch [    7/   10] | d_loss: 0.8812 | g_loss: 1.8713
Epoch [    7/   10] | d_loss: 0.7378 | g_loss: 2.1435
Epoch [    7/   10] | d_loss: 0.8578 | g_loss: 1.5956
Epoch [    7/   10] | d_loss: 0.8693 | g_loss: 1.3741
Epoch [    7/   10] | d_loss: 1.2007 | g_loss: 2.4855
Epoch [    7/   10] | d_loss: 1.0918 | g_loss: 2.9054
Epoch [    7/   10] | d_loss: 0.7359 | g_loss: 1.5343
Epoch [    7/   10] | d_loss: 0.9351 | g_loss: 1.8618
Epoch [    7/   10] | d_loss: 0.8419 | g_loss: 1.4335
Epoch [    7/   10] | d_loss: 0.7724 | g_loss: 2.0118
Epoch [    7/   10] | d_loss: 0.7322 | g_loss: 1.5820
Epoch [    7/   10] | d_loss: 1.0574 | g_loss: 1.6330
Epoch [    7/   10] | d_loss: 0.6907 | g_loss: 2.9629
Epoch [    7/   10] | d_loss: 0.8247 | g_loss: 2.4058
Epoch [    7/   10] | d_loss: 1.2070 | g_loss: 1.7138
Epoch [    7/   10] | d_loss: 0.7545 | g_loss: 1.6471
Epoch [    7/   10] | d_loss: 0.8849 | g_loss: 1.4283
Epoch [    7/   10] | d_loss: 0.7031 | g_loss: 2.4208
Epoch [    7/   10] | d_loss: 0.9178 | g_loss: 1.4827
Epoch [    7/   10] | d_loss: 0.8107 | g_loss: 1.7935
Epoch [    7/   10] | d_loss: 0.5231 | g_loss: 1.2382
Epoch [    7/   10] | d_loss: 0.6817 | g_loss: 1.1917
Epoch [    7/   10] | d_loss: 1.4161 | g_loss: 1.3589
Epoch [    7/   10] | d_loss: 0.6274 | g_loss: 1.3462
Epoch [    7/   10] | d_loss: 0.9774 | g_loss: 2.4388
Epoch [    7/   10] | d_loss: 1.1318 | g_loss: 1.4239
Epoch [    7/   10] | d_loss: 0.7300 | g_loss: 1.6497
Epoch [    7/   10] | d_loss: 0.7751 | g_loss: 1.3902
Epoch [    7/   10] | d_loss: 1.0998 | g_loss: 1.1524
Epoch [    8/   10] | d_loss: 0.7745 | g_loss: 1.5589
Epoch [    8/   10] | d_loss: 0.1952 | g_loss: 1.9528
Epoch [    8/   10] | d_loss: 1.0934 | g_loss: 1.1611
Epoch [    8/   10] | d_loss: 0.8223 | g_loss: 1.8281
Epoch [    8/   10] | d_loss: 0.8327 | g_loss: 2.4211
Epoch [    8/   10] | d_loss: 0.8277 | g_loss: 1.6745
Epoch [    8/   10] | d_loss: 1.1834 | g_loss: 2.1495
Epoch [    8/   10] | d_loss: 0.7629 | g_loss: 1.4752
Epoch [    8/   10] | d_loss: 0.8736 | g_loss: 1.9731
Epoch [    8/   10] | d_loss: 0.8836 | g_loss: 1.4550
Epoch [    8/   10] | d_loss: 0.8790 | g_loss: 1.1930
Epoch [    8/   10] | d_loss: 0.8168 | g_loss: 1.9565
Epoch [    8/   10] | d_loss: 0.8133 | g_loss: 1.8801
Epoch [    8/   10] | d_loss: 0.2667 | g_loss: 2.1719
Epoch [    8/   10] | d_loss: 0.7185 | g_loss: 1.4855
Epoch [    8/   10] | d_loss: 0.5988 | g_loss: 1.3800
Epoch [    8/   10] | d_loss: 0.7131 | g_loss: 1.4776
Epoch [    8/   10] | d_loss: 1.1290 | g_loss: 2.0439
Epoch [    8/   10] | d_loss: 0.9157 | g_loss: 1.6766
Epoch [    8/   10] | d_loss: 0.6994 | g_loss: 1.5884
Epoch [    8/   10] | d_loss: 0.4760 | g_loss: 1.9336
Epoch [    8/   10] | d_loss: 0.6372 | g_loss: 2.3007
Epoch [    8/   10] | d_loss: 0.5169 | g_loss: 2.1046
Epoch [    8/   10] | d_loss: 0.8687 | g_loss: 1.3191
Epoch [    8/   10] | d_loss: 0.7539 | g_loss: 1.4657
Epoch [    8/   10] | d_loss: 0.3068 | g_loss: 1.2879
Epoch [    8/   10] | d_loss: 0.7193 | g_loss: 2.0689
Epoch [    8/   10] | d_loss: 0.7747 | g_loss: 1.6881
Epoch [    8/   10] | d_loss: 1.6385 | g_loss: 2.6038
Epoch [    8/   10] | d_loss: 1.5554 | g_loss: 2.4991
Epoch [    8/   10] | d_loss: 0.8029 | g_loss: 2.2890
Epoch [    8/   10] | d_loss: 0.6814 | g_loss: 1.6492
Epoch [    8/   10] | d_loss: 0.8288 | g_loss: 2.4414
Epoch [    8/   10] | d_loss: 0.4880 | g_loss: 1.8276
Epoch [    8/   10] | d_loss: 0.8490 | g_loss: 1.3677
Epoch [    8/   10] | d_loss: 0.8064 | g_loss: 2.3894
Epoch [    8/   10] | d_loss: 0.6612 | g_loss: 1.3483
Epoch [    8/   10] | d_loss: 0.7024 | g_loss: 1.6808
Epoch [    8/   10] | d_loss: 0.6852 | g_loss: 1.8108
Epoch [    8/   10] | d_loss: 0.7538 | g_loss: 1.6399
Epoch [    8/   10] | d_loss: 0.9763 | g_loss: 2.1361
Epoch [    8/   10] | d_loss: 0.6160 | g_loss: 1.1456
Epoch [    8/   10] | d_loss: 1.0292 | g_loss: 2.2477
Epoch [    8/   10] | d_loss: 0.5138 | g_loss: 1.5593
Epoch [    8/   10] | d_loss: 0.9537 | g_loss: 1.0961
Epoch [    8/   10] | d_loss: 1.6807 | g_loss: 1.8236
Epoch [    8/   10] | d_loss: 0.5930 | g_loss: 1.4105
Epoch [    8/   10] | d_loss: 0.8762 | g_loss: 2.4777
Epoch [    8/   10] | d_loss: 0.6632 | g_loss: 1.4510
Epoch [    8/   10] | d_loss: 0.8326 | g_loss: 1.5180
Epoch [    8/   10] | d_loss: 0.3520 | g_loss: 2.1456
Epoch [    8/   10] | d_loss: 0.6256 | g_loss: 1.4085
Epoch [    8/   10] | d_loss: 0.5971 | g_loss: 2.1319
Epoch [    8/   10] | d_loss: 1.0908 | g_loss: 1.3454
Epoch [    8/   10] | d_loss: 1.0792 | g_loss: 1.7968
Epoch [    8/   10] | d_loss: 0.3675 | g_loss: 1.3708
Epoch [    8/   10] | d_loss: 0.8855 | g_loss: 1.9242
Epoch [    9/   10] | d_loss: 0.8582 | g_loss: 1.8080
Epoch [    9/   10] | d_loss: 1.0906 | g_loss: 0.8233
Epoch [    9/   10] | d_loss: 0.8165 | g_loss: 1.8305
Epoch [    9/   10] | d_loss: 0.7189 | g_loss: 1.9374
Epoch [    9/   10] | d_loss: 0.9483 | g_loss: 1.3720
Epoch [    9/   10] | d_loss: 0.8272 | g_loss: 2.7734
Epoch [    9/   10] | d_loss: 0.9631 | g_loss: 2.1053
Epoch [    9/   10] | d_loss: 0.8194 | g_loss: 1.0109
Epoch [    9/   10] | d_loss: 1.0263 | g_loss: 2.2061
Epoch [    9/   10] | d_loss: 1.3690 | g_loss: 1.9282
Epoch [    9/   10] | d_loss: 0.9142 | g_loss: 2.4545
Epoch [    9/   10] | d_loss: 0.6179 | g_loss: 2.5223
Epoch [    9/   10] | d_loss: 0.9032 | g_loss: 1.8190
Epoch [    9/   10] | d_loss: 0.7020 | g_loss: 1.6692
Epoch [    9/   10] | d_loss: 0.9132 | g_loss: 3.0190
Epoch [    9/   10] | d_loss: 1.2050 | g_loss: 0.8040
Epoch [    9/   10] | d_loss: 1.3123 | g_loss: 1.3175
Epoch [    9/   10] | d_loss: 0.5235 | g_loss: 1.3961
Epoch [    9/   10] | d_loss: 0.6413 | g_loss: 1.1841
Epoch [    9/   10] | d_loss: 0.7089 | g_loss: 2.2832
Epoch [    9/   10] | d_loss: 0.4798 | g_loss: 1.8185
Epoch [    9/   10] | d_loss: 0.6547 | g_loss: 2.2993
Epoch [    9/   10] | d_loss: 0.6486 | g_loss: 2.1101
Epoch [    9/   10] | d_loss: 1.0110 | g_loss: 1.1867
Epoch [    9/   10] | d_loss: 0.6927 | g_loss: 2.3921
Epoch [    9/   10] | d_loss: 1.0454 | g_loss: 2.8139
Epoch [    9/   10] | d_loss: 0.8775 | g_loss: 1.8296
Epoch [    9/   10] | d_loss: 0.7870 | g_loss: 0.9418
Epoch [    9/   10] | d_loss: 0.5527 | g_loss: 1.2854
Epoch [    9/   10] | d_loss: 0.7547 | g_loss: 2.0989
Epoch [    9/   10] | d_loss: 1.0063 | g_loss: 1.7112
Epoch [    9/   10] | d_loss: 0.7901 | g_loss: 2.8272
Epoch [    9/   10] | d_loss: 1.0376 | g_loss: 2.8343
Epoch [    9/   10] | d_loss: 0.7076 | g_loss: 2.8025
Epoch [    9/   10] | d_loss: 1.0767 | g_loss: 1.5289
Epoch [    9/   10] | d_loss: 0.8325 | g_loss: 1.8515
Epoch [    9/   10] | d_loss: 0.8334 | g_loss: 1.2393
Epoch [    9/   10] | d_loss: 0.6612 | g_loss: 1.6938
Epoch [    9/   10] | d_loss: 0.6454 | g_loss: 2.1059
Epoch [    9/   10] | d_loss: 0.6009 | g_loss: 1.5501
Epoch [    9/   10] | d_loss: 0.8743 | g_loss: 1.5529
Epoch [    9/   10] | d_loss: 0.7675 | g_loss: 2.4249
Epoch [    9/   10] | d_loss: 0.6334 | g_loss: 1.9434
Epoch [    9/   10] | d_loss: 0.8969 | g_loss: 1.2922
Epoch [    9/   10] | d_loss: 0.8360 | g_loss: 2.8245
Epoch [    9/   10] | d_loss: 1.0424 | g_loss: 1.2922
Epoch [    9/   10] | d_loss: 0.6925 | g_loss: 2.6687
Epoch [    9/   10] | d_loss: 1.0750 | g_loss: 2.3688
Epoch [    9/   10] | d_loss: 0.7650 | g_loss: 1.4822
Epoch [    9/   10] | d_loss: 0.9950 | g_loss: 2.1560
Epoch [    9/   10] | d_loss: 0.8557 | g_loss: 1.8940
Epoch [    9/   10] | d_loss: 1.2208 | g_loss: 3.3154
Epoch [    9/   10] | d_loss: 0.6318 | g_loss: 2.0889
Epoch [    9/   10] | d_loss: 0.8469 | g_loss: 2.0965
Epoch [    9/   10] | d_loss: 0.6971 | g_loss: 2.3272
Epoch [    9/   10] | d_loss: 0.7308 | g_loss: 1.9045
Epoch [    9/   10] | d_loss: 0.8270 | g_loss: 1.4362
Epoch [   10/   10] | d_loss: 0.7514 | g_loss: 1.5187
Epoch [   10/   10] | d_loss: 1.1633 | g_loss: 1.8709
Epoch [   10/   10] | d_loss: 0.5354 | g_loss: 1.9439
Epoch [   10/   10] | d_loss: 0.9974 | g_loss: 1.3070
Epoch [   10/   10] | d_loss: 0.5353 | g_loss: 1.0999
Epoch [   10/   10] | d_loss: 0.5676 | g_loss: 1.5242
Epoch [   10/   10] | d_loss: 0.7240 | g_loss: 1.8447
Epoch [   10/   10] | d_loss: 0.7954 | g_loss: 2.3823
Epoch [   10/   10] | d_loss: 0.7488 | g_loss: 1.7309
Epoch [   10/   10] | d_loss: 0.9576 | g_loss: 2.1633
Epoch [   10/   10] | d_loss: 0.6013 | g_loss: 1.5894
Epoch [   10/   10] | d_loss: 0.6339 | g_loss: 2.2795
Epoch [   10/   10] | d_loss: 0.8208 | g_loss: 1.4850
Epoch [   10/   10] | d_loss: 0.9465 | g_loss: 2.1939
Epoch [   10/   10] | d_loss: 0.5797 | g_loss: 2.6370
Epoch [   10/   10] | d_loss: 1.2278 | g_loss: 2.4698
Epoch [   10/   10] | d_loss: 0.6971 | g_loss: 2.2442
Epoch [   10/   10] | d_loss: 0.8793 | g_loss: 1.4431
Epoch [   10/   10] | d_loss: 0.7058 | g_loss: 1.8931
Epoch [   10/   10] | d_loss: 0.6888 | g_loss: 1.9359
Epoch [   10/   10] | d_loss: 0.6826 | g_loss: 1.9103
Epoch [   10/   10] | d_loss: 0.3129 | g_loss: 3.3168
Epoch [   10/   10] | d_loss: 0.9475 | g_loss: 1.6362
Epoch [   10/   10] | d_loss: 0.8743 | g_loss: 2.2536
Epoch [   10/   10] | d_loss: 0.7464 | g_loss: 2.6127
Epoch [   10/   10] | d_loss: 0.6762 | g_loss: 2.0413
Epoch [   10/   10] | d_loss: 0.4293 | g_loss: 2.3299
Epoch [   10/   10] | d_loss: 0.9826 | g_loss: 1.9518
Epoch [   10/   10] | d_loss: 0.8323 | g_loss: 2.4976
Epoch [   10/   10] | d_loss: 0.5863 | g_loss: 2.6466
Epoch [   10/   10] | d_loss: 0.7563 | g_loss: 1.9813
Epoch [   10/   10] | d_loss: 0.6710 | g_loss: 1.6453
Epoch [   10/   10] | d_loss: 0.7930 | g_loss: 2.3644
Epoch [   10/   10] | d_loss: 0.8080 | g_loss: 1.8537
Epoch [   10/   10] | d_loss: 0.8347 | g_loss: 3.4878
Epoch [   10/   10] | d_loss: 1.2580 | g_loss: 1.5513
Epoch [   10/   10] | d_loss: 0.7526 | g_loss: 1.4803
Epoch [   10/   10] | d_loss: 0.6357 | g_loss: 1.8403
Epoch [   10/   10] | d_loss: 0.7628 | g_loss: 2.2734
Epoch [   10/   10] | d_loss: 1.1632 | g_loss: 1.3058
Epoch [   10/   10] | d_loss: 1.2032 | g_loss: 2.4284
Epoch [   10/   10] | d_loss: 0.4442 | g_loss: 2.0361
Epoch [   10/   10] | d_loss: 0.7586 | g_loss: 1.5800
Epoch [   10/   10] | d_loss: 1.0770 | g_loss: 2.1147
Epoch [   10/   10] | d_loss: 0.5621 | g_loss: 2.3573
Epoch [   10/   10] | d_loss: 0.6883 | g_loss: 2.2031
Epoch [   10/   10] | d_loss: 0.6806 | g_loss: 1.2756
Epoch [   10/   10] | d_loss: 0.8227 | g_loss: 1.6562
Epoch [   10/   10] | d_loss: 1.0561 | g_loss: 2.3412
Epoch [   10/   10] | d_loss: 0.6667 | g_loss: 2.1279
Epoch [   10/   10] | d_loss: 0.7123 | g_loss: 2.4858
Epoch [   10/   10] | d_loss: 0.9022 | g_loss: 2.6269
Epoch [   10/   10] | d_loss: 0.7500 | g_loss: 2.1928
Epoch [   10/   10] | d_loss: 0.7724 | g_loss: 1.8066
Epoch [   10/   10] | d_loss: 1.0985 | g_loss: 2.2414
Epoch [   10/   10] | d_loss: 0.7816 | g_loss: 2.3334
Epoch [   10/   10] | d_loss: 0.6751 | g_loss: 1.8605
</pre>
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<h2 id="Training-loss">Training loss<a class="anchor-link" href="#Training-loss">&#182;</a></h2><p>Plot the training losses for the generator and discriminator, recorded after each epoch.</p>

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<div class="prompt input_prompt">In&nbsp;[22]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
<span class="n">losses</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">losses</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">losses</span><span class="o">.</span><span class="n">T</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Discriminator&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">losses</span><span class="o">.</span><span class="n">T</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Generator&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Training Losses&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
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<pre>&lt;matplotlib.legend.Legend at 0x7f8c654567f0&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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+JeBdzf6yXcNGe653JCx+z7U12V7uLV18455yYYJ68Wr7bpWaH3aTGm1Bh715jjYCbscrQNzgwZxnCP/0lxVIfjuUO/Wnd46F2clo7a+toKecyQdmgvs5XmOAcnb67jGnTU+VJIbY1xsgXGXN9xooXjaLzTMvR7ywfv0rDJ+ypVufRb5W8OJ9nyRmu+xbkw5qpWey3Waq/ZYIC0+m8f64l8ov7LtbHHmodzT9qdPxkA+Y5QR1GEsR/jcQ/zQMBgN4f76xnmygkiLcRANQPqMdLruRRzYgpHX65Rm2hf61Xnoq6PxVjbc90ccJRgmKLdYzwKcOpfFPg9Aof3isauKF8e92B/TPPv/g2ynR7pCHvHDZ2Yq67J8R4BgwZd7u+s2eFgX63V14iXM7xCjvLzLRFdlqXbWbYjaTKZTCaTyWQymUymnWQ/JE0mk8lkMplMJpPJtJN2RlurDp0pM301wRZpkgNxxDZtfSH3s3D5bpue9oTF0P2srbTFHgOTumNfROsvBOPkFrO/RbOICiDQN1Evuql5WlwC+Xh0JKQn+ytd8vWXYu+Wa+EEo5HQyjYiJgasjMFOkYes2c/vfO+Dizr30wZoRwPUqoFTa0kHTjibJQ0cu7DFXjQqu6IUItIi2G1C7OlEToOPp8IcHz0RUjzIN4hI3Ne9QR25YSKEJJ8Kea0QwHZeqA2uKqFcNdxk1w0C9QIVLIC3LG6AZcJlM4fjVjzUfZJ6TwGXvXOuay8xsWnUY5YKsynoVglkMQX39PBY5fjTj4WzfvDsg216OoCjHOqANEULZ7yWXTZs+nWD/loWKqvME7mByxrQjpWTY2J5pfeYFRozGrwf0aQKzr0BmR/CbZL5bTzRlf0EXHbeO3+L4wDXaYj3oXBr9J0SLoIMWuzRH++ML8AT6bTcwvWaiHYDvCehk3O8SbccP4FwJ8CMWwaqvoP/ADkGitsUdEjWV1cYV7/8Qo7Ztfv32/R8rvHml38uN9ce0LM028+4GlxwdYdP9eH06NCOcziQj0caO4aHwk1P33+6TU+Alr7ELUcILl6uhVkew6m1QfB6Vyg9Gis9nWxuejCFiyDGAEfDacxH73/4Yps+eqA58fxKeamA395cK3g7A9MTxYWpovNwGkxjzT+rUvd/A9f0+5V3Tdeur1fCqZdLtb8bBKl37AMofx8QuB3YakWkDE3RY30QY31Al9U58LWqRh66IydzoKRL4nvAJz0w+RXm+RbvN1vhcz3lDkrP8f4GR0sC0XEGZMeAUwEzHGRw6L1HtT64opuHiIdWHq6UaH/zFY5J4OjRYqkxpanVT12Mo1hYl2aR2u4Q6RrXcHhI0DZuEdJ6hHLDnJARbcXnd6hSrpcLuCVjPXNzBadW3r+nd+pj7isxhOd8bqLrQ7W72+f3UQhhux6NeKQOr5nx+AZw0+EIWCf65hDz0w1cSm+WWiu0QF4TlEXE+SwhZgou9vYSHrMDztzDe6Q4Xteifkv09RJ9OeV4w6NeyFeJuqhQNtEYYzvGBB5FyZLdUXPbkTSZTCaTyWQymUwm006yH5Imk8lkMplMJpPJZNpJu6GtDu6nBbiGPraPsZVPPHI+U7D2ACwkh0skcVYPx8xAhgJOYTGCrXsGZ+Xnt3vMRObu/HwmbgDsCjaGEfAxBtc+nAq9bB/rmReXwCYRFNjBnYzPIhoT47d9kjOC/P0pBOeqDoWpgJu6QvlosWUesGUfrenMScwGrouoo6oUTnEwERby6KnK7s9+9P42PRlq632MIN39ww2aRjxgQMdQtJecweWBI/YrlefsWnj1uzkc6uguvFTer2+EVJVwPyuBPRcrYjJos3tCPpxzLur6I13AMrh04XVcu2RQdvQRkBqPByrH9x/JnfUYDpgJ6iBO2GYQWLrF0ALksak3n1ep2l0OlCIlMo+8fAzUqJqjDZaqxxIoHZHMGDjheqUx5gp16vHczAu14tAT9vR3Nx+8i8Mmj3eCEIPdYcDvFu0vAGP2dKZGcHfGI3ZASEHruAS4G93tIuDQsafr3Ob6EANzAvoY6NyItnnHHha8VKDzJdpOIO4HHuzmAi6jJZ0q9bIHQFg/+OnH23QCDP5eFdwWleP8kWNuyoA6nRwK438C59MaY8piLhy/gpPmBCjy8FROx8OR0ks4ol9/q/Swp3I57m2OFUwQcLwdqTxjHE85muqYxtHj9/ROcCZfz5T3945VX/1I9/z6tfrsN3A7X6HN1sijL4GBAd0MjcrmPlU3lTvvnOXLa40ROdx3K2DnOVwiK+QvSnHkJyMiDwdIDJMD3Ccj+win9HpNZFyX9LobHee6xyTW/NjQlRH94uJC7zcD2pneccfH3EpHzJHGySmQyBqo5pr8IYPD69M7be9eFZyruwmwBk6d4ekVj/A0mhuqhdIBdb2Y6/M1+mb6SOsZovM8qpQCCaU7d3PnxETovgc803G+RZtCXdweVXLOuRZrMeLVyxXGWEQlqDHnOKz1UiCRSywk/BrrVTzX7/Zz4vsrBFd3KCrrK6HnMZxkWb90Nm4xP/I43hGOQrVASAu01ztHQoglA93m8ZOsWyP1ezi2gz497uGoAdb5Rat10eWZkOqLNY76YeJmhIRepPtcLVVOK5RBDVvaGHMllwjuT3Cntx1Jk8lkMplMJpPJZDLtJPshaTKZTCaTyWQymUymnbTTXrR3wkLbOwGXsdUKbrS+0VZvdSWcJW+BDZTaVG2BX0RES7GFHUgJNtiC9XAwWzOo/OYaj63pNsX2LlAjuo1FDAwKpCUA1WyBmeSpXB97B0RgiBAC2ULePbA9BkyP9/Q7P4TGlR3awOCmDdwgW6SJDbcpA5ADZcTnZSlsggjvFAjBRy/kTPj+k0e65kg45eGB0C/fOW7RkZdExh3sEJjNEPXeKxC4e4rgw0AIiqVwlfVM9TgH4sQgvyVRkET3b+Zoj3D/uk8FF1zZYYh3cBoEkHbAXMqWAWuVp+lICNSTJw/0+VDlnwI/YqBrH/G5SN8xAQUq1zndRUBL2lj5itFHEqd69Ie69+ojOK6hESzRZi+ArSbAIxvgZqtKddSHq2X7R5zYqj25KDunwOR0kW6AwtCRlQHQAwo6DcTigUDh/enQdycaOq6hA2AMJ7hQAM3q+lXA2B/1gBRVxFzhQAlEqt/HuwKHS3pAa/GuNNJucf/rher6q6/knj051BcenApnTRuNPfepENot4t+Hm/MS8xE5tjgXGngMp9aLC82VPeBY8zeYN4ELH4009xw9frhNn880lpWXOlpyNNUY+977z//f2XLxCbCvI+CpY31vcIxjHfqqO3EaMypgYtOJ5vnpWJh8L3u1Tb/DcYqLNeYTvGuJ+Xq0JxPlqq7cm7ONM3TA+Dkk0g9cvyVuCASdAeNzoK0JEPEc6GMPc2gf6yseH4hxRGcwUPpwOOqeA7dwIKkt5sHFSvjceV/XnGOOu8ExgRj8LY8Fcew/HGqsvgaafQEXTI/8EPVlGdyngmtd6BaMEeaJEjh+iroLQFsXjdYEHJNXWPNcoRxDTsQTa1d0jojRBDDHeLQZdzuekjZlu9DHLsE83yOa3mh9EoDoxrWev8Z3mxbzYJ9tXM+ii3CD+byF+2nc7ucolo/81ln+DhI6UL2MEIkhBd7dQ9sqa5VFhn5S47dG1ofzONDhAkf52AemOJrHo1a97ngVHuMSzOeHA11Lx9+aR09KOjAr7+ThPc/e0J0V/O3rBY6gAfGOUiDldBcudo8yYDuSJpPJZDKZTCaTyWTaSfZD0mQymUwmk8lkMplMO2k3myUvNCqqsAU7ZJBaba8WBZwur4TWJHD7DNgNj+CIyoDpdAdloFhfVN99PemtDmNNHfEMoAR0FITDGN0IiR4UjtvQCOi5Ek7Qg/tcQ/dTukkhYHuD4OEBWEi0JxOstg2u7Bw8PdEOYHwFnBCzmvWLvAKTa2kPCixmMhF29eGhcKhf/lQB7h8cyw2wPxUaFQFX8N32PzGbhJZ3qdAaR8QUaFxVwh3rqcr5dC5Epfzs99v0VXWp78Ltc11h659NcAKntUz4Vp3vjgp8LwXnbg0APRDEptG7rYjfwL2L7pHPhqqjpw+VTuC0GGXom+hfDbAfYtmeRnzAuG9RamI2cQTXNIwBKfppH9jMwwMhdh89UtnO6aiH4No1+i+zVcNZt5rpPikwrRrutnf6770qbANmByD1DETNcSRiQOIGjrdE0IC2xCjTO59zvMP4GTHgNBF/4HyhywOdXGNOJ0CKWG4p0LwSGE8fdV3cGTPp8gr3U2BiDdrXzbkCyH/1OwWs/+rhp9u0/3g/AdBdcO6WHicCVwGr65+qjEZj9bWDTGNgewW3vjdvtumrt5pP+0CaGNA8h+PwCY4SlAe6/hho68GjjVssg8XPgdyuzvXM4aEcYROMsR4upG1fnyOmvUvosD3G2HuEfgoMb+3UH6tKbcbjWEoT9nT0o23derHB/VK6a+I9PV1YMe6NDvSedwK3Y24doKwHQO3HQPJGfY13Y5T1aKz7H02Ea08eb+oma74bZ52dyx33qtAzHx2qjawbtYuzM819n7/Rd+eXwiCzTN/NenruBA6aF5dqyxFQwQEw1ywmHH2PCs7dnuAo4Hzbx1JlBnywmuPYEhzYE4xHNRzDF4nereKRJLiExxn7CcbPBG0J47Dv1hZciyU47lHfGadV/mlPzskt1k0Z1i0u1/WTUvXYnOmaZqZ0Cgf9sNT1wRMHxnGW3l3vz/tS5L0bZZt3GmK9egzU/PBQ7//4QOn+gcayGI6lr6+F/Z99o/Z9ijIaTPTdHo8OYRlweKj+OGa0gI5/TXH8bYSoBfEfcw7G0b11prqYob+sWq4ReMwF+DE+T7AeJKKbD3E8Mecxk93XObYjaTKZTCaTyWQymUymnWQ/JE0mk8lkMplMJpPJtJN2dG31W2fKgK3WuiL6iYDuwD0dXKLCGoFcK7pHkUkF4gmkyRM1o+MoPo/v2Hl2W+GwT4rw+9kHIrR6ZgC6W9O9CuhpWcMBKSK+p/3pBMG1KwYFdnQ1JCKqZ9ULYYn3qTa0bl5usIwMsB8R3hSoZMKI5tgyb3G9B86a94UHvP9Ujqx/+Zd/uU0/e/6+nsXIykCHiUpGHU+Q4bM8RuB4BGN1Kd3DVP4zYCGjoQr6w48UrHw0Es7R/0w43DqoLoatrmlQBk2DQPFAsEexkIb7lPfCn+l4vFgzCDGcHlHMRyOht6ePhDRNRiq7BGiUAx7hiD5ErKP4O6+JkDd/28fhEtYG9d2UToP8HEjLGM5yjx8ID5zNhd5dz4XkXcM5sAV2VMMCusbYU+K5DGL8JxAf30vBOVdHt6ioPmfQczokerrywv2PDtRMe6RTBla+062JLmNswueBBdBhrh7jGIM205W38XwPYIr43AE7J77YVjhKQMwV/Y7uei0w17MrIUuf/UGYa9RTm7lPBacxnq+WwRnzCM6nj997tk0na6FjPQdH6aB3CAkCpqMzz+A+PGnU1gc4SjAZ68hAPta46bt2FwGxbCrwVcAwk4yB6Ym3KZ3h+S5l3eFYAebiXqy5Ikn0HsSrp1NdPwR2G93AGfs+5f32yAdxRA9cmw6MGVzCT+CgO+mr7G4W59v0AP3xFGjcg4Gun8BJe4r2OhpOtunxVOnh8WZOajBm0DGec3g6lytwxPkLR3ViHLcB0e6+uYPk6fObSm2TQc9Bxt9xCm8QAn29phX//Sl456p488wY4/gaa8sWc8ASa7u7azXlexTDyb3Uyy2AfsbHck7miRsHrJ9RDxqsnW6PPJUozxZrmDQgjTVM1tN83sB1s5dqrdLrYT51colusXaeza+36eVKaW45hQAEGOvbZr2n/ugUdaH9Iy75D4d6/2McfTkcqwI4D02wznt2IKd6ajrW/eMRyh1HhJZw8K/hYHv72yQdaLw6ANrKY3QL4OhzOKwOgJuOBvidhCgAjAeQArfnurRqUF/ov7VT22+ASYfI0FaTyWQymUwmk8lkMu1Z9kPSZDKZTCaTyWQymUw7aTe0NfIuusVbQBlFYB8a4BQVEAKPLWB+HgF/9Yj0mcDJi86ugQZfCALrKjpiMdhrlwCq6YFCOSBzdARtaE0JVCMCDxZVdGUDPlcgYOsdYuy7sUHiYQwM3QZuXN+fQhtc3bk31QUvIzaTAAAgAElEQVRc2IjuAHmNgbcVa+AR2ALvAzli0Ni//OXPt+kf/eTFNj2BU2iJSq3vOGO2/zCdI0g70KkYbltxTvQPqOQKuM4hnA4zXT9AkNsJcAYPR72zS2GTtRc2cHMpDK0FmtLr7SdQrwvOxZ3z5WyhelwjAHoAQjHOVEePj4R2vP9MKE4PbrMeddEyIDHdC9GVGMCYIhJ2a2bJgMyu+W5sk8F2kx6cV+EGeXisez9HHt/NhOV8+VplUKA8WuBVRGaKFdxq8U5pvqd6dG47njYo8wSulB7jTgPH5xgOehn6UQJEPAUik2OMw8d3zKtrBOYOKCMHZD/qnARrINwpsNVAvA1IbMljAsCi4lzjZ4o6KisENKd7NN6V4+cQgbnpqPzq86+36RHw0vvWbTlmcFo8HatPnQBHjEs4k0ZKlxEcwDFFTxP13yVQutUcSBOwqwTz8uhEeegdqu/fnG/6SUAA9hpOz304y8Z3bMSJ9ONYCfpv2uPxCOBYQYjXGONQb63nHqCrrTA+nAyRh+yPDDj/SHmnIOEtnOHjXM+L0L966IOc+56f6t0wZbh4rrp72BfCejqmOyvKCNeMjtR+cjpSTm7zC/Sv0JzYx72Hqmq3vJI76+yd+v0RjjhkubDostYY8Oat2uwC71SgzUZc6wHhi3D8yP+xieMfqdC0rlhs8khcO8O6aj3DOIXvNshfStdpoIop1qvLa4yZL+isqnKMIvYBuG1iTXM7rgWMB6sbVdiaxxTg4FthzHY48hWnmM8xlOeY2Kbt6TZdfKP2XixQNhhWh8Dq18Bi897uSOT3UeQjl3cY6wA/PPo47tHDy6X4PAb+Os5xjA3O7P1HmBNzlWkGPHSFuS8ACe0D029guXobvYJr5Amw9BJjHeepcqW8DFI4wg7hFowjdQHHcCocSaFbf12jPfIoEo6fkJGNk93XObYjaTKZTCaTyWQymUymnWQ/JE0mk8lkMplMJpPJtJN2dG11Lu8wjghcVB98WwEkICu13b46xLb3KyGAZQPXtiG3VIExrbSV6+84tWLLFqhcYJD4buc5AvJT50BVwVoxgG+DYKcVnUqBajgEYG3mdKvTs1Y3wpTivjCD4GDnhS13j7zHYU/IRwiuqDd1E935WwKcHoEHrICpMdj9EG5yB3DBevhA6NiLj/9smx4hELbD/VMgaw0cwQLdIzuMJEG5+QTpFCguMNs7jrPAA5NY16fA4UZLXTOh49ZYAcN/9/KzbfrqSgHD3yHI8NkbBPlt9uNK14bWzdeb9gWTvTto7wH66YtncnH82TO56Z6e6vMUiHAAwlLRLQ1WdKwjB2fGKAOaDhc537kx1is4nKHvtiWRJ2KuwHX6umbgEIC9FIL1/lO5Al+hb87RlsuAOmKgZ2D1oFvuOEbfp0IIrugCUeeRyrYFMkcjtYRIN91c6bQIlL8Hl9sBUBwYY7oGQZFrjIke9V7jWXWHu6dw9WxRhgxUTRS6JdGMcbKFNXYLFPqOgxzGXo79AS/SAsNPB+rXV7XawMuX37r9KGzPUvRGQhNz5GM0BJrWCgesgfMWhdolXaoTBpkGopzewbqUm7TUc48mcKrFPYv5xk20BWY7PtFYNxojKDm+Vy3VXpqE51zwfOQrQkDvshZ2Pobb5MMTjAlLXROj37VAqbMlcL77lPcu7ub/GthuoKUy2noJ3K6NdH0E/Pfxgcp/Hev6A7hK9tCvc9R1nglx609UH1y9xV3BB0+0GPMncLj8EA6+AyC6wFmXbxGAfq73GI803r670T37a32Xx3kSoIJ0/a3pho1jSfeptm3cctkxxXD+XwP5rlEuHshijvbKY1wpxthjzJs8ZlWu4eSJdQktuWky7zCWpd2arwFL2mTKY7ES5npzhaNSQDh7cGRPsf7hEYAWxxASrJdGUzmfX77TOt0hikGMsuF8TYfv+1Vwzm/q5gDurI8eqC+cnCh9OFVfG2CN7jF2DIGg9zKN1Tjl5Gq4o7YrtJ81HKVxRGvV4phe96wYR6u4Juq1qq8Kc1wVhJqv+ZsG61WXaIxZoV6WONK0wHwSA8HmfJr0cCTijkM/j5R9P9mOpMlkMplMJpPJZDKZdpL9kDSZTCaTyWQymUwm007aDW31zuXdTnFCpApoUVgCg8Ru6SgSTrFw2p7PsN27uIGD2Bttqw+BMGZTbW1HCACajuAYiOdmnTtVBRfNxZdw3VzqPa6BsVyu9fwEjmeDYwUvHQ61JY4dbJc0wCkzZeZ6PtumDw8RyLsEytXQ5Wt/rnRJh54FsGZtDewPGEAMzMYjTxHwuRiB5IdjXTOaENXT/Vclmx7RNHyKdtXrcMompXvod/8dJAaiy7bg8R4pGLAICHEJtqHnVb/RI13/Ue/5Nv3mXNc8fib3s/PP/7BNvyIico8KrXNN0bmDDdVGoxWC2gJXejxQXg9OhLO0XtjfbAGcFKhGvARGA0S7B2exOIajbwUHZrSxWwqeCHNDdBoIK+OiR3DOizEeNAkckoG8HsKZczwSrtNcqQ+ugeKsybACrYzANTXV7sjH91Fog2vWmzJoMXSkQLBiokjIU0C5RMBTaiDoa7jv5XDeHPWB18Mam/29oNMiEO1bTMpjzCD61zCQO51oHQR0umDUc7q5IgA33edcw6DnGCfppA1UMAAzfH125vYjv81vP4WLNTC1Izpt1poHF9fqg5eF0kdAS1sggH0gczmjnhPDw1GR3kB9lk6L69mmHvtAxvpTPTOFU2yLPlIn6r8J2madEqNCgHtgrh51Svwz7uudDlo9t8KYtJhdbNM3NzhOco/y3rvodqDChFQhYH2vp3dI6JaMYwVjOK/2x3r/DO1yMMG4ijk3OdT751ONsf6APCvm7v4mn9EK98Dk1xZcFMEBO9Xz+0OhmkmiNVJ1rr42gkOwcuhcirma3p0BaLwLdIzWfZZ7cqdvm+CKm82YxUgBKeajCm7nIAbvHIlJo+9G9vue6za92xLI72Ck5xJTb0iDY75pu/kv5WkYYI0h4XEAIsEofxw1WyOKQgTn+QZt2XHqi/SsJMa4QmtR3D9DWS5xjOs+FTnnBt18czxRn3pwoDFrinSP/QhHLzLMfR7puoTjMN4n4kkWHA/p4ahCwBp4yH257jZxDed5/BZoa2D5WP8EzF/Lhb67RH0t6c661PXXKxxDKTAPcj2M9VWLH2gJ+m/V7o4o246kyWQymUwmk8lkMpl2kv2QNJlMJpPJZDKZTCbTTtoJbY18tA08zy3SWyzLOedqbNPG2JKvBsLLooHwlIv122369Us5YL78/cttmu5vD5/IUe74SI5JfQfXKiAEs9UGl63haDS70rbyu7dC3V4t9HkNnOHwuQK2v0dXSyAqQ7ozIXBxLwgAmQc9iw5anggbnKJcu5/f+d57l3ZoTgInUzq4EgOtGeQYQaCrWkjADQL7vr1UWcxnwrd6QLyiGFv7DXEoIHFAhi6rTdmlN8rvYiX3xculWJCkpzp6cqi6ywf6PGVwaeAiMLJyAbjuUQ8ujCM5nlaI5NqUQpCmP1Pw2dHXX7h9KIq963dIdwKX4RIYzxAuXeMj5e8ASOrFuRwSv3r75Tb97kLtNc1UdxkwjzwWUjKYIAj7RP395FTpfoem0EmsBDJZLuCuDFRyib55jTZ1fiFs+OJSqNtqpesTtC86p3mgIAFDYQtMiMRr+kdQ6vtQ27X7otS7RWhzDGZNnJVB52m8RmQtQ9vIgPrcAecTMuXAaFscW4AzoO8w9YC7EEWPgGbRcbcAKrgi3gy3byKRDZE5OGU2yBf7b4DTbw2UPmrhSLncDxLpvNseZaiA6w0O1UfGqKQ+0OIGzsaDXPU+OhGineGIRXGjvnn0WEj9+InwxAEcGIcjODOj/2SPOzfsmE7AQMCAP0VwZ+0Nhb82NfBP9NMWc8UanHoAilwAgQ9r3b8Eau1T1RexvWq1nwDocZy46XFXpv719vOMSChcHxO4fk+mqLsDlT+RvDRX2Y2mQMoxvgyP4eYKV0m6oFYOWGZXpkTj44C+jnk1oosjbSpRtocpnCyBDTYYS9+8VjvKUe8gKN0CA2gJZ2ji0Kv1fvpj64JbdIHkMRS4qvluR3WPdeNoQFwc+QaeeIl3ntLpEuNtoMt/zLrGOgeXZEnn2toQY1deJiOtKzxccAdoF22BvobjXzXGzxpl0NbEIOEWPMV4gzX+utb9G4wVUUTU9v4Uxc6Nx5t8PT9Uu3yIIysp3GPXqOxyrvUBnaOHUyD7dLMFGs7fOLHj2KS8NZdYd6Lex91Cso9nosm7GuspBJFwb67UF/5wqbzPcfxttlZ7LLBu4dzKtZPHGtDz+AvCWwQcJwnm2moymUwmk8lkMplMpn3LfkiaTCaTyWQymUwmk2kn7YS2Ou+c774R4BhVeW2RlisET10LfSgvz7fp9UrbwZcv5Q52fQGHKQQqvoaj3fK1sNjVTJ+fngp5bXO4/mWbLWyPIOMFENNFs0Aa2/1Aa7IbISTn4d02zSDtGQIOT4CkVbACG2ZCFBhnOwMe1tAxMt6PS6T33uUdtsmg5AxinnrlNZ4AhYHFV7lU/S659b9Umf79f/ntNj09Ek7w4IGQ02Gmz7Oc7nbADbvt/OVa7eXVK7WFN5dy/GVA7QdjIR8pEI4KDnIMcF8DD8jpQAgcaJILLzk+kYvv+ZnQ7Bnc4NblfgLZe+dcdothIrByD0jwMIFDIJDN+bX6wAyOxqO+6uLFh8Lh6kb3P7tQv3uzUL/OrlR2i7Fw2UVQWTz1G2QsH8Lt1anOl63y9fq16vT8rZw2awTIngFNilCnPaDmC9RjOgO6QkNBlBnrK4eTJJ2J71Pee5d3bZ3lnCJAdhaIlSKANXDx3p2gwuinhfpMCgRq5tRPbzAm12gPMdrPkO/fcToeeOp2cnDOhVb3WyCYc1EDP0a3KAs9syJPjHQD9Mw7us/p8hb1yCDaLfA0l+6nHiPv3aBDRFPYMh4glvS4zwDlwMUWcGo90PjSzlW+Leo3A7pcwMEWzccFHI1IgTS3eP8s3sxVDTAnB3fYBq6DFRwFFzNhV8sb1d3ZG42By1JtIO2p3fUivd98oecuUO2BxueF3jWg0Xw117hyr/LeRV1bHwEzzlIEKMcRnmykOh0SC4/Y7pXvMVxxh8c48oP5PhthTkwZPB7jwBp12rlNBqy5eOQoHWk+p+N+w8DlEa6BA7eDE+3Jkdrp+080xp9dwPkSbZDOsimDqqMvR+wT96jQtq68bSM0KeX4Bsf2LFM594ErR3As7WHvpVzq8yWO9iyxBh4tVS4pxu0RHNRDzv62qY8eMPYs4xEH4JZoCxwEiZc74ovoXxWOerk1nM/hWprgOEDpVO8V0Eo6hefpfuoxdpEbuU3bHGHsyjGB0wmaTq2uxyMecNmFK++c74P6vVpoLfLtF1r3zzHeBTQsPva9h5s16M+eaS06AM5KzPvqRuX/5lpz8tkNohxg3Kswro9wxKBIMfet1e4iHF9rcBSLxxY86j38CdEibEfSZDKZTCaTyWQymUw7yX5Imkwmk8lkMplMJpNpJ+3E+HjnXdS5eYJich4ozHop5GXx5tU2XSyFvEREcVJtDS/W2tZdgY9g0M8VtqHfIvDoZKVt43FfTne3gYOrRGjNupTbZ91qGzeFG+Wq0ufffivntrdOiN3DS2Ep7fvvbdPusZ4fA+3IgAFEQIMD3PAiOK35Hcnj7yvvnYu3jnrEXOA0OATmAXfBAgjF9Vxo6aivLfaTh8JWl5m27V/97ptt+hyOVO8/fr5NPzwVTpkDUW46Frimk1amtnAwIB6stvPyS7n/zhuhkgms0g7QXh6+JwfEgxO4gnk6GSoP01zXJKfKw/kbtbGzd8Ii7lMhtG5dbd61jyC5CRCaIdxpW+AUfqhrHk/0zpNDobojOPfFPTgnA1mj22aLgMRrIMgDYBO+c2COgRAH8NUtXByzRnk/Onmqe6h5uRMghBER2ZnQjrNXagNL4EgBmEfJ4M6RcJgWjN0dbPJeFVzdOeHFdxxj4dSK8orpwkaSk2MHnVLXQnHKku63wpWIPbUoFwbjvkEexp17dwIUPc+VmZuF+uAa6BSDKTugfA0Q2gyITlQhcDQQ6QhImovItjKSN8Y2uFBndwJt358i712vw+NwisHlmL9auDg2c6DLQx3lOHomV+gH0yfbtAdi12DuW840rl2g3TefawwiutRL2X425RjB9XBVC+m6fidU8u2ZxvuXbzSmtZiTUV1ueCCsKwM22cbAwQZCOCdO/e4tsLK61bhyDhRztWJd35/a0LplsXkmsdUMaPcVjuo8aIGEYly9ei1H+gj9pBlpjF2hv2dD3QenLdxopPrqoaNGaOtxs1nfLOB6ff76C90Dbb7BOBFgU55jvE/o3AsMtS51/QiuwEeHh9v07AxOmcDqHBxBM6wpDsYjtw+1TetWHeaZY3wp4Yw/6mPMTPR5D+2y31f+UrqXLjXGrVr1u3fnWiO6AqgxXHzzxzjCA8wy6tZ8car1VO15BoDB6/X8cqnP5zfqmx7tKwIKWxU814E5FHNLgeMANdxfq/q70ccoTb/z83+svA8u7Y4BlDjucQ2H1SRVWUSNxpEIqPk5jgmsF7rPCnPDstJ7vrrSuFoCwacLat9z3aDvFvNN+25WOHLX07Vv32gs/dXvvt6mv4Dz/BpjwKLhEQPlZY01SXIHT8WaC/lKY7qs6z0afDf2u+8v2o6kyWQymUwmk8lkMpl2kv2QNJlMJpPJZDKZTCbTTtqJnQwuuLZzKYqwpbootE17+a22aYsLBTcPwKs8tldTOk8h6GaNbegS28fxRMhBDazu+kbXHx4D3RlutrmzmZ4ZFtrufgNE5RpOgO+A1iwRuHwKFGRwIqfW2ZXuMwW24eHI6uH8WSFAs4dLUrhjQbifgMsuuK0zX0DZZoiYOh4j8C22yedXcFdEAOl5ofI6eymkaghM8Bzb9tdz4R+ILe5OgAWDdHJ1h91WpRCSuFR5MmDuZ598pucUv9HtgJAEp/by5FjP/GAurOyX/+IX2/QIuC5dRiOguyMvHGUyFurT7KkefXDulgzvs52hb7ZoTznwhQncCG/O4BT2qerxAv3BA7vqwdn1cKJ2cgK34iM4E0ZwN066oPZ5X6h5Qdc4D6e4vt6Jzs3ffCG3wJcXwIZrIr1qG68v9U4R8F4aeZZAXVp8N88YrHlPalvnOkyPzrDZHedV5a+X0UkWeAqcIVHVrgEKU8NZrway1sDJsU+MFm0gBQqTdMGwE2A+CzjLsU4v4UhKPLiiCysYXQbjvnMMAtfHGLcSomE1kC2gswnyzjK7T4UQXF1082OidtxcozKOUJ491fX0Pc0l46H61PmlEPGXrzRmlkSaMD5Pj3UforC9d8K0joZA7AbdURU4slbAki/fClN8daV+NwMCFnoaD2K4vL65BBYLp/STKZwM4ardh6PwoIFT+0r1W8Nt8rraD9rq2uBCsSm7LBXWWM71DgXbOhDHFuNIEaktXrzT+7z2Wi+d/wfVL/Hr0YHGz4djjYMfPtMRmg9/rPRwspmXQ60yP/uN1l+/+UJtZwYkcD3SvR+cah588ETz4MEDpRuU/xqo6vQB8E+43N8pJ6zXehjn+ggOf5/a9MdNffgSqC6OtbRor94T4VWfeogjLtlA7/PtXEee2muVSxXhGBXw46VT3ax6qt8w4ti3Sc+ugagX6Gut1l8rzAl5X3m/udZzihu12eEUazqO5anaQITjXWs4E7dLHr8Cpg1scoGh9z7lW+fS7rXX1+jzPRxtO1YbGsU8EgWUk0i31+cxjluUa9X79ZnqeoWyGHm9PyMRPD/WuHba9Ych1kSLK62zPv9S4+r/+amO3pzPEQHDaa4O+M1UYY5r4FrfZjg6hynH4ThADgfmO/M/+kQcGdpqMplMJpPJZDKZTKY9a2c3l9sNjtVSf0k7/+zzbfrdN9oNSkv9As/w17l4ib8kYGfiCH9NvVnh/jf6a+opYsINsDOCH9d3Yoz1ur881D2YeCCm0gX+ylhP9deDR88+3Ka/fqm/GJwt9FfZn+AA7OhQf5HLYLAT4XB8GeuvBxV20CL81cIhHk5APMb7VPDB1V19RGgCk0MZ3Yyw0zS/Vl20BWIuwgykxXvW+GvPGoe9z3B4OUr0V7Pjh3pWPFB7SPCXn6bbscgQczKKEIvnWn+pS/GXtx/DPObLl9otLxHnsYe//j5++nibHh8qPYBZU4rdhrLWX43aVH91nuAvjsMMW6v3qDiO3OHBJl+jXG0aG1Du5ED5Pn6k91nDXOOLc+2mf/ISsTnPVe8rXP/gscr0Jy/+bJt+PNT1v/jpC11/hL8+d2WR9xhTSfldlrrHZ1/pr3Z//5mMuy7nyBdMAy7RTmMYFExg2oQ/vrqAmK0F2ikNb/iXy8TtaWfZe5d349OIO1kwQRjAyGB0x5wC/Q67gzPsHMywwzibqYyWMElxKMcBDCgeIU7VIWLlDgabMl3hL/q8d8EdRuQx4P0ilHMKGoLOPxV2EuKWMdH0XMYHa2PuPCA+G3bs/4Q/uH4vtcG5effX4iF2VVegH3KUSz6BAQ12Hf73X/3tNv2ffo25BzHpEpgNHR9pvPvrn/10m+5/gB3PSvW4rDTnJdVm7klQhuul5in8gd7VicbeM8StvUG810uQRxFQkzHM2w4OtMPlYVQzgmHacqm8r0EBtYj1V2MX9X4VXOv/IQGzonEK3m2Fnd8YhhqPYGJ2PFWZv73QGsLXGp8/f4eYvAvUB+Ivvv1atE8SNN88eb4hYPJc7ejpjzXeu0LX9rFDcY5585MvZQ70q99rvP3pcxmdnTzGGABHqcFIBE7a13vMrkAjALa65g4hiIX71u26pMb6M0Lsvwp152DMEhcwkARR8/HzZ9v04gImVzdqG1Gl98mDdqkODrTOW6HuEjTjVdfH377Sbue3L2FshV34k1PtlD569v423UMM0Oulvjsaqc8m2JmKsKaOGMMX1MMcsTF7NEFsSULtJ152cMG1Xf3RAIhrnn5OY0Ds5GH3jjuvjBX9B8So/sM3Kq8Qq4x+8vzFNp0iDzmJL+zuZ93uZzLWPSrMR59e6TkliRqYJg4xUQ3xO+kcZAjXCD289xox3luMVXkPtCTm2QATp+hPIHZsR9JkMplMJpPJZDKZTDvJfkiaTCaTyWQymUwmk2kn7YS2tm3r1uVmS/78CyE3X38qQ5PVO6FxjCsT9WEQgS3Y/kRbtpNjYSQ/BoKWfwtUFfGAxtj6PRlwm1sITn6LjUZCOMY44N+DQUeDg7ynubaGTw+1bb4c65k9xLQZI+jLAChOA2To5kI4Q4rt47hHQwngon5fZgLORR2pwEO545Hes4WZQgOcIgBfiO44euAdcDD5AAYKjxELsIp0zwPEoBpFahu9wT+M4QeSwj0d6ntVq6a8BDZc4RDxG+COB0f67pND5fE9xLSc5sJSaA7jgTjGA7XZZQGsK1Uesv2ErXOR8y7runAG1K1PM5xj4S8HU2UkQx8ZIAboi+dCWD7/WmjpCijbkycfbNPvPZThw2qlvj8e6/5DIHx5d2g8yWB4AKOC4lL3qBHn8GisthmAGqXI1xoxywJiXY5RARFitp4Du3JAegLiVzJGbrKnOFmR967f5T2HOdUAZiwTGGFMUb+9kdplYIzdmbD4K8QWLICHoohceQPcDvjls8fCEI+nQmpvD/wHHEFIUW49UE5RprobwISpwljnGbOMqJfXe8ADxjVAals8N8OM1iAWHkIXuhiY630quOBChxFVK8bO1LgQhho7ctRvAoOOiRc++ORU90lQj8ORvns40PWM+VvD6CQ/gpEIEK/QtbsG4/oCFVDD5KH0MMMBhnqdqI8c94HvLdW/FsCeKyCpJwfCch3qtA8Tj0OMVeOGBhF7MqPzMjAqVypzh2f3MKaMU5XLNFZeTx/o3WqgnCOUf/8n6tfPabAC3n+S6FmHmEvqHsyqks39GQdwcqJ8uY81r7la18xn6oPvF2oDn34t3K/GmIHbuynm3xZHVXyFcZL4PFDBCG3sEsdM7lUhbM0L4UniEpQbacwaY9AaeOgCWOfhI8SZ/oPqF6ec3KSn9+xhTmrmGgfqTG0gPVIbGEw2ZbrG+DF7o3n4DcxzsMxyy0uN331UEs0LPdacLY479LCeqXHcYEljxUJ11DZao+UDtevC73xS7nspTRL3qItJ++c/1ZGzhziGNMR6jvFKZ3ONQcVcKPI7rNueoV/7Bngz5vu/+sXH2/QCBmgYwt2DA6xdu+9mGCfrC81lPWDUD4/UpsYjjeUxkNTFgri0GtsN+s4Ia+13K8SOxtESxoiMYT50J7Zwsvv8aDuSJpPJZDKZTCaTyWTaSfZD0mQymUwmk8lkMplMO2mnvWjvvYs6J82bWtu014hv1a6FOEzfU+y9ALegw6lcH/sj4VIF0B0Pt7QPEceHWNIAqMToQPfJ+0Cappvt3nSObdyetpWfPxSKc4Ht4KiR89jBSDjWh0Phjh5b3z04c/qE+BgwS7iWpgPdc+3k4JSkcKKt9+NKF1xwVYeiZsAw+LgK/1iUiJMFp6cM8cPWS5VdDoTi/R8/2ab/7Gc/2qZL/A3jgx/JcezBQyEKEdCsNt/cMyWmOFLeP6azHfDIG8S0+pd/8S+36aMHalMP4UZ52BNmkHhafMLZLEGcwRxxxuCM5+B8eJjvi231Lso3eYzHcEUEuj0CajYEYngCV97oEfog6u7H76mPz+Z6nwjPytEHx8CCD+DAnAHtu6VuQGe4BIg0Qji69x/pHiM64eXqU2+BrD85Eury8JTuvnrYbz+X6+EXKzin0WESYc0aD+x2T3GynHfOdeWe5UDTDjVGPBgrPUWcwR4dLYHRjEdq3zdHwKQwri7hvN0A3x/kus/pWGgUXe9WHeo0r1T+5OQj4DEHA7TBsfoCY1et14ixW4BhxVh96+facUsAACAASURBVKTpnHPzpcqpapSHOAF2lSE+GPClEPZTkd55F3fvvcAcMEfDqYFK54iZOgSS+s9/8dE2/aPn6lNvEXvXA40a4NjIOFHbeIr59+BY4+r8ndw5mw4xrxu4hWNZkAMr/WgkV+8V8LaPnmmcKNG+GsaadPr84VhzaB/jUznX2iEA8Y57ar/X4PnSPSHK3qutV0D9Sjg9ZjS3RLvsT5SnEdzho0LldfpIc2I81Nj7QaY+y/5Dl9HlBdD/UuuJyXRT1+1M6xYPTO7pgebYEgjrA3Q1j7nsJz8TTrmAe3z/WO9UVupTl1/qGuJzS7haJjju0WAuWuwJbQ3Ouap7fpLCaRRrD4T2dhWOvqQBcSEr9I1C9fLsgcq0KBGtANhogRiFRWDMP/XTFMcTRpNN33iMvrO4Ul00Ce+BBVtM52DV0UmqNlXAwbTFGibGHLKYqU01peZcuraHBphrrnGlXu/nKFaWJe7p+5vfDCenet4ER2YGqcYLxqKePMT67AAut7Xy+sF7Khce4blAbPhyKaS4rVUux4c6+tE/BLLeFW8x171zrKlHcLE+qvTMkyPN84Opxoz5ucb+o4Xa4zfnPBYHhHWGOKGMIpEijjHWXRXabBTt/rvDdiRNJpPJZDKZTCaTybST7IekyWQymUwmk8lkMpl20k5oawjBld02bAFHxRtszdYL4SmTWtvQvZ62mNtDBHHHdmwBNDACRjIaw8ko0xbsCAHr+0dCJbK+rk8Gm+3stoKr1QP9/4cfv9C1XysIb1zCrbFAYFbgYCO4shEDqCNtudMVDDTMnei8RHpTOIq12X5+5/vgXXS7lQ3kqyq03V/Cqa0GTlQhmHEEp9AJEKincJj85S9+hicTU9O7ZQM4fPZUj+tKuMxtQ42AEaUIqtsbAfV6JIShbvScBNhbjHbXz/VdDzyvcWrLDuhjWyPgLfKzqHV9EQM56O3HzcwH5+LOxrbvwWMi2w4YaIYAw0kPQWrhoJsl3+342p5+txNxlAnLiRFYN6EbMoaZ+jY4e13h/5EvBIg+BpZyFAuH+8mPhPvVc7h3AkeKF+qnl3NhKd8mcJmDoyCxn/4SOMoQyGW1H3Qn8t4NOxe/CTEntMsUGD1N1TxcNXOgflmqNjoANjl1qt+m1DgYSuIsSg/hEFsD07p1Tc3g1Jenek6LKNtZhPe4k0c45EXAZuE6GMOht6rhBhmEsxaF2kCENpAAg48jOha6vel2WGdZNGvMcWvkFe82GGoso0P0Qzg6/qgVuh1gX13znrCtHU41PzEwdwHUdt3N4z7lnKxyHqK/JEDgjoHrJ3AVLWdwOC/U73yGORl1kfdUNkuio4xR75W3ulE5Ncl+XFu98y7p5ifPox+YH+sKTqZLpXsYP2OHYOgaylwGx87hoXDhBO7ZCZwnlxcay9YXWscMRnC87eZCP8M8gKM6Duj66IDtQmUbJcpv7xDHPRwcIOFiO38r5JLt8XqtPuixVwGi1lVosyHeD6IcQnBt5xAck2HFWFMDN0ww95dA0GdwH75GGs3e5RjLLi7V7mscVThI1K/zseogjvV51M2h/YH+//RDuaTzqNQKKGlbYVw9UF0XaIMt8N4I69sW96zhXl6mqqNhq36wwhqwLjmP31nh3puyLHfP33vhnHNuwGNCeP86VhtNY33uEQWA82YC/DXH2NfAAXyANVw5Vln4x+qzY6xBA9bDbdf3qlL5GuC4yeNMA8JbjJMZ0NqToa6ftErP+vi9hf54vqKTOSY5YMwB9YufTy7G9bHfvT/ajqTJZDKZTCaTyWQymXaS/ZA0mUwmk8lkMplMJtNO2om5a9vWLTt3zhIB6N97pq33330iR7iA7dJ0oO37HpiAxTvhpBdvXm7Th3A1yoHSZcBrRn1t9+YDYbTZSBhcdBsgOALyhEDVRydyUIuwxb1C0NF+BlwEeEYDFzKiHdWNtphTuIlmcEN0mb4bIVjxDRxSS2xV36si7/wtIoCyXQNRBvHq1qXyUQZc34ihfDhVmX/wgdzMxnClS4IwgAXwF1Spi+BGGMFJMO5wu5SoFRChCPfu4XNXwK2NxemJYahS2WbrBV2t1B4iOITFjtiAvuuB7vpiP8hH670rO7TwBm2lHysfDPreItB8DPQ0AfrQB3roc7VdD0wQVeQ80I4WgcZr8IMBTo6hc0MMLHNg3g0dxoK+Nx4L14mBP0dA49xSGVs44S3zhRCsHJHpI6BMFWxkF5We26uJbu6nP3rvXNqNDSnd9BJgfMgf8fIEiBLjQYNwdIGILDDTCm62Tar6SDAtxOhLAQi+69DwBphiwPiWAJkr4VY4jDCWIo89/COCc/UcJFNbyrHSRcBs4bYIKtnFwIRipxv5bE/9MQS36pDtkQdW28MYAfT2DuqP+cMDx+/B+TPOeD2DqqNfo66JVa1vgCeuhedVnetyhPHAV3p+i0Ez6alwJ0D2Qql0CoQwwpwf0H49xvB6pbwPnNrMGqjgAnW9xrxZo/zuVd67thvjCXklOcoCn1dAMxc42lNgXk9yuGQD60/huBs16idVC7fotdZUM2BwOdzs29mm/gLnNSCcoQFmDM42Rt9pMbdHQNMdULewAqYNR+u6FnLL9UIFhDBgvC0wPud7Qludc67txiePPhix73isZ2pi3Epf1Xqfl+cag+avv9Z3OcfBepyu5oMxjnrB7TQGftl0qG2EefX4QE7y7n2V4fUK4+FSdXF+jbpYqa/HGPtjzDMDlM0QLtm9TNEVaKSdXKuNr3B2K4v3sy8VRc6NOkfyBMcrPHpnvVJ7ClyfNcqfzzhOaWxqGrrK6/4jHDOrMaEmOB4S4bhFVasN3LoFt8hvG2nsenKq3x1fX8g9vqpVp72Byn+aqb304XJ8caX0N/M32zT7WsC6LyT+Oz9vSX673dc5tiNpMplMJpPJZDKZTKadZD8kTSaTyWQymUwmk8m0k3ZCW+u6dlfvNoExyzcK1pkdwl3xVI6KLW6fJXIkq7B1evFaAVAj4C9Zre1jmpf2YiBKxMCwlZsDF/G3bnXA/WIE0o3AcA5SIB/YAk6w0xv3gRfhPeh21QLtyIdwB4VraAKcrwXGcIXgv5dw/7pvaQcfeN9Kz25abuUjKDOcLn0BB13gMnQdLOByVmfADwoEEZ/KBauBc+8dF7DOcRRmq3fcCpMUqNsCiCXQi5j4GJ2pgK6sgdx41KMHOuvhchrjuTFw7/FAbosPTp66fahtg1t19bGcKU8wGrzj/HlzKSRlCuwshltfAH6RAktKUBf0SiTO6+BgG+BwWgFjvcW3QNm4vK97D3KiRir/mG6cwGyI69QRntPC9hHYjwMKOoID3ALOdWGN9pOhvSf7cd+NvHf9DoGK7xhREmdFG63Ud4hQ0w2zQbBhIry9hOi4+kAZgAyhDVRAoxZwrG67+s00pLkcRwZa9JEcwcdLIM8pnAY9OnZTs99j8AXy2dJ6tdbntYcbNrDJFI0mBW523wpdua8Wet5qqUKqSuR1iXq8ExgeEx7QOzqrjrzKtMqBJ9Jh26vuihXHVcw9XRHFOTDFNeYBjGlhQKdWuG4PVe/lkgM0HI8xn1aol7LVmLTAXJHC5b14+3qbnr0RBtauaO16fwrOuaZzYCwwji3gduvggjuo9W6//Uy445NTrWFGQHIDKhvx5V0Ahrd8p/e8ngnNn4MxPAXqXPruRlhXpBiz13BlZmD0Figs+2CLfte0yuQS2H+JNn7zDuuWa13D8kuBLvewBsuT/exnBOdc263L4oYYNI57gOmLsK8S1VxDqix+99s/bNPxWm33vfeEIf74VO7Ko5Hec3ggJ9whHFwzzCvrzv0/NCpbDN9uciCcOc7xvQBn34UQx3Ku8h8cwdEZTvnTkfqadxgnGLA+xviwRN9H+S33ZYcdNN6XOO7iG6LzwK9xBCXCbxC6/CdY33q4zd85/9RgvMNYFseY5zAXs8/k7W1eEOUAfXDyQHn/0eLRNv3mWvV4/rXGgGfvCW9OGWWAdXTnCBXyizVCi/G85fk14qzR7kcGbEfSZDKZTCaTyWQymUw7yX5Imkwmk8lkMplMJpNpJ+3EasVx7CaHG/ex4uMfbT9/88kn23SLwKWDU23ZZkfa1q/hxhnl2lYfDoUHpJm2sBNgo9UCuCc+TxF0uy6FHNyidwHBeWugWzdASBiw1cE9krvdHsiB5xY38sJf5yBq4RvoXI1g1AHOqR5oyrrcTwD0EIKruoDKOYI9z1FG/Z623lkWUYIyz4VHrIBHLlshOtfAPwYLvCeZOGBCFfC4co2Ayh25MLiDpcHBD5hNA3wvVLpfhcpIgCGw7uo18KUIbleFkIMcLr41QM8YjqB50HefPXrm9qG6bdy7+cahrWI7g1NtBDTuo/eEHx2O9T4e7p29CtgEMEE/ULl4oIdEwGugUR7BfBmJ+vbTDDhYhADoGRAV9rteggDOxCDnwAPRfktggzWRW6bRB3vAhJI+cVlds4AL5n3Ke++y22jJoE0qlifcd4lHxgHoKa7vw8I1Baobofsk6PsxnEwroqIOTq3A4NruvEEKF9ZeD+WPOm/ZLzDWpSnQOyDzAU6SFdA47787+PWiUhnQda8/RXBtXN9UdE69P3nvXNqh7mugvedLleFboEvPTuR0HUq9QwBmHDU6EpIDRYqATPWA/BYg9j0Q/wAHwrimg21Xj0D/iLfT4bWAK2ENFDyfoA04NDDMZTGCh4eE+BxcBPHeaaKjAb/97D9u07MCaFu2H5QuyXN38sHGif56huDy51orzM/17DUcrX93oTH2o1dCUqdYn2RAl4tCR3tiOh2jrm+A/K6xumjh9ulnmzZ9c6H5tk6Ul8EATqITHSXJ6LqN/h2Acxa16q6pdM0SqPX1Wvm9Ig6Pow9DoPdrjE8Jibx7VAhyz6xxPinieg7caMv5PofjcVDdfTtXff35g4fb9KMjrWMnE0QZgGt/nqhz9sbqbwnWndFt0a3prqnxKqPTZq41msczn03VH+niW2NCpdMy0eIm8HhIi8+Vx95Q7zGDW3yzwpx/n/Jye4/gKF1UOAoHl2dfw7W1D2d/tN041eexg4Mr5rCoUL0HuLY2xPex1nSYq6KujPqF6qLN9f/rhZ5zONUY7yd65jXccRd03cZ69WyhPr6GS3nE94Nbbesw90VEXvVxeSe8wfeT7UiaTCaTyWQymUwmk2kn2Q9Jk8lkMplMJpPJZDLtpN3Q1ihyB6PNNmwfX335iQLmjh9ra/z0mZC+CFaSoCbc4CPhr2mlQKoeQTfDDbbPEbS3zuEuB2ZrdgmnxQ5hXAOBW86FnLw+k/usG+t39VEkVGHAgLxw/iyB99Bg1E3x+xz4Td2Ho9oK6BlQ3wIoQp7tz10w6tyeqhJlBbSjYtBkBAwmHhEBVQF15i7h6Fu+QzD4IZzCUoC+oAMC3aNyYCfFpt5pDNYHllMBg20ZaB6B1lNg1yWZY7jlNRHQqTuusUreAFVLgf3mdPWEo2y8J3anrVt30wWk7fVVtiXwl8sb4RGXlwhkCxyNLpZhqj7lQHIS8YyBeQQgQzHc/WoUWFvrnrd9pgHOnA7kQFnDKXbtGUxYbbCq6Vqq+xTIMN1GG7jvtqiXQEQXKNkoVdl44NPENe9TkXOu12EmRJE93JLZ7xI42LKuW+KbRJGAizfAXwPw44Dy9WivDZzg6qD6ffNug3id3ah/X98Ag8Ug34OLs8/Rjvqq6whsTcMJAqhVDX47AQPcoO5q9uWSGK1u6cL+3AW3zrLI6w1Q/zOgh+ULtC24YQ6WqIu+rm+XwE/hQkvMt2zhqsljGBy3gTEng00dJGx3wLyJsM6uVNc99Fk3BJIKZ847HoJwt6Zzcgu8OfQ0J7yphZH+58+1vlgAK1uU++mPSZK5o4cb9/njp3A5juWYubr4RtejPU0Wr7bpb85U5o+mGpsmxzgagaDyNfD9BuuGGd75d7/+apt+Dcf71cUmzSMek0O1o1/89S+3aXQLF4CF+xWcOdHvyoVw7OWZ8lvdaDw4w5xYYL3QoB8UGHvXkZ6bAdG9T3nnXNSNE/UdB2e0RYyHMcbbFm20AHae9dU3RsAmHV1W4eTp1hirOcYdK8B8VWp+9B12X2MuTTHGr4GapwM4yWM+z3hkgbhyhLUr0MoG7s5+qcZRAMVlpIMUR3v6GEorjCH3qRC8q7rn93Akii78gREcsAwLwFkbXN/SJjsAI8ZpshLzZoG5LcxVXkmu/EQJ5rMOXw8euCsWuuUM8wD6Wp5oDExzFe7bC/X185ny/u5Cv5kWOD6Q99A2edwBjs0BY0zAOsfjeNH3le1Imkwmk8lkMplMJpNpJ9kPSZPJZDKZTCaTyWQy7aSdI2zXHRKZI4jpjz/6yTZ9ePrn2/QEQc/nc7mfff3ll9v0UV/3qeHy2rwGonOj7xJmaYExffX7L7bp16/OdNHtdnv+3VgUI4D3V9pWLsdCd/o9bqfrPhkcCCvwIsUaeGStbeIMDk/ZQOkY7kkFUIvRcn9oa9PhnwFukB5/V0jBBwQPl78WmCLwi/OZkJc3wADmcOc8AW53fqProwVwGQSHpVNVfusuCJTxwbGc/dJUbS3BXj7RvAC3vBRugfUfCXru4erZAC+hM2Qb6GxG/FNl1iz342bmI++ywaZMc2CCriHuqXebNXD+AuIwX6pO6XDawOEriVG+wFziAlgI0J0WwXeXhVCQuENQErosowxjBNsd0c2YbnJwayuBrhBHmhUMoq13ukb/rSIigUB04XKWJQgmXwtHuVd571znfks6qAX+mwAjr8mCV0RSdM0KbbpCgOYUQdXzFEgz8H0yiXMga1cz4D23+aFbHgi1PhwFs4H+o71Td8CMEVi5RpstMVbfIW4wZsZE2VG/AQhw7Ee4Zj9IpI8i1+sCfTeVnlEgiPbZWpigG3AM0sc13P/aVn22cN8q3bBMgeRlPIZBt01g4uibty7JCXDuUV+I5eoSLqCxxonVUphrdKNxPYbrc5pzecG61qclXLJvUKf/6//x99v0qxsdlWgwPi3X+3E190ni8qONs+kKc8kolfN8/xSOuxg/k5XmpLcXv9mm3+BIzhHQxwhzTFSqnbQp0OFMZbpOVHjlm9fb9G3w+MFEZXj4REeLDp4/0e1GcPVcKF8Fjw2thMyt1lp/3Vyq3r8Gpv35t2+26RjjSot5pkDfLDDI1O3uLpHfS94532G2Acd2GjjJMlh703Cdo/5VN3ArxtBRwbF81IMLLeY7P1BfqrHWPHuNNeqXwqSLeNM2Isy9BwM4wg7k8BkwT6UYHImXx5gTPOYBHj1osF5YcTynYzawzQz35Pqiv6dtqcYFN+v6SQ/zRB9HMBKgmcFzrsS6jXMP6pduxU2Od5upD6wXauuMdEA3+XWtem+7smiI9GNOXsaq0znWxd+8erlNv3jx3jb96WdaI//d10L9z3AEkNEVXIzn4hgXj78E/NaoeaRud7LVdiRNJpPJZDKZTCaTybSb7IekyWQymUwmk8lkMpl20k5oa9u2rugCYPbG2mIfHWrbewiHvgiuTwPgMofY7ndwyYyGcEgbCyNpsMWcAlEogLXRbSqj22mHwkQIst0fC+0YjuG6hCC5ASgdWZwMbkgxXJ3qGE5dcBFkvNJ+DkcmOmLBra4Pp8oYFNR96zaHAW5+OfOBYMMN8LkYiF0LPPQGgbZffilnOVf8q20yQr2sX8mF6pszoR1vb/Q5MdMHDzao0XSq9tUDOj1B3nvACdbAZpKWyBhQFOA3NQk/T99BOH5FRD6BKwMZaoCanq/gDHyP8t679BY5Id4WmFYdLQvlu1iqna3xDnUgXoV2D4w8BZaaow3kcE5Oc6DhcHlzXWDsBJjxAkG/Hdz86OQZEIg8wP2vgevg1UxtZzZXe5xf6/oVkFcHnJMYcw3cbjgFajvaH2p+S5yAurrjIlhjrEswRtANM0I7JixWA21JEFwb1PkdB9sI7n69nsb5kyO9f79zF0z6CLiN4wPVXHkEnelcBOc6BJeOiSZVwDPprAvX5QRRxTM4QNOFusWYHwHrymJauN6jQthiYnFMR0e4JRYqo9cYA59+JFSyCjjqcAVscoTA5UDfiKknkfoa6zGGq3UNPm9xvUHsSmCHq1car+aXQvCyofp0eqLr/UrY1xrY+2qFOflOf1cfTICqzd/p8z/8/vNtmjh0D4jd2sFh+h7lXeSyePOuHgHXGQg8xXqjPxLO2gc6dlHL5fV6pvGoPMIcGnDcAGOQx1ohe6Q++ODhg216eS5n27jDUp89frr97PTRifLrsbaioza2EiJim2inxVxj77uF2sOv/1ZHlN6eawz3Tm0QJK4b4LjHCVw2DwZwcL9HhRBc3Y33dHaO8LgmwGkzAgoOJ/0Kc+sV1oU3V6rTo2eq656Hezjw1wTTYAAu2wLX7nfr50GuOh+ifGIeAyHrn/HYDtaxDfFvODfD4bzBEQDncTwFk0iLuSjGuDKEa2myp3G1rht3frYZYyocrXrvufqd49EjOlTXqt8VxpqILvCMVnCp9cR8/t0u5INDrTvzQyGqYaG6XtSb766Aqy/gqPz7t8LSP4Ur9SUw/vff+7EeX6tO353rnstC9TjEGthjfiyxjs0wDxZoSxGw2PhPYFttR9JkMplMJpPJZDKZTDvJfkiaTCaTyWQymUwmk2kn7YS2RlHkhh3eQvef47G29UtskzdX2L5HoOTpVNhqDb6qznSfdS4XsBzBjxctAjQDNYlS4AFDYI7dNm0fWNB0AGwW2/31SvcgttkgSmm5Bq4DZ9MY6A5dCtOcOBZdlfDdoZiHuND7ZXv7mR9c6FCFBI5ww5HynaXK36ygMxRtJXWNR1Dh19dCbn5/Lsz18anKPZuoTg8Kfe5iOF/BAfDxyQb9OnkkdKc/Uj3DMNUVK9VXBjyjRF3H8P+t4NwWtcAzUP7pHYcr5T3rscxUj9czIUCvf/uJ24eyXuae/+TF5nmXwuQqvP8ATa5F+1sjCPG8UFn0PYLHwxXRpwxOrM9DI7TDIdh8AFpBRDVtNvev5rg3cMQUCEmBANllUL/weI+ba7339bkcBV9fCrW6xH2uKgRpx33o1Op7dBoEbkZXtHtUcMHVnZMosbMK3FkfGFPjNKbEQHrYviO6sKJvhBSBxoGOJwlRdhwZAHYVg9O/JfxHJQLQZ2oLNwj4vIyBlAMxS1O+K94PY0wF/KYGzkkf5IAyCEDvUzjwBRwl8NF+BtY2BFd2fSOB+2Ev0XiRZEq/AX59U6i9Mq+9VMirK4UxxX0iZZhjAtyVcVQjfajPyxVcJbtrFlfqO01P5XZwqGMot460zjmXwTk4y/ScNRzLi5IOq5g3gJ75TAjfzULzxhoYfo45yqMNRH+Cu+D3kffeRZ3rYYSg7zEQ4iom94f0VPVyfPxwm57jfdpadRGAgS7X6puzpRC3s7ca+84u1GbefqNrBh1KnQ507Rzt68vPNQf9xc//2TY9fCA312iiumhX+m6Bef7yRnl8DVy6RB+cDICF4kjIFMc9hlgjjfv7QSKjKHKDrs1mDFIPN+wG81SBdkn3cq5R3f/D3pv0SJKkaXoiutpuvnt4RGRk5FaZvRWbxSIJzIDggXeClwH4FwiCR/If8CfxSKJJgMQArO6Z6uquLbNzjS0jfHdbdRMeTN3exziRw7AadzYQ+N5LSliqqYrKbi6PvB8w62+u1WeuYyHHe4hoEAPlD1hQ+Bw4Kdaanfb4Tw5cn0su71WGNdxJY4zZRYLjYiWPgaCdbqwL6LwO7BnnLGrMFTHWAsR+U1qO36HqJrjrdk1zcaVjbl0chTvEUTuP3wVVB7x2rbIrgJw6HP9ZeODyQJ1zHMeL4GDfFMTR1ciy9hjGtNBns4X668WZ1oc/nis9Rx29xpG+s+nbjys1QJFdrHetPec4jFuBv5lwTyDoTY22+Y6yHUmTyWQymUwmk8lkMm0l+yFpMplMJpPJZDKZTKattBXa6r1zt2Z0xGbKRFvAb57JgejqlQIoj3a0rbx/DDyxJ5x1cgm8p9K29QQIxYRBP4HLFAismwOHylu0YacDh889bVMjFqtbZLpHOdEzGQzcYds8DLTFn8H9K3HEP7GVfKg8TF9qO3tJ1yxgV3V0Py6RkY9cr3VljeGC1w0q83Ij0DkQQGJhcBccwN2xhjPmyzdCbV4cq230gAF0h8pDZ3yyTjeXqIP2WcWFtvs7dJDNWVbApYHceAQib+C4GxoGZkd9MVAtXrsDd6wSgV8vbxQ09u9/83fr9P/563/t7kNxnLid8Qp9q4GH3iyFe3rwX0u0aZ/RoRhObcAjogBsccKg5/pu3VEZzdGZOoinDbNcdzld5a04FeYxL4COT9W/QYW4+Ux9pARuev1G7eH8RlgKsdjzKyCyQFFqoExZRNc7OO0xoLG7J7S1adxyvkJtMjjcphmCJgPj84HtGK65wFnYjlNcA3LYJcBiGBScdRABa5tcC3cr23IsEXx7gjG4IiIFXDxBfyRq3QAbpjsmx89Ai0mw7MSr+JfRGOMnMcjI39PfT4NzoUWTaqDITQb3YxzrKFR07tUrjZP9J8JZY7js5Tg+UGw4egPnRWD0AOfPTlftyqMOboPd+/6u7oFxYvEjEMegDC9u1Kfirjp7jIHSFyoDmMm66VTttwOM/GrGozDAnue6poN2nURbLV/eXT5ycbwquwhIaoz+mKMPxjimkuM4xu6jz/X5XG2xjDVOLYCyXb1RWf/qN39Yp/+vX8nB9vUF3Ksxbi9aDLH5hy/Xn43h6Hywq/n5y2d6/i/+6sk6/WBHeGYKpHcC5PYNnHWncGOO4Sq5mOmaIdYXPeDYI6CtXaTvUqEJrmjngRyOsQkGg1lBZBDzPcb6CvNXgznuNZDjCzhQH2O9mvZwbAZjVoajBA5HS5JiVaccJ+kuzuNcvoO1Io9glDwygDGeODbmQUesEfW4rLFegAt1TbQSyv94tgAAIABJREFUQ/XynsbVEJyrWjdojzH9+kb5G4/VvjOncSrgfRpMfoGLC8wNOa6PHdzpE63daxw9mMGWOEFbcnnK/6y+h3Y08qr/QYrFEnDT5+jrr15rbUlX/h6ccmOsW4hDz0q1rwxzRYSLYowl2Z+wv2g7kiaTyWQymUwmk8lk2kr2Q9JkMplMJpPJZDKZTFtpKzYkBBmuJXDca2ZwDpxpC3a0p+3mGJhNmiCIJ1zYfAfBhjM4M5Zwgqt0/dWZUJArYAYVtt73223+5VBb+Uvs6ucjuE7SsLOHoNgoJr8RDBzb4InebzkHZniNLem5kMPz74X2FWD/ImBC1eJ+ULoojlx3uHpOJ2VAXtQjgsTHQIhSYCFJD46KwBOTTBjA9UL18hw4404feORc9Xvzo8poCXT5YLTCcR48PFp/1hCtPYRr14BOYkCt4HhWAQ8IdNOFQ1sDd7IARORqrrJh0NofrxVk9tff/26dfnPOiOx3p8Vy6f7w1T8555yLgUidncv98ARuY2eIOF0v4WC7A4SjQ8dh1DsCWlfAnmcT1dfNmTBTGL65i4nKK2oRoAJR6nso5xSOyzO4xi4ioprAGoFdlUBXzqa6ZrqBKKN+6fpIGj2GWx2c6JJ7cqVz3jnf4jIJWJifchdlwPqIqBPGI49A2BX+XpiEtyNbkxu1mRevlJ5eCxOaAxe+HRPSjOMkyq3S5wWRLuBtMfLSFMojSFU3Byq55P11yYZzXUCZRRzPge1H0f3VY2gRMD6iRP6KG40X80QBta9K4lJ8B8ybXbhUw2bv4rncI5/d6DhJAgysv6cjA9m+ntsUq4xmqcbsFHW0SNVIbuAYen2hoxkfYL7t58Bc0ZencCPHa7j5RP33xzd6jyXmnAiO6DSeHDDC+x0q8sHlLXJbAyvsVBjH0e4zBIzvjlWOQ7TdnK6SMJKcAg0/v4BzLvr4Ndx6fV91czCC+3w7n9GJ2gFzHgJjuy6Ftp6eqh5ToI9DOMteXev6F+eqxwC34CaDG3Sh+3z+wYfrNExbHWHWLGFvvjuFENyydWjNaN+OyWmJBuWBCRIfjBNg93D9vsGY9eOZyuXJnsquF6nuyqXq4OI7jbE1ogX0h6vv9nZUtznQxxhzsi9176xDVJNHAPB+RHc3Tl/BbR3vl+A+BdY/JY4IcY6uivtZrzZNcDezVT/5YFdH4aqgdUWNfJQoC7rZeqCfDm69jNAwh6NvBax9hvVSjvVq51J9PwJKntwi+ziO0Sd6ivnIAY8N4GxPL3F+AUc/6JJNZ+wIqDPXMNUCzr1Y6HQYFgJrobrZvh5tR9JkMplMJpPJZDKZTFvJfkiaTCaTyWQymUwmk2krbYe2NsGVLd6UAG+7mgpvIzKXdxDMGOhMTRSJeFOCbVqaVgEtKOEIlgCnXMBpji5+z1vEbTwGEntKl9Tn62QXW9P9vjiMwUDv0QWSmQADjOBq1e0LY7l8I4RhdqE8RsB4L+Ci9ofncmib1/eDYHnvXbfd/u8g2HO5RIBh8L8JMJ6fcm2NcE0X+MXsR2Cguyr3FMhBOtGz5lfYkoct3MVidQ3M8twenMrKRPfuA8uJBwgGnmP/Hu2rBibGYLu+eTtyQ4qkGQltOE7VTj47+at1enF6P+67rgnOteXSTNQXiE4t6L4L9OT6VPVysI8A2cAauqjrbgrHyI1MMCCuktfAXCfXaPets1lChzc4N15fwm0VCNboQGWbpbTg1H0mcL+r4K4XwUFzIxAzAox3gXkkaJsZkJIkJgt7d/IuclmLxiee6CevAa6DossSOpPC4TTger4+EGXil8NduXZ+DHfQcg8Y87nqI26RyAJ9cA7U6qbStSVdBGO0hRhHHNiX0cBKYGihVt7rSnXta6DReKmohMsmgp5X90S2Rt67TosmB7S5BHmdV6q86UJ98MUPuv5gpDHryT4cs+EOuvtA/cEjtvb0VPPNFe6fAKUiRpx0VvV+HYRVlkt97/zLl+v089c/rtOzRPX75LGOG/SGKvPlAqgV3ntZqM2+fqPMv35JVA2DGLBfD9Q0ze7n7+DeR64Tr+qgAT7X5Hq3PtDbOlJ99XBsJ8rh6FiqvqalxsaAdUsXOPpnD3TPxScH6/Texx+t00+OP1unxwcrXPnmSuVZB7hYv9GxkqQUMnd0IIfg4b7WLZOJjuRcImD6ZAo0+wZHJejYjbXeHsabGGNYVKkM3Ph+XFudF57pA5e6yjePLUXA/ui8XwNzbThOYY305pXKutjV+3fhWB2h7Nxcg1yK9aqfrfLDoPN+H3nHfB5mONZR4xhKH/M5XJ9JU3K8bYBfllhTN5hoKjjROoxtFRy+HZxx71KhKV29WI1rear+1cXZhRKu9Q7jgud8t3FkBfMKf2sARy+Btk7P1V59V2W90xFqS5f/snVKLRdqFzd0lZ/q3hnqusK4Fy+Vl30cUao5nyKKRYajN4RTuWZP8LIRUOt+F98tt58gbUfSZDKZTCaTyWQymUxbyX5Imkwmk8lkMplMJpNpK22FtvrIu6QN/L6YwzEKt9k//mCdpuNh47VlvoHPAdcpPRyQYmEACa8Pug8dAH/5l4/X6dlM29nLFlscwQWrM5DbWwmXpgwoSobtXZ/D6RCOrK7B9nSsLe4GwWk9MMuLqVw9PbBQxtl+MdNW9ZtLbYXfpbx3Lr11cYMDVwPEogMHSAaAD3SJpEMcMNzOUOXbwH23AsEyyoTuZMDODh4Jewooo+FB6zLbVXlGCJocw8mq19E1DhhXQ8ddOLhGyHuDdIzAsw1wGOJVEW0EgeTlcGtriH/coaIkdv0WR4rGesbTTG1xiD7VjeFcHJS/CgHCczgkLjzw0BGRRL1/Hqusdw8RmBvBux/W7O+rcu/ARbCu9fyrS2Hy/any0hmrvi7RR6a1yn9RAB1Cn53O1E8XQFoSoKB5BzgHHP6WwF4SoEF3qeDglEbUH1hODpw3oftbRJwFGA+cPwNxwPgn0HSM1flQ+NCyFgYXkIfpfOVSWMLxj3hbA+S5AmKXetw7guMfiv+6ABbrePQBroM4nRBQp559NkafRXusGIz7DhVFkeu1lqQF5pU5XPOWldwdO8NH6/Q3Z8JG/dfK98dPhTXmlTBLD468/0B44on7RJ+/FOZK1im+Uf/ptq6wOYJpn58Ka3z+zVfr9ALnCj78VPN8d6C+Oce64HJGvBmOlZUy89VrIZc/nitdwy22xjjUxZyfxffj9hlHkRv3V3PYNZw881rjS5Vr3Otg7qkwb+7twrX2DbC/LpwnMSanuE8Kh+RHT7R2aUqV0eSVynH2x/Yzr/aV4yhN01V7+ejk4To93nl7gPIlsP8Gjph0Zp7WakcFFjEHOMlRLYUEJsQGMYdkfqtl6DvLe++SbJWZBm2FiG2OIxYbTu7AFOl2GmMs9YhccIa+OcvkkDwkNol9m50e5r+52nSoV3WW1movfq5+RCfvDhDaNFeh10A4EYveJTjGVKD8a6c6mgKtDB1MeGgbDdY8AfPJ7t6huw/FUeSG7VGzhcdaqtb755hvepjXYnS7Em7CCdD0QHdlrH/yWMc9dkZCS4mKRj2sLzEcVWU7DxQYr+DuHNC/Xl9rzXMFVLVMMfbAzT2ZwSkdx/HKDNEKcNSsj7mCbtBoDhuO74GW++8o25E0mUwmk8lkMplMJtNWsh+SJpPJZDKZTCaTyWTaStuhrc65qHUWC8ARPJgvEAFufiUnuHkhXMY3wnX8EAjlUtjGFM5icUOXV7iD4WFL4AeMtH3TuqJdnWr7eO9YaMlgR9vXYQB0CphnFhHD0GM8AqA3hVCUkGg7uwOn0Fqv5y7hUJfvCV35fE+4k4uVZ/eDsNj/UKVR7A76q636m5lwnQDXuHQsPHUKh6mZ0/Ux3KYaYKuLGZDITNfPpnA26+v+faCEAcxazkDqbXDrzo7wgE5PeGzYCGANzAPb9AWxVaAaOdz4CqC+FZBeVLVr5vrH9QROXAg2vrzGdxs4nt2l6sa5m1V5dXp6/4OhXBQ/+VDYW88pT8WSDom6pcd9ljPgrMB4unApdDmd7oAXA8Woz4VrNH7VryvURUBA6r5Xuyj6qovFjfr0t8+EAc7ncKJF3cXAOehQ1wHS4+FU1qNDHesa40Ad3Q/b6p1wacZMzsCeZF2VC73xCKFUCD4dItYLPdxoBYt3g0thDBQ5Ak5KPMz3V9dHU31vgSDPFQlatB3+6bLBmD0Dg1Uw8Du+Sqyewz2RwIQPAMHqgTXl90PSOR+Cy1uklahuCafF6yu4gAIF9qi7M1xzAafc8bFcNTNw9B0eKxipzSwm6qdEjXte94m6qzYQLhFke6AyfPpQAeXrXfWd8Y7m8AJHHBYzzdsc9Sq0r7O53u+3r+WafhUJy0wbtXcHl3cfOIbf09/B6+BCO950Gxy1GGnd0OsL0R7Emj96I6SB/CalxuHuTD24gdtmRQdXHBP4gu6gcM6d/E5lPW9Hghrj5CLTXDquVJ5VpvI//V7pAtjwfIJxFQHYY2DJOcanHrD63V3dZz+FIyXmimECjLeHur5D+eBd2g6oAeNCAJqYAXlPMZiWOELVwBU678L1stHnl1e6/vkLHM94JCRyzHGwozbQx1Gc0LaZbAKUcQdpoLVx9+1r3hqzQsRjVlycI725LkJdAOuuMLcnXZafxpK0r/5xlwpN7Yp27fim4qDOo3D76/ROh068GgM9HM4rHJfzONYRo73GucrCx+pLy1P1uwb1UVY8CrVSPcWxMKwl4oCxAWNjH+PNDRYi85rO38R76fiqd+rxiAdcbJkH9glf4Chfs/06x3YkTSaTyWQymUwmk8m0leyHpMlkMplMJpPJZDKZtpIPZIT+P/TLX/4y/OpXv7rH7Jh+St77vw0h/PIu7mX1+M8nq8f3Q1aP74esHt8PWT2+H7J6fD9k9fh+6F3r0XYkTSaTyWQymUwmk8m0lbbakfTev3HOfXd/2TH9e/RhCOFOAvVYPf6zyurx/ZDV4/shq8f3Q1aP74esHt8PWT2+H3qnetzqh6TJZDKZTCaTyWQymUyGtppMJpPJZDKZTCaTaSvZD0mTyWQymUwmk8lkMm0l+yFpMplMJpPJZDKZTKatZD8kTSaTyWQymUwmk8m0leyHpMlkMplMJpPJZDKZtpL9kDSZTCaTyWQymUwm01ayH5Imk8lkMplMJpPJZNpK9kPSZDKZTCaTyWQymUxbyX5Imkwmk8lkMplMJpNpK9kPSZPJZDKZTCaTyWQybSX7IWkymUwmk8lkMplMpq1kPyRNJpPJZDKZTCaTybSV7IekyWQymUwmk8lkMpm2kv2QNJlMJpPJZDKZTCbTVrIfkiaTyWQymUwmk8lk2kr2Q9JkMplMJpPJZDKZTFvJfkiaTCaTyWQymUwmk2krJdtcfHBwEJ4+fXpPWTH9+/S3f/u3pyGEw7u4l9XjP5+sHt8PWT2+H7J6fD9k9fh+yOrx/ZDV4/uhd63HrX5IPn361P3qV7/603Nl+pPlvf/uru5l9fjPJ6vH90NWj++HrB7fD1k9vh+yenw/ZPX4fuhd63GrH5K/++qZ+0/+m//ROefcYnew/jxLDtbpeE+3HGT67u44Xaf38+E6fdRt1unjeLlOH468rh90dM/BSPcc7a3TSa7nzq7P1+miOFvl9+pS+e111+luV+nGKy/e99bptKv8nl9fr9PBx7p+rvzGiYjh3fHOOt0fKu/e505f0PVVVeg95jfuPvTy69+4//lffeycc+74WO9WVdU6/ebNdJ0+nyzW6W6qfD8Yqw3soE53Ryq7YV/vnwaV13w2WafLZrZOZz3Vdaej79bp6rtVXa4/i1Fukeuv00WqMvRO10eJ2mDs1Dg7D8ZvfX7S1zVZpHf1I13jGr1T8Lp/5vXdJNd73KX++Nt/dP/Vz//COefc9ULvfFMq7bzKKEuVpzqgrcfqOyHS9Y0ucbXD9QHXO7X7JEZZhFrfrZX2fnV9F+W8t6N+fHLyEPeWfnzxSunXr9fpyVR9pFhq/Mg76tfIllss5+t0tVQ55bna9Weff7FO/8v/8l+s04f7GufuUr/5+1+7Dx8drf6BsaOsVebFUn2zQd3FEcbbofrgcKj+EKuK3LLQO4dS360d6gglH3mmdX3T1i/HqwZ1nkYq9LpW3stK/bEpdb0LqO1G6U6u++xmev7RQPXbwwtmPdVjsqNrLpcaz27O1U7uUt9//ZX77//b/9o559x3r9RGX74+XafLQu8WUC8sW/ZHj/7FemefqtiXmaEIdaoqcBWKOmnnsHqjv+riKFFeOK9FeFA31TW9nsb+3YHG1R7q7smDI30+1DU3C80zeCXnU8wbc9VdgbZ8l/r++2fuf/jv/ifnnHNVrTzFtd6/qDWOLCdaE9SN2ndZ6Lsl3i3BPLSYax6cLPRuEepjgT4TY82B6dQNO6ty3xlqntpF+uBYY9fJ08fr9OWF+sWb1xe6N8aV433V0YcffqK81Mr7Dz88W6e/+15rT5+oP/b3NM7HqfrmcqGyvEvd3Ny4//1v/jfnnHN1jPkebbFGX/i//49/s07/zd/8L+v0+Zn6cj9VGxj39W7LUjdiO17O1JcmC61zOonmv2xH6Qf9VVn3e8rv5Epz3DXGsRh5jyN1mB3UXYL17e5IcwLHnjRRQ4qz3XV6Vqo9np7rudeV3uPFhdbV8xt9fpf6x3/8nfuzP/+lc26z32VBdREqlbn3mFcwl83RzgLHUsw3XHM0+FeNucpHXHeqIEv0fQ2yes6jHa0DH32wv04fjFTmZxP1qSuU+Rx1EfFEIgbiFGs91h1falFiIuD74Z2qJcvv3WRnJE0mk8lkMplMJpPJtJXsh6TJZDKZTCaTyWQymbbSVmirSyMXH60QimFXuAOxgSQonWL7PCm1fZ4AZ82AZ2ReW8O9IGyA2/YJtrMXNbZ+n2tL+OtvfqublivspAsk4XikbeXuyQPlFzhJ1NX1uVMmiwUwLWzl7+wNcb1e3GMLvQEy5MHbJU361s+zBGzwHSpyzuXxKl+dVNvby1r5zrvK0wOgS4d7wnPjSHXUy4RngEpyRSnkYDrXs1LgSim2/JMesJNKd6pajqdEPXrgcGUjbKGeAPuK1KZS1EuV6t7zV8IAekACR1OhQcVA5ZHjzy8NMLSE2OAQKERDYOLuFJrgyuXq/TzQuKgBvgCMKtQbLMw62YB188DXiBv6BhgJKphvVgK3C+EncKz2CxX6Ub3QtddnwqtcBQTsRnXUFEAona6pwO/VwFx9muJ69akYg08XCFYPWHIB9KvuCs26W3mXtO0oy5SPqtJ7xqHC50pnyLcr1b6Xl0BbIiI6KmvijIQiG/8TmCvqtGrbUgD6GiPdOOZX9/uprhAqotbEq5WeAwt9fa3+vj9Wnz2MhFY+Gguh/PxI89Xl6x/W6f/133z79gz9Caqqyp2dr45SzK40N0R4hzRROW/2I4yN+B9pDrwe6HwO9M0DuRyM1R4GucZkL8LNzS80Jk9aDH6J8ixqtZ26xNzbxXKhwRiLcaWaq7+cLtVeDvvKwHysufLgUD4OfqDxdjlTHojkZ5HyOc3uB6VrqsZNL1c4YXEJdN6p3G5utN4IAUcpgHQTy0bzdg367wz9MQA7q73aST3X5yFGfaCfhGT1eYoHRUTjL4UgLi8033aBxnWQfnV9tU5PcZxnAKT8cKy1wN6+6vTVtfra+Y/CupOO+mmGeX5ZbY/SvbvaIzHA9SIcg7o+Vf3++tf/ep3+7ttv1ulhR/1uuKv22se6qMCRibRRH/RA7Yc4/jPeVTkePdB69GdPVtjxyaHGrqpAn3p1pveIOd9ybaV26mZEMnE0oVL/mqE9Xtyorl9j7js7VT1yahl01AbqzgZYf3cKzkXtGDfwakNRpHwvgNvGgfOQlAD9rLCHRoycqCivdx2sRRdoSzgOl0VqJ53Bqqx3MHb9Zz/7cJ1+/ES/Oz78TJ9fTzSW/O53X67TX//wfJ2eFRgP8IYLrK8zjsk4njDo4AggxudypnTB9eM7ynYkTSaTyWQymUwmk8m0leyHpMlkMplMJpPJZDKZttJWaKuPYxftrLayq562d7vAX8ZAD7GL6nZS7YfvZbp+L9V9hsCrQgV3xTkQt1KOrN9/KVzj+vQP6/T5hfC4uHUj7AJnKMb63sGN7jfchZvcnp7pYm2nD3M5LD2/erlOd6dAvHLgr3DTjOGilxJ7yfTdBKieg5PkXcrHznWHq3oqgdOUjcq/C1xquKs8jYdCx4hsVXNsk6NZZRmcUgdAZ+GoSLdHDwyyAeZ7iydGQKpgmOrqmXCOGniRwzb9Aq7A5QT5FcWzgXZMj4Sc7AA9a6JH63Q6RLvqAS+BG1/j7gdRrkNwNy0WRMQwQbtpYro+AqPC35CaiAjWv+uw6pxztSckAkSY+OtPuKUF5CG5xcQxTiyBbU7mcAGFQ+8S+BjrfeNvYSAyyg20EjgYcPEsUVvOhyqzm4Vwp+enP67T/Z6QrbuU98751jkPRe5iupECY+t1lNeAPhLVSi+BGTuUb4Mx2aNcCrQfTwdPtocNk9VV3iKg0CDjna/ejsfU7Ee0BYZA27sF8Tzkdwnn4HQJnA/YT/VaGNhHI/X93b37cVEu68q9OGtdwpdvP8YQNRxH4L6LsuvBLXoPzpC7fbXXkyMhZWO0XbpBduFcDLppAyWctpjrEq69NTC9GZCxCuU8neua8xnQu0v104sb9aMf4baYnuv9Pvj403W6nym/KZBtOnXnXu8XF9udzHlXVXXlzi9W9TifAG2tURboFynwtUAsHGhc2ahc+N0CztEJxsQuMLl+Fy7h6BtVgFNlW0ZpjoYEF8nZXM+cX2nC+/jTn63Tjx+pLn7/jdDOr75W+ndfCrcrT+T+eowjQg+G6muTS9U7HWo9cNHonshWH0UubR36YxyJSnB04Xd/kFPrP/3x9/ou8PIe3fYdkNCJ2v1eR31z5xM55O6NhcI+PHmyTj94pM9Hu/ruIF2luxvHmuAMynUxnEod3s8VaqdzzGXNjdpaifl8Dhz92Y9yR18CB341QRvHcaVsqLH0wUjv/ffub91dyXud0MkzvGfNtQJxVoxlGOvoQM3jPzFcfHnyIu/onXmcpopwbAbT3MND1ePD1rH6P/3ig/Vnf/nz/3idPnl6rOfA1b9Gv//0I60zf/8Pv1mn//GPcki+hBPt6zf6XeMiHkNQ+4k6GkuI0jeYdKPl9vuLtiNpMplMJpPJZDKZTKatZD8kTSaTyWQymUwmk8m0lbZiQ0IIa8cxfy5MocI2ahVru3R3rK3eEfCqAbZUs0zpAqhkAbepH6/lslddKzjs9bd/1OfY5h/mwClbp6yIKAUQqRLucDMvDKCEk2VyAwRrJOfGAQIuL4H65LEQnUVBpEVllgH9SirgOnACizcQvruTD5FLihWuWzEo6UR5WsIhcX+h/E0YWBlI5CXcpvbHQADh6Nvvw3EL6EYAvhZwzwxRc+sWZYvgUtXAmTOpgEXTmbKGCyyCtJZAz66AHydXeu/r16rT8rGeu/8zIRzDAk5dwLHwSq5K7qcigwPuByYywP3YBbi2AnEgbtoA8wjElfFnJrq2NhvYJJL8sxSwrgh1GreuaBEQZro+lqi7ChhguUSwcuC0NfBIupkykHsMZ90UQ14ON9cY5VSg+CZnwn4uhnCUvVP5dfnW4EM9yhnk6UYgagYnLhwCtGP8qvDlCH1qA2PeQINoMYmyDgR/bkW0GW2ExxRoT0r7SrriAaddovNwrO4Ck8+Bbxd41s21sK5yqv47vxTmOt6TO+hdqqmDm16vxhgf2P7pcArUCuXZhbvjMdDWg5E+/2CkfJ/syAFyMADamuHoAbDjFDh0w2jk++0RBwS9D3BtLRdKz+cq20s4eZ7ONK6/7uiaf6w0V78+1+evc6VnaO+7KRBOjEkb+DT7frm9u+C7KIRm7VybbDgRYxwnYUcrYhQtXayXQFhrHndBHxhgThzD5bYP3C2Bi+8EaGXduu+OU33v+FBHMzL0l50DzV+HD4TY9bG2SXpqa5wTnn371Tr9/TPVL7FcnmmqgUEuKyDeU621HI/z3KG8cy5ux7KUa9RU7eZXv/7VOn0DFDuC2zlOFbgIOPXDHZXXR58DWz2GI+enH63ToyPhrJ1c/TSGU6i/DXwflvj/bHf6XijRF7DuDpjARqXyWANVLYCzLgugmnDfXyJI/Qu4Ot8s6GyK9Vrvfo7weO9d3s7hdBleLnA0gEcG2B+x5uFawePzlPMQ7j9gv2OUAaxpH8Ax/JefC/X+j36+wsQfPlb97z5SX0tz2GjjmFuDObk3FHY+RP/tJvru77/6VnnEsuxmon5Xoh4jzKEOUSRiDFxTHIF6V9mOpMlkMplMJpPJZDKZtpL9kDSZTCaTyWQymUwm01bazrXVNy6NV1hKlGordITt2B3u2GZCBYbAZVIEzgRh6ObYwudWcswt6UqOY7EXItIFghLgONq0KEzANi6x1UlJd1hsdwNLyUttK0cICp30tK29QN7ncG7rAq1MEdSUwd5ph0hUjbjZXSo456o2sDGzUSKgrAfa8c1ESC5IFTccqrJ3gV1lh0JbOx197uEYRdfOEo5YRA4CXLZunTobYG816xzodAH2j7jjAm5eCyCUy1ovdTUDTol6uUbV/exYLm4ue7hORmoOzmfERbdHBd5FwTlXt9hChfcnY9rA7TRyRIXfjk1WpHBhj8r7R28nR1yE4YRB5SM4gq0dLNFflkAfGyDqTYFgu7imQj027DtAWLOu8JM8Vf/NMK5EcP6MMjihImj8Es5wb+Bod9fyLWrMAMPsgzG4lQplETAGRkB06i6CVS/1PgvYzMWobPYZD9ywQlnEGDdv6z0APW0itfN4g3lWssE/IjoNZ0CHgOIQUc6B9dHocY5gytde88yoq/otMYbPX8Cm+Q4VnHNlO37zWELAO5Ci8sDLR3Bn3R9qnHz4A8/TAAAgAElEQVQEdGq/p897PDKAOSnDuOoj3TOBc3SWwY2wvf4WjXTOuQBc36Euqi5cRXPVwGCil82BTpGgvZzqeMrpldwFb+AEe4j5tMa8HFUck3FEJbq/cbVs1zQREVasCSrUXYBDdI35m7gYlkgbrtN9lNc+jgLtwXE3w9GInYFc4z3Q1VmLZe7uqAwfAlsdjDRndYaYn9GOcqQfPzxZpxMcm6Br+tc/yOX0hzeqo6M9IZwFxk8eJ4lxzwTuxXepyHvXbcf+JFff+fKbb9fpr34vF9orHEMa4IjRFMcqjvZV/p//xc/X6S9+8Rfr9MGurhkDQY/pYL9hOc+jPa0LO8ZmjqUenapBH0x4v5TLej2ziXV9iXYaYZ05AAL/5EBt4OxjlcH54lvlradndQb3c2QgirzrdFfvFxdwKt5YB9ANG19GP41RzjQMp+P9AGPsPo4MYGnnhpgT//OP5HT8V7/4Yp3ee7zCx8djObJmQf2LR7Q4mYVIz48yPefg+Ok6/Zd/jSMRCOzw+z++WKevuzo+UGD9FWNcoVvtix91VKGqiZ2/m2xH0mQymUwmk8lkMplMW8l+SJpMJpPJZDKZTCaTaStthbZmUeYe9lbORDuZsJJODge5BI6sTnjKfiXkiNu6IAxdmdBdEO6gQQ5T1aWwpAECIW9EXAZWWLfub1ENXAeIRY3vLSM4qznd2zs9M8rh/gVkMXhgmEDDSiCE0ULXl7netbOA+xa3oTcArruTD87dvmpF7BBY1ORKZfTilcqig63xgwNtw+8+FgYxGgOj6QDFAXLsiHlEaicxHPqaJdC3Fr+AUZlLEGx26YDNIoC1B3aUwoWrSuAOql19F+BeSFziGoGpX3z/cp3u9fWueztChio6qqX3FHHZyWGTLpEbzpCIQN+QSUW/I57q/dtdzlyJd2CAdSCqBLGJ2nikk3hVB3Scq+AE7OACR/SPCCW/y/fuAV/qdYXZ0JUtgStbA24t2QhWDOx6JkTkx5na6V3Ke78ul2IJx2HgxB1gnTMEnPY8JoD3oXMdcVJfAu9BvadAoEqgsynaDyOHh7Y/VkAimd+KxxHoOvgTbpwBCHoEFDkG9jad6L0D23gM52QErL6Aq+cy4fxzPwpOjsKh/nedip1zLoIzaR/B4w+Gaq8HPSGOBwONL0Mgjh1M3WlAf0R9xWgPOeogRR+7ZdkL1G1MZ+xY+U3p3NxRO82BsadApGsnrOsJ0Klv4OB68eaN7vPJJ/ou5v8A++gkpQv1/bh9Nk3tJu3aop4qHx06Y8MFNALqVgG9qwqUM9riAHPfz46En350crROH+8DiURdjw9UpnR8nZydOuecm2KM2h/qHj2mRwD1UJ59ONtzLNnHMz/+VO6kX/9Brvk/fn+qfEV6Fh2+abI7h7tylMFt+i4VeRd3VnWwmGn+/sPvheRenv6o64HtkpquZsrfg0/lePvkI9XXowM5tWaYhxIGhofrb7zh5I65tV0jlZxj0aeISHOeChjvN1xe0ddrrFe57k2wpu3DObiAk/SHD3WE59kb1R3MXDfG5LtUU1duPl05pjcTOPXj9wIt5jeOFWwcx0A/xXomBwo8RN0d4AjABwfqM58dqn3furM659x4X2vjbj9p8wgH8ghzHI8Bob5qvFMOd9YaP5R2gI5/9sXn63SMeeDrr75bpyeY8+OB3q/EHLWcYN1bmWuryWQymUwmk8lkMpnuWfZD0mQymUwmk8lkMplMW2krtDXJYnf4eIXv7eTaYu7N4Q5Xaru0HwGJBFq0wSduOPoBxXFCRIpLuSU2cHwLwEZ7MQMuC9FIW/Staeh0qGd6IgFAZaISCGuCAMJAHH1Gty0gAQNtSXvgW65UOgP+eh0rWHbcEMO7H3QnOOfKFtuMukR1dc0lgnmfz1XOPxurnA8fCuc43BeiEyVCsxI4wRFZc3SDTHWNR4Oo4aZ666Aao301CICbgLFoiFsCOY7gcubQHHOgHUugd85riz9FO5ldCHW+AWo92VXw3xTvF8p7rMc2Xx4IIJq3KxBclsHoSRlvkDV0wgVHs9FnmAdgkMRGaQW78ahb/ILoGq71cF4tEEC5qlC/yEEXLnMpUJAe3OSItyRsD2h3jIkdAh19lfvl/H7QVuec8y12HIAYeqLIGEdiYPpTuNyWwGIDgxADEW7ozoq2XsPRjkcPmkB0GQGtW6y8ATrOYMoBdtABWE6EdyKG6eECXlYab5fIC+uxAtaeABmqvOp0v69xiC7j9eyeUDonfCpG//dAp/a6aqPDHhw7YXe+1wPOCjfhDEhklmOuStgHgAVjvE1xH+LoTdvfMs7DwB2TpQbKplHZduAWTCdaUuoHTgjc0b7e6QLzTIG6Y+D3DRdKOPoS2x/078clsq4qd3mxQm4jBjQHQp1lXDphDkXbTYDdZxizPjgQmvb5J0JFT4Cf9gdquzmdFlHvMcfe3ZWDa7czwbXAn1FJccR76C3okByDbusCx3588GidPsD8/9vf/0b5fQNc1Ou7Nwutc1L0iazcahn6zvLOO98O7Mul1m3ljTDrDspiXqnsrpe6Jk3QzuCsOwDy69EeAnDSgD6TIB04tqPdh7a9pRv/H2O5pxu87hdzUkbfDAnmzY3jJujjODaRAG/uLjGfZhoHjo+0zrl+rvVPPcWi6g5VN7W7nKzqIwWeGvP4Bo/BYC1UYxyu4QLP9U+EPpUjckEHmOknRzqi9cWnH6/Tw5HaNx2rb7MTYR70G075mJM3sGTUKaIcJFO13y7wYz8Sav30M8zncBr+7kz9boHyoFP4EMjrcrF9PdqOpMlkMplMJpPJZDKZtpL9kDSZTCaTyWQymUwm01baiinwLnJZvNru7gJBJL44gBvp6AZbrQgUXTAweo4AynALWkyEFoRzbZ9XcFYd5kTTgADBKatqkaYOsRnkPW+IeQC9ZIBTmlGVeo80IHhoCvy1FBJADpCumUtgFBvIGJxd6Wx6pwre+WJVRqAg3EJZcq9ew/kUSO6DR8BZBwqInHeAeRBVJIpDlA0IVkCZetilEQm7JYyI3zBgfQSHLQ93MuJF9RzOhcADY+CEKb7bAPdLGPz2tfI7G79ep6djlUeWycE1PUI7vUuF4Fy4DWAMlI64ErFVR/QQjm/oD0TAScvQZYyYKw3iYv5dio6vQE2W1Qp3y9AXYjBtMd4jIcLaVXnmfbizoh1VRDLhEu2AHTG4NjHPBGhMBXe9BjjrooBL9B3Ku+DiFjOt5kAGeQ3wrzlQ0YLugnRkBfYW4Z09MCneH0Sxy4DXEBmqgLhH7bc77McJsVn0OyA9HfTpTgf9Gy56c9TdYqE5xDOINnJP99cc7TSh2yXwvJvsnv5+GpxrbpFfIJF0oqbr6AC46SAFMoe8xkQAkW1PJ1g4QBLrz/D+dLYlB3eL/Ho4jLIfN3RGbIBtYs4vgD8TT616cCbH3NqAK4t/iqJifpGFHpzFs/S+XFsbN5+s+n031Vwe0Ec23NjhfugxfmXA6E/2hK1+/lDHQB7tad7s4n16I12foj2kaEslsONuG5mcDpRZDpw5Jh6p9wgcM2tUBtpRj0dPdpSXj598uE7/9ne/Xadfnl2s08O+8rNYqP00BRYeOJ5wtwrrIx83k/P1p+dv5Lpe4/hKA/d8F6tcsoHe4dPHcun0FTByHFVyWPM41EeFZ8V0Tg50cG2POABBZH016BcB430N5Jvrr3pj/QlEPMaxEXSwCkuVCrx7hDn81rG7/fJak7nq/S4VQnDVctVeUrTF2nO+4/EYjF9Y/zQ4GrFhMY+5ZznBbxYsdE4eq8/u7Wot0u1irEYZNX41fiSsW+KsTuP9xm8ErJtg+Lo5QWO8T2L1o0FfY8aIeVzoiEE1Vx/v4HfS4VDj3OxG17+rbEfSZDKZTCaTyWQymUxbyX5Imkwmk8lkMplMJpNpK22FtoYQXNFiVdwOH6TE1LQtOkmVzoFsFSVQBritTq7l9jWci7Nk0OuBh4MZtt49cbscCGOLCEQMwIqt4QioV8pd6ECUj86uSqdB2FtSy9mrAW/m8VwGVXfAeOsayAdYBFJFd6ng5J45meoh37+WI+51oS3+40M5Vh3tAsXJtD3v4bIbOgreuuEsR4IjFU4AgnSTiKRxWVK31wK3AOsVkF8GpCXasYFC4DlsOxXaQ/gJPK8MctA6Pxfa0D19sU6PRUK4YaXyu1N550Kb+YZ/EkJw3gqIDguD1xOFDXT4bIhEEjnFd4HxbAS+x/WLGs5xLfqXMUB2F05lqJgcDpyjHZUh3dEauCQu4PJaMJdgRIiexWgPPoLzNJDXYknX0nuS9y5JVu8UpzgCQHQJTrJzYGEejX3T0VG3Z6DoBKhVjIaf9lXWdH8tgPbSkfIWzcp6Go/7dMGFu+Bypuf0BkTQla9JqecUeH6F8YP1xSDwIxxxSDEm0PU27sJxs94+4PK7qHHO3ZZQg/fvcyCjKzWDhYNvoqNjinmoRn2xu0cbOBRYLo59iAaf0om3/W7YwOt0Dw4fm+L1sGoFggVTcxfDoZZYe0iVLx4fyNiWcLSi+Am8927lxROyI+F5dOYsiZEDqxuirT891rGH3V3icLq+CxfaXkfpyHG9gnGYJyZaTLri2ECkmk6PdEzHLRyPimAeiHHcpIv8/uxjObg+PJIT7XevhI4uU7n1dvDdhkdFyp9sZP+B8i66bddLvc+Pb+RiWW6MNXhPoNujXc09B8dH63RaAVulyy3m35ATPwU2CddpLIXW8/mGUuKsKLfAeY1u61zIKlk1mlviGtg73sMv4QaNfk1X7QJuzKXDEa3i/lzNbwe8mq7jKLeKYyOPM6G/lA6u5kBhF0B1b3CUItnRGmWvr3Vvih8KMeZfOrGGYnXPKuA4ANBiX+IcGRb6EZx4icKm4e19J4IrcoVzamMcBepWRLl1+xLHuAocDRv3tkfNbUfSZDKZTCaTyWQymUxbyX5Imkwmk8lkMplMJpNpK23n2to0Lp2vtruHsGvaieSw2sBFKE60dVomcIkCyTCZIvg3HIVGgC5GHSGUGdClZiEXxShBgFUGpG+3+ROgKDkYyzyn+x35WCUDgvluOOQBI0o6wgDoaEc0q6TD4gbtBGdEPMsn94N8NLVz08kqA69ulO/Ta2UwRRDkB4fa4h+MlS4DnV31zlEMzBTBpBs4hbkSCCXQ3lADkwLy4tekEdAe4Ax1D89ZAJGia2mlNlKjPdawKktTOsjquwFI7QLubtNrtf3LVwi4jDYbn7h7kl+jFX5JDFLpFP2oRAD6zb8gMWgucXGgGhv4Da4BaxbAwdG106PvNS3qEeDc6B2cP+EMmeVwK4zoXgncD8+sc6Ilqscaba2CQzDxNDZNT5SIqOB9sa0hrAOtJ3i30qksIuBKEWovYCDpwEGugKNjhPek63GEBl7O1DZKRJVPgaMd7gvrOt5foT4P4A5HF1KH8g9wZz0YaFwpr0/X6X/48tk6/SoWInUz1xjDYwgebXy/p742RBlsYGIFULJ4A+i7U90iU6DIXOgAqceYFqM/xsQKGWgb3D8dCxO8Q5ISnwNKlRFxg5MknMpv+2HAQMnA2WHDtRX9u4Pnl8Iw41Ljoe/CoZcu75ir/QTzpgOa3UMfn6gec4xPfNc7lXcuavthgUk7j99+TCUAuR6j/Z3saq7cHahv9GigS+N5zGER6o4E7wZKBxf02yrjGJwgv56TGdoX3TvdT6HFxIm7+sfBiSa2P/vs83X6Gm18gSNKnVh9n87qxdtwzjuQ996l+aoM6DQa42jEhtP3EhakGRw7Hwrb7WKMixAKoML7VFj/JIEO2ECNIyKqxExb1Bz4ZEMkE67FAbh6QH7dEkel0F8C50EMDRXHno3zRzzmA/ySEyHXAuk97kvdHrPBeoMu9BuOqMCyPdY/MebWJTDjEmunBm3j5EBIc3eE9Rx+13iv9kCUvFm25ULzafLP6N+MVhFSjYf1XGMpF2Apf1904Nycai4e7+v9Dh48VN7PFGWgcfpuiXVR509wNbcdSZPJZDKZTCaTyWQybSX7IWkymUwmk8lkMplMpq20FdoaJc4NdlbbwHsdbbv2gPE0Szl/FnSJwo55s7F7ri3YAbCnEciKrEAQ0plQiZoBU4lxIGhr3uJxKRwg6cgVOzio4R4NtsGJuhER2cD34CznBgzeKkwroLhjbKdXDIzu6a6n8rhLVSG4121w4CsgHwE45kFH73x8qC3zAKSZTlkkoCIgFw64Q9QQuQCGCHxwAycF0nFLUDAwLt3nHHFWoM0LYg4ozgiYaw4UZcoM4LvERRnwdwY0+2Yq1Dq5UnDexUwur3cp772LWwSGyGKAcx9dujwDD+N9QPe4mtgKETdcFIBU1XDbJHLKP1F14EYY5qsMFUEIxxSB7gc9Of4WSwTSdUCngV6kDLoOcsQDg5wAgZ8v9dw4Vt+PGEQadnALoG3zObDrO1Tjglu0qE0DR8s8RzmjXuhMOltojG2Ab9ZwsB3AfS7NiRmrTmdnaqMp+uzjB3Kr++svFIB8VKzGiqMTlr/ud7T30TpdzfR550gN8uK12s7h4PE6/dvv1Xf+7XM5eZ9fYz7xrF/dp9ujizCdJ93/Dwpr52Iek6jRdzgPbtCGGIMKjMkNsORAR1q01xL3TxiwHg7FMCXe6PuhnXsCBopAN9A5xvKN+ZGfY/4CvpjA5dcDCeTtSziyw+DcFXDZTOEKz/7YVPfjvhtCcEW16usx0LhZTddi5a8P1+k+3I/HA40vGfDuJNMY57lu2cCPOd8An+P8t+G0u/o8Aia5MZRvBDdHEvMgkWqioBxLPcb4PNfnn336s3X6FVxRv3kBfI7HSehCWdzPmQEfRS7LV+0xIaqL+SbaQCJ1SUK09YMP1ukMx40irDOJnFa0E0U5Mjh9hH4asT+2aCnnsoCxJAB1946IOuoOA0uN/lJhnUXEPsLxiAZHEqIScw7dwdE2+0Q30/tBlEPQcTjP5s11C+ZND+QVw6era/wDY2+JPjVAPz080VGOABS2qdR/OYgHlFccrfp+oyWMc324Yc+0lmhwBIBu502C9QaiEjRci9FJGgXS20OkBRxz4TpuzmMI3+l3W7Pcfp1jO5Imk8lkMplMJpPJZNpK9kPSZDKZTCaTyWQymUxbaSu0NXHOHbZbqUMGyZ0JRQqJMCMPbOW6IqoBFAf40U4qBK4PDLFcags2AFvMgVk04GKiFC6Q7d42UaMSeADxPSIJIHQ2UL4sA56agxcC3sNA6ssNV7C3o4IMHB0xWLS7H9W1c5OW9osQiDQHktoHZtzPlK6AONC1NuBvEiQ7YEzoInAJEbCYjDv7uCZ0VDDL1tUyRvmAMHVN/RN4gAcKFSHoOlwKYyDKnbna7BT1lSA9m+maslF7n0/0+eACzpMXwgbuUt4Jl+kNFPh5MlF/KYANVcCSGRy5QUuLmrfjKazfBn2GGEkGTLwEduaBHd86vvkF+mME5Bl9J8+Vr4O+cJIMqHkFbIOkc5ayHeGewLSWxMrQUCsEJS6mwGvvKZB9CM7d3joDds880ZW6AVZXoK1XS7JsQKo4zGNMrhZwBAUi89Hhg3X6F5/JsfCjgRDZpO0/O3Cp7BxonOgA+1o4zQ+lKGN381pl24s1ln788GCdrmEv+McgZO4aDt8RxqQl+mkDB8Kd/O1OjXeqoIDhSUKUE47iROwQlJzOgYsYfecYxzrQdqd4hV4K1GoAB2ogaD91tqRZD6Log2+n3p3nP+D8ukQA9gXGkkVKa0i4rWIsqeEYOQGG59F/S7p3o8zoxHuXCk1wVXv0g7aqBY5a5GhPOdZCA4xN/VR9Y2ck1CwboL5iIsp6n5zOiQhCv+Emj/k3bq8PHAPQp2OgpDFtYCOOMRgz4cjebFhPAnfMdRRm/5HGiZ19vOurF7oP2kNxo75fR0R0706R9y5v6yMFZnyNQWjZMGA8sN2B3m0Ep/oai5VUU67rgPGMGHieIQpyrl1QB0BCo7bz1ThWw4gDdEBnf6wTuM1jPVOTY2b/whhT8igM3UzR+4sFcV00woLu+1js3bHW1CZwfZDYrkZfiHiOAXkNKHO6uW703x31zUFX81mN/hgB0W48nKZzOPS2+aELfsO+ifsFz/URjqpwHY05v8HCl67anmu3nvKS8WjLhd6pwUC/vEEaDq7vKtuRNJlMJpPJZDKZTCbTVrIfkiaTyWQymUwmk8lk2krbuba62uX+yjnnXJgI18tq4F+RkL4pt5uBusXY7u/VCPAK3HFyqW3y6zfnuoa4FwLC5gjKHAN5Cflqm/am5KsCJYBLlcuEP9QTXA1EqtsVzzAcMQ30rqd36pypPCpHF1u6C0oMuh3dE4HlvLAvujtmCOi+Mxba4bp0pkLwa5QLHTYZJrob4FwHrCti4HvcJyHSAWez0KJOFYMGg+3YoBmAUUWwKwwxMBb8DYW4com81DMGvyZaoOdeIj8DuHrO4aI2fSHnybtUcHKEXAYErweXXUVqyBWwMBr+eSAODQOdR3CFA1oZlnChhWtZBPfCHtC3JlLbiFt34w3HXbTzIeyaD4BkfPahnPPmCFI/v6JLtJ6zhMMiA6OfAWtfTlQ2fL9uX20276v91PdjSuec9861CFZJXA0DwKISjrVAwOllQSQRYyMQqGWh79Ldd7nU5x0geQ8fq/2c9DXGdbtq3532Pp0e+iDxb/9ynf76mYIgX9wIu/7yn96s0/tDYETAl8Z7ev6nQfjcy5nus0R/nwOv6qEtd4Hl1sX9IMrOy+2xi4DTWfp2THGGuji7UtudLZS/q0rv44HAjTE+j+GKPJyrvPpDpcddzU85xq+6Zaqrko6GaEfh7Ujq5Y3msjeFxoPTM73HxZurdfrHa70TDBbdwqlN3Zzr+sMnwpvnlZ5VY26Pwv2grc67tWM3xymaUsdoW4OR2u7BnhzOiXjmWCsUnEtQvzGDgtdwlOY4DHd4T/fGtp42sT4lQ6Pyr7FWampdRLzN5wh2j7F80Fe783CJHMFt+/EHJ+v018+/0rMmetZk+nbX9jtVEO53tC8HTgcH4QVcrzNg+keH+7pNQrSa6wA4/iNN1/hAFBnOm3S/ZR+7Ne6NedwEyHHMc1AxEVo44sY4kgOMucF6asm+QzfXmfI4m2qMrYA603G9xPoio/P5ncq7pl0XL4GXk20lhuvhzgrydMPxn7fJhxo/90fqv0kHRwDgzt/gqIznkQGuaduPG7pho9/VOEYW8xgQcHi2kTiwfumSneJzRHyY6bmDIcahHR0zmVWqx7O56rFYbj8/2o6kyWQymUwmk8lkMpm2kv2QNJlMJpPJZDKZTCbTVtoSbW1cv15thzYOrltBaEsAZpTBpaheAkPFbvAEW7adhTCt2UzY1ZtLoa10j6STZm8KLEE7uS5rkdaiBmIKl7l5oe37N8BylkBeSzjL9YCx9Pe1Df6zpwrW/WfZX6zTdLhkEO0oQ/BSbNHXwJcCtrDvUsE5V7ZISwknyiE4ACKpDbbhXZdICrbAIyEvDKSe9HSfBQKHz661lU5zv1FHmEHeFYJyG3jeMwBsoa15mrZWC5VbAfxmCZfKKYLUvzxVG5jNlV4AMYsbtAe6ssFB6+ZK1+zu4j4jlcFdKjSNW7bulZNzPa8EqhrDPbLfF95HTnNZqt03aIsR2gNIUZfAnbXTVb3vjoSjPTyBwydQidv2dgPn2xg44tFYnbc/AB5b0zVOyRnedXKp9uWAkZdwPOui7qZwLCamPobD4ml1qvss76c/uiDUpZzrHWK0rTHQzKpA8Gui5hgbc7xbP8N34draAFHaH+qa40T1e7ijjrWHYOtHx3vOOeeykRCwGM5+56cas68GcDC+Vr0cj1XmCZzzalD1GVC9Bwe6/qAWSneKeeDlmVDnOIFLM64p7+nIQOS8y9pxqgumbQi8rAt0voOxnuNaUamOzm80Tnogsg3cCM/OVb7n0x/W6T7G4Y+fPlqnP3wqV97sdi4kGo8+lcDp8AL96w/ffbtO//aZEOXLG42raQe4H+lFYL8OXXY5xZwIR/RsoTmh7hDLxPmTO5Zv+5LHeJihTrtA2saZxqmDfbVRnKpwz757tk5/+0rY9zhXOx4fKH2yr7H0eF99bNxT5yBVl7ZMZMDRGIexju6k1+cqt4sLrd3KBfog2mOKIO0nT3TE4PFDtSkPt+3hjvJ7fCik9Ify1TrdYBy6L3d6553z7fgxHKtsj461VkvgtEnX1tHunm6DsfTrH1WPr4FiPz5UWRw/Ol6ne8AjGTnAN3TnJB7ZurZuGOXiKMOCx23UqRaFOtJiorG3ADJ/faF+GuGY0QCseYkxPMX8XwAvn+LYToArfKjuCVF2q9Mfzm0Y8rtA/JcMMV2JsW4hhlpjETHsae47ONDxCZ+qr03xbl38Tklx9MXHur65PfKUEndVHkuuXTeO4qHigVHzSIrDeingSErGI0049jcErnuExfbXX36/Ti+ANNPB/V1lO5Imk8lkMplMJpPJZNpK9kPSZDKZTCaTyWQymUxbaSu01fnaNelqO7+utX3ewAkxzLVNW9Geja6PQVuwA2zHDhBE83yhLfkbuGHSVXIO7OcIbmIDoAjpaPXcolReTs8U2HqCwOiFYzBWOGwBQ53Ola/FqZC974C37O5pe3yYa1s5plUmtq0jsp0oywS4yF2qDsHdtFgqXSJ9AxQMdVchWDaDlWYoZw+0YHIlzGL+Uo6l19eqx4gINNzS6kPdf9wV0pS1ro4BmHGI6QInzORmqnu8vBTyeXNFXFpIT4ZArktgXWWt/J7OkHds/XvgW1fAZU+vVTYPgNXcpXzkXd5y4gy2SyfeBRw7F0BYGTA9Qd/kiNAQ58X9s1R9NoLLbifXc3eJVvaAyLQIzgh9fQrnvBnyOJ8qMy/+IPe/G9TFFAg8kbwYfXYAxGt3R9hRH222ieBcR4e0hO6n9CO+O4XQuLJ1UOMY1OFY14ABTJWP3MS9uZoAACAASURBVAFRGqtOl0CUpkv1jQCkOceY2QMik3aItSkPvZH642C0Qtb6QG4nQc8pgcOfwR339VTpc7jPRh6BvoFtlh2NsRlQrgxIYJiqbEYjvRMDnc8xbhXz+wmc7b1zWYuv3bq3OudcF67QY7R7R+weqB9PEtQ4kjHq6J2nmB9fE38FnncF1+mXwNp++FZz0metw+berj4b76l/LyfKzOmpkMw//CAn3meXqvcZxp5RSUxe+VriyMAc/bTACYAI4w2dJysEA6/vCVF2Lrjmth/SGROYWgd12oUL6BTte7ZQuhPr5QbAdqOu7nmFIzxXN0K037wQEvr4RMjl8aHSvdahN8VzlkFt59Ur1dfzF0p/91rofmiA647Ur0+ePF6na/SjGZzac5THIVwiHx1/vE6/eKb249E3m+p+xlXnnKvbsZzj3meP9D7jrt4z5KqL0QOV7T76xl4qdDmF0/Fvv/9ynf7j139Ypx99IIz86WM9t4dg9xnctm+TDcaoy1r19Rp19803Wlu9OlV6AQfO2Y3a1G6OdSmdhvdVd/tjjfFVR+306lptaYljaougeSNZal6+U3m3ZlsDjWEbHHPyHGuAv/NyjLe4xPUQceEmqH2/mmiNOMO682ymcvkY420Hx/3yaDXOB4xXTQcIK8b4+aU+Ly712+TiTOOqLzVmjnvqXzsPhY4P95SOO2qz3b6u382Enbve362T2UCf10FjwrvKdiRNJpPJZDKZTCaTybSV7IekyWQymUwmk8lkMpm20lZoq2+8S5ftdj6cTyfzJa5BMGP8Tq0ZVBfRQLsDbbGXsHB78VyBM1/DVbPu6PqAQJ5duIkWyMNtpPooCClaghK7nOgfNQKXX8AF029ElYV70y7cEF8K2zg8erhOnzzUe/e7O+t0s1E2cHZicPjofhCs0AS3mK2eM0VA5Mxj6x0GXJ1G5cKiXcKB8exC2/rnL1V3VxN9PgGCdvRQ2+0PgLlWcIhbArUJLWIXAzGYTYUenKON/PBGz//hlVCBOd0ugTLWQLAKoMu8JiCIOWho1yfWDRex69fKz2s4m96lkjhx++MVgjM4Al4FF7BvngmLOr8QFuM9kEGgVjA43ei/Dlh2BaRkgQDrk0yf/wAEag+BkKO2jDzc8ubXQpuuSrWRCTA5uijTHI6uuURXMriyBaDFe0M14J2+Pn8JB77iRunLC7WlJRDcu1RTN27eokMMdM7yHwChrhG0OO5rfNnZ1/ucwY2xmtM1F+j2UmVx4VXul6+FCxeHcPHbVTspW4zp7FQI3hW+908/yN3wuzfKy+UVKw/INxyqT+Fc+/pM3x0ONfb3OqqLG7xHH8Glfab717XyNqnvB8HyzrlO63bZ8arHnVz11ccRiIaodKxxryjpuqx+EgrdM+4pTTfmAEfU8kbveYl6ej7V/Xf2VgjUaKg8hoCxBAjtt8/hznqhPjKfAc3CUYmXE42BfbhEOvT9ARDWUVc4VoZA2ws4iPa88jbD+HyX8s6vj6GkQNcyINddjGms092h0McOHMvnOG5RAel2OFbhgdFXQPimBY9M6PMcLqBZ+6yEzpQYryYTtIWl0MeqUf2mXeXdIbj5YqrnX881Hg5rHNtJ0DcxDu3tqz9uMNt0j27uZ53jXHC+XVvVcD6t8LwOXDJh0Ov2vN4td5q/PcaaGdarvQ4Dw6t9f/vyxTp9daO1yEeP5H57sKO10K1LdbFUmV+dq99994Pu98evv1mnX1+rXk52hdM+evpX6/Turt4jQt4LRF24xPqniyNHi3OVXwJMvcH8X/l7qscg9+QU42GF9WqMdbMHCh97srCqYB49qICj/9u/0zr+W/THUV9lQSz46bEQ6H/5VHX64YerzxOsnSdnWOcUKuff/yAs+dm52oiv9ZxRT+mHR5rPH8GW9gRj/+5I+Yr7rHddv3si9+JOLBx7WikP7yrbkTSZTCaTyWQymUwm01baakeyCY2bVatf0mGuX7YdxGyD94a7Qqy4qsJfgWFAc444hi++0y/z0x/1F883PMSLe4ZIf4XYH+MvIzSB6bWviL+UJn39uj9/rV/f02uY6uCPKynMcGb4a/aDSs+P8FfGGf7iVTJ2EA7Wp9iFa/BXyYYGRfcUl6d2zk3bv/A02F2aIlaQw197HOI5zmF89OwaB4OxOzlFuVzhL9f0Ghos1QYmHeyKvtFfh+YL/aXssL8ySekgzuTNqcr8DXaRZnOV4RIx8S5udL8l/jrlsUvj0YBpwnOFv0Q2OMJNc55Rjl36Qtdzt/QulaaZe3jy1DnnXFHqL5gxdl4fPtb7l9hmLrAbkuCduVPu8Ne0wNBC2CmPsbsQYOCT91VPvS7jG/o27/or2eni+To9RTuq8JfFJkVQNpyU7w701+8RDGNOjvTX9cM9XbMDA6cJxoSLGcwE+Jdz7DzU99Qfg3OubndWM8T+291XGX16IpOgwVCfL7Hjf4k4rSPsknQeyOThCrtEF5c6VD+Aec3DRzq0f7vj7ZxzDf6aOb1c7W7fnKm/fvWddr9/QKy6EjtpIUP5gwaZY8dgiB28ZqTyxybfhknYDuK0Jj3smqLNVgFjQnE/O8tRFLlea6azCzONXbS/Md6tBF1TY9dnjrkyx1/gX2Jn6tVz1V0XO+6fP/ponT55orp7MEb8waA2s9vev9PTPfIcZjuN2ks8UNkePFScw/oSdY15rQTFMRzAxGOGWNAd7l4pPQQtsFioPBZTGIbd046k894lrYlZAlOYBON7D2uCIf7ivzsGpQTy6suXGuNewFTHIyZfClMyxousuBtSqByvUS6HLUoSI1/VHAROAJWAOet77FQntebHfCh6aowx2XURS/ZEbS1JlN+Avsmd6CFooybBjufknkxanF/v+EYYPDLu/KKNJiDSIpAuQ8Twu5mq311NtQs4K9VnmlT3eXSscXs4gMEcdqi7Fei33dV9Cqwnr0BYOcROfYQ4nidPn6zT3z4TefTqSt+N8N5Hh8rLTqr7LGHykwT8PEBXCzPErEbexzl2n+9S3q1/qQT0+diRMPP/ry+0YgxfriHw2+HZmfpmAwoq2tf4WYOSeQYDxxdv1H+OMA4/PFmVRW9P5dwJGhu+/IPWzjOQlWWp6yeYEwrEhx3i98UM46EvVF+eazesx0lY7A1gHIU5dPFye/Mr25E0mUwmk8lkMplMJtNWsh+SJpPJZDKZTCaTyWTaStvFkQzeRcVqezh12spPcgRl8dqyT4FBRg3wSBwo/e03Sn/3UlvyAeYDEeI0zWvdfx+Y0P6e4qDsIt5Z1OYzTbE1PAR6AWzz6hTGDsATDveEecQdbU+PD7Q1fAxDlSFwyi7eI3VCVyIcjAVp4gr8o67vB91pmuBmi6LNk/KRgugb4HBvGgP/SPQ+52dAe5HVEUwxGCOq39XW/4MDoVEHQHcOUaYOdZ2kqzptgAItECvPA58bof6HQEu+/UYH1c+vhCcQJatgHBUjNlYPiMSkVFvqAIuNgJR2um9HvO5SRVG4b3/4wTnn3NUpcCk45ozHKudHh0JYzoE1VjDGoRlLBFSUsWIztIEO0LsMaCuPuMeos532muNHqpcKGDCy4hpgbzXiJU6AKO8PZFTw9LFQlH/x13+2Tn/8kZ4VF8rLl99+v05/809KX84QK3aCOJwFXLruUJH3LmvLMQeSklZq0ydDjTtPP1Q8sPmVkO4X32v8PB2qLe7uqg1cXmqc+iNiVn56pGsOe3oWce0a7bg/WPXZ/IHy+M03MiroEjuiuQqOFTxnmwI6PgA+14PRyiDTd/dwn50PVL+Tme7zegqDESC4DQfcO1Ts/RpdPQTKeQTckWZAJY3OYDqXnsFcDicdxsAHl0C0H47VHv7qYyFuOU0xdoCrIkZh1h5tgE+WS2AW0oOx04MdtZHHR3r+6bXa4Pm5ULo5zYSAvBZAegd76r+cHxLElyRSmnYxsizvJ85y5L3LW7OfDcQRpmS7Q+DKQFu7tcr8q2+FzE0u1Ra7KRDALuNGA7nElDFHDL9iwCMJKK82bh2P7SQwbcqR3/gCfQdI87LQvLEL7K0BLnuJeebVtzLUGu3onWrEbAwZ8OYxYtVyaRPupz+G0LiiNfVpGsTe7ase+0D6ZjB9S3C8gSjsPsplD7E2a8yDZYC5Ftp6irjMEfD6gDqLW4RxiWv3jrS2PYJJzxJxYi8RWznB0Z44Uf12cMSki/Lo4vjVcE/vdMPJGH2QMaX30JY/eCCTn7uU996lbX+M2bbQN2N6uNGwDvNHF8c9JjcaYwuUXQ+mYyfHGpuODnUUq4S52NW5+gPjd1e3wwBMq7qHajs7F/pN8UfEWq+BeS9vtPZwOALYPNB39w6ertMDmjbBhM87Hp3TfWpHQy21h5s/Yb1qO5Imk8lkMplMJpPJZNpK9kPSZDKZTCaTyWQymUxbabs4kol36c5q23iILfNIZIsLE/02jXuI7Vhoy/bNtTCj/QFcCr94qu/CmTDpEA8VQjAaaBv6aABXuhgoTLv77Z3ye6idYffJQ2EDxzvavr5E/KwM7mvHA315F+jd7pGwQboq5pnSjI0VA3+owHk0cIei89KdyjtXt6hmDXwhgpNmlsBNjngAkN8PHgqpOkIsxoYGWo90TZe4bECMHCCkLKMGzlrVctneG/HWGtWLh1Mv3ah8R5+nH52s0xcXuA/cI6dLPb8EfnKBdldUur4KdBZVPTL22dXsfpDIsizcix9XsaQqxNfM4ZTXAR45HqHPOrj/TeFKN4P7K9xZMziejeCo6OC2ORjAHQwEWgRmutPGez0+gntlo75zDWfUKeK2BcSB3QEGuDvUgx7tqG8eom/2iV2j81/AUTiCLV0B1HkCnLWq7idOlo8i123xuAWC3IYEbsKJ8neAeGAHj4TzPoVT7XdfI34qXG4ffCJH1s8earxrgAztHej+HZRpmqqu99r4WZNLlWGCdgcK1T3sKF81+i/rcbpU+ypu1O/GwEL/8pOPdc/HitVbA6l+dYn4mT8ILfyO7tnufpRlqfugdbw9HqkM+5ibejiOEcFhdmeHDuQq8xkQuypW+X/2oTCy4Vj3zFHXvhC+NQKi2uzCibd12FwQW0b8wS6wu0dYLtQIureb6X7XGG9vroXQFjgacAVL9P1j4bJppOdeX+q7IahPxBhji+X91GQUeddr8eoMa4kukMgdYI1H+0LKIrij7uwAodyRw2nIgcBh3kyAkHqgwCPMbSdHetbxvtYuo9GqL2ep+vSwg7hyQ5Xhn3+AfCFGosuUrzGOCu0MlO4Bqe4PsT5Z8PiLxuQu3qkLx3W6o/t76pDeRy5r+1uF9edT4NRPj1Qvv18qll6NehwCCx4k6puM2RnBbTuK4GCLd8OSypWl1pcdnAuK2jadLrHmBeo/Hmg9VfR1w/61+vrJL3RNk+qausY8jLqOvcqmAFM9u4BNdgfOxIfqsw8+lSP4YV/lepfyDmt6msrTbZ9LZaxbfMr4nuh3mO/HcIv+688UW/Hnf651SQ/IOl3dv6lVjzVw5LgdB0OscTdNNQ8++FAN4xcwLb54rd9GnTFcoodqA8cff7pOn+B3R45jEzGOJ8RoP8kljoZdaY0wgRvxZGloq8lkMplMJpPJZDKZ7ln2Q9JkMplMJpPJZDKZTFtpK3YyjRL3YLja1s4ioRKzS7BjHSSxrXwGVGP/UL9fPzgUajWCW2AMF6yCuBeyTIQv8tqODUBzinb7O0IQ5thra/oQbnZ5ru8dzZT3+USf59z2BVqZp7pmuCt0JEvpyqZ7BuB+AS6CICJd7e7HtdU77/JolZfa6xldMKlpAKKMzyM4do6BbTRAmhLwHAFBeCMEQ41xHzen5RZda1EYt2hDCXz0SqhXhQC/5Uhl24dL53EPiIgnjiUsZHYBRy4wN8tEdX1GTA60Yw3XOxfDpZAWpneo0DSunLfuu3AHjoGdzRGwPqDt9hHw+glc4c5v4GI30/Vd9LUBgq37UnXwAH22i/cfRvp8v7/CL0a5cJKDA/WXT+YaD15fAvMGFpTC3bAH3Gx/AHS8huNZBSRvoRtVpe4foY1XeO8GyJ+/pz+7xVHs+t3V2BcKOBEjoLiP9J55QDD0HZXjCKjoEu85uVEb2Hso/GgCh7gUrnCHO0JwxnCa83hufovioqyyvtCag0jtIkVby4H61CUCMeNdoz11qqdPhO48+FCOhTnceq+ApneAeE3eyFEvKt/uOnyXil1wg7ahDjJ2euBlGCJAHroELt45HMb7ME50aPcOjnsxxiO6naZwjOzmmHsqtaVl66xKTKzGuNeB4+4cZZgslO4gkDvMql0fVrAchyLMg3lH95kv1GdDTndGzI/Ay+8LiYydd6MWlx6h7eKkjhv11I73hhiD9oX9PX0q/JoB05cL9Y0l3IprYP0edd3vqLzGB+rvPbj4xnnrTj/AOIFy222EZHaAgndTjHtwic+83q8DtDbvqa4TfE63/gaDdYO2H6PCkggO9hvt+g7lnYui1fM3e47K5fhEjs/fvfpBX810TYOjTQOg/vHGhKAnxBGQV8x9S8yVfoE1RK3rQ4vUNnSNhVuwx5qw19HnEfDyKLx9bVk1b3+nGM93NdyFMSeMd3DUrNSzHveEUocSjOYd65b+zTO1ywWO1QQ6/2Isi/F5VamN7gL3/OKJ+ul/8fOfrdMfHOj3yBLv9vpruZOPE5V1M0UkgOXqueNdPcdjjN/FOJH/mcbp+gnqaKoxk8dtBkhHhY5yOKyXo0R4M8fJyqvMXjxXFAOPqBo8rvWush1Jk8lkMplMJpPJZDJtJfshaTKZTCaTyWQymUymrbSda6sPLo5XW68NECyYdLkMCNwSTnwZsNGTD4Ur7ewJLXAVEEoEoy/gjkU0KCAgawxssgTmGie3AWn1vRrb931gRL4EhtnT50c72uKOYL0VYXvcL7ElfSFEx3shAX5XW9XeqWxCUFnWgRjP/QTq9d67pMW7Oh5B5Dt65wYIRQP0hARBQ5wDOIsHOuZRpz7Hu6EefcJAzBv/Y52MWmyyhKtYBJTy7EauU9GZ7pcC/csivV+O9BCozxyNuQpy0AKN5Tp4vxI9qI7CWz/P7+nPNT7yLm2RtQxuuhH+PpQCaUuJ9AFb6aK/fPEEwe6BR0ao6/0h8NCZ7nlyLMwlT4SgHI5VBw8frZCOwUCf+Vq4RX2ge+wDHyuR3xlcPR0wnh5YwZQOiEB9pxdwYQVa2aBh17hnlKgsM/Rl587dXcnHkeu2ZcQQ61GMcQyI2M4enBmBUDbA1HZGwIwHcJ4cqb56GMtiYHIHJ0Qi0X+6cAftrdDS3lDlfNBHMGsv5Ga4Q9dBobIp+l2KDpYgcHkPuGwCJ94IrnQpjg9cnspF9vX5xTo9LeiGfT9HBpoQ3LJtp3O4bydE3RIg+EDjYg/HW6Cqfcw9DeaJGP09YEyMU47JuCccuRdzzU9F64iao69xbG7g+tzBvReY/xu4ISaYE3sYbwrcJ65VR2Whvj8vNd52UdfEbiuWQXxPRz+iyHW7q7aZod8Ne2qXA7xbv6M6GvTUvjNgwR5j8hIO26UDEkq0FfWbwmc4y1WPPM6Qtu6kWY72gjLvw3G5g7GBcx8d3BtgcgnchaOGRyh0/waIu+N6EPch8hljXO3l93T2w3nn2yUu1zBRA1QYqOoOHKIzrCd9AyQVzpz9vhBPB+y/4RoGU24FF/iAIxM1cPCq/QJx7pIodKw1ZHcMd/YNd1YEo4+4nsSDdEtXA2mOgI4v4SbbwdrGjfR+dAa+OL8nRNkJly6BZgb0zYBBqwlYi2Lt1cNxsgd7Qku/+FDHJD55pPYwQJtZ4gfEK6DRKdrJJdz5q0X7rErjagx8NMuQ3uEcrvxGJ/qdFMGJtiyF0EY4xhcRl4YbdMB3a7jyT9GuahwRKrFeelfZjqTJZDKZTCaTyWQymbaS/ZA0mUwmk8lkMplMJtNW2gptDXXjmtYhz1dCl2Jsn8fAUGNsAfcLIUqDobaSc+CJS+BroabLmbZvl8DRYjiLOrhcNUCD6vYV5zfa0q2W2NJFoFrE1HUwk3MVgvYOxkoXcKVtYmKhEt0m6fDZIChxRO42VnpR0LLv7uSd6iwHV9GFq1RCFAnYX4LA8BGcWhs4lqZknWNgFshDEvA52U/UdQPntFuiKcmB6wyFEXXzN+v0DdyuQMC5BkG5U2ARBWqsB9Q5B1qbwckqp+sg6uv/ae/MmiRJruvsHmvuVV1V3dPLDAaAQFLLg/QA0z+W6b/IIEp8IUCAhM3WU9215xoZq+sho/J8ZdYQO8FKo1nbPU8xOVmREe7Xr3t0fH4ujD/dCPGbHcnu0zu/x5uGseKyhZtwgMtth3ugM+NirrEcgJFdXLzZH08Q32/OhfScfAOkB2hWmqntZmNd2/ls0l8LXCfhIDcbCrFI0BdpK9StHcJB9wGFnUG6deg70DpuXQifm9/qvombxRHdZ3UNW3848vE5inzk8t51cfYLYavdg9DMgFzXFShi/hLYP3Cx6dfqo2mhMXV6qs8Hifp3diG33Aa5NIK7IhmstnfAi+HYOX4hJLYCpkjkeILj0xdCyZJU/RsPFS8l3ElbjKkWeGqNxH1/J2xyvRRqxK0YTxz+nlHeBed7zLTaosg3YihgDCa4DI/xOMa8EgEpS4Ay5jHzsPJaQJbtgCh1yAkb4E2P+SEGMhrRRBtuo555L+N2DH2/QtHzEtsjAlg6bkMhXl5jGwRr3Ufc7oH831SHuwt+jrxzLumxzfVWMXQK3LTGtpOu+bR7ZAxH9AjbN2K4bboGTssoUt8BTevgftt5ukgT1+w/A+L4pHWwzkrQzskA24nglFtz9wBcPduMFpAYm8hPKfJ5Atx+DNf0KRDd7q9wifwchdC5uu+b7UL56MErR4Qp/gBkZoW4LDdAUksd+wmRY/Vp1QFDLJUHWriGlqXmnhRbBqretbVC7KBbXA133HiLdc4M2D+WG8zfKdaZNaoucA1cADV3WEeNI2xr8GrLWa57vUN1hefWY34MJZBNtHN4sudNhx1xXjDXJ3Q8xvpgjJycY0GxxBjfICcUQLpn2ObRPrZFgHt8B7f7hFuREHh48IgD13FYf0bqa6SPJy7oHR422rVibXX/cX9cwtl+izbY/hVbP+yNpMlkMplMJpPJZDKZDpI9SJpMJpPJZDKZTCaT6SAdhLZ2oXWbcocFjICqoCano7lTwrfKcGlMx0BCPV/lohh8Cfe9DyoAWpfEm3T6AZDaVdAr+e18hwLcruSyOIObWpYR4dT51sBmOq9X2XmNQr25jvnaPEbx8CcWeEBEfI3iocSHgFH4Ag37nIqcS3okrYGTVQL8Jh3CrRKQDDG1gA5OUPw6NGrfgO8ncHmL4BDboGB6AFcFcmGPP2atkIQp3N6mI8XXtoMrL9wIWT+5WSl40Fuuxr+tDHCNCKknxXw7fD8DggQCww2SI7mZeefieNc3MRClFLFIB1cPnJQOnwVIhmKtceeGuu5qLOTy1yh6PQTenCCW2gp4JBCNpo+lAMcwkh05MKcIjsLDqdD4ERzG3r3W3zZA+fxavz9HofO7lTCPB6BkZUO8R2OwBRLmgI48q3znQrz7/cFUcTwbCzeNgNU9AM+9qIEu4VIvRto+0ES6n1GqdnxxjvMPibDq/A1w5RZB3UW9O+lCbdjA5a7piEQCexsqT0TIn3FENAm/Q+QG17Wd67puFw/741UhRzsWHidyye0Xz6kQnGt6zrMBmraB6+MIc0CN7QMpsbdK90/nzwxbBjK49dLRl/losdK8tQIGNwcyPXvMm8Qd6aCLrQmu1LmZM9KRfp95j8hxXWDsVJif8f0TzP+BjuVg9ULL+eE4SGTbBbfokcQO220e4I5bAZVucR1diRyL8RBzksH3G8x3EfBQoo3NAngk8jZd0PMeB28WdHd8Mnh0CNwyrJQb0yFcuomRc7POBufHPdXYkuIS5ZgIfXqSaCvK+Ytz3cdcY/ZZFfx+v8l6i8LtV8oXI2K1OLy6+bA/LksggFvd2wxjtua81akfa2wtqTBoPMZ1Cofix3aMgTLC7NO1wFObiM6++FLEdSbwTw6XBtcYA2lGvi+xtaRR6nVDBPO20Hc2D8A4n1HBOfeYDjzGBSsLBOSIBpNGg3wxiBVzP28Vc283eO6I9XnqxD2XiPvbuRqjDMS4gbbWu9zborJEnWGdu0bOxjNCBMfdslP+joHQVqyigO0s7kyOsw22K7UI7IA1T11jzVOq6kFbH/7cYW8kTSaTyWQymUwmk8l0kOxB0mQymUwmk8lkMplMB+kgtNUH56Ke0vF8jQunsojWlXhDmsB6qglCfTq8XqWb3AbIhYdjVBcDJyjwt8DOArCT4fkORfi7E6FeLQp0rh+EvK7gZOXg7LpFIfJort9scmEO5y+EKsRwnvSxUK4WBaJ9y1fbeEUPlKZyh7snfY588M73hYKjGk50G2I2cImiEx1ee8fol4acMVx8A3DWLZyvujnwQaA7OVwgI+Bbae8+5sFOZ6fql+xS/yayAt7TAqFsnuBbwDYTFh8GelYBqUIh5mWp+0P9bUfPsgCkx0fHKbgc+8hNekQmRvuzADqd/SrEVlfp85wFoWElOb8VBhEBxV4t1V9TYDEBjGpHJjHB+O3xrQ5/l8BBrYSrWFUjrwBHzECUp6nGWgxssAC+tQV+0gFVLYC/3t3pXtcoLByx0HN3HLTVO+8GvctsBDawhnvaVaHru36lXDbbCBf7yguRmp6pTfOVclA6FaIcow/o+NYC4WuAUq0LRHjvBHtzJSTm8oNy6RaOqQOg0GdE/5BXiCV3xDyR4yvk5AW2ANzdCeO5x++WsKKje58/EtrqnHNxj+W2FTFgOEQncJuFA2QNZ9cEmFYN5DrndT9xKdfnS8ybDzdCWEu4MaYJx/4uNp44qcJxOQXexvvw7afbNgJmSyyabqMbFGPvUOA9wXyCVPUk59OpvfbHsHHdkQAAHYxJREFUQVu7rnOLfrsF54ky5djEccl4VdvF/Gd6bpNA39XNp1HUDeP7QWPMYSvQi1Ohel2fQyfMwcAXN8D7N3OM0wehfOh2N8rhAoo9IR0wuWqtsVY5Xe821ucBaHQ80PH5qbDB+Qrc5DMqhNaV1e6+lze3+8/XLfIYHP5HE8VfsVC7LBfKL92ZtgOUwMWjwK0aakiOmRLzVpwqPycnmB/vexdlbAdoWqybuHVshFyC+wjAmFOmOgyqFtsdfKscU2I8Rmv9bo3tXQ0wS5fq+A8PP7pjKITg2np3Ldyqw21jHRBWNlIHtHizVpytW/XR5Vjn+ad/utLfnqnxvvvp5/3xHM8AS6wvT5GbVj3+2vwCFSKwPco3nNewZeNGY7ObY35GP6ZYr41fKgfkI2xTw5y73SpnLN5jfYUtZdfXivcFXHw/V/ZG0mQymUwmk8lkMplMB8keJE0mk8lkMplMJpPJdJAOQltDCK7tnYQCsAkW3mXh7Jp4X4vC3ithBo5Of8BiQgpUL9Pr8/MT4aT+VK94N0A0igLIVO/W1U30inkIvC2cweESTkpzFN7NR8IQ0hcX++PZC7kkpSgSmgfgmSyOCjfRhNfAAvLAmrJwnOf84MK+IHyS6zeWAYVWYdPVZrrnNgbmSnQpANOCq2kD9zeP9/NdAtffAStzw80WjlRd7xDLurPlg34nzVBgNkUswCGwAarqGiK0uq4N8A86uN6V+nwBR8EK6FfMvwW6vG2Og+5EsXeT2Q6LaYgMAnNl6fUYbq4li3xj3D1B3PB5gfvZdGrTBfo0QvtugGyNwXTkPTaaouh6DSex+QooCDDbeiG8KzjhmWkmRKoFPpfAETTJNU5dofO/L/5lf7ysUbyeDqIYwKE7Dkrno8hFgz5+4fz78VYYSgf09O38zf74Am2eeeWXDBauMRxfI4zZBoihx+/GyE3Lj9f747v3cjLc9KjR9YNi+yPcFxMgeD4TZkM/uKbAGIFDHdKnq4CRF0BVKzhab4Hirv7C8RNYpzncle5z5L13cY8BBmBXNTDvuAbqD/YxRj8O4JbcYA4tgbhFnLorom/6rYw21cTtWMi7v84t0LD2WkjsEn/nM+QJoHQlkDHWMydKvwYKS0Q5Hp/pGHhgqIHeYYtHh/Ok0XG2fnTOuceMFOP3tnCq95gHOxSJL9CPUcR5/dPoY1uqrx+WGj/vL3/EscYd6foW7sZvX+1ywvRcqPsw1ZqEvxlhvdYWcun2wOo3A8TRRLnax5wfsDUAmGeG7RR3S6F69T3wWhSv3xRHcvvsgqt6BL8CrtfCQbgCtvqrr5VXf/jn7/bHi5XurcWaZLPWdSfYVuBh/9+BF8bwdUs4KhcPasdp775ebuGsC8w5JLr20QmQ8idrMfwmrj3GfNphDGKouW6JrQy44BLu3F1QzFwu4Hh6nG50zu3WrM4512JeQfi7Bv/B7TzBc57QPayc1gc3WDv9HtskrjGf/fnPmotb4OMTVCso8JxS91trUiDM8URrFa75uf3q9kq/M79XXiW6e3KhMe6GOs/gROuc7RLOstiq8+H77/fHl7fCeP/lg/IN3YU/V/ZG0mQymUwmk8lkMplMB8keJE0mk8lkMplMJpPJdJAORFs71/RuQ3yNmwN5aYCFBbwybtbCbEq4SsWJXg2TwwtwQhvC7SsF6jP0uvzTc73WrWo4dfr+2vAqvwUqw+KbAc/Vr98KuclQGH081n2MYuBjQFLpXBtYBRb4QQ0cJrDoNxDgGmjhcyqEzjXb3avvYa57y1nTtgSWDEe2vAFKmH76nqNYbZpHdDCr8R1gruBVk4jIrz5f3+/irir1On5+I8RiXQpJCFs4BAOFaNEXdMoq7/UdYnJzuJMVcGEs4f4aoeh2DmetSUpc9Dj/XuOdd1nvMjtELFbAjCsWv8YAixBnHKct3YThxlhl+s5yrfMPYiKqipmfr4U0zVEw/u13751zzr15J7cxByRmA2ffAfDUCeznWC+3q3XubCyM5OQFXaKB9IDaqB6A8ayBEqEguwcyE8XH6ce269x6vcNuPOLsAU6yHpj7RzgQ+u03Og/ccdfAVlM6HU8+7dTKcRfjPCevhXulI32+vL/trwsIawt0B/joZCAUh0g/Y42Foyu6WlbYpgD0rgEa9ARzBf66hXv3ky0UHYHv55N3zsWPSCvzIVwEaW4dAjlFIIN0msZ8Wo0wl6DtErj4xcBZB1OMgXudcwUkb7F4PEa+R84YzoTsjWYoxg7HbI/YWWPbSoWbpVNpDqflU6CYzJOpR8zCZbblvJEcZ3503u/XJS0QwxpjcwAH9u1a/TjGHENnyM0WxcVzzIk453KpOWww1Vj7m+G3++MWsfTxJ2Hn17e749sH5cOTidZEw5nG5myqfkwG+p0I8Thfqx/jCtt/MMlVQCh/ftD3v/v73++Pf/iga3wN9G4EZ/sc9/qc6rrWbda7Nl3eAbEFEp2MdW8Dp2si/np9rTYtsMUlxZYBx1jEMN0CV96Uyuc/fveTPkfueznZjbcB5vDRRGPkdAI3XYyXEOscOdaNW+RGB6fQBs76rKKAtPIkr3JTRwy8do05f3Ry4o6ioLkienIlyFnIq3S8jZD3o7+w1a7Y6I//+PvL/fEVqgZcAXmdJIqTb77VuPoNnIgvTnfO6gnOkWM7T4vYwRLKnb96uT/+8A/CTW+2Wq8G5JKLV3pOcaiA0XW63hJxt9po/RzDzdXDld//FcsceyNpMplMJpPJZDKZTKaDZA+SJpPJZDKZTCaTyWQ6SIehra5zVehfk8IhkYXeMyBoARhKFcE9Cg6nZH1iXE56IuS128LBrQTqs4GLHVzUEhY779HKLd7Z08kpboRVxCjSOkUR+dELFQBvU2Kr4ABwXQUQzgTIZdTpnhK43jqij0B64+I4CFYIwdW9o94WaFri4TCFyPAs8Aqsga6qcYx25GXjtb1H/3ZBseERM3FKjEnnn/RYwAaOsNVMr/ubW1xjDmdKkB1xru+sHoQHrIGrbMA+VoijLbBVD+yK/xQzQtHpAVwNoyOhrS4E1/bOagO0vwc6ViMWPYuyA20BPeg6YOEeGElZqb2uac8WPo3UxHA4HABNnxe78TC+0TUOhxoXLeJxCae91RpYygZFtHHfMwReVCCWYV657vQfP93JnZLumDFYk4AY9EdCzdu22bsbNlPlmg3wmwbOhtdrXXcdA1eCm3CzAgrcadxVA+Rh9C/dlVn0uQkcQGjIHlGdAHHMgREt4fIXgItvFnAXnqKgefNpvOoJxgwn1CeIKNDdDYL5ya4C4s3hOHnVee98nzMy5AjGUEwHUiTHGlghyFbn4R7ugexzCmUB7sTDrTjSGJvCnTyfqh+batfAWzj7ZQNgVwN9NwLSVT1B/TVnrTa0boR7JGJz/JWw9gw4HNHxFLFJF8YU7RFwf88r70LPdzWJ7qFAXijQd1vYXm7giBoBxWa99DAHUgbXdIc54yRXu4zHQhs74GsvpmrHut1dgweWnwNnDRjfgUj5FoiulzP2olCO9WvEA/B2Opz/AAfI99c4D7YUnQ3UX5j+XRQfB211zrnHKZw5PQu655NzFHT/VrnsH//xT/vjmzthuwWcpmdTzVsV4rus0HZAoPNU3//lf/rF/niLLTTT3n0+Zz8i5p+6L2PNs1GAbRM6HmMOhftr1GFe47YROM7y8wHWFLPJ3+yP25fK829+qbnL/Y//6Z5LIQRX99swkqcLUxwjvoH5RuA0U8RAjDVJiTUlmsgFPANMgBePMrWpb3X86vzr/XE22LXd+vpnnTB+q/+famymuaoivPrlf9sfF/8d2zT+/n/puuAkHTvizXDvXsOFHlbas9fqo1/+Wtcz+sOf98d06P1c2RtJk8lkMplMJpPJZDIdJHuQNJlMJpPJZDKZTCbTQToIbe2Cc2WPDnVAcVq4k03GwFBQTHoAN7kt3SMbvT5OUOgzxivmuhb6EGq9egfl4TyQkgSv7esexfRALDq8pk/w6nsIhGYAbOZkJJeziq6irY47ooJwQ+xwT1lL11Z9P8tw3zhPGY5T4TV2zk163DJCe64ivA6fIDTQ16GmaxlQlRSILB2gGmBUiAdQcE/QtBQucilceR8dYk9QBDmq5VjVoaB5AUxxvdTn7RoupGDmkhxOh8BFWJg1NLhgIFgnI/3tBJjSBIjIsVwiQwiu7R2QoxGuDwXHn7jp4m/jDggxEG2SjBHwvLrWPayATUT4rddox5djjRk3Bh72WCB5qTg6GQq3oMvvEgjWYiOH3gBkLB8Cpy3gPJpr7ETAt368lQPfD5fv98cerUOnN7qSMk6fU13Tuc3N7noHXgjNpoD77hKIEhw4l3f6zsUp8sgICGUHF9A1XYwxvhD3y7nQtOWVsK6bKzkw+kcnTeSGBDFVlrreYq3fX2eKneFG/ZLlwsoCingTZ20wZjvExv1CfV0gPyG1uQD0rPV0/ns+hdC5rkedwoCO3vq9Dscx8lSHeSjQVRz4YFujfR8wNuGang4Zu8gDiONxCqfOvt39TI6aHo6CLRzWS5xv/aDxuEDx64AlRQJ8bOzpaCgErM6QJ8A7hvTT6F1Cl3ei1s8o7yOX9YXEK+SaDdYb13Drflfqnke1+jeNif9qDFRLoWP1Bvd2pnsLY2yDAbI2yIArg+xtg8aPpDYsMQex3HjVKX/M4RJdLrB2m+n+1nAzvXrQtp2rS+XV+UJj/OxMcXXxlfJ8hLgusG3iORVF0b693nz7Tv8DW1zKUr89OZdD9btX+v5yIVQ1YK3msYVmBSfzAlsyMjjeJ9gKlBaKk+lEYyDPd8x6Csy5Q481ROOxRWvZaDymdOMEgs45rsI2rgKurW6M/ITtWidTobgZtqJMNfRdfn4s1Dw418dv4JYBbjXB4sZj30P6ZAsVciyeESrMiSX2QiWN4j6b6njY4Xlko2u4+yhn4K7ejaWH95o/z+40Rs4u1J7Tr4SYktZ9+2shxM2dYrBYaWtLWmLrASa8boh+RD7PM60vvn2nz2ej/7s/vl6gUz9T9kbSZDKZTCaTyWQymUwHyR4kTSaTyWQymUwmk8l0kA5DW7136x5fowtYluo1+RBoHIu0ZmO81gciRvSOBTJdKyxmdSfUav5Rr3hz2PJNgNI9KUja40M1ilO3QYhWngkJyVB8Oc2A0ARiniiInAMb5G8CaXFAR1ykV+ItnDy3RBeACvK1/HMqirwb9SgkqChXtEIcHm70+vzN3wpFIpLqHa+VxVZ1by0co2oUSW9pVpfAAe8WbsDAMppy91sBv1kDqdqgoPz9UqjbDyhE/GIs9OL1mbDYyZkc8n6+1d8GoL4xKOMB0IZkpNiYzoAWwlmrAQ70nGqDc4se2UvQd0Q+iMUQzGzhcBpjLHdwqmVn18BfWzjbwpzVrfH5oNFxClx71uPjXVB/beCKtwGCeF0DtUIB+vEIYxNOlptY8VDAjbkCcvx//iSEY7kRmuWBUzLG2oBx7Y6ERDphmAX6q4abHFH4Bdr2FsXQ350SCSVOjb7IhRi2K/3t6kaui9//4fv98eXlx/3xHYqdx/FuLDVAWyO4d4cUCBIwrTHG4NtXcqs7e4lcGtS/DdytK4ypZaFruVsJ66qBjhKJ3AItPBKh7EIIruj7ZhA+HSseSG4FB8In9cyBzke4nwpjYAvMt1kr7vNKc9gwAXYfsZA5UNjHXA0kcw20aT7XfLvF3FRjjNDZdTbW73ggtCW4UA88E3Sea4EKeoy7GIXiIzgpxslBy5fPlo8SF41eOeecC9WH/eelU764nivm7l/p+l6w0DjmuEmuz2+WisWf7jW+Vpe6/yHWImOcaERXXuSsrHeRTfH7EebVgq7FcNNv4NJdrdTXM+TY4QvNlbfA9wpsV2qwkJjM9Lf/+b/+h/3xlPg6kOFtepx1jnOaCxM4xs6mmu9vEcc+1vj69jf/cX/8hz/+w/647rQQSCK1i2cexLplhdwU0O+TMdyKt8zbuz7AqtHFwGnLROcoEs2bHebe0UA48QDrMge0tqMdNnKSL/T5Sao19WwqJPJug3E3wVa29FN49b9dwcmBu8MWtsCYbulsizkgAeYLLJZLsgrr+wS4/KbGou9W9/nVu2/2xy3i/vs1YuN0N07HwJZXNZyDV3AsT5QDAuKl2agvxtOv9sfTtzoenGsOjcfq9waI7upB66gt4mGNnQE3hXJb0xB+/zzZG0mTyWQymUwmk8lkMh0ke5A0mUwmk8lkMplMJtNBOowNCd75evcnHfBNIhx1pFfvQzg9wtjVxRkc2VAwPQFe4/BKOkNx3glcUFu8gi3vdJ7lrfCL0XD3up14Hd01Y5FebgAUiK6ABbCcMME1wuU1JjgIjDawgCzcvLocBWfxujlKhbSE0XGQj9g7d9JfFotPR0td9/VH4U2/eqnX3oNv9Co9w/07FM1NWSQVRazbtRDlAkVPl6DwUqc+8ECa4nyHy9RgYgMQuLJAEMJdL0I/vjuVa9zXb3QfZQoEDMWBVxWw60bYwiNm65xzfgsHUWCu4xHQ73Akls4FF3qEcVOq78Yprhtt2AHdyeFCGzDWOpyHdF4H7DyULKCsPhgBk/I4T4LzJ33TdcDSBjPFfwdWdgYH3wL4SQrn5BIunZt7uBTGKIq9VD54/2chnC3yUwTH2Qj91cFdMMqOVzjb9wjj5k7jrlwKcOrgyLYF8rK+VnuVM7grw024RU5OErjYAZMaI9d8/VIY06sp8LhLoDO9A/O2QZ7sNPAeVrqPGAjccIJ4Qe4JcE/sgPSv0RebO8XUTz+rT68+6m8DtxhgeqODaZwC93pGheBc6LG2gHvL6NoKXDzlVNLhWoFQs3h8mtCaUN+vG8XJ6kpbEipgWtEQbo8t8uZ21y4RC9bjukZwVY1i9S9R4fEI2CzGdcOY5XoByOWmUr+Mcp0nwXinwzTn0yY9DmruXOSiPm9y7ZHUasP5Qmj15b2u4/UUjt6nGi+k4ifALF9OhUcWG225KYCjreDuO0Cxe7qNT4a7tsuAtnLLSMvtCwj/2mPLABDT2Qv1e4P1yR2cpGMvlDEqdU8jrK/OR2o/D6S2rjVmp2dw7n1GBedc169FuFapOE9hK0WN+f70pfru5DvdQwBzSgBwmNMJWW1R3+gPNnfCFoul4j7AefvRYTvF+Rzy93qrMdgOsNZ++1Jfx1azDrmuKp8sjPaHj5UYnHvqjD1I1C81YmnuFPul03dOB9hy8ozyzrv48SEDcUw37AZJy3ObAPoUxuSuxFp8iPlpOtHcF+H5osPxYqP7v8jwbJIofz3msnyMufQbbRGbnel4eAIXWDjOJnDT3VzBERZbRVpUTqCz+/pa3x8Ajf767+QQm15qnA78v21OtDeSJpPJZDKZTCaTyWQ6SPYgaTKZTCaTyWQymUymg3QY2hoF1/TFXMMEDm610MczvGJm4eeAAqhVJyRiQjwUr5gHQEqmQBLXQ72+rT8IU6vuhPSsPAr+9ujVZKzXxyMgHNlIr3RfXLzStcDJc4HX/RUwmwj3WsOFjK57FTDA4PTqP8N3VgXcJudCKMuC3l3PqMg51zfHGs6Q46naaA53rA9bXd9bIlsobpoDceiAG4ZEbTecAHMBRpzAzaz1RKAUJ0nvypt7oLJjYT4nS2EjXUDR86EQ1vMLoBeIfOKL+UzXWK4UXzdbxZSHI+ar14rNbASsDo6+716zcPYf3XPJe++SHmVqWCw8AA+GO2sAVtdEQP3o5ga0oiNJBzRrgwL3ZaO2PkVsgG5ygwh47eP54azG4rm+1bUTtSq3QB+BqW9QML2Fo95VoXxw9YCcgb7OgF3XXmMtkO0DPucdnVCfUd670P9OQF7wGdA0uB+XcIJ+f/9+f/wruOnNyIvD3bGqFMcZsKfJiRj/MZysG2D99VTHVd8fLZxUN1td1wOcRGtYkjKOiHC2wCCbROcpgY5fwhXv+3vdx10JJ8NY19MRHcVWAjocPrcef7PFeCw7xXQGN9uW958ANQNyTWfSCI03GOt+TnLhkQ4xStdvFqX2QBWTHhVtULDex7qWDBhVgvEywVwRuLUFboEb5GQPl/K2Uv9mmBNB27nY4RpTbncAgtUeC20NLsS7mBpifTDsNEaKTujYh7kw+nUnJLJodZ9pUHvdYkwNz4XD/ZeL8/3xExdK5FsHRDiFo/F4uhuzAzhndpjbibbmM83Vgfhxo/mUiONDoc/XpcZ1A+dtzqc5OnJbKAZSYOfxQNd5OtI64tnV59MGkxnzeAc0n+7H05mu6eKN+n1eMjdx+xXWKkN95+L1m/1xm6mv4xRbP4Cp573LJ12Lm1bXNcEWm+RMaw9WCsAS1bVL9V0LjHcLB/2y1TmXG82z0ZnG+3Il7LqJFcvDse57NDsO2uq8c9Fj/og4l2CbE51GmWuw/nHYJlFhHeBb/W0c6X5enysGFvfCWRcLjf0F2v0s1vfLu12f+hNsBwF6Gp0gx+JZJ6alOKoGeHC5qzXQ4ntsF1upH1PgrKO37/bHkxP1UTFXXL08V4xfPmjMuvLznkHsjaTJZDKZTCaTyWQymQ6SPUiaTCaTyWQymUwmk+kgHYa2ds49Grc1EZ2mgHLmKD4OJKUF2rEp+Bpa5xnhlfQAroMeDm7TU+EBbi6kp7oAclrqPPVo9wp70MItb6zXxCPgmdGEhY/1M/kZCukGFFOGq5KH2ycx1yfuesR+iRBu6QYnFOH6XgVnn1M+OJdVu/ZIRnCuBCpzCmShRnH3Val2nD5xpYNb3BYoJ1zhfE5cCRjoVp/XQKyarf626XbtkrdwEUQnnXnFQhgDnVrq9X0LXKdDf22BghRrfefqWn2x2cIhDQjrGIWbPTCHKRzMhqdCF55TkfNu1LsYr4HrbVG4PKBIfELXPCCJdEh0wHZT9GmDyuFFIUTjYwM0GkXPGxQdR1lfV/eIxmotNDHBNY6G+rsG17gFIh4NFC8DxCmxHAfUpWUxeuCBOXKMQ05qUKSa2NHRymYH5+I+Z3kUOPZugGO1V7FSfP/w4+X++O5ccfZyrPjL4XK7AiI7w/jJprg7uOH5GVA5YOdRjyeGOVxg4Vo8Giivbr1+s1noOAAbjmjrDbSzWKrfH4AGreCgWaG/Knyf4z1gfBwNUXbO+T6Wlyg4nefAVoGbTuBA+uiG7pxzIeY8ofsZ0A0STo4REVY4ogdgoHSvroBJJT2Cm+G7MVcFiJFoABwPWDQLdxcr9dG8VP4cABVcVtoKUwJHHwTldg8MbZy+3h/nuLg6P86/g8cuuFkfUzUwzZSOsRvF0GqhOLud6/5fYZ1BRD4C6l8ABR7AnZWG6BFd0PH99YPasehdZKdjIWo5UMPRVK6eswvliQ4O5N1SMbvlGKw/vdZr6CaLuT2FO3izAZY71HdeTzFvDo+TWYNzrjdRdjXiOB4KCR1huweWHm4C987yN3+7P+ZaZQFU9IXS5JN1ToC3awdMPxnQRRdbP8a7zzmms0x9mnD9A+y8AZ5ZrBef/nxL12X1+xzbdhaN1kuu1E1tgNpOz4RgZzlQ/aB+f0754Fza7xmo6aiO+Yhup7Rt9aim0CJ2I1Lx+NNtpXzkG82bTDWB29gQA9NG/T7rt2JFa+RMYLYx1kchUb+UN8JmXYotXwXmZG5zuVUOiPH8MhjDdbnV9+//pO1at3eKk4tT5YezidDW9Zqrt78seyNpMplMJpPJZDKZTKaDZA+SJpPJZDKZTCaTyWQ6SD4cUCz9t7/9bfjd7353xMsx/SV57/93COG3z3Eu68d/P1k/fhmyfvwyZP34Zcj68cuQ9eOXIevHL0Of24/2RtJkMplMJpPJZDKZTAfpoDeS3vtr59z3x7sc0/9H34YQXv7rX/vXZf347yrrxy9D1o9fhqwfvwxZP34Zsn78MmT9+GXos/rxoAdJk8lkMplMJpPJZDKZDG01mUwmk8lkMplMJtNBsgdJk8lkMplMJpPJZDIdJHuQNJlMJpPJZDKZTCbTQbIHSZPJZDKZTCaTyWQyHSR7kDSZTCaTyWQymUwm00GyB0mTyWQymUwmk8lkMh0ke5A0mUwmk8lkMplMJtNBsgdJk8lkMplMJpPJZDIdJHuQNJlMJpPJZDKZTCbTQfp/eRJOZ4LwprYAAAAASUVORK5CYII=
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<h3 id="Question:-What-do-you-notice-about-your-generated-samples-and-how-might-you-improve-this-model?">Question: What do you notice about your generated samples and how might you improve this model?<a class="anchor-link" href="#Question:-What-do-you-notice-about-your-generated-samples-and-how-might-you-improve-this-model?">&#182;</a></h3><p>When you answer this question, consider the following factors:</p>
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<li>The dataset is biased; it is made of "celebrity" faces that are mostly white</li>
<li>Model size; larger models have the opportunity to learn more features in a data feature space</li>
<li>Optimization strategy; optimizers and number of epochs affect your final result</li>
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<p><strong>Answer:</strong></p>
<p>My network for Generator and Discriminator is the same network which I used for finishing my DCGAN assignment. However I got to play with real and fake loss functions with label smoothing. The dataset is indeed biased and hence most of the generated faces are white.</p>
<p>The dataset can be more diverse and large, which can improve the model to give more realistic and real-world images.</p>
<p>I got to play little with hyper-parameters because of the time-constraint.</p>
<p>However the first samples generated by my model were very very bad and looked quite fake. That is why I had to experiment with hyperparameters and label smoothing.</p>
<p>At first, I didn't use label smoothing and the loss took quite time to decrease even after 15 epochs of training.
Then I used a label smoothing constant 0.9 for real loss and 0.1 for fake loss. Though it gave quite good result, I wanted that label smoothing factor to be uniformly random.</p>
<p>Hence I went through some previous Github repositories and used random.uniform function to smooth the labels in a uniformly random fashion</p>
<p>For real loss - I used a range of (0.7,1.05)
For fake loss - I used a range of (0.0,0.35)</p>
<p>My d_conv_dim and g_conv_dim were assignned to 32 considering my network model.
batch-size and image-size = 32</p>
<p>I used Adam Optimizers for the network optimization.
The other hyperparameters I used are -
lr = 0.0002
beta1=0.5
beta2=0.999</p>
<p>And these are taken from DCGAN paper and these gave a pretty good result with generation faces.</p>
<p>However some of the present generated samples are still distorted and needs some more training. The no of epochs I used were 10 for the current hyperparameters. I could have trained for another 5 epochs to see improved faces. I also observed that some faces which were realistic are of white people. May be because of that bias, white people faces are quite realistic when generated.</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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