run.html


<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />

<title>run</title>

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<style type="text/css">
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/*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */
html {
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aside,
details,
figcaption,
figure,
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video {
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[hidden],
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sub {
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figure {
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.glyphicon-triangle-bottom:before {
  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.7.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.7.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.7.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff2?v=4.7.0') format('woff2'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.7.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.7.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.7.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.fa-pull-left {
  float: left;
}
.fa-pull-right {
  float: right;
}
.fa.fa-pull-left {
  margin-right: .3em;
}
.fa.fa-pull-right {
  margin-left: .3em;
}
/* Deprecated as of 4.4.0 */
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
.fa-pulse {
  -webkit-animation: fa-spin 1s infinite steps(8);
  animation: fa-spin 1s infinite steps(8);
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1)";
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook-f:before,
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-feed:before,
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before,
.fa-gratipay:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper-pp:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-resistance:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-y-combinator-square:before,
.fa-yc-square:before,
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
.fa-buysellads:before {
  content: "\f20d";
}
.fa-connectdevelop:before {
  content: "\f20e";
}
.fa-dashcube:before {
  content: "\f210";
}
.fa-forumbee:before {
  content: "\f211";
}
.fa-leanpub:before {
  content: "\f212";
}
.fa-sellsy:before {
  content: "\f213";
}
.fa-shirtsinbulk:before {
  content: "\f214";
}
.fa-simplybuilt:before {
  content: "\f215";
}
.fa-skyatlas:before {
  content: "\f216";
}
.fa-cart-plus:before {
  content: "\f217";
}
.fa-cart-arrow-down:before {
  content: "\f218";
}
.fa-diamond:before {
  content: "\f219";
}
.fa-ship:before {
  content: "\f21a";
}
.fa-user-secret:before {
  content: "\f21b";
}
.fa-motorcycle:before {
  content: "\f21c";
}
.fa-street-view:before {
  content: "\f21d";
}
.fa-heartbeat:before {
  content: "\f21e";
}
.fa-venus:before {
  content: "\f221";
}
.fa-mars:before {
  content: "\f222";
}
.fa-mercury:before {
  content: "\f223";
}
.fa-intersex:before,
.fa-transgender:before {
  content: "\f224";
}
.fa-transgender-alt:before {
  content: "\f225";
}
.fa-venus-double:before {
  content: "\f226";
}
.fa-mars-double:before {
  content: "\f227";
}
.fa-venus-mars:before {
  content: "\f228";
}
.fa-mars-stroke:before {
  content: "\f229";
}
.fa-mars-stroke-v:before {
  content: "\f22a";
}
.fa-mars-stroke-h:before {
  content: "\f22b";
}
.fa-neuter:before {
  content: "\f22c";
}
.fa-genderless:before {
  content: "\f22d";
}
.fa-facebook-official:before {
  content: "\f230";
}
.fa-pinterest-p:before {
  content: "\f231";
}
.fa-whatsapp:before {
  content: "\f232";
}
.fa-server:before {
  content: "\f233";
}
.fa-user-plus:before {
  content: "\f234";
}
.fa-user-times:before {
  content: "\f235";
}
.fa-hotel:before,
.fa-bed:before {
  content: "\f236";
}
.fa-viacoin:before {
  content: "\f237";
}
.fa-train:before {
  content: "\f238";
}
.fa-subway:before {
  content: "\f239";
}
.fa-medium:before {
  content: "\f23a";
}
.fa-yc:before,
.fa-y-combinator:before {
  content: "\f23b";
}
.fa-optin-monster:before {
  content: "\f23c";
}
.fa-opencart:before {
  content: "\f23d";
}
.fa-expeditedssl:before {
  content: "\f23e";
}
.fa-battery-4:before,
.fa-battery:before,
.fa-battery-full:before {
  content: "\f240";
}
.fa-battery-3:before,
.fa-battery-three-quarters:before {
  content: "\f241";
}
.fa-battery-2:before,
.fa-battery-half:before {
  content: "\f242";
}
.fa-battery-1:before,
.fa-battery-quarter:before {
  content: "\f243";
}
.fa-battery-0:before,
.fa-battery-empty:before {
  content: "\f244";
}
.fa-mouse-pointer:before {
  content: "\f245";
}
.fa-i-cursor:before {
  content: "\f246";
}
.fa-object-group:before {
  content: "\f247";
}
.fa-object-ungroup:before {
  content: "\f248";
}
.fa-sticky-note:before {
  content: "\f249";
}
.fa-sticky-note-o:before {
  content: "\f24a";
}
.fa-cc-jcb:before {
  content: "\f24b";
}
.fa-cc-diners-club:before {
  content: "\f24c";
}
.fa-clone:before {
  content: "\f24d";
}
.fa-balance-scale:before {
  content: "\f24e";
}
.fa-hourglass-o:before {
  content: "\f250";
}
.fa-hourglass-1:before,
.fa-hourglass-start:before {
  content: "\f251";
}
.fa-hourglass-2:before,
.fa-hourglass-half:before {
  content: "\f252";
}
.fa-hourglass-3:before,
.fa-hourglass-end:before {
  content: "\f253";
}
.fa-hourglass:before {
  content: "\f254";
}
.fa-hand-grab-o:before,
.fa-hand-rock-o:before {
  content: "\f255";
}
.fa-hand-stop-o:before,
.fa-hand-paper-o:before {
  content: "\f256";
}
.fa-hand-scissors-o:before {
  content: "\f257";
}
.fa-hand-lizard-o:before {
  content: "\f258";
}
.fa-hand-spock-o:before {
  content: "\f259";
}
.fa-hand-pointer-o:before {
  content: "\f25a";
}
.fa-hand-peace-o:before {
  content: "\f25b";
}
.fa-trademark:before {
  content: "\f25c";
}
.fa-registered:before {
  content: "\f25d";
}
.fa-creative-commons:before {
  content: "\f25e";
}
.fa-gg:before {
  content: "\f260";
}
.fa-gg-circle:before {
  content: "\f261";
}
.fa-tripadvisor:before {
  content: "\f262";
}
.fa-odnoklassniki:before {
  content: "\f263";
}
.fa-odnoklassniki-square:before {
  content: "\f264";
}
.fa-get-pocket:before {
  content: "\f265";
}
.fa-wikipedia-w:before {
  content: "\f266";
}
.fa-safari:before {
  content: "\f267";
}
.fa-chrome:before {
  content: "\f268";
}
.fa-firefox:before {
  content: "\f269";
}
.fa-opera:before {
  content: "\f26a";
}
.fa-internet-explorer:before {
  content: "\f26b";
}
.fa-tv:before,
.fa-television:before {
  content: "\f26c";
}
.fa-contao:before {
  content: "\f26d";
}
.fa-500px:before {
  content: "\f26e";
}
.fa-amazon:before {
  content: "\f270";
}
.fa-calendar-plus-o:before {
  content: "\f271";
}
.fa-calendar-minus-o:before {
  content: "\f272";
}
.fa-calendar-times-o:before {
  content: "\f273";
}
.fa-calendar-check-o:before {
  content: "\f274";
}
.fa-industry:before {
  content: "\f275";
}
.fa-map-pin:before {
  content: "\f276";
}
.fa-map-signs:before {
  content: "\f277";
}
.fa-map-o:before {
  content: "\f278";
}
.fa-map:before {
  content: "\f279";
}
.fa-commenting:before {
  content: "\f27a";
}
.fa-commenting-o:before {
  content: "\f27b";
}
.fa-houzz:before {
  content: "\f27c";
}
.fa-vimeo:before {
  content: "\f27d";
}
.fa-black-tie:before {
  content: "\f27e";
}
.fa-fonticons:before {
  content: "\f280";
}
.fa-reddit-alien:before {
  content: "\f281";
}
.fa-edge:before {
  content: "\f282";
}
.fa-credit-card-alt:before {
  content: "\f283";
}
.fa-codiepie:before {
  content: "\f284";
}
.fa-modx:before {
  content: "\f285";
}
.fa-fort-awesome:before {
  content: "\f286";
}
.fa-usb:before {
  content: "\f287";
}
.fa-product-hunt:before {
  content: "\f288";
}
.fa-mixcloud:before {
  content: "\f289";
}
.fa-scribd:before {
  content: "\f28a";
}
.fa-pause-circle:before {
  content: "\f28b";
}
.fa-pause-circle-o:before {
  content: "\f28c";
}
.fa-stop-circle:before {
  content: "\f28d";
}
.fa-stop-circle-o:before {
  content: "\f28e";
}
.fa-shopping-bag:before {
  content: "\f290";
}
.fa-shopping-basket:before {
  content: "\f291";
}
.fa-hashtag:before {
  content: "\f292";
}
.fa-bluetooth:before {
  content: "\f293";
}
.fa-bluetooth-b:before {
  content: "\f294";
}
.fa-percent:before {
  content: "\f295";
}
.fa-gitlab:before {
  content: "\f296";
}
.fa-wpbeginner:before {
  content: "\f297";
}
.fa-wpforms:before {
  content: "\f298";
}
.fa-envira:before {
  content: "\f299";
}
.fa-universal-access:before {
  content: "\f29a";
}
.fa-wheelchair-alt:before {
  content: "\f29b";
}
.fa-question-circle-o:before {
  content: "\f29c";
}
.fa-blind:before {
  content: "\f29d";
}
.fa-audio-description:before {
  content: "\f29e";
}
.fa-volume-control-phone:before {
  content: "\f2a0";
}
.fa-braille:before {
  content: "\f2a1";
}
.fa-assistive-listening-systems:before {
  content: "\f2a2";
}
.fa-asl-interpreting:before,
.fa-american-sign-language-interpreting:before {
  content: "\f2a3";
}
.fa-deafness:before,
.fa-hard-of-hearing:before,
.fa-deaf:before {
  content: "\f2a4";
}
.fa-glide:before {
  content: "\f2a5";
}
.fa-glide-g:before {
  content: "\f2a6";
}
.fa-signing:before,
.fa-sign-language:before {
  content: "\f2a7";
}
.fa-low-vision:before {
  content: "\f2a8";
}
.fa-viadeo:before {
  content: "\f2a9";
}
.fa-viadeo-square:before {
  content: "\f2aa";
}
.fa-snapchat:before {
  content: "\f2ab";
}
.fa-snapchat-ghost:before {
  content: "\f2ac";
}
.fa-snapchat-square:before {
  content: "\f2ad";
}
.fa-pied-piper:before {
  content: "\f2ae";
}
.fa-first-order:before {
  content: "\f2b0";
}
.fa-yoast:before {
  content: "\f2b1";
}
.fa-themeisle:before {
  content: "\f2b2";
}
.fa-google-plus-circle:before,
.fa-google-plus-official:before {
  content: "\f2b3";
}
.fa-fa:before,
.fa-font-awesome:before {
  content: "\f2b4";
}
.fa-handshake-o:before {
  content: "\f2b5";
}
.fa-envelope-open:before {
  content: "\f2b6";
}
.fa-envelope-open-o:before {
  content: "\f2b7";
}
.fa-linode:before {
  content: "\f2b8";
}
.fa-address-book:before {
  content: "\f2b9";
}
.fa-address-book-o:before {
  content: "\f2ba";
}
.fa-vcard:before,
.fa-address-card:before {
  content: "\f2bb";
}
.fa-vcard-o:before,
.fa-address-card-o:before {
  content: "\f2bc";
}
.fa-user-circle:before {
  content: "\f2bd";
}
.fa-user-circle-o:before {
  content: "\f2be";
}
.fa-user-o:before {
  content: "\f2c0";
}
.fa-id-badge:before {
  content: "\f2c1";
}
.fa-drivers-license:before,
.fa-id-card:before {
  content: "\f2c2";
}
.fa-drivers-license-o:before,
.fa-id-card-o:before {
  content: "\f2c3";
}
.fa-quora:before {
  content: "\f2c4";
}
.fa-free-code-camp:before {
  content: "\f2c5";
}
.fa-telegram:before {
  content: "\f2c6";
}
.fa-thermometer-4:before,
.fa-thermometer:before,
.fa-thermometer-full:before {
  content: "\f2c7";
}
.fa-thermometer-3:before,
.fa-thermometer-three-quarters:before {
  content: "\f2c8";
}
.fa-thermometer-2:before,
.fa-thermometer-half:before {
  content: "\f2c9";
}
.fa-thermometer-1:before,
.fa-thermometer-quarter:before {
  content: "\f2ca";
}
.fa-thermometer-0:before,
.fa-thermometer-empty:before {
  content: "\f2cb";
}
.fa-shower:before {
  content: "\f2cc";
}
.fa-bathtub:before,
.fa-s15:before,
.fa-bath:before {
  content: "\f2cd";
}
.fa-podcast:before {
  content: "\f2ce";
}
.fa-window-maximize:before {
  content: "\f2d0";
}
.fa-window-minimize:before {
  content: "\f2d1";
}
.fa-window-restore:before {
  content: "\f2d2";
}
.fa-times-rectangle:before,
.fa-window-close:before {
  content: "\f2d3";
}
.fa-times-rectangle-o:before,
.fa-window-close-o:before {
  content: "\f2d4";
}
.fa-bandcamp:before {
  content: "\f2d5";
}
.fa-grav:before {
  content: "\f2d6";
}
.fa-etsy:before {
  content: "\f2d7";
}
.fa-imdb:before {
  content: "\f2d8";
}
.fa-ravelry:before {
  content: "\f2d9";
}
.fa-eercast:before {
  content: "\f2da";
}
.fa-microchip:before {
  content: "\f2db";
}
.fa-snowflake-o:before {
  content: "\f2dc";
}
.fa-superpowers:before {
  content: "\f2dd";
}
.fa-wpexplorer:before {
  content: "\f2de";
}
.fa-meetup:before {
  content: "\f2e0";
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  padding: 0;
  margin: -1px;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

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

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

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

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

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Part0：总览

基本思路为：(1)FastText生成embedding向量 -> (2)Stack-Bi-LSTM（GRU）模型 -> (3)Bi-Sample Training

(1)FastText生成embedding向量
复赛数据为arg_a(arg_1)和arg_b(arg_2)的匹配问题，本程序针对arg_b进行滑窗采样以生成训练数据。
这就可能会产生一个问题，由于arg_b在text中的分布不均匀导致网络词向量不能很好得到训练，而且随着滑窗的缩小，问题可能越来越明显。所以，这里先使用train text训练FastText生成词向量，再导入Stack-Bi-LSTM模型进行训练。

(2)Stack-Bi-LSTM（GRU）模型
Stack是指三个输入：text、arg_a、arg_b分别通过embedding和Bi-LSTM后连接到一起，再一同送入Bi-LSTM、Bi-GRU模型这样的一个模型结构。
其中text为滑窗范围内（此处为320）的文本编码；arg_a为滑窗范围内所有arg_a的索引值；arg_b为此滑窗内需要匹配的某一个arg_b索引值。
模型的输出为，此滑窗内针对此arg_b的arg_a的0/1真值序列。

(3)Bi-Sample Training
Bi-LSTM和Bi-GRU虽然为双向结构，但文本本身会存在左右顺序，所以这里使用正向、反向两份数据进行训练。也就相当于数据增强了一倍。但是，如果将两份数据混在一起训练，可能会彼此产生噪音，所以，在训练时间相同的情况下，正反向分别训练一个模型然后融合预测。

目录结构：
|-run.ipynb # 代码，只有一个文件，直接运行程序即可。程序会先训练模型，然后预测并生成结果。
|-readme.txt # 说明文档
|-Demo 
  |-DataSets # 数据文件，内部结构保持不变
  |-Models 
    |-s2_01 # 存放模型文件，以及训练历史文件。复现时请新建此文件夹！！！
  |-result
    |-s2_01_final_v4_b_raw # 存放结果文件。复现时请新建此文件夹！！！
Part1: 相关软件包

这里看上去导入了很多，仅是个人习惯，实际用到的不多，本程序主要用到的（除numpy等必须的之外）：
1.jieba：对train text进行简单的分词，以方便FastText进行embedding的初始化，然后送入keras进行训练。
2.gensim：使用gensim的FastText进行embedding的初始化
3.keras：深度序列模型
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">os</span>
<span class="kn">import</span> <span class="nn">sys</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">import</span> <span class="nn">random</span>
<span class="kn">import</span> <span class="nn">warnings</span>
<span class="kn">import</span> <span class="nn">re</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">pandas</span> <span class="k">as</span> <span class="nn">pd</span>

<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">KFold</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">accuracy_score</span>
<span class="kn">from</span> <span class="nn">sklearn.linear_model</span> <span class="k">import</span> <span class="n">Ridge</span><span class="p">,</span> <span class="n">RidgeCV</span>
<span class="kn">from</span> <span class="nn">sklearn.linear_model</span> <span class="k">import</span> <span class="n">ElasticNet</span><span class="p">,</span> <span class="n">Lasso</span><span class="p">,</span> <span class="n">BayesianRidge</span><span class="p">,</span> <span class="n">LassoLarsIC</span>
<span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="k">import</span> <span class="n">RandomForestRegressor</span><span class="p">,</span> <span class="n">RandomForestClassifier</span><span class="p">,</span> <span class="n">GradientBoostingRegressor</span><span class="p">,</span> <span class="n">GradientBoostingClassifier</span>
<span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="k">import</span> <span class="n">AdaBoostRegressor</span><span class="p">,</span> <span class="n">BaggingRegressor</span><span class="p">,</span> <span class="n">BaggingClassifier</span>
<span class="kn">from</span> <span class="nn">sklearn.tree</span> <span class="k">import</span> <span class="n">ExtraTreeRegressor</span><span class="p">,</span> <span class="n">ExtraTreeClassifier</span>
<span class="kn">from</span> <span class="nn">sklearn.kernel_ridge</span> <span class="k">import</span> <span class="n">KernelRidge</span>
<span class="kn">from</span> <span class="nn">sklearn.pipeline</span> <span class="k">import</span> <span class="n">make_pipeline</span>
<span class="kn">from</span> <span class="nn">sklearn.preprocessing</span> <span class="k">import</span> <span class="n">RobustScaler</span>
<span class="kn">from</span> <span class="nn">sklearn.base</span> <span class="k">import</span> <span class="n">BaseEstimator</span><span class="p">,</span> <span class="n">TransformerMixin</span><span class="p">,</span> <span class="n">RegressorMixin</span><span class="p">,</span> <span class="n">clone</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">KFold</span><span class="p">,</span> <span class="n">cross_val_score</span><span class="p">,</span> <span class="n">train_test_split</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">mean_squared_error</span>
<span class="kn">from</span> <span class="nn">sklearn.feature_selection</span> <span class="k">import</span> <span class="n">SelectFromModel</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">StratifiedKFold</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">f1_score</span><span class="p">,</span> <span class="n">roc_auc_score</span>

<span class="kn">from</span> <span class="nn">sklearn.feature_extraction.text</span> <span class="k">import</span> <span class="n">TfidfVectorizer</span><span class="p">,</span> <span class="n">TfidfTransformer</span><span class="p">,</span> <span class="n">HashingVectorizer</span><span class="p">,</span> <span class="n">CountVectorizer</span>
<span class="kn">from</span> <span class="nn">sklearn.decomposition</span> <span class="k">import</span> <span class="n">TruncatedSVD</span>
<span class="kn">from</span> <span class="nn">sklearn</span> <span class="k">import</span> <span class="n">preprocessing</span><span class="p">,</span> <span class="n">pipeline</span>


<span class="kn">import</span> <span class="nn">xgboost</span> <span class="k">as</span> <span class="nn">xgb</span>
<span class="kn">import</span> <span class="nn">lightgbm</span> <span class="k">as</span> <span class="nn">lgb</span>
<span class="kn">from</span> <span class="nn">keras.models</span> <span class="k">import</span> <span class="n">Model</span><span class="p">,</span> <span class="n">load_model</span><span class="p">,</span> <span class="n">Sequential</span>
<span class="kn">from</span> <span class="nn">keras.layers</span> <span class="k">import</span> <span class="n">Input</span><span class="p">,</span> <span class="n">Add</span><span class="p">,</span> <span class="n">Dense</span><span class="p">,</span> <span class="n">Flatten</span><span class="p">,</span> <span class="n">BatchNormalization</span><span class="p">,</span> <span class="n">Activation</span><span class="p">,</span> <span class="n">UpSampling2D</span><span class="p">,</span> <span class="n">Embedding</span>
<span class="kn">from</span> <span class="nn">keras.layers.core</span> <span class="k">import</span> <span class="n">Lambda</span>
<span class="kn">from</span> <span class="nn">keras.layers.convolutional</span> <span class="k">import</span> <span class="n">Conv2D</span><span class="p">,</span> <span class="n">Conv2DTranspose</span>
<span class="kn">from</span> <span class="nn">keras.layers.pooling</span> <span class="k">import</span> <span class="n">MaxPooling2D</span><span class="p">,</span> <span class="n">GlobalAveragePooling2D</span>
<span class="kn">from</span> <span class="nn">keras.layers.merge</span> <span class="k">import</span> <span class="n">concatenate</span>
<span class="kn">from</span> <span class="nn">keras.callbacks</span> <span class="k">import</span> <span class="n">EarlyStopping</span><span class="p">,</span> <span class="n">ModelCheckpoint</span><span class="p">,</span> <span class="n">ReduceLROnPlateau</span>
<span class="kn">from</span> <span class="nn">keras</span> <span class="k">import</span> <span class="n">backend</span> <span class="k">as</span> <span class="n">K</span>
<span class="kn">from</span> <span class="nn">keras</span> <span class="k">import</span> <span class="n">losses</span><span class="p">,</span> <span class="n">metrics</span><span class="p">,</span> <span class="n">optimizers</span>
<span class="kn">from</span> <span class="nn">keras.applications</span> <span class="k">import</span> <span class="n">MobileNet</span>
<span class="c1"># from keras.applications.mobilenet import relu6, DepthwiseConv2D</span>

<span class="kn">import</span> <span class="nn">tensorflow</span> <span class="k">as</span> <span class="nn">tf</span>
<span class="kn">import</span> <span class="nn">keras</span>

<span class="kn">from</span> <span class="nn">glob</span> <span class="k">import</span> <span class="n">glob</span>

<span class="kn">import</span> <span class="nn">simplejson</span> <span class="k">as</span> <span class="nn">json</span>

<span class="kn">import</span> <span class="nn">pickle</span>
<span class="kn">import</span> <span class="nn">gensim</span>
<span class="kn">import</span> <span class="nn">jieba</span>
<span class="kn">import</span> <span class="nn">itertools</span>
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<pre>Using TensorFlow backend.
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</div>Part2：训练部分
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">LABELS</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Normal&#39;</span><span class="p">,</span>
<span class="s1">&#39;Disease&#39;</span><span class="p">,</span>
<span class="s1">&#39;Reason&#39;</span><span class="p">,</span>
<span class="s1">&#39;Symptom&#39;</span><span class="p">,</span>
<span class="s1">&#39;Test&#39;</span><span class="p">,</span>
<span class="s1">&#39;Test_Value&#39;</span><span class="p">,</span>
<span class="s1">&#39;Drug&#39;</span><span class="p">,</span>
<span class="s1">&#39;Frequency&#39;</span><span class="p">,</span>
<span class="s1">&#39;Amount&#39;</span><span class="p">,</span>
<span class="s1">&#39;Method&#39;</span><span class="p">,</span>
<span class="s1">&#39;Treatment&#39;</span><span class="p">,</span>
<span class="s1">&#39;Operation&#39;</span><span class="p">,</span>
<span class="s1">&#39;Anatomy&#39;</span><span class="p">,</span>
<span class="s1">&#39;Level&#39;</span><span class="p">,</span>
<span class="s1">&#39;Duration&#39;</span><span class="p">,</span>
<span class="s1">&#39;SideEff&#39;</span><span class="p">,</span>
<span class="p">]</span>


<span class="n">LABELS_0</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Normal&#39;</span><span class="p">,</span> <span class="s1">&#39;Test&#39;</span><span class="p">,</span> <span class="s1">&#39;Symptom&#39;</span><span class="p">,</span> <span class="s1">&#39;Treatment&#39;</span><span class="p">,</span> <span class="s1">&#39;Drug&#39;</span><span class="p">,</span> <span class="s1">&#39;Anatomy&#39;</span><span class="p">,</span> <span class="p">]</span>
<span class="n">LABELS_1</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Normal&#39;</span><span class="p">,</span> <span class="s1">&#39;Frequency&#39;</span><span class="p">,</span> <span class="s1">&#39;Duration&#39;</span><span class="p">,</span> <span class="s1">&#39;Amount&#39;</span><span class="p">,</span> <span class="s1">&#39;Method&#39;</span><span class="p">,</span> <span class="s1">&#39;SideEff&#39;</span><span class="p">,</span> <span class="p">]</span>

<span class="n">LABELS</span><span class="p">,</span> <span class="n">LABELS_0</span><span class="p">,</span> <span class="n">LABELS_1</span>
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<pre>([&#39;Normal&#39;,
  &#39;Disease&#39;,
  &#39;Reason&#39;,
  &#39;Symptom&#39;,
  &#39;Test&#39;,
  &#39;Test_Value&#39;,
  &#39;Drug&#39;,
  &#39;Frequency&#39;,
  &#39;Amount&#39;,
  &#39;Method&#39;,
  &#39;Treatment&#39;,
  &#39;Operation&#39;,
  &#39;Anatomy&#39;,
  &#39;Level&#39;,
  &#39;Duration&#39;,
  &#39;SideEff&#39;],
 [&#39;Normal&#39;, &#39;Test&#39;, &#39;Symptom&#39;, &#39;Treatment&#39;, &#39;Drug&#39;, &#39;Anatomy&#39;],
 [&#39;Normal&#39;, &#39;Frequency&#39;, &#39;Duration&#39;, &#39;Amount&#39;, &#39;Method&#39;, &#39;SideEff&#39;])</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">LABELS_DICT</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">LABELS</span><span class="p">,</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">LABELS</span><span class="p">))))</span>
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<pre>{&#39;Normal&#39;: 0,
 &#39;Disease&#39;: 1,
 &#39;Reason&#39;: 2,
 &#39;Symptom&#39;: 3,
 &#39;Test&#39;: 4,
 &#39;Test_Value&#39;: 5,
 &#39;Drug&#39;: 6,
 &#39;Frequency&#39;: 7,
 &#39;Amount&#39;: 8,
 &#39;Method&#39;: 9,
 &#39;Treatment&#39;: 10,
 &#39;Operation&#39;: 11,
 &#39;Anatomy&#39;: 12,
 &#39;Level&#39;: 13,
 &#39;Duration&#39;: 14,
 &#39;SideEff&#39;: 15}</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">LABELS_DICT_IDX</span> <span class="o">=</span> <span class="p">{</span><span class="nb">str</span><span class="p">(</span><span class="n">v</span><span class="p">):</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">LABELS_DICT</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>
<span class="n">LABELS_DICT_IDX</span>
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<pre>{&#39;0&#39;: &#39;Normal&#39;,
 &#39;1&#39;: &#39;Disease&#39;,
 &#39;2&#39;: &#39;Reason&#39;,
 &#39;3&#39;: &#39;Symptom&#39;,
 &#39;4&#39;: &#39;Test&#39;,
 &#39;5&#39;: &#39;Test_Value&#39;,
 &#39;6&#39;: &#39;Drug&#39;,
 &#39;7&#39;: &#39;Frequency&#39;,
 &#39;8&#39;: &#39;Amount&#39;,
 &#39;9&#39;: &#39;Method&#39;,
 &#39;10&#39;: &#39;Treatment&#39;,
 &#39;11&#39;: &#39;Operation&#39;,
 &#39;12&#39;: &#39;Anatomy&#39;,
 &#39;13&#39;: &#39;Level&#39;,
 &#39;14&#39;: &#39;Duration&#39;,
 &#39;15&#39;: &#39;SideEff&#39;}</pre>
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</div>实体关系类别名称
1、检查方法 -> 疾病（Test_Disease）
2、临床表现 -> 疾病（Symptom_Disease）
3、非药治疗 -> 疾病（Treatment_Disease）
4、药品名称 -> 疾病（Drug_Disease）
5、部位 -> 疾病（Anatomy_Disease）
6、用药频率 -> 药品名称（Frequency_Drug）
7、持续时间 -> 药品名称（Duration_Drug）
8、用药剂量 -> 药品名称（Amount_Drug）
9、用药方法 -> 药品名称（Method_Drug）
10、不良反应 -> 药品名称（SideEff_Drug）
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">ARG_0a_SET</span> <span class="o">=</span> <span class="nb">set</span><span class="p">([</span><span class="s1">&#39;Test&#39;</span><span class="p">,</span> <span class="s1">&#39;Symptom&#39;</span><span class="p">,</span> <span class="s1">&#39;Treatment&#39;</span><span class="p">,</span> <span class="s1">&#39;Drug&#39;</span><span class="p">,</span> <span class="s1">&#39;Anatomy&#39;</span><span class="p">])</span>

<span class="n">ARG_1a_SET</span> <span class="o">=</span> <span class="nb">set</span><span class="p">([</span><span class="s1">&#39;Frequency&#39;</span><span class="p">,</span> <span class="s1">&#39;Duration&#39;</span><span class="p">,</span> <span class="s1">&#39;Amount&#39;</span><span class="p">,</span> <span class="s1">&#39;Method&#39;</span><span class="p">,</span> <span class="s1">&#39;SideEff&#39;</span><span class="p">])</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">ARG_0b</span> <span class="o">=</span> <span class="s1">&#39;Disease&#39;</span>
<span class="n">ARG_1b</span> <span class="o">=</span> <span class="s1">&#39;Drug&#39;</span>

<span class="n">ARG_0b</span><span class="p">,</span> <span class="n">ARG_1b</span>
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<pre>(&#39;Disease&#39;, &#39;Drug&#39;)</pre>
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</div>训练数据，测试数据
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_ann_file_list</span> <span class="o">=</span> <span class="n">glob</span><span class="p">(</span><span class="s1">&#39;./Demo/DataSets/ruijin_round2_train/ruijin_round2_train/*.ann&#39;</span><span class="p">)</span>
<span class="n">train_txt_file_list</span> <span class="o">=</span> <span class="n">glob</span><span class="p">(</span><span class="s1">&#39;./Demo/DataSets/ruijin_round2_train/ruijin_round2_train/*.txt&#39;</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># test_txt_file_list = glob(&#39;./Demo/DataSets/ruijin_round2_test_a/ruijin_round2_test_a/*.txt&#39;)</span>
<span class="c1"># test_ann_file_list = glob(&#39;./Demo/DataSets/ruijin_round2_test_a/ruijin_round2_test_a/*.ann&#39;)</span>

<span class="n">test_txt_file_list</span> <span class="o">=</span> <span class="n">glob</span><span class="p">(</span><span class="s1">&#39;./Demo/DataSets/ruijin_round2_test_b/ruijin_round2_test_b/*.txt&#39;</span><span class="p">)</span>
<span class="n">test_ann_file_list</span> <span class="o">=</span> <span class="n">glob</span><span class="p">(</span><span class="s1">&#39;./Demo/DataSets/ruijin_round2_test_b/ruijin_round2_test_b/*.ann&#39;</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">test_ann_file_list_dict</span> <span class="o">=</span> <span class="p">{</span><span class="nb">str</span><span class="p">(</span><span class="n">path</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;/&#39;</span><span class="p">)[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;.&#39;</span><span class="p">)[</span><span class="mi">0</span><span class="p">]):</span><span class="n">path</span> <span class="k">for</span> <span class="n">path</span> <span class="ow">in</span> <span class="n">test_ann_file_list</span><span class="p">}</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">len</span><span class="p">(</span><span class="n">test_ann_file_list_dict</span><span class="p">)</span>
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<pre>54</pre>
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</div>train_text_dict：各个文本文件
train_anno_dict：各个文件实体标注部分
train_arg_dict：各个文件实体关系标注部分
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">remove_semicolon</span><span class="p">(</span><span class="n">t</span><span class="p">):</span>
    
    <span class="k">if</span> <span class="s1">&#39;;&#39;</span> <span class="ow">in</span> <span class="p">(</span><span class="n">t</span><span class="p">):</span>
        
        <span class="n">temp</span> <span class="o">=</span> <span class="n">t</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;;&#39;</span><span class="p">)</span>
        <span class="n">temp_0</span> <span class="o">=</span> <span class="n">temp</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39; &#39;</span><span class="p">)[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
        <span class="n">temp_1</span> <span class="o">=</span> <span class="n">temp</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39; &#39;</span><span class="p">)[</span><span class="o">-</span><span class="mi">1</span><span class="p">:]</span>
        
        <span class="k">return</span> <span class="n">temp_0</span> <span class="o">+</span> <span class="n">temp_1</span>

    <span class="k">else</span><span class="p">:</span>
        <span class="k">return</span> <span class="n">t</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39; &#39;</span><span class="p">)</span>
    
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">split_arg</span><span class="p">(</span><span class="n">t</span><span class="p">):</span>
    
    <span class="n">t_list</span> <span class="o">=</span> <span class="n">t</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39; &#39;</span><span class="p">)</span>
    
    <span class="k">if</span> <span class="s1">&#39;_&#39;</span> <span class="ow">in</span> <span class="n">t_list</span><span class="p">[</span><span class="mi">0</span><span class="p">]:</span>
        <span class="n">arg_a</span><span class="p">,</span> <span class="n">arg_b</span> <span class="o">=</span> <span class="n">t_list</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;_&#39;</span><span class="p">)</span>
    <span class="k">elif</span> <span class="s1">&#39;-&#39;</span> <span class="ow">in</span> <span class="n">t_list</span><span class="p">[</span><span class="mi">0</span><span class="p">]:</span>
        <span class="n">arg_a</span><span class="p">,</span> <span class="n">arg_b</span> <span class="o">=</span> <span class="n">t_list</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;-&#39;</span><span class="p">)</span>
        
    <span class="n">arg1</span> <span class="o">=</span> <span class="n">t_list</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;:&#39;</span><span class="p">)[</span><span class="mi">1</span><span class="p">]</span>
    <span class="n">arg2</span> <span class="o">=</span> <span class="n">t_list</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;:&#39;</span><span class="p">)[</span><span class="mi">1</span><span class="p">]</span>
        
    <span class="k">return</span> <span class="p">[</span><span class="n">arg_a</span><span class="p">,</span> <span class="n">arg_b</span><span class="p">,</span> <span class="n">arg1</span><span class="p">,</span> <span class="n">arg2</span><span class="p">]</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">get_df</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">filted</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
    
    <span class="k">if</span> <span class="n">arg</span><span class="p">:</span>
        <span class="n">anno</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">sep</span><span class="o">=</span><span class="s1">&#39;</span><span class="se">\t</span><span class="s1">&#39;</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span>

        <span class="n">anno</span> <span class="o">=</span> <span class="n">anno</span><span class="p">[</span><span class="n">anno</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="s1">&#39;R&#39;</span><span class="p">)]</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
        
        <span class="n">anno_1</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vstack</span><span class="p">((</span><span class="n">anno</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">split_arg</span><span class="p">)))</span>

        <span class="n">anno_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">()</span>
        <span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;id&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">anno</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
        <span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;arg_a&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">anno_1</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span>
        <span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;arg_b&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">anno_1</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">]</span>
        <span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;arg_1&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">anno_1</span><span class="p">[:,</span> <span class="mi">2</span><span class="p">]</span>
        <span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;arg_2&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">anno_1</span><span class="p">[:,</span> <span class="mi">3</span><span class="p">]</span>
        
        <span class="k">return</span> <span class="n">anno_df</span><span class="p">,</span> <span class="n">anno</span>
    
    <span class="k">else</span><span class="p">:</span>
        <span class="n">anno</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">sep</span><span class="o">=</span><span class="s1">&#39;</span><span class="se">\t</span><span class="s1">&#39;</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span>

        <span class="n">anno</span> <span class="o">=</span> <span class="n">anno</span><span class="p">[</span><span class="n">anno</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="s1">&#39;T&#39;</span><span class="p">)]</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
        
        <span class="n">anno_1</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">vstack</span><span class="p">((</span><span class="n">anno</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">remove_semicolon</span><span class="p">)))</span>

        <span class="n">anno_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">()</span>
        <span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;id&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">anno</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
        <span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;label&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">anno_1</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span>
        <span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;idx_0&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">anno_1</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)</span>
        <span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;idx_1&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">anno_1</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="nb">int</span><span class="p">)</span>
        <span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;text&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">anno</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span>
        
        <span class="k">if</span> <span class="n">filted</span><span class="p">:</span>
            <span class="n">anno_df</span> <span class="o">=</span> <span class="n">anno_df</span><span class="p">[</span><span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;label&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isin</span><span class="p">(</span><span class="n">ARG_ALL</span><span class="p">)]</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">anno_df</span><span class="p">,</span> <span class="n">anno</span>
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</div>这里将一些全角字符转换为半角
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">TRAN_TAB</span> <span class="o">=</span> <span class="nb">str</span><span class="o">.</span><span class="n">maketrans</span><span class="p">(</span><span class="sa">u</span><span class="s1">&#39;！？【】『』〔〕（）％＃＠＆１２３４５６７８９０“”’‘&#39;</span><span class="p">,</span> <span class="sa">u</span><span class="s1">&#39;!?[][][]()%#@&amp;1234567890&quot;&quot;</span><span class="se">\&#39;\&#39;</span><span class="s1">&#39;</span><span class="p">)</span>

<span class="k">def</span> <span class="nf">text_filter</span><span class="p">(</span><span class="n">text</span><span class="p">):</span>
    
    <span class="n">_l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">text</span><span class="p">)</span>
    <span class="n">_text</span> <span class="o">=</span> <span class="n">text</span><span class="o">.</span><span class="n">translate</span><span class="p">(</span><span class="n">TRAN_TAB</span><span class="p">)</span>
    <span class="k">assert</span> <span class="n">_l</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">_text</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">_text</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_text_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">path</span> <span class="ow">in</span> <span class="n">train_txt_file_list</span><span class="p">:</span>
    <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">path</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
        <span class="n">train_text_dict</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">path</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;/&#39;</span><span class="p">)[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;.&#39;</span><span class="p">)[</span><span class="mi">0</span><span class="p">])]</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">text_filter</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">f</span><span class="o">.</span><span class="n">read</span><span class="p">())))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="n">train_text_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;0&#39;</span><span class="p">)[</span><span class="mi">2235</span><span class="o">-</span><span class="mi">10</span><span class="p">:</span> <span class="mi">2287</span><span class="o">+</span><span class="mi">10</span><span class="p">])</span>
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<pre>[&#39;展&#39;, &#39;i&#39;, &#39;1&#39;, &#39; &#39;, &#39;8&#39;, &#39;|&#39;, &#39;。&#39;, &#39;\n&#39;, &#39;2&#39;, &#39;.&#39;, &#39;口&#39;, &#39;服&#39;, &#39;降&#39;, &#39;糖&#39;, &#39;药&#39;, &#39;物&#39;, &#39;未&#39;, &#39;达&#39;, &#39;标&#39;, &#39;加&#39;, &#39;用&#39;, &#39;或&#39;, &#39;改&#39;, &#39;用&#39;, &#39;胰&#39;, &#39;岛&#39;, &#39;素&#39;, &#39;的&#39;, &#39;患&#39;, &#39;\n&#39;, &#39;者&#39;, &#39;,&#39;, &#39;其&#39;, &#39;血&#39;, &#39;糖&#39;, &#39;控&#39;, &#39;制&#39;, &#39;目&#39;, &#39;标&#39;, &#39;值&#39;, &#39;可&#39;, &#39;适&#39;, &#39;当&#39;, &#39;放&#39;, &#39;宽&#39;, &#39;至&#39;, &#39;H&#39;, &#39;B&#39;, &#39;A&#39;, &#39;1&#39;, &#39;C&#39;, &#39; &#39;, &#39; &#39;, &#39;。&#39;, &#39;&lt;&#39;, &#39;7&#39;, &#39;%&#39;, &#39;,&#39;, &#39;以&#39;, &#39;减&#39;, &#39;\n&#39;, &#39;少&#39;, &#39;低&#39;, &#39;血&#39;, &#39;糖&#39;, &#39;和&#39;, &#39;体&#39;, &#39;重&#39;, &#39;增&#39;, &#39;加&#39;, &#39;这&#39;, &#39;两&#39;]
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># train_anno_dict = {str(path.split(&#39;/&#39;)[-1].split(&#39;.&#39;)[0]):get_df(path, filted=True)[0] for path in train_ann_file_list}</span>
<span class="n">train_anno_dict</span> <span class="o">=</span> <span class="p">{</span><span class="nb">str</span><span class="p">(</span><span class="n">path</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;/&#39;</span><span class="p">)[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;.&#39;</span><span class="p">)[</span><span class="mi">0</span><span class="p">]):</span><span class="n">get_df</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">filted</span><span class="o">=</span><span class="kc">False</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">path</span> <span class="ow">in</span> <span class="n">train_ann_file_list</span><span class="p">}</span>
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<pre>(388, 5)</pre>
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      <th>0</th>
      <td>T1</td>
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      <td>1845</td>
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      <td>1型糖尿病</td>
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      <th>1</th>
      <td>T2</td>
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      <td>1983</td>
      <td>1988</td>
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      <th>2</th>
      <td>T4</td>
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      <td>30</td>
      <td>35</td>
      <td>2型糖尿病</td>
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      <td>T5</td>
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      <td>1822</td>
      <td>1827</td>
      <td>2型糖尿病</td>
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      <th>4</th>
      <td>T6</td>
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<pre>array([&#39;Disease&#39;, &#39;Test&#39;, &#39;Test_Value&#39;, &#39;Symptom&#39;, &#39;Level&#39;, &#39;SideEff&#39;,
       &#39;Anatomy&#39;, &#39;Drug&#39;, &#39;Reason&#39;, &#39;Duration&#39;], dtype=object)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_arg_dict</span> <span class="o">=</span> <span class="p">{</span><span class="nb">str</span><span class="p">(</span><span class="n">path</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;/&#39;</span><span class="p">)[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;.&#39;</span><span class="p">)[</span><span class="mi">0</span><span class="p">]):</span><span class="n">get_df</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">arg</span><span class="o">=</span><span class="kc">True</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">path</span> <span class="ow">in</span> <span class="n">train_ann_file_list</span><span class="p">}</span>
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      <td>T14</td>
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      <td>T3</td>
      <td>T25</td>
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      <td>T31</td>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">_add_anno_to_arg</span><span class="p">(</span><span class="n">df_anno</span><span class="p">,</span> <span class="n">df_arg</span><span class="p">):</span>
    
    <span class="n">anno_a</span> <span class="o">=</span> <span class="n">df_anno</span> <span class="c1"># train_anno_dict.get(&#39;0&#39;)</span>
    <span class="n">anno_b</span> <span class="o">=</span> <span class="n">df_arg</span> <span class="c1"># train_arg_dict.get(&#39;0&#39;)</span>
    
    <span class="n">arg1_df</span> <span class="o">=</span> <span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">anno_b</span><span class="p">[[</span><span class="s1">&#39;id&#39;</span><span class="p">,</span> <span class="s1">&#39;arg_1&#39;</span><span class="p">,</span> <span class="s1">&#39;arg_a&#39;</span><span class="p">]],</span> 
              <span class="n">anno_a</span><span class="p">[[</span><span class="s1">&#39;id&#39;</span><span class="p">,</span> <span class="s1">&#39;idx_0&#39;</span><span class="p">,</span> <span class="s1">&#39;idx_1&#39;</span><span class="p">,</span> <span class="s1">&#39;label&#39;</span><span class="p">,</span> <span class="s1">&#39;text&#39;</span><span class="p">]],</span> 
              <span class="n">left_on</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;arg_1&#39;</span><span class="p">],</span> 
              <span class="n">right_on</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;id&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;arg_1&#39;</span><span class="p">,</span> <span class="s1">&#39;id_y&#39;</span><span class="p">]))</span><span class="o">.</span><span class="n">rename</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;id_x&#39;</span><span class="p">:</span><span class="s1">&#39;id&#39;</span><span class="p">,</span>
                                                                                <span class="s1">&#39;idx_0&#39;</span><span class="p">:</span><span class="s1">&#39;arg_1_idx_0&#39;</span><span class="p">,</span>
                                                                                <span class="s1">&#39;idx_1&#39;</span><span class="p">:</span><span class="s1">&#39;arg_1_idx_1&#39;</span><span class="p">,</span> 
                                                                                <span class="s1">&#39;label&#39;</span><span class="p">:</span><span class="s1">&#39;arg_a_label&#39;</span><span class="p">,</span> 
                                                                                <span class="s1">&#39;text&#39;</span><span class="p">:</span><span class="s1">&#39;arg_a_text&#39;</span><span class="p">})</span>    
    <span class="n">arg2_df</span> <span class="o">=</span> <span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">anno_b</span><span class="p">[[</span><span class="s1">&#39;id&#39;</span><span class="p">,</span> <span class="s1">&#39;arg_2&#39;</span><span class="p">,</span> <span class="s1">&#39;arg_b&#39;</span><span class="p">]],</span> 
              <span class="n">anno_a</span><span class="p">[[</span><span class="s1">&#39;id&#39;</span><span class="p">,</span> <span class="s1">&#39;idx_0&#39;</span><span class="p">,</span> <span class="s1">&#39;idx_1&#39;</span><span class="p">,</span> <span class="s1">&#39;label&#39;</span><span class="p">,</span> <span class="s1">&#39;text&#39;</span><span class="p">]],</span> 
              <span class="n">left_on</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;arg_2&#39;</span><span class="p">],</span> 
              <span class="n">right_on</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;id&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;arg_2&#39;</span><span class="p">,</span> <span class="s1">&#39;id_y&#39;</span><span class="p">]))</span><span class="o">.</span><span class="n">rename</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;id_x&#39;</span><span class="p">:</span><span class="s1">&#39;id&#39;</span><span class="p">,</span>
                                                                                <span class="s1">&#39;idx_0&#39;</span><span class="p">:</span><span class="s1">&#39;arg_2_idx_0&#39;</span><span class="p">,</span>
                                                                                <span class="s1">&#39;idx_1&#39;</span><span class="p">:</span><span class="s1">&#39;arg_2_idx_1&#39;</span><span class="p">,</span> 
                                                                                <span class="s1">&#39;label&#39;</span><span class="p">:</span><span class="s1">&#39;arg_b_label&#39;</span><span class="p">,</span>
                                                                                <span class="s1">&#39;text&#39;</span><span class="p">:</span><span class="s1">&#39;arg_b_text&#39;</span><span class="p">})</span>    
    <span class="k">return</span> <span class="n">pd</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">anno_b</span><span class="p">,</span> <span class="n">arg1_df</span><span class="p">),</span> <span class="n">arg2_df</span><span class="p">)</span>

<span class="k">def</span> <span class="nf">add_anno_to_arg</span><span class="p">(</span><span class="n">df_anno_dict</span><span class="p">,</span> <span class="n">df_arg_dict</span><span class="p">):</span>
    
    <span class="n">arg_dict</span> <span class="o">=</span> <span class="p">{}</span>
    
    <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">df_anno_dict</span><span class="p">:</span>
        <span class="n">anno</span> <span class="o">=</span> <span class="n">_add_anno_to_arg</span><span class="p">(</span><span class="n">df_anno_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">k</span><span class="p">),</span> <span class="n">df_arg_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">k</span><span class="p">))</span>
        <span class="n">idx_all</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sort</span><span class="p">(</span><span class="n">anno</span><span class="p">[[</span><span class="s1">&#39;arg_1_idx_0&#39;</span><span class="p">,</span> <span class="s1">&#39;arg_1_idx_1&#39;</span><span class="p">,</span> <span class="s1">&#39;arg_2_idx_0&#39;</span><span class="p">,</span> <span class="s1">&#39;arg_2_idx_1&#39;</span><span class="p">]]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
        <span class="n">idx_len</span> <span class="o">=</span> <span class="n">idx_all</span><span class="p">[:,</span> <span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">idx_all</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span>
        <span class="n">anno</span><span class="p">[</span><span class="s1">&#39;idx_len_max&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">idx_len</span>
        <span class="n">anno</span><span class="p">[</span><span class="s1">&#39;idx_len_mid&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="n">anno</span><span class="p">[</span><span class="s1">&#39;arg_2_idx_1&#39;</span><span class="p">]</span><span class="o">+</span><span class="n">anno</span><span class="p">[</span><span class="s1">&#39;arg_2_idx_0&#39;</span><span class="p">])</span><span class="o">/</span><span class="mi">2</span> <span class="o">-</span> <span class="p">(</span><span class="n">anno</span><span class="p">[</span><span class="s1">&#39;arg_1_idx_1&#39;</span><span class="p">]</span><span class="o">+</span><span class="n">anno</span><span class="p">[</span><span class="s1">&#39;arg_1_idx_0&#39;</span><span class="p">])</span><span class="o">/</span><span class="mi">2</span>
        <span class="n">anno</span><span class="p">[</span><span class="s1">&#39;arg_len&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">anno</span><span class="p">[</span><span class="s1">&#39;arg_2&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">str</span><span class="p">[</span><span class="mi">1</span><span class="p">:]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)</span> <span class="o">-</span> <span class="n">anno</span><span class="p">[</span><span class="s1">&#39;arg_1&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">str</span><span class="p">[</span><span class="mi">1</span><span class="p">:]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)</span>
        <span class="n">anno</span><span class="p">[</span><span class="s1">&#39;len_abs_min&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">anno</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">min</span><span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="s1">&#39;idx_len_max&#39;</span><span class="p">]),</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="s1">&#39;idx_len_mid&#39;</span><span class="p">]),</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="s1">&#39;arg_len&#39;</span><span class="p">]))),</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
        
<span class="c1">#         anno = anno[~(anno[&#39;arg_a&#39;] != anno[&#39;arg_a_label&#39;]) | (anno[&#39;arg_b&#39;] != anno[&#39;arg_b_label&#39;])].reset_index(drop=True)</span>
        <span class="n">anno</span> <span class="o">=</span> <span class="n">anno</span><span class="p">[(</span><span class="n">anno</span><span class="p">[</span><span class="s1">&#39;arg_a&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="n">anno</span><span class="p">[</span><span class="s1">&#39;arg_a_label&#39;</span><span class="p">])</span> <span class="o">&amp;</span> <span class="p">(</span><span class="n">anno</span><span class="p">[</span><span class="s1">&#39;arg_b&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="n">anno</span><span class="p">[</span><span class="s1">&#39;arg_b_label&#39;</span><span class="p">])]</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    
<span class="c1">#         thres = np.mean(anno[&#39;idx_len_max&#39;]) + np.std(anno[&#39;idx_len_max&#39;]) * 2</span>
<span class="c1">#         anno = anno[(anno[&#39;idx_len_max&#39;] &lt; thres) | (anno[&#39;idx_len_max&#39;] &lt; 350)]</span>
<span class="c1">#         anno = anno[(anno[&#39;idx_len_max&#39;] &lt; thres)]</span>
        
        <span class="n">arg_dict</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="n">anno</span>
        
    <span class="k">return</span> <span class="n">arg_dict</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_arg_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;0&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">(),</span> <span class="n">train_arg_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;0&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">shape</span>
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<pre>(   id arg_a    arg_b arg_1 arg_2  arg_1_idx_0  arg_1_idx_1 arg_a_label  \
 0  R1  Test  Disease  T369  T368            9           14        Test   
 1  R2  Test  Disease   T13   T25           61           63        Test   
 2  R3  Test  Disease   T14   T25           89           94        Test   
 3  R4  Test  Disease    T3   T25          100          103        Test   
 4  R5  Test  Disease   T31   T33          242          244        Test   
 
   arg_a_text  arg_2_idx_0  arg_2_idx_1 arg_b_label arg_b_text  idx_len_max  \
 0      HBA1C            4            9     Disease      2型糖尿病           10   
 1         血糖           66           69     Disease        糖尿病            8   
 2      HBA1C           66           69     Disease        糖尿病           28   
 3        血 糖           66           69     Disease        糖尿病           37   
 4         血糖          249          257     Disease   糖尿病微血管病变           15   
 
    idx_len_mid  arg_len  len_abs_min  
 0         -5.0       -1          1.0  
 1          5.5       12          5.5  
 2        -24.0       11         11.0  
 3        -34.0       22         22.0  
 4         10.0        2          2.0  , (175, 17))</pre>
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</div>train_encode_dict：文字编码（索引）
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_text_set</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span>
<span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">train_text_dict</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    <span class="n">train_text_set</span> <span class="o">=</span> <span class="n">train_text_set</span> <span class="o">|</span> <span class="nb">set</span><span class="p">(</span><span class="n">v</span><span class="p">)</span>
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<pre>3266</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_encode_dict</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="nb">sorted</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">train_text_set</span><span class="p">)),</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">train_text_set</span><span class="p">))))</span>
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<pre>3266</pre>
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<span class="n">TOTAL_SIZE</span>
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<pre>3267</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_text_encoded_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">train_text_dict</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    <span class="n">train_text_encoded_dict</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">train_encode_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> 
                                          <span class="k">if</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">train_encode_dict</span> <span class="k">else</span> <span class="mi">0</span><span class="p">,</span> <span class="n">v</span><span class="p">))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">len</span><span class="p">(</span><span class="n">train_text_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;0&#39;</span><span class="p">))</span>
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<pre>6774</pre>
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<pre>([&#39;中&#39;, &#39;国&#39;, &#39;成&#39;, &#39;人&#39;, &#39;2&#39;, &#39;型&#39;, &#39;糖&#39;, &#39;尿&#39;, &#39;病&#39;, &#39;H&#39;],
 [184, 705, 1157, 240, 18, 732, 2239, 936, 1993, 40],
 6774,
 6774)</pre>
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<pre>184</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_encode_dict_idx</span> <span class="o">=</span> <span class="p">{</span><span class="nb">str</span><span class="p">(</span><span class="n">v</span><span class="p">):</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">train_encode_dict</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>
<span class="nb">len</span><span class="p">(</span><span class="n">train_encode_dict_idx</span><span class="p">)</span>
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</div>3276
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<pre>{&#39;Normal&#39;: 0,
 &#39;Disease&#39;: 1,
 &#39;Reason&#39;: 2,
 &#39;Symptom&#39;: 3,
 &#39;Test&#39;: 4,
 &#39;Test_Value&#39;: 5,
 &#39;Drug&#39;: 6,
 &#39;Frequency&#39;: 7,
 &#39;Amount&#39;: 8,
 &#39;Method&#39;: 9,
 &#39;Treatment&#39;: 10,
 &#39;Operation&#39;: 11,
 &#39;Anatomy&#39;: 12,
 &#39;Level&#39;: 13,
 &#39;Duration&#39;: 14,
 &#39;SideEff&#39;: 15}</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># ARG_0a_SET, ARG_0b, ARG_1a_SET, ARG_1b</span>

<span class="n">ARG_0b</span><span class="p">,</span> <span class="n">ARG_1b</span>
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<pre>(&#39;Disease&#39;, &#39;Drug&#39;)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">get_a_labels_dict</span><span class="p">(</span><span class="n">anno_dict</span><span class="p">,</span> <span class="n">text_dict</span><span class="p">,</span> <span class="n">labels_dict</span><span class="p">):</span>
    <span class="n">train_ab_lables_dict</span> <span class="o">=</span> <span class="p">{}</span>
    <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">anno_dict</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>

        <span class="n">_labels</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="nb">len</span><span class="p">(</span><span class="n">text_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">k</span><span class="p">)),</span> <span class="mi">1</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span> <span class="o">*</span> <span class="n">labels_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;Normal&#39;</span><span class="p">)</span>

        <span class="k">for</span> <span class="n">idx</span><span class="p">,</span> <span class="n">row</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">v</span><span class="o">.</span><span class="n">itertuples</span><span class="p">()):</span>
            
            <span class="n">_label</span> <span class="o">=</span> <span class="n">row</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span>
            
            <span class="k">if</span> <span class="n">_label</span> <span class="ow">in</span> <span class="n">labels_dict</span><span class="p">:</span>

                <span class="n">_idx_0</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">row</span><span class="p">[</span><span class="mi">3</span><span class="p">])</span>
                <span class="n">_idx_1</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">row</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span>

                <span class="k">if</span> <span class="n">_idx_0</span> <span class="o">&gt;=</span> <span class="n">_idx_1</span><span class="p">:</span>
                    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Bad idx&#39;</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">row</span><span class="p">)</span>
                    <span class="k">break</span>
                    
                <span class="n">_labels</span><span class="p">[</span><span class="n">_idx_0</span><span class="p">:</span><span class="n">_idx_1</span><span class="p">]</span> <span class="o">=</span> <span class="n">labels_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">_label</span><span class="p">)</span>

        <span class="n">train_ab_lables_dict</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="n">_labels</span>
            
    <span class="k">return</span> <span class="n">train_ab_lables_dict</span>

<span class="k">def</span> <span class="nf">get_aa_labels_dict</span><span class="p">(</span><span class="n">anno_dict</span><span class="p">,</span> <span class="n">text_dict</span><span class="p">,</span> <span class="n">labels_set</span><span class="p">):</span>
    <span class="n">train_ab_lables_dict</span> <span class="o">=</span> <span class="p">{}</span>
    <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">anno_dict</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>

        <span class="n">_labels</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="nb">len</span><span class="p">(</span><span class="n">text_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">k</span><span class="p">)),</span> <span class="mi">1</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>

        <span class="k">for</span> <span class="n">idx</span><span class="p">,</span> <span class="n">row</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">v</span><span class="o">.</span><span class="n">itertuples</span><span class="p">()):</span>
            
            <span class="n">_label</span> <span class="o">=</span> <span class="n">row</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span>
            
            <span class="k">if</span> <span class="n">_label</span> <span class="ow">in</span> <span class="n">labels_set</span><span class="p">:</span>

                <span class="n">_idx_0</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">row</span><span class="p">[</span><span class="mi">3</span><span class="p">])</span>
                <span class="n">_idx_1</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">row</span><span class="p">[</span><span class="mi">4</span><span class="p">])</span>

                <span class="k">if</span> <span class="n">_idx_0</span> <span class="o">&gt;=</span> <span class="n">_idx_1</span><span class="p">:</span>
                    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Bad idx&#39;</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">row</span><span class="p">)</span>
                    <span class="k">break</span>
                    
<span class="c1">#                 _labels[_idx_0:_idx_1] = labels_dict.get(_label)</span>
                <span class="n">_labels</span><span class="p">[</span><span class="n">_idx_0</span><span class="p">:</span><span class="n">_idx_1</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>

        <span class="n">train_ab_lables_dict</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="n">_labels</span>
            
    <span class="k">return</span> <span class="n">train_ab_lables_dict</span>
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    </div>
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</div>这里将每个文本中arg_a的部分标注出来
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_0a_lables_dict</span> <span class="o">=</span> <span class="n">get_aa_labels_dict</span><span class="p">(</span><span class="n">train_anno_dict</span><span class="p">,</span> <span class="n">train_text_dict</span><span class="p">,</span> <span class="n">LABELS_0</span><span class="p">)</span>
<span class="n">train_1a_lables_dict</span> <span class="o">=</span> <span class="n">get_aa_labels_dict</span><span class="p">(</span><span class="n">train_anno_dict</span><span class="p">,</span> <span class="n">train_text_dict</span><span class="p">,</span> <span class="n">LABELS_1</span><span class="p">)</span>

<span class="n">train_a_lables_dict</span> <span class="o">=</span> <span class="n">get_a_labels_dict</span><span class="p">(</span><span class="n">train_anno_dict</span><span class="p">,</span> <span class="n">train_text_dict</span><span class="p">,</span> <span class="n">LABELS_DICT</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="p">(</span><span class="n">train_0a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;0&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">(),</span> <span class="n">train_0a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;0&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> 

<span class="n">train_a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;0&#39;</span><span class="p">)[:,</span> <span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">sum</span><span class="p">(),</span> <span class="n">train_a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;0&#39;</span><span class="p">)[:,</span> <span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">sum</span><span class="p">(),</span> <span class="n">train_a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;0&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
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<pre>(595, (6774, 1), 0, 6819, (6774, 1))</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="p">(</span><span class="n">train_0a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;0&#39;</span><span class="p">)[:</span><span class="mi">10</span><span class="p">],</span> 
<span class="n">train_a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;0&#39;</span><span class="p">)[:</span><span class="mi">10</span><span class="p">],</span> <span class="n">train_a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;0&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">max</span><span class="p">())</span>
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<pre>(array([[0],
        [0],
        [0],
        [0],
        [0],
        [0],
        [0],
        [0],
        [0],
        [1]], dtype=uint8), array([[0],
        [0],
        [0],
        [0],
        [1],
        [1],
        [1],
        [1],
        [1],
        [4]], dtype=uint8), 15)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">LABELS_DICT</span><span class="p">)):</span>
    <span class="nb">print</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">i</span><span class="p">),</span> <span class="s1">&#39;counts:&#39;</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">train_a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;0&#39;</span><span class="p">)</span><span class="o">==</span><span class="n">i</span><span class="p">))</span>
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<pre>0 counts: 5256
1 counts: 506
2 counts: 13
3 counts: 53
4 counts: 471
5 counts: 231
6 counts: 38
7 counts: 0
8 counts: 0
9 counts: 0
10 counts: 0
11 counts: 0
12 counts: 30
13 counts: 65
14 counts: 9
15 counts: 102
</pre>
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</div>模型训练参数：滑窗长度为320
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">TRAIN_LENGTH_HALF</span> <span class="o">=</span> <span class="mi">160</span>
<span class="n">TRAIN_LENGTH</span> <span class="o">=</span> <span class="p">(</span><span class="n">TRAIN_LENGTH_HALF</span><span class="o">*</span><span class="mi">2</span><span class="p">)</span>

<span class="n">LEN_LABELS</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">LABELS_DICT</span><span class="p">)</span>

<span class="n">TRAIN_LENGTH</span><span class="p">,</span> <span class="n">LEN_LABELS</span>
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<pre>(320, 16)</pre>
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<pre>16</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">train_arg_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;0&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>id</th>
      <th>arg_a</th>
      <th>arg_b</th>
      <th>arg_1</th>
      <th>arg_2</th>
      <th>arg_1_idx_0</th>
      <th>arg_1_idx_1</th>
      <th>arg_a_label</th>
      <th>arg_a_text</th>
      <th>arg_2_idx_0</th>
      <th>arg_2_idx_1</th>
      <th>arg_b_label</th>
      <th>arg_b_text</th>
      <th>idx_len_max</th>
      <th>idx_len_mid</th>
      <th>arg_len</th>
      <th>len_abs_min</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>R1</td>
      <td>Test</td>
      <td>Disease</td>
      <td>T369</td>
      <td>T368</td>
      <td>9</td>
      <td>14</td>
      <td>Test</td>
      <td>HBA1C</td>
      <td>4</td>
      <td>9</td>
      <td>Disease</td>
      <td>2型糖尿病</td>
      <td>10</td>
      <td>-5.0</td>
      <td>-1</td>
      <td>1.0</td>
    </tr>
    <tr>
      <th>1</th>
      <td>R2</td>
      <td>Test</td>
      <td>Disease</td>
      <td>T13</td>
      <td>T25</td>
      <td>61</td>
      <td>63</td>
      <td>Test</td>
      <td>血糖</td>
      <td>66</td>
      <td>69</td>
      <td>Disease</td>
      <td>糖尿病</td>
      <td>8</td>
      <td>5.5</td>
      <td>12</td>
      <td>5.5</td>
    </tr>
    <tr>
      <th>2</th>
      <td>R3</td>
      <td>Test</td>
      <td>Disease</td>
      <td>T14</td>
      <td>T25</td>
      <td>89</td>
      <td>94</td>
      <td>Test</td>
      <td>HBA1C</td>
      <td>66</td>
      <td>69</td>
      <td>Disease</td>
      <td>糖尿病</td>
      <td>28</td>
      <td>-24.0</td>
      <td>11</td>
      <td>11.0</td>
    </tr>
    <tr>
      <th>3</th>
      <td>R4</td>
      <td>Test</td>
      <td>Disease</td>
      <td>T3</td>
      <td>T25</td>
      <td>100</td>
      <td>103</td>
      <td>Test</td>
      <td>血 糖</td>
      <td>66</td>
      <td>69</td>
      <td>Disease</td>
      <td>糖尿病</td>
      <td>37</td>
      <td>-34.0</td>
      <td>22</td>
      <td>22.0</td>
    </tr>
    <tr>
      <th>4</th>
      <td>R5</td>
      <td>Test</td>
      <td>Disease</td>
      <td>T31</td>
      <td>T33</td>
      <td>242</td>
      <td>244</td>
      <td>Test</td>
      <td>血糖</td>
      <td>249</td>
      <td>257</td>
      <td>Disease</td>
      <td>糖尿病微血管病变</td>
      <td>15</td>
      <td>10.0</td>
      <td>2</td>
      <td>2.0</td>
    </tr>
  </tbody>
</table>
</div>
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</div>模型训练参数：在text和arg_a中增加一点noise，以防止预测时会有未出现的字符的情况
MARGIN_LIST：针对每个arg_b的中间位置，滑窗左右便宜从而采样的列表。
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">NOISE_RATIO</span> <span class="o">=</span>  <span class="mf">0.02</span>
<span class="n">NOISE_ARGA</span> <span class="o">=</span> <span class="mf">0.01</span>

<span class="n">MARGIN_LIST</span> <span class="o">=</span> <span class="p">[</span><span class="o">-</span><span class="mi">140</span><span class="p">,</span> <span class="o">-</span><span class="mi">112</span><span class="p">,</span> <span class="o">-</span><span class="mi">84</span><span class="p">,</span> <span class="o">-</span><span class="mi">56</span><span class="p">,</span> <span class="o">-</span><span class="mi">28</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">28</span><span class="p">,</span> <span class="mi">56</span><span class="p">,</span> <span class="mi">84</span><span class="p">,</span> <span class="mi">112</span><span class="p">,</span> <span class="mi">140</span><span class="p">]</span>

<span class="nb">len</span><span class="p">(</span><span class="n">MARGIN_LIST</span><span class="p">)</span>
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<pre>11</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">_get_set_b_list_dict</span><span class="p">(</span><span class="n">b_dict</span><span class="p">,</span> <span class="n">set_b</span><span class="p">,</span> <span class="n">arg_df</span><span class="p">,</span> <span class="n">len_text</span><span class="p">):</span>
    
    <span class="k">for</span> <span class="n">_b</span> <span class="ow">in</span> <span class="n">set_b</span><span class="p">:</span>
        <span class="n">_df</span> <span class="o">=</span> <span class="n">arg_df</span><span class="p">[</span><span class="n">arg_df</span><span class="p">[</span><span class="s1">&#39;arg_2&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="n">_b</span><span class="p">]</span>
        <span class="n">_x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">len_text</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
        
        <span class="k">for</span> <span class="n">idx_b</span><span class="p">,</span> <span class="n">row_b</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">_df</span><span class="o">.</span><span class="n">itertuples</span><span class="p">()):</span>
            
            <span class="k">assert</span> <span class="n">row_b</span><span class="p">[</span><span class="mi">6</span><span class="p">]</span> <span class="o">&gt;=</span> <span class="mi">0</span>
            <span class="k">assert</span> <span class="n">row_b</span><span class="p">[</span><span class="mi">7</span><span class="p">]</span> <span class="o">&gt;=</span> <span class="mi">0</span>
            <span class="k">assert</span> <span class="n">row_b</span><span class="p">[</span><span class="mi">6</span><span class="p">]</span> <span class="o">&lt;=</span> <span class="n">len_text</span>
            <span class="k">assert</span> <span class="n">row_b</span><span class="p">[</span><span class="mi">7</span><span class="p">]</span> <span class="o">&lt;=</span> <span class="n">len_text</span>
            
            <span class="n">_x</span><span class="p">[</span><span class="n">row_b</span><span class="p">[</span><span class="mi">6</span><span class="p">]:</span><span class="n">row_b</span><span class="p">[</span><span class="mi">7</span><span class="p">]]</span> <span class="o">=</span> <span class="mi">1</span>
        
        <span class="n">b_dict</span><span class="p">[</span><span class="n">_b</span><span class="p">]</span> <span class="o">=</span> <span class="n">_x</span>
        
    <span class="k">return</span> <span class="n">b_dict</span>

<span class="k">def</span> <span class="nf">_get_meta_data</span><span class="p">(</span><span class="n">data_x_text_list</span><span class="p">,</span> <span class="n">data_x_arga_list</span><span class="p">,</span> <span class="n">data_x_argaa_list</span><span class="p">,</span> <span class="n">data_x_argb_list</span><span class="p">,</span> <span class="n">data_y_list</span><span class="p">,</span>
                   <span class="n">text_encoded</span><span class="p">,</span> <span class="n">b_dict</span><span class="p">,</span> <span class="n">list_a</span><span class="p">,</span> <span class="n">df_b</span><span class="p">,</span> <span class="n">x_idx</span><span class="p">,</span> <span class="n">len_text</span><span class="p">,</span> <span class="n">set_b</span><span class="p">,</span> <span class="n">list_aa</span><span class="p">):</span>
    
    <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="mi">522</span><span class="p">)</span>
    
    <span class="k">for</span> <span class="n">idx_b</span><span class="p">,</span> <span class="n">row_b</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">df_b</span><span class="o">.</span><span class="n">itertuples</span><span class="p">()):</span> 
        
        <span class="n">_</span><span class="p">,</span> <span class="n">id_b</span><span class="p">,</span> <span class="n">label_b</span><span class="p">,</span> <span class="n">idx_b_0</span><span class="p">,</span> <span class="n">idx_b_1</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">row_b</span>
        
        <span class="n">_idx_b_mid</span> <span class="o">=</span> <span class="nb">int</span><span class="p">((</span><span class="n">idx_b_0</span> <span class="o">+</span> <span class="n">idx_b_1</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span><span class="p">)</span>
        
        <span class="k">for</span> <span class="n">margin</span> <span class="ow">in</span> <span class="n">MARGIN_LIST</span><span class="p">:</span>
            
            <span class="n">idx_b_mid</span> <span class="o">=</span> <span class="n">_idx_b_mid</span> <span class="o">+</span> <span class="n">margin</span>
        
            <span class="n">_left</span> <span class="o">=</span> <span class="n">idx_b_mid</span> <span class="o">-</span> <span class="n">TRAIN_LENGTH_HALF</span>
            <span class="n">_right</span> <span class="o">=</span> <span class="n">idx_b_mid</span> <span class="o">+</span> <span class="n">TRAIN_LENGTH_HALF</span>

            <span class="n">idx_left</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">_left</span><span class="p">)</span>
            <span class="n">idx_right</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">len_text</span><span class="p">,</span> <span class="n">_right</span><span class="p">)</span>

            <span class="n">idx_pad_left</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="nb">min</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">_left</span><span class="p">))</span>
            <span class="n">idx_pad_right</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="nb">min</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">len_text</span> <span class="o">-</span> <span class="n">_right</span><span class="p">))</span>

            <span class="c1"># x arg b</span>
            <span class="n">_b</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">TRAIN_LENGTH</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
            <span class="n">b_start</span> <span class="o">=</span> <span class="n">idx_pad_left</span> <span class="o">+</span> <span class="p">(</span><span class="n">idx_b_0</span> <span class="o">-</span> <span class="n">idx_left</span><span class="p">)</span>
            <span class="n">b_end</span> <span class="o">=</span> <span class="n">idx_pad_left</span> <span class="o">+</span> <span class="p">(</span><span class="n">idx_b_1</span> <span class="o">-</span> <span class="n">idx_left</span><span class="p">)</span>

            <span class="k">if</span> <span class="p">(</span><span class="n">b_start</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span><span class="n">b_end</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span><span class="n">b_start</span> <span class="o">&gt;</span> <span class="n">TRAIN_LENGTH</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span><span class="n">b_end</span> <span class="o">&gt;</span> <span class="n">TRAIN_LENGTH</span><span class="p">):</span>
                <span class="k">continue</span>
                
            <span class="k">assert</span> <span class="n">b_start</span> <span class="o">&gt;=</span> <span class="mi">0</span>
            <span class="k">assert</span> <span class="n">b_end</span> <span class="o">&gt;=</span> <span class="mi">0</span>
            <span class="k">assert</span> <span class="n">b_start</span> <span class="o">&lt;=</span> <span class="n">TRAIN_LENGTH</span>
            <span class="k">assert</span> <span class="n">b_end</span> <span class="o">&lt;=</span> <span class="n">TRAIN_LENGTH</span>

            <span class="n">_b</span><span class="p">[</span><span class="n">b_start</span><span class="p">:</span><span class="n">b_end</span><span class="p">]</span> <span class="o">=</span> <span class="n">x_idx</span><span class="o">+</span><span class="mi">1</span>
            
            <span class="c1"># x arg a</span>
            <span class="n">_a</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">pad</span><span class="p">(</span><span class="n">list_a</span><span class="p">[</span><span class="n">idx_left</span><span class="p">:</span><span class="n">idx_right</span><span class="p">],</span> <span class="p">((</span><span class="n">idx_pad_left</span><span class="p">,</span> <span class="n">idx_pad_right</span><span class="p">),</span> <span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">)),</span> <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;constant&#39;</span><span class="p">,</span> <span class="n">constant_values</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
                        
            <span class="c1"># x arg aa</span>
            <span class="n">_aa</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">pad</span><span class="p">(</span><span class="n">list_aa</span><span class="p">[</span><span class="n">idx_left</span><span class="p">:</span><span class="n">idx_right</span><span class="p">],</span> <span class="p">((</span><span class="n">idx_pad_left</span><span class="p">,</span> <span class="n">idx_pad_right</span><span class="p">),</span> <span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">)),</span> <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;constant&#39;</span><span class="p">,</span> <span class="n">constant_values</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
            
            <span class="c1"># x text</span>
            <span class="n">_x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">pad</span><span class="p">(</span><span class="n">text_encoded</span><span class="p">[</span><span class="n">idx_left</span><span class="p">:</span><span class="n">idx_right</span><span class="p">],</span> <span class="p">(</span><span class="n">idx_pad_left</span><span class="p">,</span> <span class="n">idx_pad_right</span><span class="p">),</span> <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;constant&#39;</span><span class="p">,</span> <span class="n">constant_values</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
            
            <span class="n">mask_t</span> <span class="o">=</span> <span class="kc">None</span>
            <span class="n">mask_a</span> <span class="o">=</span> <span class="kc">None</span>
            <span class="k">if</span> <span class="n">NOISE_RATIO</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">mask</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">_a</span> <span class="o">+</span> <span class="n">_b</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)[</span><span class="n">idx_pad_left</span><span class="p">:</span><span class="n">TRAIN_LENGTH</span><span class="o">-</span><span class="n">idx_pad_right</span><span class="p">]</span>
<span class="c1">#                 mask = np.argwhere(np.squeeze(_b) == 0).reshape(-1)[idx_pad_left:TRAIN_LENGTH-idx_pad_right]</span>
                <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">mask</span><span class="p">)</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">:</span>
                    <span class="n">mask_t</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">choice</span><span class="p">(</span><span class="n">mask</span><span class="p">,</span> <span class="nb">int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">mask</span><span class="p">)</span><span class="o">*</span><span class="n">NOISE_RATIO</span><span class="p">))</span>
                    <span class="n">_x</span><span class="p">[</span><span class="n">mask_t</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
    
            <span class="k">if</span> <span class="n">NOISE_ARGA</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">mask</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">_a</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span> <span class="c1">#[idx_pad_left:TRAIN_LENGTH-idx_pad_right]</span>
                <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">mask</span><span class="p">)</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">:</span>
<span class="c1">#                     mask_a = np.random.choice(mask, int(np.ceil(len(mask)*NOISE_ARGA)))</span>
                    <span class="n">mask_a</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">choice</span><span class="p">(</span><span class="n">mask</span><span class="p">,</span> <span class="nb">int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">mask</span><span class="p">)</span><span class="o">*</span><span class="n">NOISE_ARGA</span><span class="p">))</span>
                    <span class="n">_x</span><span class="p">[</span><span class="n">mask_a</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
<span class="c1">#                     _a[mask_a] = 0</span>
<span class="c1">#                     _aa[mask_a] = 0</span>
                    
            <span class="n">data_x_arga_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_a</span><span class="p">)</span>
            <span class="n">data_x_argaa_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_aa</span><span class="p">)</span>
            <span class="n">data_x_argb_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_b</span><span class="p">)</span>
            <span class="n">data_x_text_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_x</span><span class="p">)</span>

            <span class="c1"># y</span>
            <span class="n">_y</span> <span class="o">=</span> <span class="kc">None</span>
            <span class="k">if</span> <span class="n">id_b</span> <span class="ow">in</span> <span class="n">set_b</span><span class="p">:</span>
                <span class="n">_y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">pad</span><span class="p">(</span>
                        <span class="n">b_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">id_b</span><span class="p">)[</span><span class="n">idx_left</span><span class="p">:</span><span class="n">idx_right</span><span class="p">],</span> 
                        <span class="p">(</span><span class="n">idx_pad_left</span><span class="p">,</span> <span class="n">idx_pad_right</span><span class="p">),</span> 
                        <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;constant&#39;</span><span class="p">,</span> <span class="n">constant_values</span><span class="o">=</span><span class="mi">0</span><span class="p">)[</span><span class="o">...</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">newaxis</span><span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
<span class="c1">#                 if mask_a is not None:</span>
<span class="c1">#                     _y[mask_a] = 0</span>

            <span class="k">else</span><span class="p">:</span>
                <span class="n">_y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">TRAIN_LENGTH</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
                            
            <span class="n">data_y_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_y</span><span class="p">)</span>


    <span class="k">return</span> <span class="p">(</span><span class="n">data_x_text_list</span><span class="p">,</span> <span class="n">data_x_arga_list</span><span class="p">,</span> <span class="n">data_x_argaa_list</span><span class="p">,</span> <span class="n">data_x_argb_list</span><span class="p">,</span> <span class="n">data_y_list</span><span class="p">)</span>


<span class="k">def</span> <span class="nf">get_meta_data</span><span class="p">(</span><span class="n">data_x_text_list</span><span class="p">,</span> <span class="n">data_x_arga_list</span><span class="p">,</span> <span class="n">data_x_argaa_list</span><span class="p">,</span> <span class="n">data_x_argb_list</span><span class="p">,</span> <span class="n">data_y_list</span><span class="p">,</span> 
                  <span class="n">text_encoded</span><span class="p">,</span> <span class="n">anno_df</span><span class="p">,</span> <span class="n">list_a</span><span class="p">,</span> <span class="n">arg_df</span><span class="p">,</span> <span class="n">list_0a</span><span class="p">,</span> <span class="n">list_1a</span><span class="p">):</span>
    
    <span class="n">len_text</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">text_encoded</span><span class="p">)</span>
    
    <span class="n">df_0b</span> <span class="o">=</span> <span class="n">anno_df</span><span class="p">[</span><span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;label&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="n">ARG_0b</span><span class="p">]</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="s1">&#39;idx_0&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    <span class="n">df_1b</span> <span class="o">=</span> <span class="n">anno_df</span><span class="p">[</span><span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;label&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="n">ARG_1b</span><span class="p">]</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="s1">&#39;idx_0&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    
    <span class="n">set_0b</span> <span class="o">=</span> <span class="kc">None</span>
    <span class="n">set_1b</span> <span class="o">=</span> <span class="kc">None</span>
    <span class="n">b_dict</span> <span class="o">=</span> <span class="kc">None</span>
    <span class="k">if</span> <span class="n">arg_df</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
        <span class="n">set_0b</span> <span class="o">=</span> <span class="n">arg_df</span><span class="p">[</span><span class="n">arg_df</span><span class="p">[</span><span class="s1">&#39;arg_b&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="n">ARG_0b</span><span class="p">][</span><span class="s1">&#39;arg_2&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">()</span>
        <span class="n">set_1b</span> <span class="o">=</span> <span class="n">arg_df</span><span class="p">[</span><span class="n">arg_df</span><span class="p">[</span><span class="s1">&#39;arg_b&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="n">ARG_1b</span><span class="p">][</span><span class="s1">&#39;arg_2&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">()</span>
        
        <span class="n">b_dict</span> <span class="o">=</span> <span class="p">{}</span>
        <span class="n">b_dict</span> <span class="o">=</span> <span class="n">_get_set_b_list_dict</span><span class="p">(</span><span class="n">b_dict</span><span class="p">,</span> <span class="n">set_0b</span><span class="p">,</span> <span class="n">arg_df</span><span class="p">,</span> <span class="n">len_text</span><span class="p">)</span>
        <span class="n">b_dict</span> <span class="o">=</span> <span class="n">_get_set_b_list_dict</span><span class="p">(</span><span class="n">b_dict</span><span class="p">,</span> <span class="n">set_1b</span><span class="p">,</span> <span class="n">arg_df</span><span class="p">,</span> <span class="n">len_text</span><span class="p">)</span>
            
<span class="c1">#     print(df_0b.shape, df_1b.shape, list_0a.shape, list_1a.shape, len(set_0b), len(set_1b))</span>
    
<span class="c1">#     list_a = list_0a</span>
    <span class="n">list_aa</span> <span class="o">=</span> <span class="n">list_0a</span>
    <span class="n">df_b</span> <span class="o">=</span> <span class="n">df_0b</span>
    <span class="n">set_b</span> <span class="o">=</span> <span class="n">set_0b</span>
    <span class="n">x_idx</span> <span class="o">=</span> <span class="mi">0</span>

    <span class="p">(</span><span class="n">data_x_text_list</span><span class="p">,</span> <span class="n">data_x_arga_list</span><span class="p">,</span> <span class="n">data_x_argaa_list</span><span class="p">,</span> <span class="n">data_x_argb_list</span><span class="p">,</span> <span class="n">data_y_list</span><span class="p">)</span> <span class="o">=</span> \
        <span class="n">_get_meta_data</span><span class="p">(</span><span class="n">data_x_text_list</span><span class="p">,</span> <span class="n">data_x_arga_list</span><span class="p">,</span> <span class="n">data_x_argaa_list</span><span class="p">,</span> <span class="n">data_x_argb_list</span><span class="p">,</span> <span class="n">data_y_list</span><span class="p">,</span> 
                       <span class="n">text_encoded</span><span class="p">,</span> <span class="n">b_dict</span><span class="p">,</span> <span class="n">list_a</span><span class="p">,</span> <span class="n">df_b</span><span class="p">,</span> <span class="n">x_idx</span><span class="p">,</span> <span class="n">len_text</span><span class="p">,</span> <span class="n">set_b</span><span class="p">,</span> <span class="n">list_aa</span><span class="p">)</span>
    
<span class="c1">#     list_a = list_1a</span>
    <span class="n">list_aa</span> <span class="o">=</span> <span class="n">list_1a</span>
    <span class="n">df_b</span> <span class="o">=</span> <span class="n">df_1b</span>
    <span class="n">set_b</span> <span class="o">=</span> <span class="n">set_1b</span>
    <span class="n">x_idx</span> <span class="o">=</span> <span class="mi">1</span>

    <span class="p">(</span><span class="n">data_x_text_list</span><span class="p">,</span> <span class="n">data_x_arga_list</span><span class="p">,</span> <span class="n">data_x_argaa_list</span><span class="p">,</span> <span class="n">data_x_argb_list</span><span class="p">,</span> <span class="n">data_y_list</span><span class="p">)</span> <span class="o">=</span> \
        <span class="n">_get_meta_data</span><span class="p">(</span><span class="n">data_x_text_list</span><span class="p">,</span> <span class="n">data_x_arga_list</span><span class="p">,</span> <span class="n">data_x_argaa_list</span><span class="p">,</span> <span class="n">data_x_argb_list</span><span class="p">,</span> <span class="n">data_y_list</span><span class="p">,</span> 
                       <span class="n">text_encoded</span><span class="p">,</span> <span class="n">b_dict</span><span class="p">,</span> <span class="n">list_a</span><span class="p">,</span> <span class="n">df_b</span><span class="p">,</span> <span class="n">x_idx</span><span class="p">,</span> <span class="n">len_text</span><span class="p">,</span> <span class="n">set_b</span><span class="p">,</span> <span class="n">list_aa</span><span class="p">)</span>

    <span class="k">return</span> <span class="p">(</span><span class="n">data_x_text_list</span><span class="p">,</span> <span class="n">data_x_arga_list</span><span class="p">,</span> <span class="n">data_x_argaa_list</span><span class="p">,</span> <span class="n">data_x_argb_list</span><span class="p">,</span> <span class="n">data_y_list</span><span class="p">)</span>
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</div>训练数据
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<div class=" highlight hl-ipython3"><pre><span></span><span class="o">%%time</span>

<span class="n">data_x_text_list</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">data_x_arga_list</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">data_x_argaa_list</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">data_x_argb_list</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">data_y_list</span> <span class="o">=</span> <span class="p">[]</span>


<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">train_text_encoded_dict</span><span class="p">:</span>
    
    <span class="n">t0</span> <span class="o">=</span> <span class="n">train_text_encoded_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    <span class="n">anno_0</span> <span class="o">=</span> <span class="n">train_anno_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    <span class="n">arg_0</span> <span class="o">=</span> <span class="n">train_arg_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    <span class="n">list_a</span> <span class="o">=</span> <span class="n">train_a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    <span class="n">list_0a</span> <span class="o">=</span> <span class="n">train_0a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    <span class="n">list_1a</span> <span class="o">=</span> <span class="n">train_1a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    
    <span class="p">(</span><span class="n">data_x_text_list</span><span class="p">,</span> <span class="n">data_x_arga_list</span><span class="p">,</span> <span class="n">data_x_argaa_list</span><span class="p">,</span> <span class="n">data_x_argb_list</span><span class="p">,</span> <span class="n">data_y_list</span><span class="p">)</span> <span class="o">=</span> \
        <span class="n">get_meta_data</span><span class="p">(</span><span class="n">data_x_text_list</span><span class="p">,</span> <span class="n">data_x_arga_list</span><span class="p">,</span> <span class="n">data_x_argaa_list</span><span class="p">,</span> <span class="n">data_x_argb_list</span><span class="p">,</span> <span class="n">data_y_list</span><span class="p">,</span> 
                      <span class="n">text_encoded</span><span class="o">=</span><span class="n">t0</span><span class="p">,</span> <span class="n">anno_df</span><span class="o">=</span><span class="n">anno_0</span><span class="p">,</span> <span class="n">list_a</span><span class="o">=</span><span class="n">list_a</span><span class="p">,</span> <span class="n">arg_df</span><span class="o">=</span><span class="n">arg_0</span><span class="p">,</span> <span class="n">list_0a</span><span class="o">=</span><span class="n">list_0a</span><span class="p">,</span> <span class="n">list_1a</span><span class="o">=</span><span class="n">list_1a</span><span class="p">)</span>
    
<span class="c1">#     break</span>
<span class="c1">#     print(&#39;k&#39;, k, &#39;-----------------------&#39;)</span>

<span class="nb">print</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">data_x_text_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">data_x_arga_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">data_x_argaa_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">data_x_argb_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">data_y_list</span><span class="p">),</span> <span class="p">)</span>
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<pre>(550278, 320) (550278, 320, 1) (550278, 320, 1) (550278, 320, 1) (550278, 320, 1)
CPU times: user 4min 40s, sys: 2.84 s, total: 4min 43s
Wall time: 4min 42s
</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">data_y_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">data_y_list</span><span class="p">)</span>
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<pre>(3079758, 3079758)</pre>
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<pre>&#39;9_3&#39;</pre>
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</div>
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</div>np.argwhere(np.asarray(data_x_argb_list) == 2)[100:]
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">idx</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">randint</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">data_x_text_list</span><span class="p">))</span>
<span class="n">idx</span>
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<pre>68857</pre>
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</div>idx=70
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data_x_text_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)[:</span><span class="mi">5</span><span class="p">]</span>
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<pre>array([[0],
       [1],
       [2],
       [3],
       [4]])</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">_margin</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data_x_text_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
<span class="n">_margin</span>
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<pre>0</pre>
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</div>len(x_text_list[idx])
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="n">train_encode_dict_idx</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">t</span><span class="p">))</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">data_x_text_list</span><span class="p">[</span><span class="n">idx</span><span class="p">][</span><span class="n">_margin</span><span class="p">:]]))</span>
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<pre>、0. 2 ng / ml(正常参考范围 0. 3 ~ 3. 73,下
同)。 谷氨酸脱羧酶抗体(GADA) ± 。 血清肌钙蛋白 I( TnI)
33. 2 ng / ml(0 ~ 0. 03)。 血肌红蛋白&gt;1 000 ng / ml。 肌肉活检病
理:肌核增多,部分肌纤维模糊或消失,未
明显炎细胞浸润。
EB 病毒抗体、抗胰岛素自身抗体 ( IAA)、抗胰岛细胞抗体

ICA)、抗核抗体谱、肝炎标志物均阴性。 胰腺、泌尿系超声未
见异常(余化验见表 1)。
住院治疗情况:治疗方案基本同急诊科。 入院第 2 天患者
肌酶急骤升高,肾功能不全加重,予碱化尿液,间段性血液滤过
5 次(第 2、3、4
6、9 天,约 4 h /次)等
</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">_margin</span> <span class="o">=</span> <span class="mi">0</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">list</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="o">*</span><span class="p">([</span><span class="n">train_encode_dict_idx</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">t</span><span class="p">))</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">data_x_text_list</span><span class="p">[</span><span class="n">idx</span><span class="p">][(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data_x_arga_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">-</span><span class="n">_margin</span><span class="p">)[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)]],</span>
           <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data_x_arga_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">-</span><span class="n">_margin</span><span class="p">)[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">),</span> 
           <span class="n">data_x_arga_list</span><span class="p">[</span><span class="n">idx</span><span class="p">][(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data_x_arga_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">-</span><span class="n">_margin</span><span class="p">)[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">),</span>
           <span class="n">data_x_argaa_list</span><span class="p">[</span><span class="n">idx</span><span class="p">][(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data_x_arga_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">-</span><span class="n">_margin</span><span class="p">)[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">))))</span>
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<pre>[(&#39;0&#39;, 1, 5, 0),
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 (&#39; &#39;, 3, 5, 0),
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 (&#39;谷&#39;, 40, 4, 1),
 (&#39;氨&#39;, 41, 4, 1),
 (&#39;酸&#39;, 42, 4, 1),
 (&#39;脱&#39;, 43, 4, 1),
 (&#39;羧&#39;, 44, 4, 1),
 (&#39;酶&#39;, 45, 4, 1),
 (&#39;抗&#39;, 46, 4, 1),
 (&#39;体&#39;, 47, 4, 1),
 (&#39;G&#39;, 49, 4, 1),
 (&#39;A&#39;, 50, 4, 1),
 (&#39;D&#39;, 51, 4, 1),
 (&#39;A&#39;, 52, 4, 1),
 (&#39;±&#39;, 55, 5, 0),
 (&#39;血&#39;, 59, 4, 1),
 (&#39;清&#39;, 60, 4, 1),
 (&#39;肌&#39;, 61, 4, 1),
 (&#39;钙&#39;, 62, 4, 1),
 (&#39;蛋&#39;, 63, 4, 1),
 (&#39;白&#39;, 64, 4, 1),
 (&#39; &#39;, 65, 4, 1),
 (&#39;I&#39;, 66, 4, 1),
 (&#39;T&#39;, 69, 4, 1),
 (&#39;n&#39;, 70, 4, 1),
 (&#39;I&#39;, 71, 4, 1),
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 (&#39; &#39;, 82, 5, 0),
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 (&#39; &#39;, 84, 5, 0),
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 (&#39;&gt;&#39;, 105, 5, 0),
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 (&#39;病&#39;, 125, 4, 1),
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 (&#39;肌&#39;, 129, 5, 0),
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 (&#39;或&#39;, 141, 5, 0),
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 (&#39;失&#39;, 143, 5, 0),
 (&#39;未&#39;, 145, 5, 0),
 (&#39;\n&#39;, 146, 5, 0),
 (&#39;明&#39;, 147, 5, 0),
 (&#39;显&#39;, 148, 5, 0),
 (&#39;炎&#39;, 149, 5, 0),
 (&#39;细&#39;, 150, 5, 0),
 (&#39;胞&#39;, 151, 5, 0),
 (&#39;浸&#39;, 152, 5, 0),
 (&#39;润&#39;, 153, 5, 0),
 (&#39;E&#39;, 156, 4, 1),
 (&#39;B&#39;, 157, 4, 1),
 (&#39; &#39;, 158, 4, 1),
 (&#39;病&#39;, 159, 4, 1),
 (&#39;毒&#39;, 160, 4, 1),
 (&#39;抗&#39;, 161, 4, 1),
 (&#39;体&#39;, 162, 4, 1),
 (&#39;抗&#39;, 164, 4, 1),
 (&#39;胰&#39;, 165, 4, 1),
 (&#39;岛&#39;, 166, 4, 1),
 (&#39;素&#39;, 167, 4, 1),
 (&#39;自&#39;, 168, 4, 1),
 (&#39;身&#39;, 169, 4, 1),
 (&#39;抗&#39;, 170, 4, 1),
 (&#39;体&#39;, 171, 4, 1),
 (&#39;I&#39;, 175, 4, 1),
 (&#39;A&#39;, 176, 4, 1),
 (&#39;A&#39;, 177, 4, 1),
 (&#39;抗&#39;, 180, 4, 1),
 (&#39;胰&#39;, 181, 4, 1),
 (&#39;岛&#39;, 182, 4, 1),
 (&#39;细&#39;, 183, 4, 1),
 (&#39;胞&#39;, 184, 4, 1),
 (&#39;抗&#39;, 185, 4, 1),
 (&#39;体&#39;, 186, 4, 1),
 (&#39;I&#39;, 189, 4, 1),
 (&#39;C&#39;, 190, 4, 1),
 (&#39;A&#39;, 191, 4, 1),
 (&#39;抗&#39;, 194, 4, 1),
 (&#39;核&#39;, 195, 4, 1),
 (&#39;抗&#39;, 196, 4, 1),
 (&#39;体&#39;, 197, 4, 1),
 (&#39;谱&#39;, 198, 4, 1),
 (&#39;肝&#39;, 200, 4, 1),
 (&#39;炎&#39;, 201, 4, 1),
 (&#39;标&#39;, 202, 4, 1),
 (&#39;志&#39;, 203, 4, 1),
 (&#39;物&#39;, 204, 4, 1),
 (&#39;胰&#39;, 210, 4, 1),
 (&#39;腺&#39;, 211, 4, 1),
 (&#39;、&#39;, 212, 4, 1),
 (&#39;泌&#39;, 213, 4, 1),
 (&#39;尿&#39;, 214, 4, 1),
 (&#39;系&#39;, 215, 4, 1),
 (&#39;超&#39;, 216, 4, 1),
 (&#39;声&#39;, 217, 4, 1),
 (&#39;肌&#39;, 263, 4, 1),
 (&#39;酶&#39;, 264, 4, 1),
 (&#39;急&#39;, 265, 5, 0),
 (&#39;骤&#39;, 266, 5, 0),
 (&#39;升&#39;, 267, 5, 0),
 (&#39;高&#39;, 268, 5, 0),
 (&#39;肾&#39;, 270, 1, 0),
 (&#39;功&#39;, 271, 1, 0),
 (&#39;能&#39;, 272, 1, 0),
 (&#39;不&#39;, 273, 1, 0),
 (&#39;全&#39;, 274, 1, 0),
 (&#39;碱&#39;, 279, 10, 1),
 (&#39;化&#39;, 280, 10, 1),
 (&#39;尿&#39;, 281, 10, 1),
 (&#39;液&#39;, 282, 10, 1),
 (&#39;间&#39;, 284, 10, 1),
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 (&#39;液&#39;, 288, 10, 1),
 (&#39;滤&#39;, 289, 10, 1),
 (&#39;过&#39;, 290, 10, 1),
 (&#39;5&#39;, 292, 7, 0),
 (&#39; &#39;, 293, 7, 0),
 (&#39;次&#39;, 294, 7, 0),
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 (&#39; &#39;, 313, 7, 0),
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 (&#39;次&#39;, 317, 7, 0)]</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">list</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="o">*</span><span class="p">([</span><span class="n">train_encode_dict_idx</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">t</span><span class="p">))</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">data_x_text_list</span><span class="p">[</span><span class="n">idx</span><span class="p">][(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data_x_argb_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">-</span><span class="n">_margin</span><span class="p">)[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)]],</span>
           <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data_x_argb_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">-</span><span class="n">_margin</span><span class="p">)[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">),</span> 
           <span class="n">data_x_argb_list</span><span class="p">[</span><span class="n">idx</span><span class="p">][(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data_x_argb_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">-</span><span class="n">_margin</span><span class="p">)[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">))))</span>
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<pre>[(&#39;肾&#39;, 270, 1), (&#39;功&#39;, 271, 1), (&#39;能&#39;, 272, 1), (&#39;不&#39;, 273, 1), (&#39;全&#39;, 274, 1)]</pre>
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</div>(np.argwhere(x_argb_list[idx]>0)-_margin)
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">list</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="o">*</span><span class="p">([</span><span class="n">train_encode_dict_idx</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">t</span><span class="p">))</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">data_x_text_list</span><span class="p">[</span><span class="n">idx</span><span class="p">][(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data_y_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">-</span><span class="n">_margin</span><span class="p">)[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)]],</span>
           <span class="n">data_x_arga_list</span><span class="p">[</span><span class="n">idx</span><span class="p">][(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data_y_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">-</span><span class="n">_margin</span><span class="p">)[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)],</span>
           <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data_y_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">-</span><span class="n">_margin</span><span class="p">)[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">),</span> 
           <span class="n">data_y_list</span><span class="p">[</span><span class="n">idx</span><span class="p">][(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data_y_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">-</span><span class="n">_margin</span><span class="p">)[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">),</span>
           <span class="n">data_x_argaa_list</span><span class="p">[</span><span class="n">idx</span><span class="p">][(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data_y_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">-</span><span class="n">_margin</span><span class="p">)[:,</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)])))</span>
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<pre>[(&#39;肌&#39;, array([4], dtype=uint8), 263, 1, array([1], dtype=uint8)),
 (&#39;酶&#39;, array([4], dtype=uint8), 264, 1, array([1], dtype=uint8)),
 (&#39;碱&#39;, array([10], dtype=uint8), 279, 1, array([1], dtype=uint8)),
 (&#39;化&#39;, array([10], dtype=uint8), 280, 1, array([1], dtype=uint8)),
 (&#39;尿&#39;, array([10], dtype=uint8), 281, 1, array([1], dtype=uint8)),
 (&#39;液&#39;, array([10], dtype=uint8), 282, 1, array([1], dtype=uint8)),
 (&#39;间&#39;, array([10], dtype=uint8), 284, 1, array([1], dtype=uint8)),
 (&#39;段&#39;, array([10], dtype=uint8), 285, 1, array([1], dtype=uint8)),
 (&#39;性&#39;, array([10], dtype=uint8), 286, 1, array([1], dtype=uint8)),
 (&#39;血&#39;, array([10], dtype=uint8), 287, 1, array([1], dtype=uint8)),
 (&#39;液&#39;, array([10], dtype=uint8), 288, 1, array([1], dtype=uint8)),
 (&#39;滤&#39;, array([10], dtype=uint8), 289, 1, array([1], dtype=uint8)),
 (&#39;过&#39;, array([10], dtype=uint8), 290, 1, array([1], dtype=uint8))]</pre>
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<pre>{&#39;Normal&#39;: 0,
 &#39;Disease&#39;: 1,
 &#39;Reason&#39;: 2,
 &#39;Symptom&#39;: 3,
 &#39;Test&#39;: 4,
 &#39;Test_Value&#39;: 5,
 &#39;Drug&#39;: 6,
 &#39;Frequency&#39;: 7,
 &#39;Amount&#39;: 8,
 &#39;Method&#39;: 9,
 &#39;Treatment&#39;: 10,
 &#39;Operation&#39;: 11,
 &#39;Anatomy&#39;: 12,
 &#39;Level&#39;: 13,
 &#39;Duration&#39;: 14,
 &#39;SideEff&#39;: 15}</pre>
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</div>使用gensim的FastText，先对train text进行预训练，已得到词向量。
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<span class="n">W2V_LEN_ARGA</span> <span class="o">=</span> <span class="mi">32</span>
<span class="n">W2V_LEN_ARGB</span> <span class="o">=</span> <span class="mi">8</span>

<span class="n">TOTAL_ARGA</span> <span class="o">=</span> <span class="n">LEN_LABELS</span> <span class="o">+</span> <span class="mi">1</span>
<span class="n">TOTAL_ARGB</span> <span class="o">=</span> <span class="mi">3</span>

<span class="n">FLAG_DROP</span> <span class="o">=</span> <span class="kc">True</span>

<span class="n">TOTAL_ARGA</span><span class="p">,</span> <span class="n">TOTAL_ARGB</span>
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<pre>(17, 3)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model_ft</span> <span class="o">=</span> <span class="n">gensim</span><span class="o">.</span><span class="n">models</span><span class="o">.</span><span class="n">FastText</span><span class="p">([</span><span class="n">jieba</span><span class="o">.</span><span class="n">lcut</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">v</span><span class="p">))</span> <span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">train_text_dict</span><span class="o">.</span><span class="n">values</span><span class="p">()],</span> <span class="n">size</span><span class="o">=</span><span class="n">W2V_LEN_TEXT</span><span class="p">,</span> <span class="n">word_ngrams</span><span class="o">=</span><span class="mi">9</span><span class="p">,</span> <span class="n">window</span><span class="o">=</span><span class="mi">24</span><span class="p">,</span> <span class="n">min_count</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">workers</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="mi">522</span><span class="p">)</span>
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<pre>Building prefix dict from the default dictionary ...
Loading model from cache /tmp/jieba.cache
Loading model cost 1.261 seconds.
Prefix dict has been built succesfully.
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<pre>/home/admin/.local/lib/python3.6/site-packages/gensim/matutils.py:737: FutureWarning: Conversion of the second argument of issubdtype from `int` to `np.signedinteger` is deprecated. In future, it will be treated as `np.int64 == np.dtype(int).type`.
  if np.issubdtype(vec.dtype, np.int):
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<pre>[(&#39;高血糖&#39;, 0.7226872444152832),
 (&#39;负荷量&#39;, 0.6889748573303223),
 (&#39;物而血&#39;, 0.6794244050979614),
 (&#39;超负荷&#39;, 0.6688441634178162),
 (&#39;负荷&#39;, 0.6630635261535645),
 (&#39;状态&#39;, 0.6603191494941711),
 (&#39;受损&#39;, 0.6461359858512878),
 (&#39;降血糖&#39;, 0.6429497003555298),
 (&#39;尿病&#39;, 0.6414780020713806),
 (&#39;中间状态&#39;, 0.6407528519630432)]</pre>
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<span class="n">count_emb_0</span> <span class="o">=</span> <span class="mi">0</span>

<span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">train_encode_dict</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    
    <span class="n">_k</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
    <span class="k">if</span> <span class="n">_k</span> <span class="ow">in</span> <span class="n">model_ft</span><span class="o">.</span><span class="n">wv</span><span class="p">:</span>
        <span class="n">emb_weights</span><span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="o">=</span> <span class="n">model_ft</span><span class="o">.</span><span class="n">wv</span><span class="p">[</span><span class="n">_k</span><span class="p">]</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">count_emb_0</span> <span class="o">+=</span> <span class="mi">0</span>
    
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<pre>array([-0.9834579 ,  0.05197863,  7.518318  ,  3.5358949 , -3.1459315 ,
        4.338649  , -2.7696872 , -3.2993584 , -7.2040715 , 13.103886  ,
       -5.8388543 , -3.5557675 , -3.5331068 , -4.491297  ,  2.7360206 ,
       -2.477428  , -5.33715   ,  1.3084834 ,  6.3279724 , -6.4140277 ,
       -4.8403606 ,  9.534268  ,  1.1119591 , -4.9246264 , -0.25238538,
       -4.333956  , -4.126724  ,  4.788044  ,  0.04831977,  6.0481157 ,
       -3.4960608 ,  1.2231584 ,  0.32451007, -3.3348854 , -0.26541775,
        2.928936  ,  1.258896  , -7.087802  ,  4.975445  ,  5.734035  ,
       -3.2088532 , -1.6371982 ,  4.6978326 ,  1.8530223 , -6.658251  ,
       -3.131555  ,  3.9441943 ,  3.8292234 ,  6.9782686 ,  5.438328  ,
       -1.8807151 , -2.0759587 , -8.704267  ,  2.94937   ,  1.841884  ,
        7.9934874 ,  2.0881963 ,  3.9320498 , -6.154572  ,  6.710253  ,
        6.3011317 ,  5.688347  , -5.53253   ,  5.286709  ], dtype=float32)</pre>
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</div>(['中', '国', '成', '人', '2', '型', '糖', '尿', '病', 'H'],
 [184, 705, 1157, 240, 18, 732, 2239, 936, 1993, 40],
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<pre>True</pre>
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<span class="n">data_x_arga_list</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">data_x_arga_list</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">data_x_argaa_list</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">data_x_argaa_list</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
<span class="n">data_x_argb_list</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">data_x_argb_list</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">data_y_list</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">data_y_list</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
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</div>数据1/10用来作为验证集，9/10用来作为训练集。
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<span class="n">train_idx</span><span class="p">,</span> <span class="n">valid_idx</span> <span class="o">=</span> <span class="nb">next</span><span class="p">(</span><span class="n">kf</span><span class="p">)</span>
<span class="n">train_idx</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">valid_idx</span><span class="o">.</span><span class="n">shape</span>
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<span class="n">train_x_arga_list</span> <span class="o">=</span> <span class="n">data_x_arga_list</span><span class="p">[</span><span class="n">train_idx</span><span class="p">]</span>
<span class="n">train_x_argaa_list</span> <span class="o">=</span> <span class="n">data_x_argaa_list</span><span class="p">[</span><span class="n">train_idx</span><span class="p">]</span>
<span class="n">train_x_argb_list</span> <span class="o">=</span> <span class="n">data_x_argb_list</span><span class="p">[</span><span class="n">train_idx</span><span class="p">]</span>
<span class="n">train_y_list</span> <span class="o">=</span> <span class="n">data_y_list</span><span class="p">[</span><span class="n">train_idx</span><span class="p">]</span>

<span class="n">valid_x_text_list</span> <span class="o">=</span> <span class="n">data_x_text_list</span><span class="p">[</span><span class="n">valid_idx</span><span class="p">]</span>
<span class="n">valid_x_arga_list</span> <span class="o">=</span> <span class="n">data_x_arga_list</span><span class="p">[</span><span class="n">valid_idx</span><span class="p">]</span>
<span class="n">valid_x_argaa_list</span> <span class="o">=</span> <span class="n">data_x_argaa_list</span><span class="p">[</span><span class="n">valid_idx</span><span class="p">]</span>
<span class="n">valid_x_argb_list</span> <span class="o">=</span> <span class="n">data_x_argb_list</span><span class="p">[</span><span class="n">valid_idx</span><span class="p">]</span>
<span class="n">valid_y_list</span> <span class="o">=</span> <span class="n">data_y_list</span><span class="p">[</span><span class="n">valid_idx</span><span class="p">]</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">train_x_text_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">train_x_arga_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">train_x_argaa_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">train_x_argb_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">train_y_list</span><span class="p">),</span> 
      <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">valid_x_text_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">valid_x_arga_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">valid_x_argaa_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">valid_x_argb_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">valid_y_list</span><span class="p">),</span> <span class="p">)</span>
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<pre>(495250, 320) (495250, 320) (495250, 320, 1) (495250, 320) (495250, 320, 1) (55028, 320) (55028, 320) (55028, 320, 1) (55028, 320) (55028, 320, 1)
</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">train_y_list</span><span class="p">)</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">valid_y_list</span><span class="p">)</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span>
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<pre>(2776641, 303117)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="p">(</span><span class="n">train_x_text_list</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> 
<span class="n">train_x_arga_list</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> 
<span class="n">train_x_argaa_list</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> 
<span class="n">train_x_argb_list</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> 
<span class="n">train_y_list</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> 
<span class="n">valid_x_text_list</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> 
<span class="n">valid_x_arga_list</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> 
<span class="n">valid_x_argaa_list</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> 
<span class="n">valid_x_argb_list</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> 
<span class="n">valid_y_list</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
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<pre>((495250, 320),
 (495250, 320),
 (495250, 320, 1),
 (495250, 320),
 (495250, 320, 1),
 (55028, 320),
 (55028, 320),
 (55028, 320, 1),
 (55028, 320),
 (55028, 320, 1))</pre>
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<pre>(3265, 3265, 3267, 16)</pre>
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<pre>(15, 2, 1)</pre>
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</div>模型：大体分为三层
（1）text、arg_a、arg_b分别送入Embedding和Bi-LSTM
（2）将（1）合并后分两路分别送入Bi-LSTM和Bi-GRU
（3）将（2）合并后送入Bi-LSTM并生成此arg_b所对应arg_a的位置0/1真值序列
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">keras.models</span> <span class="k">import</span> <span class="n">Sequential</span>
<span class="kn">from</span> <span class="nn">keras.layers</span> <span class="k">import</span> <span class="n">Dense</span><span class="p">,</span> <span class="n">Dropout</span><span class="p">,</span> <span class="n">Concatenate</span><span class="p">,</span> <span class="n">Add</span><span class="p">,</span> <span class="n">SpatialDropout1D</span>
<span class="kn">from</span> <span class="nn">keras.layers</span> <span class="k">import</span> <span class="n">Embedding</span>
<span class="kn">from</span> <span class="nn">keras.layers</span> <span class="k">import</span> <span class="n">LSTM</span><span class="p">,</span> <span class="n">TimeDistributed</span><span class="p">,</span> <span class="n">Bidirectional</span><span class="p">,</span> <span class="n">CuDNNLSTM</span><span class="p">,</span> <span class="n">CuDNNGRU</span>

<span class="kn">import</span> <span class="nn">keras.backend</span> <span class="k">as</span> <span class="nn">K</span> 

<span class="k">def</span> <span class="nf">get_model</span><span class="p">():</span>

    <span class="n">inputs_text</span> <span class="o">=</span> <span class="n">Input</span><span class="p">((</span><span class="n">TRAIN_LENGTH</span><span class="p">,</span> <span class="p">))</span>
    <span class="n">emb_text</span> <span class="o">=</span> <span class="n">Embedding</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="n">TOTAL_SIZE</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span><span class="n">output_dim</span><span class="o">=</span><span class="n">W2V_LEN_TEXT</span><span class="p">,</span> <span class="n">weights</span><span class="o">=</span><span class="p">[</span><span class="n">emb_weights</span><span class="p">],</span> <span class="n">trainable</span><span class="o">=</span><span class="kc">False</span><span class="p">)(</span><span class="n">inputs_text</span><span class="p">)</span>
    <span class="n">emb_text</span> <span class="o">=</span> <span class="n">SpatialDropout1D</span><span class="p">(</span><span class="mf">0.3</span><span class="p">)(</span><span class="n">emb_text</span><span class="p">)</span>
    <span class="n">x_text</span> <span class="o">=</span> <span class="n">Bidirectional</span><span class="p">(</span><span class="n">CuDNNLSTM</span><span class="p">(</span><span class="mi">128</span><span class="p">,</span> <span class="n">return_sequences</span><span class="o">=</span><span class="kc">True</span><span class="p">))(</span><span class="n">emb_text</span><span class="p">)</span>
    <span class="n">x_text</span> <span class="o">=</span> <span class="n">Dropout</span><span class="p">(</span><span class="mf">0.5</span><span class="p">)(</span><span class="n">x_text</span><span class="p">)</span>

    <span class="n">inputs_arg_a</span> <span class="o">=</span> <span class="n">Input</span><span class="p">((</span><span class="n">TRAIN_LENGTH</span><span class="p">,</span> <span class="p">))</span>
    <span class="n">emb_arga</span> <span class="o">=</span> <span class="n">Embedding</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="n">TOTAL_ARGA</span><span class="p">,</span><span class="n">output_dim</span><span class="o">=</span><span class="n">W2V_LEN_ARGA</span><span class="p">)(</span><span class="n">inputs_arg_a</span><span class="p">)</span>
    <span class="n">emb_arga</span> <span class="o">=</span> <span class="n">SpatialDropout1D</span><span class="p">(</span><span class="mf">0.3</span><span class="p">)(</span><span class="n">emb_arga</span><span class="p">)</span>
    <span class="n">x_arg_a</span> <span class="o">=</span> <span class="n">Bidirectional</span><span class="p">(</span><span class="n">CuDNNLSTM</span><span class="p">(</span><span class="mi">128</span><span class="p">,</span> <span class="n">return_sequences</span><span class="o">=</span><span class="kc">True</span><span class="p">))(</span><span class="n">emb_arga</span><span class="p">)</span>
    <span class="n">x_arg_a</span> <span class="o">=</span> <span class="n">Dropout</span><span class="p">(</span><span class="mf">0.5</span><span class="p">)(</span><span class="n">x_arg_a</span><span class="p">)</span>

    <span class="n">inputs_arg_b</span> <span class="o">=</span> <span class="n">Input</span><span class="p">((</span><span class="n">TRAIN_LENGTH</span><span class="p">,</span> <span class="p">))</span>
    <span class="n">emb_argb</span> <span class="o">=</span> <span class="n">Embedding</span><span class="p">(</span><span class="n">input_dim</span><span class="o">=</span><span class="n">TOTAL_ARGB</span><span class="p">,</span><span class="n">output_dim</span><span class="o">=</span><span class="n">W2V_LEN_ARGB</span><span class="p">)(</span><span class="n">inputs_arg_b</span><span class="p">)</span>
    <span class="n">x_arg_b</span> <span class="o">=</span> <span class="n">Bidirectional</span><span class="p">(</span><span class="n">CuDNNLSTM</span><span class="p">(</span><span class="mi">128</span><span class="p">,</span> <span class="n">return_sequences</span><span class="o">=</span><span class="kc">True</span><span class="p">))(</span><span class="n">emb_argb</span><span class="p">)</span>

    <span class="n">inputs_all</span> <span class="o">=</span> <span class="n">Concatenate</span><span class="p">()([</span><span class="n">x_text</span><span class="p">,</span> <span class="n">x_arg_a</span><span class="p">,</span> <span class="n">x_arg_b</span><span class="p">])</span>

    <span class="n">x0</span> <span class="o">=</span> <span class="n">Bidirectional</span><span class="p">(</span><span class="n">CuDNNLSTM</span><span class="p">(</span><span class="mi">128</span><span class="p">,</span> <span class="n">return_sequences</span><span class="o">=</span><span class="kc">True</span><span class="p">))(</span><span class="n">inputs_all</span><span class="p">)</span>
    <span class="n">x1</span> <span class="o">=</span> <span class="n">Bidirectional</span><span class="p">(</span><span class="n">CuDNNGRU</span><span class="p">(</span><span class="mi">128</span><span class="p">,</span> <span class="n">return_sequences</span><span class="o">=</span><span class="kc">True</span><span class="p">))(</span><span class="n">inputs_all</span><span class="p">)</span>

    <span class="n">x</span> <span class="o">=</span> <span class="n">Concatenate</span><span class="p">()([</span><span class="n">x0</span><span class="p">,</span> <span class="n">x1</span><span class="p">])</span>

    <span class="n">x</span> <span class="o">=</span> <span class="n">Bidirectional</span><span class="p">(</span><span class="n">CuDNNLSTM</span><span class="p">(</span><span class="mi">128</span><span class="p">,</span> <span class="n">return_sequences</span><span class="o">=</span><span class="kc">True</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">Dropout</span><span class="p">(</span><span class="mf">0.5</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">TimeDistributed</span><span class="p">(</span><span class="n">Dense</span><span class="p">(</span><span class="mi">64</span><span class="p">,</span> <span class="n">activation</span><span class="o">=</span><span class="s1">&#39;relu&#39;</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">Dropout</span><span class="p">(</span><span class="mf">0.5</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">TimeDistributed</span><span class="p">(</span><span class="n">Dense</span><span class="p">(</span><span class="mi">1</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">Activation</span><span class="p">(</span><span class="s1">&#39;sigmoid&#39;</span><span class="p">)(</span><span class="n">x</span><span class="p">)</span>

    <span class="n">model</span> <span class="o">=</span> <span class="n">Model</span><span class="p">(</span><span class="n">inputs</span><span class="o">=</span><span class="p">[</span><span class="n">inputs_text</span><span class="p">,</span> <span class="n">inputs_arg_a</span><span class="p">,</span> <span class="n">inputs_arg_b</span><span class="p">],</span> <span class="n">outputs</span><span class="o">=</span><span class="n">x</span><span class="p">)</span>
    <span class="n">model</span><span class="o">.</span><span class="n">compile</span><span class="p">(</span><span class="n">loss</span><span class="o">=</span><span class="n">losses</span><span class="o">.</span><span class="n">binary_crossentropy</span><span class="p">,</span>
                  <span class="n">optimizer</span><span class="o">=</span><span class="n">optimizers</span><span class="o">.</span><span class="n">RMSprop</span><span class="p">(),</span>
                  <span class="n">metrics</span><span class="o">=</span><span class="p">[</span><span class="n">metrics</span><span class="o">.</span><span class="n">binary_accuracy</span><span class="p">,</span> <span class="n">metrics</span><span class="o">.</span><span class="n">binary_crossentropy</span><span class="p">])</span>

    <span class="k">return</span> <span class="n">model</span>
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</div>25个epoch
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</div>先使用正向数据训练一个模型
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">MODEL_BASE</span> <span class="o">=</span> <span class="s1">&#39;s2_01&#39;</span>
<span class="n">MODEL_NAME</span> <span class="o">=</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;_final_v4_0&#39;</span>
<span class="n">MODEL_BASE</span><span class="p">,</span> <span class="n">MODEL_NAME</span>
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<pre>(&#39;s2_01&#39;, &#39;s2_01_final_v4_0&#39;)</pre>
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    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span> <span class="o">=</span> <span class="n">get_model</span><span class="p">()</span>
<span class="n">model</span><span class="o">.</span><span class="n">summary</span><span class="p">()</span>
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<pre>__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_1 (InputLayer)            (None, 320)          0                                            
__________________________________________________________________________________________________
input_2 (InputLayer)            (None, 320)          0                                            
__________________________________________________________________________________________________
embedding_1 (Embedding)         (None, 320, 64)      209152      input_1[0][0]                    
__________________________________________________________________________________________________
embedding_2 (Embedding)         (None, 320, 32)      544         input_2[0][0]                    
__________________________________________________________________________________________________
spatial_dropout1d_1 (SpatialDro (None, 320, 64)      0           embedding_1[0][0]                
__________________________________________________________________________________________________
spatial_dropout1d_2 (SpatialDro (None, 320, 32)      0           embedding_2[0][0]                
__________________________________________________________________________________________________
input_3 (InputLayer)            (None, 320)          0                                            
__________________________________________________________________________________________________
bidirectional_1 (Bidirectional) (None, 320, 256)     198656      spatial_dropout1d_1[0][0]        
__________________________________________________________________________________________________
bidirectional_2 (Bidirectional) (None, 320, 256)     165888      spatial_dropout1d_2[0][0]        
__________________________________________________________________________________________________
embedding_3 (Embedding)         (None, 320, 8)       24          input_3[0][0]                    
__________________________________________________________________________________________________
dropout_1 (Dropout)             (None, 320, 256)     0           bidirectional_1[0][0]            
__________________________________________________________________________________________________
dropout_2 (Dropout)             (None, 320, 256)     0           bidirectional_2[0][0]            
__________________________________________________________________________________________________
bidirectional_3 (Bidirectional) (None, 320, 256)     141312      embedding_3[0][0]                
__________________________________________________________________________________________________
concatenate_1 (Concatenate)     (None, 320, 768)     0           dropout_1[0][0]                  
                                                                 dropout_2[0][0]                  
                                                                 bidirectional_3[0][0]            
__________________________________________________________________________________________________
bidirectional_4 (Bidirectional) (None, 320, 256)     919552      concatenate_1[0][0]              
__________________________________________________________________________________________________
bidirectional_5 (Bidirectional) (None, 320, 256)     689664      concatenate_1[0][0]              
__________________________________________________________________________________________________
concatenate_2 (Concatenate)     (None, 320, 512)     0           bidirectional_4[0][0]            
                                                                 bidirectional_5[0][0]            
__________________________________________________________________________________________________
bidirectional_6 (Bidirectional) (None, 320, 256)     657408      concatenate_2[0][0]              
__________________________________________________________________________________________________
dropout_3 (Dropout)             (None, 320, 256)     0           bidirectional_6[0][0]            
__________________________________________________________________________________________________
time_distributed_1 (TimeDistrib (None, 320, 64)      16448       dropout_3[0][0]                  
__________________________________________________________________________________________________
dropout_4 (Dropout)             (None, 320, 64)      0           time_distributed_1[0][0]         
__________________________________________________________________________________________________
time_distributed_2 (TimeDistrib (None, 320, 1)       65          dropout_4[0][0]                  
__________________________________________________________________________________________________
activation_1 (Activation)       (None, 320, 1)       0           time_distributed_2[0][0]         
==================================================================================================
Total params: 2,998,713
Trainable params: 2,789,561
Non-trainable params: 209,152
__________________________________________________________________________________________________
</pre>
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<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">keras.callbacks</span> <span class="k">import</span> <span class="n">EarlyStopping</span><span class="p">,</span> <span class="n">ModelCheckpoint</span><span class="p">,</span> <span class="n">ReduceLROnPlateau</span>

<span class="n">checkpoint</span> <span class="o">=</span> <span class="n">ModelCheckpoint</span><span class="p">(</span><span class="s1">&#39;./Demo/Models/&#39;</span> <span class="o">+</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;/&#39;</span> <span class="o">+</span> <span class="n">MODEL_NAME</span> <span class="o">+</span> <span class="s1">&#39;_</span><span class="si">{epoch:02d}</span><span class="s1">.hd5&#39;</span><span class="p">,</span> <span class="n">monitor</span><span class="o">=</span><span class="s1">&#39;val_loss&#39;</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> 
                             <span class="n">save_best_only</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">save_weights_only</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;auto&#39;</span><span class="p">,</span> <span class="n">period</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">lr_reduce</span> <span class="o">=</span> <span class="n">ReduceLROnPlateau</span><span class="p">(</span><span class="n">monitor</span><span class="o">=</span><span class="s1">&#39;val_loss&#39;</span><span class="p">,</span> <span class="n">factor</span><span class="o">=</span><span class="mf">0.6</span><span class="p">,</span> <span class="n">min_delta</span><span class="o">=</span><span class="mf">1e-5</span><span class="p">,</span> <span class="n">patience</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">min_lr</span> <span class="o">=</span> <span class="mf">0.00001</span><span class="p">)</span>
</pre></div>

    </div>
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</div>
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<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="o">%%time</span>

<span class="n">hist_0</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="n">train_x_text_list</span><span class="p">,</span> <span class="n">train_x_arga_list</span><span class="p">,</span> <span class="n">train_x_argb_list</span><span class="p">],</span> <span class="n">y</span><span class="o">=</span><span class="n">train_y_list</span><span class="p">,</span>
          <span class="n">batch_size</span><span class="o">=</span><span class="mi">512</span><span class="p">,</span>
          <span class="n">epochs</span><span class="o">=</span><span class="n">EPOCHS</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="n">validation_data</span><span class="o">=</span><span class="p">([</span><span class="n">valid_x_text_list</span><span class="p">,</span> <span class="n">valid_x_arga_list</span><span class="p">,</span> <span class="n">valid_x_argb_list</span><span class="p">],</span> <span class="n">valid_y_list</span><span class="p">),</span>
          <span class="n">callbacks</span><span class="o">=</span><span class="p">[</span><span class="n">checkpoint</span><span class="p">,</span> <span class="n">lr_reduce</span><span class="p">],</span>
          <span class="n">verbose</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>

<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;./Demo/Models/&#39;</span> <span class="o">+</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;/&#39;</span> <span class="o">+</span> <span class="n">MODEL_NAME</span> <span class="o">+</span> <span class="s1">&#39;_hist.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">pickle</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">hist_0</span><span class="o">.</span><span class="n">history</span><span class="p">,</span> <span class="n">f</span><span class="p">)</span>
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<pre>Train on 495250 samples, validate on 55028 samples
Epoch 1/25
 - 868s - loss: 0.0341 - binary_accuracy: 0.9877 - binary_crossentropy: 0.0341 - val_loss: 0.0169 - val_binary_accuracy: 0.9928 - val_binary_crossentropy: 0.0169

Epoch 00001: saving model to ../Demo/Models/s2_01/s2_01_final_v4_0_01.hd5
Epoch 2/25
 - 857s - loss: 0.0167 - binary_accuracy: 0.9931 - binary_crossentropy: 0.0167 - val_loss: 0.0152 - val_binary_accuracy: 0.9935 - val_binary_crossentropy: 0.0152

Epoch 00002: saving model to ../Demo/Models/s2_01/s2_01_final_v4_0_02.hd5
Epoch 3/25
</pre>
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    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span> 
</pre></div>

    </div>
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</div>
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<div class="input">
<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span> 
</pre></div>

    </div>
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</div>

</div>再使用反向数据训练一个模型
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    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">MODEL_BASE</span> <span class="o">=</span> <span class="s1">&#39;s2_01&#39;</span>
<span class="n">MODEL_NAME</span> <span class="o">=</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;_final_v4_1&#39;</span>
<span class="n">MODEL_BASE</span><span class="p">,</span> <span class="n">MODEL_NAME</span>
</pre></div>

    </div>
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</div>
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<div class="input">
<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span> <span class="o">=</span> <span class="n">get_model</span><span class="p">()</span>
<span class="n">model</span><span class="o">.</span><span class="n">summary</span><span class="p">()</span>
</pre></div>

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

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">keras.callbacks</span> <span class="k">import</span> <span class="n">EarlyStopping</span><span class="p">,</span> <span class="n">ModelCheckpoint</span><span class="p">,</span> <span class="n">ReduceLROnPlateau</span>

<span class="n">checkpoint</span> <span class="o">=</span> <span class="n">ModelCheckpoint</span><span class="p">(</span><span class="s1">&#39;./Demo/Models/&#39;</span> <span class="o">+</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;/&#39;</span> <span class="o">+</span> <span class="n">MODEL_NAME</span> <span class="o">+</span> <span class="s1">&#39;_</span><span class="si">{epoch:02d}</span><span class="s1">.hd5&#39;</span><span class="p">,</span> <span class="n">monitor</span><span class="o">=</span><span class="s1">&#39;val_loss&#39;</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> 
                             <span class="n">save_best_only</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">save_weights_only</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;auto&#39;</span><span class="p">,</span> <span class="n">period</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">lr_reduce</span> <span class="o">=</span> <span class="n">ReduceLROnPlateau</span><span class="p">(</span><span class="n">monitor</span><span class="o">=</span><span class="s1">&#39;val_loss&#39;</span><span class="p">,</span> <span class="n">factor</span><span class="o">=</span><span class="mf">0.6</span><span class="p">,</span> <span class="n">min_delta</span><span class="o">=</span><span class="mf">1e-5</span><span class="p">,</span> <span class="n">patience</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">min_lr</span> <span class="o">=</span> <span class="mf">0.00001</span><span class="p">)</span>
</pre></div>

    </div>
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</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="o">%%time</span>

<span class="n">hist_1</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="n">train_x_text_list</span><span class="p">[:,</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">train_x_arga_list</span><span class="p">[:,</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">train_x_argb_list</span><span class="p">[:,</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">]],</span> <span class="n">y</span><span class="o">=</span><span class="n">train_y_list</span><span class="p">[:,</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="p">:],</span>
          <span class="n">batch_size</span><span class="o">=</span><span class="mi">512</span><span class="p">,</span>
          <span class="n">epochs</span><span class="o">=</span><span class="n">EPOCHS</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="n">validation_data</span><span class="o">=</span><span class="p">([</span><span class="n">valid_x_text_list</span><span class="p">[:,</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">valid_x_arga_list</span><span class="p">[:,</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">valid_x_argb_list</span><span class="p">[:,</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">]],</span> <span class="n">valid_y_list</span><span class="p">[:,</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="p">:]),</span>
          <span class="n">callbacks</span><span class="o">=</span><span class="p">[</span><span class="n">checkpoint</span><span class="p">,</span> <span class="n">lr_reduce</span><span class="p">],</span>
          <span class="n">verbose</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>

<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;./Demo/Models/&#39;</span> <span class="o">+</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;/&#39;</span> <span class="o">+</span> <span class="n">MODEL_NAME</span> <span class="o">+</span> <span class="s1">&#39;_hist.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">pickle</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">hist_1</span><span class="o">.</span><span class="n">history</span><span class="p">,</span> <span class="n">f</span><span class="p">)</span>
</pre></div>

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<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span> 
</pre></div>

    </div>
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</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span> 
</pre></div>

    </div>
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</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[&nbsp;]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span> 
</pre></div>

    </div>
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</div>

</div>验证模型训练有无问题
<div class="cell border-box-sizing code_cell rendered">
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">MODEL_BASE</span> <span class="o">=</span> <span class="s1">&#39;s2_01&#39;</span>
<span class="n">MODEL_NAME</span> <span class="o">=</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;_final_v4_1&#39;</span>
<span class="n">MODEL_BASE</span><span class="p">,</span> <span class="n">MODEL_NAME</span>

<span class="n">w_p</span> <span class="o">=</span> <span class="s1">&#39;./Demo/Models/&#39;</span> <span class="o">+</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;/&#39;</span> <span class="o">+</span> <span class="n">MODEL_NAME</span> <span class="o">+</span> <span class="s1">&#39;_</span><span class="si">%02d</span><span class="s1">.hd5&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="mi">20</span><span class="p">)</span>
<span class="n">model</span><span class="o">.</span><span class="n">load_weights</span><span class="p">(</span><span class="n">w_p</span><span class="p">)</span>
</pre></div>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">valid_x_text_list</span><span class="o">.</span><span class="n">shape</span>
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<pre>(55028, 320)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">idx</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">randint</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">valid_x_text_list</span><span class="p">))</span>
<span class="n">idx</span>
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<pre>13545</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># pre = model.predict([valid_x_text_list[[idx]], valid_x_arga_list[[idx]], valid_x_argb_list[[idx]]]).reshape(-1)</span>
<span class="n">pre</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">([</span><span class="n">valid_x_text_list</span><span class="p">[[</span><span class="n">idx</span><span class="p">],</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">valid_x_arga_list</span><span class="p">[[</span><span class="n">idx</span><span class="p">],</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">valid_x_argb_list</span><span class="p">[[</span><span class="n">idx</span><span class="p">],</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">]])[:,</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
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<pre>(8.1103305e-17, 0.9999809)</pre>
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<pre>(array([1.0217501e-07, 1.6723038e-07, 3.8222831e-07, 3.8686889e-07,
        4.3885061e-06, 4.5276129e-06, 6.1275914e-06, 7.7656487e-06,
        1.1705354e-05, 1.2914673e-05, 1.8179266e-05, 1.8553075e-05,
        2.4884936e-05, 3.4156812e-05, 9.9670756e-01, 9.9934298e-01,
        9.9985909e-01, 9.9991119e-01, 9.9995708e-01, 9.9998093e-01],
       dtype=float32),
 array([156, 292, 293, 294, 307, 306, 305, 308, 304, 309, 313, 314, 315,
        312,  70,  69,  65,  68,  66,  67]))</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">valid_x_arga_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
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<pre>array([  0,   2,   3,  28,  29,  30,  31,  33,  34,  35,  36,  54,  55,
        56,  65,  66,  67,  68,  69,  70,  75,  76,  77,  82,  83,  84,
        85,  86,  87,  97,  98,  99, 100, 101, 102, 106, 107, 108, 112,
       113, 114, 115, 135, 136, 137, 156, 157, 158, 168, 169, 170, 171,
       172, 174, 175, 176, 177, 178, 180, 181, 182, 183, 184, 186, 187,
       188, 190, 191, 192, 193, 195, 196, 197, 198, 200, 201, 207, 208,
       209, 210, 211, 212, 213, 214, 215, 292, 293, 294, 304, 305, 306,
       307, 308, 309, 312, 313, 314, 315])</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">valid_x_argb_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
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<pre>array([75, 76, 77])</pre>
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<pre>array([65, 66, 67, 68, 69, 70])</pre>
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<pre>array([65, 66, 67, 68, 69, 70])</pre>
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</div>保存模型训练历史
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">MODEL_BASE</span> <span class="o">=</span> <span class="s1">&#39;s2_01&#39;</span>
<span class="n">MODEL_NAME</span> <span class="o">=</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;_final_v4_0&#39;</span>

<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;./Demo/Models/&#39;</span> <span class="o">+</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;/&#39;</span> <span class="o">+</span> <span class="n">MODEL_NAME</span> <span class="o">+</span> <span class="s1">&#39;_hist_end.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">pickle</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">hist_0</span><span class="o">.</span><span class="n">history</span><span class="p">,</span> <span class="n">f</span><span class="p">)</span>
    
<span class="n">MODEL_BASE</span> <span class="o">=</span> <span class="s1">&#39;s2_01&#39;</span>
<span class="n">MODEL_NAME</span> <span class="o">=</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;_final_v4_1&#39;</span>

<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;./Demo/Models/&#39;</span> <span class="o">+</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;/&#39;</span> <span class="o">+</span> <span class="n">MODEL_NAME</span> <span class="o">+</span> <span class="s1">&#39;_hist_end.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">pickle</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">hist_1</span><span class="o">.</span><span class="n">history</span><span class="p">,</span> <span class="n">f</span><span class="p">)</span>
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</div>Part3：预测部分
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<span class="k">for</span> <span class="n">path</span> <span class="ow">in</span> <span class="n">test_txt_file_list</span><span class="p">:</span>
    <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">path</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
        <span class="n">test_text_dict</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">path</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;/&#39;</span><span class="p">)[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;.&#39;</span><span class="p">)[</span><span class="mi">0</span><span class="p">])]</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">text_filter</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">f</span><span class="o">.</span><span class="n">read</span><span class="p">())))</span>
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<span class="n">tk</span>
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<pre>&#39;130_10&#39;</pre>
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<pre>[&#39;临&#39;, &#39;床&#39;, &#39;研&#39;, &#39;究&#39;, &#39;\n&#39;]</pre>
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    <span class="n">test_text_encoded_dict</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">train_encode_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> 
                                          <span class="k">if</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">train_encode_dict</span> <span class="k">else</span> <span class="mi">0</span><span class="p">,</span> <span class="n">v</span><span class="p">))</span>
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<pre>([187, 1013, 2096, 2166, 0], 2975)</pre>
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<p>get anno df</p>

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      <th>idx_0</th>
      <th>idx_1</th>
      <th>text</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>T1</td>
      <td>Disease</td>
      <td>38</td>
      <td>44</td>
      <td>2 型糖尿病</td>
    </tr>
    <tr>
      <th>1</th>
      <td>T2</td>
      <td>Disease</td>
      <td>133</td>
      <td>139</td>
      <td>2 型糖尿病</td>
    </tr>
    <tr>
      <th>2</th>
      <td>T3</td>
      <td>Disease</td>
      <td>1667</td>
      <td>1673</td>
      <td>2 型糖尿病</td>
    </tr>
    <tr>
      <th>3</th>
      <td>T4</td>
      <td>Disease</td>
      <td>5939</td>
      <td>5945</td>
      <td>2 型糖尿病</td>
    </tr>
    <tr>
      <th>4</th>
      <td>T5</td>
      <td>Disease</td>
      <td>6158</td>
      <td>6164</td>
      <td>2 型糖尿病</td>
    </tr>
  </tbody>
</table>
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<p>get arga labels</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">test_0a_lables_dict</span> <span class="o">=</span> <span class="n">get_aa_labels_dict</span><span class="p">(</span><span class="n">test_anno_dict</span><span class="p">,</span> <span class="n">test_text_dict</span><span class="p">,</span> <span class="n">LABELS_0</span><span class="p">)</span>
<span class="n">test_1a_lables_dict</span> <span class="o">=</span> <span class="n">get_aa_labels_dict</span><span class="p">(</span><span class="n">test_anno_dict</span><span class="p">,</span> <span class="n">test_text_dict</span><span class="p">,</span> <span class="n">LABELS_1</span><span class="p">)</span>

<span class="n">test_a_lables_dict</span> <span class="o">=</span> <span class="n">get_a_labels_dict</span><span class="p">(</span><span class="n">test_anno_dict</span><span class="p">,</span> <span class="n">test_text_dict</span><span class="p">,</span> <span class="n">LABELS_DICT</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">test_a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">tk</span><span class="p">),</span> <span class="n">test_a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">tk</span><span class="p">)</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">test_a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">tk</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
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<pre>(array([[0],
        [0],
        [0],
        ...,
        [0],
        [0],
        [0]], dtype=uint8), (19603, 1), 9891)</pre>
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<p>get argb and rearrange data</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">_get_test_meta_data</span><span class="p">(</span><span class="n">b_list</span><span class="p">,</span> <span class="n">idx_pad_left_list</span><span class="p">,</span> <span class="n">idx_left_list</span><span class="p">,</span> <span class="n">idx_right_list</span><span class="p">,</span> 
                        <span class="n">x_text_list</span><span class="p">,</span> <span class="n">x_arga_list</span><span class="p">,</span> <span class="n">x_argaa_list</span><span class="p">,</span> <span class="n">x_argb_list</span><span class="p">,</span> <span class="n">y_list</span><span class="p">,</span> <span class="n">text_encoded</span><span class="p">,</span> <span class="n">list_a</span><span class="p">,</span> <span class="n">df_b</span><span class="p">,</span> <span class="n">x_idx</span><span class="p">,</span> <span class="n">len_text</span><span class="p">,</span> <span class="n">list_aa</span><span class="p">):</span>
    
  
    <span class="k">for</span> <span class="n">idx_b</span><span class="p">,</span> <span class="n">row_b</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">df_b</span><span class="o">.</span><span class="n">itertuples</span><span class="p">()):</span> 
        
        <span class="n">_</span><span class="p">,</span> <span class="n">id_b</span><span class="p">,</span> <span class="n">label_b</span><span class="p">,</span> <span class="n">idx_b_0</span><span class="p">,</span> <span class="n">idx_b_1</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">row_b</span>
        
        <span class="n">_idx_b_mid</span> <span class="o">=</span> <span class="nb">int</span><span class="p">((</span><span class="n">idx_b_0</span> <span class="o">+</span> <span class="n">idx_b_1</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span><span class="p">)</span>
        
        <span class="k">for</span> <span class="n">margin</span> <span class="ow">in</span> <span class="n">MARGIN_LIST</span><span class="p">:</span>
            
            <span class="n">idx_b_mid</span> <span class="o">=</span> <span class="n">_idx_b_mid</span> <span class="o">+</span> <span class="n">margin</span>
        
            <span class="n">_left</span> <span class="o">=</span> <span class="n">idx_b_mid</span> <span class="o">-</span> <span class="n">TRAIN_LENGTH_HALF</span>
            <span class="n">_right</span> <span class="o">=</span> <span class="n">idx_b_mid</span> <span class="o">+</span> <span class="n">TRAIN_LENGTH_HALF</span>

            <span class="n">idx_left</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">_left</span><span class="p">)</span>
            <span class="n">idx_right</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">len_text</span><span class="p">,</span> <span class="n">_right</span><span class="p">)</span>

            <span class="n">idx_pad_left</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="nb">min</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">_left</span><span class="p">))</span>
            <span class="n">idx_pad_right</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="nb">min</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">len_text</span> <span class="o">-</span> <span class="n">_right</span><span class="p">))</span>

            <span class="c1"># x arg b</span>
            <span class="n">_b</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">TRAIN_LENGTH</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
            <span class="n">b_start</span> <span class="o">=</span> <span class="n">idx_pad_left</span> <span class="o">+</span> <span class="p">(</span><span class="n">idx_b_0</span> <span class="o">-</span> <span class="n">idx_left</span><span class="p">)</span>
            <span class="n">b_end</span> <span class="o">=</span> <span class="n">idx_pad_left</span> <span class="o">+</span> <span class="p">(</span><span class="n">idx_b_1</span> <span class="o">-</span> <span class="n">idx_left</span><span class="p">)</span>
            
            <span class="k">if</span> <span class="p">(</span><span class="n">b_start</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span><span class="n">b_end</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span><span class="n">b_start</span> <span class="o">&gt;</span> <span class="n">TRAIN_LENGTH</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span><span class="n">b_end</span> <span class="o">&gt;</span> <span class="n">TRAIN_LENGTH</span><span class="p">):</span>
                <span class="k">continue</span>
                
            <span class="k">assert</span> <span class="n">b_start</span> <span class="o">&gt;=</span> <span class="mi">0</span>
            <span class="k">assert</span> <span class="n">b_end</span> <span class="o">&gt;=</span> <span class="mi">0</span>
            <span class="k">assert</span> <span class="n">b_start</span> <span class="o">&lt;=</span> <span class="n">TRAIN_LENGTH</span>
            <span class="k">assert</span> <span class="n">b_end</span> <span class="o">&lt;=</span> <span class="n">TRAIN_LENGTH</span>

            
            <span class="n">_b</span><span class="p">[</span><span class="n">b_start</span><span class="p">:</span><span class="n">b_end</span><span class="p">]</span> <span class="o">=</span> <span class="n">x_idx</span><span class="o">+</span><span class="mi">1</span>

            <span class="n">x_argb_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_b</span><span class="p">)</span>
            
            
            <span class="c1"># b_list</span>
            <span class="n">b_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">id_b</span><span class="p">)</span>
            
            <span class="c1"># idx_pad_left</span>
            <span class="n">idx_pad_left_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">idx_pad_left</span><span class="p">)</span>
            
            <span class="c1"># idx_left_list</span>
            <span class="n">idx_left_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">idx_left</span><span class="p">)</span>
            
            <span class="c1"># idx_right_list</span>
            <span class="n">idx_right_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">idx_right</span><span class="p">)</span>

            <span class="c1"># x arg a</span>
            <span class="n">_a</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">pad</span><span class="p">(</span><span class="n">list_a</span><span class="p">[</span><span class="n">idx_left</span><span class="p">:</span><span class="n">idx_right</span><span class="p">],</span> <span class="p">((</span><span class="n">idx_pad_left</span><span class="p">,</span> <span class="n">idx_pad_right</span><span class="p">),</span> <span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">)),</span> <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;constant&#39;</span><span class="p">,</span> <span class="n">constant_values</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
                        
            <span class="n">x_arga_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_a</span><span class="p">)</span>

            <span class="c1"># x arg aa</span>
            <span class="n">_aa</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">pad</span><span class="p">(</span><span class="n">list_aa</span><span class="p">[</span><span class="n">idx_left</span><span class="p">:</span><span class="n">idx_right</span><span class="p">],</span> <span class="p">((</span><span class="n">idx_pad_left</span><span class="p">,</span> <span class="n">idx_pad_right</span><span class="p">),</span> <span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">)),</span> <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;constant&#39;</span><span class="p">,</span> <span class="n">constant_values</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
            
            <span class="n">x_argaa_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_aa</span><span class="p">)</span>

            <span class="c1"># x text</span>
            <span class="n">_x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">pad</span><span class="p">(</span><span class="n">text_encoded</span><span class="p">[</span><span class="n">idx_left</span><span class="p">:</span><span class="n">idx_right</span><span class="p">],</span> <span class="p">(</span><span class="n">idx_pad_left</span><span class="p">,</span> <span class="n">idx_pad_right</span><span class="p">),</span> <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;constant&#39;</span><span class="p">,</span> <span class="n">constant_values</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
            
            <span class="n">x_text_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_x</span><span class="p">)</span>

    <span class="k">return</span> <span class="n">b_list</span><span class="p">,</span> <span class="n">idx_pad_left_list</span><span class="p">,</span> <span class="n">idx_left_list</span><span class="p">,</span> <span class="n">idx_right_list</span><span class="p">,</span> <span class="n">x_text_list</span><span class="p">,</span> <span class="n">x_arga_list</span><span class="p">,</span> <span class="n">x_argaa_list</span><span class="p">,</span> <span class="n">x_argb_list</span><span class="p">,</span> <span class="n">y_list</span>

<span class="k">def</span> <span class="nf">get_test_meta_data</span><span class="p">(</span><span class="n">x_text_list</span><span class="p">,</span> <span class="n">x_arga_list</span><span class="p">,</span> <span class="n">x_argaa_list</span><span class="p">,</span> <span class="n">x_argb_list</span><span class="p">,</span> <span class="n">y_list</span><span class="p">,</span> <span class="n">text_encoded</span><span class="p">,</span> <span class="n">anno_df</span><span class="p">,</span> <span class="n">list_a</span><span class="p">,</span> <span class="n">list_0a</span><span class="p">,</span> <span class="n">list_1a</span><span class="p">):</span>
    
    <span class="n">len_text</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">text_encoded</span><span class="p">)</span>
    
    <span class="n">df_0b</span> <span class="o">=</span> <span class="n">anno_df</span><span class="p">[</span><span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;label&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="n">ARG_0b</span><span class="p">]</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="s1">&#39;idx_0&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    <span class="n">df_1b</span> <span class="o">=</span> <span class="n">anno_df</span><span class="p">[</span><span class="n">anno_df</span><span class="p">[</span><span class="s1">&#39;label&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="n">ARG_1b</span><span class="p">]</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="s1">&#39;idx_0&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    
    <span class="n">b_list</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">idx_pad_left_list</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">idx_left_list</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">idx_right_list</span> <span class="o">=</span> <span class="p">[]</span>
                    
<span class="c1">#     list_a = list_0a</span>
    <span class="n">list_aa</span> <span class="o">=</span> <span class="n">list_0a</span>
    <span class="n">df_b</span> <span class="o">=</span> <span class="n">df_0b</span>
    <span class="n">x_idx</span> <span class="o">=</span> <span class="mi">0</span>

    <span class="n">b_list</span><span class="p">,</span> <span class="n">idx_pad_left_list</span><span class="p">,</span> <span class="n">idx_left_list</span><span class="p">,</span> <span class="n">idx_right_list</span><span class="p">,</span> <span class="n">x_text_list</span><span class="p">,</span> <span class="n">x_arga_list</span><span class="p">,</span> <span class="n">x_argaa_list</span><span class="p">,</span> <span class="n">x_argb_list</span><span class="p">,</span> <span class="n">y_list</span> <span class="o">=</span> \
        <span class="n">_get_test_meta_data</span><span class="p">(</span><span class="n">b_list</span><span class="p">,</span> <span class="n">idx_pad_left_list</span><span class="p">,</span> <span class="n">idx_left_list</span><span class="p">,</span> <span class="n">idx_right_list</span><span class="p">,</span> <span class="n">x_text_list</span><span class="p">,</span> <span class="n">x_arga_list</span><span class="p">,</span> <span class="n">x_argaa_list</span><span class="p">,</span> <span class="n">x_argb_list</span><span class="p">,</span> <span class="n">y_list</span><span class="p">,</span> <span class="n">text_encoded</span><span class="p">,</span> <span class="n">list_a</span><span class="p">,</span> <span class="n">df_b</span><span class="p">,</span> <span class="n">x_idx</span><span class="p">,</span> <span class="n">len_text</span><span class="p">,</span> <span class="n">list_aa</span><span class="p">)</span>
    
<span class="c1">#     list_a = list_1a</span>
    <span class="n">list_aa</span> <span class="o">=</span> <span class="n">list_1a</span>
    <span class="n">df_b</span> <span class="o">=</span> <span class="n">df_1b</span>
    <span class="n">x_idx</span> <span class="o">=</span> <span class="mi">1</span>

    <span class="n">b_list</span><span class="p">,</span> <span class="n">idx_pad_left_list</span><span class="p">,</span> <span class="n">idx_left_list</span><span class="p">,</span> <span class="n">idx_right_list</span><span class="p">,</span> <span class="n">x_text_list</span><span class="p">,</span> <span class="n">x_arga_list</span><span class="p">,</span> <span class="n">x_argaa_list</span><span class="p">,</span> <span class="n">x_argb_list</span><span class="p">,</span> <span class="n">y_list</span> <span class="o">=</span> \
        <span class="n">_get_test_meta_data</span><span class="p">(</span><span class="n">b_list</span><span class="p">,</span> <span class="n">idx_pad_left_list</span><span class="p">,</span> <span class="n">idx_left_list</span><span class="p">,</span> <span class="n">idx_right_list</span><span class="p">,</span> <span class="n">x_text_list</span><span class="p">,</span> <span class="n">x_arga_list</span><span class="p">,</span> <span class="n">x_argaa_list</span><span class="p">,</span> <span class="n">x_argb_list</span><span class="p">,</span> <span class="n">y_list</span><span class="p">,</span> <span class="n">text_encoded</span><span class="p">,</span> <span class="n">list_a</span><span class="p">,</span> <span class="n">df_b</span><span class="p">,</span> <span class="n">x_idx</span><span class="p">,</span> <span class="n">len_text</span><span class="p">,</span> <span class="n">list_aa</span><span class="p">)</span>

    <span class="k">return</span> <span class="p">(</span><span class="n">b_list</span><span class="p">,</span> <span class="n">idx_pad_left_list</span><span class="p">,</span> <span class="n">idx_left_list</span><span class="p">,</span> <span class="n">idx_right_list</span><span class="p">,</span> <span class="n">x_text_list</span><span class="p">,</span> <span class="n">x_arga_list</span><span class="p">,</span> <span class="n">x_argaa_list</span><span class="p">,</span> <span class="n">x_argb_list</span><span class="p">,</span> <span class="n">y_list</span><span class="p">)</span>
</pre></div>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span> <span class="o">=</span> <span class="n">get_model</span><span class="p">()</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span><span class="o">.</span><span class="n">summary</span><span class="p">()</span>
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<pre>__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to                     
==================================================================================================
input_7 (InputLayer)            (None, 320)          0                                            
__________________________________________________________________________________________________
input_8 (InputLayer)            (None, 320)          0                                            
__________________________________________________________________________________________________
embedding_7 (Embedding)         (None, 320, 64)      209152      input_7[0][0]                    
__________________________________________________________________________________________________
embedding_8 (Embedding)         (None, 320, 32)      544         input_8[0][0]                    
__________________________________________________________________________________________________
spatial_dropout1d_5 (SpatialDro (None, 320, 64)      0           embedding_7[0][0]                
__________________________________________________________________________________________________
spatial_dropout1d_6 (SpatialDro (None, 320, 32)      0           embedding_8[0][0]                
__________________________________________________________________________________________________
input_9 (InputLayer)            (None, 320)          0                                            
__________________________________________________________________________________________________
bidirectional_13 (Bidirectional (None, 320, 256)     198656      spatial_dropout1d_5[0][0]        
__________________________________________________________________________________________________
bidirectional_14 (Bidirectional (None, 320, 256)     165888      spatial_dropout1d_6[0][0]        
__________________________________________________________________________________________________
embedding_9 (Embedding)         (None, 320, 8)       24          input_9[0][0]                    
__________________________________________________________________________________________________
dropout_9 (Dropout)             (None, 320, 256)     0           bidirectional_13[0][0]           
__________________________________________________________________________________________________
dropout_10 (Dropout)            (None, 320, 256)     0           bidirectional_14[0][0]           
__________________________________________________________________________________________________
bidirectional_15 (Bidirectional (None, 320, 256)     141312      embedding_9[0][0]                
__________________________________________________________________________________________________
concatenate_5 (Concatenate)     (None, 320, 768)     0           dropout_9[0][0]                  
                                                                 dropout_10[0][0]                 
                                                                 bidirectional_15[0][0]           
__________________________________________________________________________________________________
bidirectional_16 (Bidirectional (None, 320, 256)     919552      concatenate_5[0][0]              
__________________________________________________________________________________________________
bidirectional_17 (Bidirectional (None, 320, 256)     689664      concatenate_5[0][0]              
__________________________________________________________________________________________________
concatenate_6 (Concatenate)     (None, 320, 512)     0           bidirectional_16[0][0]           
                                                                 bidirectional_17[0][0]           
__________________________________________________________________________________________________
bidirectional_18 (Bidirectional (None, 320, 256)     657408      concatenate_6[0][0]              
__________________________________________________________________________________________________
dropout_11 (Dropout)            (None, 320, 256)     0           bidirectional_18[0][0]           
__________________________________________________________________________________________________
time_distributed_5 (TimeDistrib (None, 320, 64)      16448       dropout_11[0][0]                 
__________________________________________________________________________________________________
dropout_12 (Dropout)            (None, 320, 64)      0           time_distributed_5[0][0]         
__________________________________________________________________________________________________
time_distributed_6 (TimeDistrib (None, 320, 1)       65          dropout_12[0][0]                 
__________________________________________________________________________________________________
activation_3 (Activation)       (None, 320, 1)       0           time_distributed_6[0][0]         
==================================================================================================
Total params: 2,998,713
Trainable params: 2,789,561
Non-trainable params: 209,152
__________________________________________________________________________________________________
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</div>模型预测时针对每一个arg_b进行滑窗采样，使用正反模型分别进行预测。
为了提高模型鲁棒性，这里使用epoch分别为[17, 19, 21, 23, 25]的模型进行预测后融合。
对于arg_a的预测值整体分数在阈值（此处为0.6）之上为真。
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<span class="n">PRE_THRES</span> <span class="o">=</span> <span class="mf">0.6</span>

<span class="n">pre_final_dict</span> <span class="o">=</span> <span class="p">{}</span>

<span class="k">for</span> <span class="n">file_k</span> <span class="ow">in</span> <span class="n">test_text_encoded_dict</span><span class="p">:</span>
    
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Start &#39;</span><span class="p">,</span> <span class="n">file_k</span><span class="p">,</span> <span class="s1">&#39;---------------------------------&#39;</span><span class="p">)</span>
    
    <span class="c1"># 1. get model data inputs</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Part 1...&#39;</span><span class="p">)</span>
    <span class="n">test_x_text_list</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">test_x_arga_list</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">test_x_argaa_list</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">test_x_argb_list</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">test_y_list</span> <span class="o">=</span> <span class="p">[]</span>

    <span class="n">test_b_list</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">test_idx_pad_left_list</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">test_idx_left_list</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">test_idx_right_list</span> <span class="o">=</span> <span class="p">[]</span>
    
    <span class="n">t0</span> <span class="o">=</span> <span class="n">test_text_encoded_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">file_k</span><span class="p">)</span>
    <span class="n">anno_0</span> <span class="o">=</span> <span class="n">test_anno_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">file_k</span><span class="p">)</span>
    <span class="c1"># arg_0 = train_arg_dict.get(file_k)</span>
    <span class="n">arg_0</span> <span class="o">=</span> <span class="kc">None</span>
    <span class="n">list_a</span> <span class="o">=</span> <span class="n">test_a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">file_k</span><span class="p">)</span>
    <span class="n">list_0a</span> <span class="o">=</span> <span class="n">test_0a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">file_k</span><span class="p">)</span>
    <span class="n">list_1a</span> <span class="o">=</span> <span class="n">test_1a_lables_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">file_k</span><span class="p">)</span>
    
    <span class="n">test_b_list</span><span class="p">,</span> <span class="n">test_idx_pad_left_list</span><span class="p">,</span> <span class="n">test_idx_left_list</span><span class="p">,</span> <span class="n">test_idx_right_list</span><span class="p">,</span> <span class="n">test_x_text_list</span><span class="p">,</span> <span class="n">test_x_arga_list</span><span class="p">,</span> <span class="n">test_x_argaa_list</span><span class="p">,</span> <span class="n">test_x_argb_list</span><span class="p">,</span> <span class="n">test_y_list</span> <span class="o">=</span> \
        <span class="n">get_test_meta_data</span><span class="p">(</span><span class="n">test_x_text_list</span><span class="p">,</span> <span class="n">test_x_arga_list</span><span class="p">,</span> <span class="n">test_x_argaa_list</span><span class="p">,</span> <span class="n">test_x_argb_list</span><span class="p">,</span> <span class="n">test_y_list</span><span class="p">,</span> 
                      <span class="n">text_encoded</span><span class="o">=</span><span class="n">t0</span><span class="p">,</span> <span class="n">anno_df</span><span class="o">=</span><span class="n">anno_0</span><span class="p">,</span> <span class="n">list_a</span><span class="o">=</span><span class="n">list_a</span><span class="p">,</span> <span class="n">list_0a</span><span class="o">=</span><span class="n">list_0a</span><span class="p">,</span> <span class="n">list_1a</span><span class="o">=</span><span class="n">list_1a</span><span class="p">)</span>
    
    <span class="nb">print</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">test_b_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">test_idx_left_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">test_x_text_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">test_x_arga_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">test_x_argaa_list</span><span class="p">),</span> 
          <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">test_x_argb_list</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">test_y_list</span><span class="p">))</span>
    
    <span class="c1"># 2. get predictions</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Part 2...&#39;</span><span class="p">)</span>
    <span class="n">test_x_text_list</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">test_x_text_list</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)</span>
    <span class="n">test_x_arga_list</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">test_x_arga_list</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)</span>
    <span class="n">test_x_argaa_list</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">test_x_argaa_list</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">int</span><span class="p">)</span>
    <span class="n">test_x_argb_list</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">test_x_argb_list</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">int</span><span class="p">)</span>
    
    <span class="n">pre_list</span> <span class="o">=</span> <span class="p">[]</span>
    
    <span class="n">MODEL_BASE</span> <span class="o">=</span> <span class="s1">&#39;s2_01&#39;</span>
    <span class="n">MODEL_NAME</span> <span class="o">=</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;_final_v4_0&#39;</span>
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">17</span><span class="p">,</span> <span class="mi">19</span><span class="p">,</span> <span class="mi">21</span><span class="p">,</span> <span class="mi">23</span><span class="p">,</span> <span class="mi">25</span><span class="p">]:</span>
        <span class="n">w_p</span> <span class="o">=</span> <span class="s1">&#39;./Demo/Models/&#39;</span> <span class="o">+</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;/&#39;</span> <span class="o">+</span> <span class="n">MODEL_NAME</span> <span class="o">+</span> <span class="s1">&#39;_</span><span class="si">%02d</span><span class="s1">.hd5&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)</span>
        <span class="n">model</span><span class="o">.</span><span class="n">load_weights</span><span class="p">(</span><span class="n">w_p</span><span class="p">)</span>
        <span class="n">pre_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">([</span><span class="n">test_x_text_list</span><span class="p">,</span> <span class="n">test_x_arga_list</span><span class="p">,</span> <span class="n">test_x_argb_list</span><span class="p">]))</span>

    <span class="n">MODEL_NAME</span> <span class="o">=</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;_final_v4_1&#39;</span>
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">17</span><span class="p">,</span> <span class="mi">19</span><span class="p">,</span> <span class="mi">21</span><span class="p">,</span> <span class="mi">23</span><span class="p">,</span> <span class="mi">25</span><span class="p">]:</span>
        <span class="n">w_p</span> <span class="o">=</span> <span class="s1">&#39;./Demo/Models/&#39;</span> <span class="o">+</span> <span class="n">MODEL_BASE</span> <span class="o">+</span> <span class="s1">&#39;/&#39;</span> <span class="o">+</span> <span class="n">MODEL_NAME</span> <span class="o">+</span> <span class="s1">&#39;_</span><span class="si">%02d</span><span class="s1">.hd5&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)</span>
        <span class="n">model</span><span class="o">.</span><span class="n">load_weights</span><span class="p">(</span><span class="n">w_p</span><span class="p">)</span>
        <span class="n">pre_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">([</span><span class="n">test_x_text_list</span><span class="p">[:,</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">test_x_arga_list</span><span class="p">[:,</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">test_x_argb_list</span><span class="p">[:,</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">]])[:,</span> <span class="p">::</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="p">:])</span>

    <span class="n">pre</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">pre_list</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">pre</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
    
    <span class="c1"># 3. get pre dict for each output</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Part 3...&#39;</span><span class="p">)</span>
    <span class="n">pre_test_dict</span> <span class="o">=</span> <span class="p">{}</span>
    <span class="k">for</span> <span class="n">idx</span><span class="p">,</span> <span class="n">p</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">pre</span><span class="p">):</span>

    <span class="c1">#     if not len(np.argwhere(p&gt;0.5)) &gt; 0: continue</span>

        <span class="n">_test_b</span> <span class="o">=</span> <span class="n">test_b_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span>
        <span class="n">_test_idx_pad_left</span> <span class="o">=</span> <span class="n">test_idx_pad_left_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span>
        <span class="n">_test_idx_left</span> <span class="o">=</span> <span class="n">test_idx_left_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span>
        <span class="n">_test_idx_right</span> <span class="o">=</span> <span class="n">test_idx_right_list</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span>

        <span class="n">_test_b_label</span> <span class="o">=</span> <span class="n">anno_0</span><span class="p">[</span><span class="n">anno_0</span><span class="p">[</span><span class="s1">&#39;id&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="n">_test_b</span><span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="s1">&#39;label&#39;</span><span class="p">]</span>

        <span class="k">if</span> <span class="n">_test_b_label</span> <span class="o">==</span> <span class="n">ARG_0b</span><span class="p">:</span>
<span class="c1">#             _anno_0 = anno_0[(anno_0[&#39;label&#39;].isin(LABELS_0_DICT.keys())) &amp; (anno_0[&#39;idx_0&#39;] &gt;= _test_idx_left) &amp; (anno_0[&#39;idx_1&#39;] &lt;= _test_idx_right)]</span>
            <span class="n">_anno_0</span> <span class="o">=</span> <span class="n">anno_0</span><span class="p">[(</span><span class="n">anno_0</span><span class="p">[</span><span class="s1">&#39;label&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isin</span><span class="p">(</span><span class="n">ARG_0a_SET</span><span class="p">))</span> <span class="o">&amp;</span> <span class="p">(</span><span class="n">anno_0</span><span class="p">[</span><span class="s1">&#39;idx_0&#39;</span><span class="p">]</span> <span class="o">&gt;=</span> <span class="n">_test_idx_left</span><span class="p">)</span> <span class="o">&amp;</span> <span class="p">(</span><span class="n">anno_0</span><span class="p">[</span><span class="s1">&#39;idx_1&#39;</span><span class="p">]</span> <span class="o">&lt;=</span> <span class="n">_test_idx_right</span><span class="p">)]</span>

        <span class="k">if</span> <span class="n">_test_b_label</span> <span class="o">==</span> <span class="n">ARG_1b</span><span class="p">:</span>
<span class="c1">#             _anno_0 = anno_0[(anno_0[&#39;label&#39;].isin(LABELS_1_DICT.keys())) &amp; (anno_0[&#39;idx_0&#39;] &gt;= _test_idx_left) &amp; (anno_0[&#39;idx_1&#39;] &lt;= _test_idx_right)]</span>
            <span class="n">_anno_0</span> <span class="o">=</span> <span class="n">anno_0</span><span class="p">[(</span><span class="n">anno_0</span><span class="p">[</span><span class="s1">&#39;label&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isin</span><span class="p">(</span><span class="n">ARG_1a_SET</span><span class="p">))</span> <span class="o">&amp;</span> <span class="p">(</span><span class="n">anno_0</span><span class="p">[</span><span class="s1">&#39;idx_0&#39;</span><span class="p">]</span> <span class="o">&gt;=</span> <span class="n">_test_idx_left</span><span class="p">)</span> <span class="o">&amp;</span> <span class="p">(</span><span class="n">anno_0</span><span class="p">[</span><span class="s1">&#39;idx_1&#39;</span><span class="p">]</span> <span class="o">&lt;=</span> <span class="n">_test_idx_right</span><span class="p">)]</span>

        <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">_anno_0</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>

            <span class="k">for</span> <span class="n">_idx_a</span><span class="p">,</span> <span class="n">_row_a</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">_anno_0</span><span class="o">.</span><span class="n">itertuples</span><span class="p">()):</span>
                <span class="n">_</span><span class="p">,</span> <span class="n">_id_a</span><span class="p">,</span> <span class="n">_label_a</span><span class="p">,</span> <span class="n">_idx_a_0</span><span class="p">,</span> <span class="n">_idx_a_1</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">_row_a</span>

                <span class="n">_k</span> <span class="o">=</span> <span class="n">_label_a</span> <span class="o">+</span> <span class="n">_test_b_label</span> <span class="o">+</span> <span class="n">_id_a</span> <span class="o">+</span> <span class="n">_test_b</span>

                <span class="k">if</span> <span class="n">_k</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">pre_test_dict</span><span class="p">:</span>
                    <span class="n">pre_test_dict</span><span class="p">[</span><span class="n">_k</span><span class="p">]</span> <span class="o">=</span> <span class="p">{}</span>
                    <span class="n">pre_test_dict</span><span class="p">[</span><span class="n">_k</span><span class="p">][</span><span class="s1">&#39;arg_a&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">_label_a</span>
                    <span class="n">pre_test_dict</span><span class="p">[</span><span class="n">_k</span><span class="p">][</span><span class="s1">&#39;arg_b&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">_test_b_label</span>
                    <span class="n">pre_test_dict</span><span class="p">[</span><span class="n">_k</span><span class="p">][</span><span class="s1">&#39;arg_1&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">_id_a</span>
                    <span class="n">pre_test_dict</span><span class="p">[</span><span class="n">_k</span><span class="p">][</span><span class="s1">&#39;arg_2&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">_test_b</span>
                    <span class="n">pre_test_dict</span><span class="p">[</span><span class="n">_k</span><span class="p">][</span><span class="s1">&#39;values&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
                    <span class="n">pre_test_dict</span><span class="p">[</span><span class="n">_k</span><span class="p">][</span><span class="s1">&#39;counts&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>

                <span class="n">_v_l</span> <span class="o">=</span> <span class="n">p</span><span class="p">[</span><span class="n">_test_idx_pad_left</span> <span class="o">+</span> <span class="n">_idx_a_0</span> <span class="o">-</span> <span class="n">_test_idx_left</span><span class="p">:</span> <span class="n">_test_idx_pad_left</span> <span class="o">+</span> <span class="n">_idx_a_1</span> <span class="o">-</span> <span class="n">_test_idx_left</span><span class="p">]</span>
                <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">_v_l</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span>
<span class="c1">#                 if len(_v_l) == 0:</span>
<span class="c1">#                     print(_row_a)</span>
<span class="c1">#                     break</span>
                <span class="n">_value</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">_v_l</span><span class="p">)</span>
                <span class="n">pre_test_dict</span><span class="p">[</span><span class="n">_k</span><span class="p">][</span><span class="s1">&#39;values&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">pre_test_dict</span><span class="p">[</span><span class="n">_k</span><span class="p">][</span><span class="s1">&#39;values&#39;</span><span class="p">]</span> <span class="o">+</span> <span class="n">_value</span>
                <span class="n">pre_test_dict</span><span class="p">[</span><span class="n">_k</span><span class="p">][</span><span class="s1">&#39;counts&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">pre_test_dict</span><span class="p">[</span><span class="n">_k</span><span class="p">][</span><span class="s1">&#39;counts&#39;</span><span class="p">]</span> <span class="o">+</span> <span class="mi">1</span>
                
    <span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">pre_test_dict</span><span class="p">))</span>
                
    <span class="c1"># 4. filter pre with threshold</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Part 4...&#39;</span><span class="p">)</span>
    <span class="n">len_max</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="n">pre_test_df</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">r_id_idx</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">pre_test_dict</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
        <span class="n">_mean</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="s1">&#39;values&#39;</span><span class="p">]</span> <span class="o">/</span> <span class="n">v</span><span class="p">[</span><span class="s1">&#39;counts&#39;</span><span class="p">]</span>

        <span class="n">len_max</span> <span class="o">=</span> <span class="n">len_max</span> <span class="k">if</span> <span class="n">len_max</span> <span class="o">&gt;</span> <span class="n">v</span><span class="p">[</span><span class="s1">&#39;counts&#39;</span><span class="p">]</span> <span class="k">else</span> <span class="n">v</span><span class="p">[</span><span class="s1">&#39;counts&#39;</span><span class="p">]</span>
        <span class="k">assert</span> <span class="n">len_max</span> <span class="o">&lt;=</span> <span class="nb">len</span><span class="p">(</span><span class="n">MARGIN_LIST</span><span class="p">)</span>

        <span class="k">if</span> <span class="n">_mean</span> <span class="o">&gt;</span> <span class="n">PRE_THRES</span><span class="p">:</span>
            <span class="n">_row</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;R&#39;</span><span class="o">+</span><span class="nb">str</span><span class="p">(</span><span class="n">r_id_idx</span><span class="p">),</span> <span class="n">v</span><span class="p">[</span><span class="s1">&#39;arg_a&#39;</span><span class="p">]</span><span class="o">+</span><span class="s1">&#39;_&#39;</span><span class="o">+</span><span class="n">v</span><span class="p">[</span><span class="s1">&#39;arg_b&#39;</span><span class="p">]</span><span class="o">+</span><span class="s1">&#39; &#39;</span><span class="o">+</span><span class="s1">&#39;Arg1:&#39;</span><span class="o">+</span><span class="n">v</span><span class="p">[</span><span class="s1">&#39;arg_1&#39;</span><span class="p">]</span><span class="o">+</span><span class="s1">&#39; &#39;</span><span class="o">+</span><span class="s1">&#39;Arg2:&#39;</span><span class="o">+</span><span class="n">v</span><span class="p">[</span><span class="s1">&#39;arg_2&#39;</span><span class="p">]]</span>
            <span class="n">pre_test_df</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_row</span><span class="p">)</span>
            <span class="n">r_id_idx</span> <span class="o">+=</span> <span class="mi">1</span>
            
    <span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">pre_test_df</span><span class="p">))</span>
            
    <span class="n">pre_final_dict</span><span class="p">[</span><span class="n">file_k</span><span class="p">]</span> <span class="o">=</span> <span class="n">pre_test_df</span>
    
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;End &#39;</span><span class="p">,</span> <span class="n">file_k</span><span class="p">,</span> <span class="s1">&#39;---------------------------------&#39;</span><span class="p">)</span>
    
<span class="c1">#     break</span>
</pre></div>

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

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


<div class="output_area">

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


<div class="output_subarea output_stream output_stdout output_text">
<pre>Start  130_10 ---------------------------------
Part 1...
(1001,) (1001,) (1001, 320) (1001, 320, 1) (1001, 320, 1) (1001, 320, 1) (0,)
Part 2...
(1001, 320, 1)
Part 3...
1731
Part 4...
205
End  130_10 ---------------------------------
Start  130_11 ---------------------------------
Part 1...
(2123,) (2123,) (2123, 320) (2123, 320, 1) (2123, 320, 1) (2123, 320, 1) (0,)
Part 2...
(2123, 320, 1)
Part 3...
1602
Part 4...
238
End  130_11 ---------------------------------
Start  130_12 ---------------------------------
Part 1...
(2145,) (2145,) (2145, 320) (2145, 320, 1) (2145, 320, 1) (2145, 320, 1) (0,)
Part 2...
(2145, 320, 1)
Part 3...
3654
Part 4...
287
End  130_12 ---------------------------------
Start  130_16 ---------------------------------
Part 1...
(1045,) (1045,) (1045, 320) (1045, 320, 1) (1045, 320, 1) (1045, 320, 1) (0,)
Part 2...
(1045, 320, 1)
Part 3...
1538
Part 4...
240
End  130_16 ---------------------------------
Start  130_2 ---------------------------------
Part 1...
(506,) (506,) (506, 320) (506, 320, 1) (506, 320, 1) (506, 320, 1) (0,)
Part 2...
(506, 320, 1)
Part 3...
618
Part 4...
95
End  130_2 ---------------------------------
Start  130_21 ---------------------------------
Part 1...
(2035,) (2035,) (2035, 320) (2035, 320, 1) (2035, 320, 1) (2035, 320, 1) (0,)
Part 2...
(2035, 320, 1)
Part 3...
2134
Part 4...
229
End  130_21 ---------------------------------
Start  130_22 ---------------------------------
Part 1...
(2706,) (2706,) (2706, 320) (2706, 320, 1) (2706, 320, 1) (2706, 320, 1) (0,)
Part 2...
(2706, 320, 1)
Part 3...
3106
Part 4...
258
End  130_22 ---------------------------------
Start  130_23 ---------------------------------
Part 1...
(2002,) (2002,) (2002, 320) (2002, 320, 1) (2002, 320, 1) (2002, 320, 1) (0,)
Part 2...
(2002, 320, 1)
Part 3...
2194
Part 4...
240
End  130_23 ---------------------------------
Start  130_24_1 ---------------------------------
Part 1...
(1991,) (1991,) (1991, 320) (1991, 320, 1) (1991, 320, 1) (1991, 320, 1) (0,)
Part 2...
(1991, 320, 1)
Part 3...
3399
Part 4...
405
End  130_24_1 ---------------------------------
Start  130_24_2 ---------------------------------
Part 1...
(1419,) (1419,) (1419, 320) (1419, 320, 1) (1419, 320, 1) (1419, 320, 1) (0,)
Part 2...
(1419, 320, 1)
Part 3...
1608
Part 4...
220
End  130_24_2 ---------------------------------
Start  130_6 ---------------------------------
Part 1...
(2112,) (2112,) (2112, 320) (2112, 320, 1) (2112, 320, 1) (2112, 320, 1) (0,)
Part 2...
(2112, 320, 1)
Part 3...
1226
Part 4...
73
End  130_6 ---------------------------------
Start  130_9 ---------------------------------
Part 1...
(2915,) (2915,) (2915, 320) (2915, 320, 1) (2915, 320, 1) (2915, 320, 1) (0,)
Part 2...
(2915, 320, 1)
Part 3...
2969
Part 4...
184
End  130_9 ---------------------------------
Start  155_10 ---------------------------------
Part 1...
(264,) (264,) (264, 320) (264, 320, 1) (264, 320, 1) (264, 320, 1) (0,)
Part 2...
(264, 320, 1)
Part 3...
487
Part 4...
62
End  155_10 ---------------------------------
Start  155_11 ---------------------------------
Part 1...
(660,) (660,) (660, 320) (660, 320, 1) (660, 320, 1) (660, 320, 1) (0,)
Part 2...
(660, 320, 1)
Part 3...
235
Part 4...
32
End  155_11 ---------------------------------
Start  155_12 ---------------------------------
Part 1...
(1254,) (1254,) (1254, 320) (1254, 320, 1) (1254, 320, 1) (1254, 320, 1) (0,)
Part 2...
(1254, 320, 1)
Part 3...
1068
Part 4...
133
End  155_12 ---------------------------------
Start  155_18 ---------------------------------
Part 1...
(1111,) (1111,) (1111, 320) (1111, 320, 1) (1111, 320, 1) (1111, 320, 1) (0,)
Part 2...
(1111, 320, 1)
Part 3...
977
Part 4...
117
End  155_18 ---------------------------------
Start  155_21 ---------------------------------
Part 1...
(3883,) (3883,) (3883, 320) (3883, 320, 1) (3883, 320, 1) (3883, 320, 1) (0,)
Part 2...
(3883, 320, 1)
Part 3...
3875
Part 4...
361
End  155_21 ---------------------------------
Start  155_4 ---------------------------------
Part 1...
(825,) (825,) (825, 320) (825, 320, 1) (825, 320, 1) (825, 320, 1) (0,)
Part 2...
(825, 320, 1)
Part 3...
992
Part 4...
104
End  155_4 ---------------------------------
Start  155_6 ---------------------------------
Part 1...
(1584,) (1584,) (1584, 320) (1584, 320, 1) (1584, 320, 1) (1584, 320, 1) (0,)
Part 2...
(1584, 320, 1)
Part 3...
2264
Part 4...
230
End  155_6 ---------------------------------
Start  155_7 ---------------------------------
Part 1...
(748,) (748,) (748, 320) (748, 320, 1) (748, 320, 1) (748, 320, 1) (0,)
Part 2...
(748, 320, 1)
Part 3...
792
Part 4...
118
End  155_7 ---------------------------------
Start  156_11 ---------------------------------
Part 1...
(803,) (803,) (803, 320) (803, 320, 1) (803, 320, 1) (803, 320, 1) (0,)
Part 2...
(803, 320, 1)
Part 3...
1023
Part 4...
205
End  156_11 ---------------------------------
Start  156_12 ---------------------------------
Part 1...
(559,) (559,) (559, 320) (559, 320, 1) (559, 320, 1) (559, 320, 1) (0,)
Part 2...
(559, 320, 1)
Part 3...
160
Part 4...
42
End  156_12 ---------------------------------
Start  156_15 ---------------------------------
Part 1...
(1342,) (1342,) (1342, 320) (1342, 320, 1) (1342, 320, 1) (1342, 320, 1) (0,)
Part 2...
(1342, 320, 1)
Part 3...
2430
Part 4...
156
End  156_15 ---------------------------------
Start  156_16 ---------------------------------
Part 1...
(737,) (737,) (737, 320) (737, 320, 1) (737, 320, 1) (737, 320, 1) (0,)
Part 2...
(737, 320, 1)
Part 3...
852
Part 4...
85
End  156_16 ---------------------------------
Start  156_18 ---------------------------------
Part 1...
(2585,) (2585,) (2585, 320) (2585, 320, 1) (2585, 320, 1) (2585, 320, 1) (0,)
Part 2...
(2585, 320, 1)
Part 3...
1860
Part 4...
194
End  156_18 ---------------------------------
Start  156_19 ---------------------------------
Part 1...
(913,) (913,) (913, 320) (913, 320, 1) (913, 320, 1) (913, 320, 1) (0,)
Part 2...
(913, 320, 1)
Part 3...
1007
Part 4...
192
End  156_19 ---------------------------------
Start  156_20 ---------------------------------
Part 1...
(1914,) (1914,) (1914, 320) (1914, 320, 1) (1914, 320, 1) (1914, 320, 1) (0,)
Part 2...
(1914, 320, 1)
Part 3...
1869
Part 4...
198
End  156_20 ---------------------------------
Start  156_6 ---------------------------------
Part 1...
(1870,) (1870,) (1870, 320) (1870, 320, 1) (1870, 320, 1) (1870, 320, 1) (0,)
Part 2...
(1870, 320, 1)
Part 3...
1647
Part 4...
75
End  156_6 ---------------------------------
Start  156_7 ---------------------------------
Part 1...
(616,) (616,) (616, 320) (616, 320, 1) (616, 320, 1) (616, 320, 1) (0,)
Part 2...
(616, 320, 1)
Part 3...
1419
Part 4...
121
End  156_7 ---------------------------------
Start  156_8 ---------------------------------
Part 1...
(946,) (946,) (946, 320) (946, 320, 1) (946, 320, 1) (946, 320, 1) (0,)
Part 2...
(946, 320, 1)
Part 3...
1305
Part 4...
83
End  156_8 ---------------------------------
Start  156_9 ---------------------------------
Part 1...
(979,) (979,) (979, 320) (979, 320, 1) (979, 320, 1) (979, 320, 1) (0,)
Part 2...
(979, 320, 1)
Part 3...
1768
Part 4...
206
End  156_9 ---------------------------------
Start  157_10 ---------------------------------
Part 1...
(330,) (330,) (330, 320) (330, 320, 1) (330, 320, 1) (330, 320, 1) (0,)
Part 2...
(330, 320, 1)
Part 3...
659
Part 4...
89
End  157_10 ---------------------------------
Start  157_14 ---------------------------------
Part 1...
(924,) (924,) (924, 320) (924, 320, 1) (924, 320, 1) (924, 320, 1) (0,)
Part 2...
(924, 320, 1)
Part 3...
1564
Part 4...
233
End  157_14 ---------------------------------
Start  157_15 ---------------------------------
Part 1...
(1287,) (1287,) (1287, 320) (1287, 320, 1) (1287, 320, 1) (1287, 320, 1) (0,)
Part 2...
(1287, 320, 1)
Part 3...
1234
Part 4...
232
End  157_15 ---------------------------------
Start  157_16 ---------------------------------
Part 1...
(440,) (440,) (440, 320) (440, 320, 1) (440, 320, 1) (440, 320, 1) (0,)
Part 2...
(440, 320, 1)
Part 3...
207
Part 4...
24
End  157_16 ---------------------------------
Start  157_17 ---------------------------------
Part 1...
(1199,) (1199,) (1199, 320) (1199, 320, 1) (1199, 320, 1) (1199, 320, 1) (0,)
Part 2...
(1199, 320, 1)
Part 3...
1881
Part 4...
216
End  157_17 ---------------------------------
Start  157_18 ---------------------------------
Part 1...
(1067,) (1067,) (1067, 320) (1067, 320, 1) (1067, 320, 1) (1067, 320, 1) (0,)
Part 2...
(1067, 320, 1)
Part 3...
1500
Part 4...
143
End  157_18 ---------------------------------
Start  157_2 ---------------------------------
Part 1...
(1606,) (1606,) (1606, 320) (1606, 320, 1) (1606, 320, 1) (1606, 320, 1) (0,)
Part 2...
(1606, 320, 1)
Part 3...
1571
Part 4...
152
End  157_2 ---------------------------------
Start  157_20 ---------------------------------
Part 1...
(946,) (946,) (946, 320) (946, 320, 1) (946, 320, 1) (946, 320, 1) (0,)
Part 2...
(946, 320, 1)
Part 3...
2076
Part 4...
169
End  157_20 ---------------------------------
Start  157_21 ---------------------------------
Part 1...
(1659,) (1659,) (1659, 320) (1659, 320, 1) (1659, 320, 1) (1659, 320, 1) (0,)
Part 2...
(1659, 320, 1)
Part 3...
1036
Part 4...
132
End  157_21 ---------------------------------
Start  157_3 ---------------------------------
Part 1...
(1936,) (1936,) (1936, 320) (1936, 320, 1) (1936, 320, 1) (1936, 320, 1) (0,)
Part 2...
(1936, 320, 1)
Part 3...
2315
Part 4...
173
End  157_3 ---------------------------------
Start  157_4 ---------------------------------
Part 1...
(1177,) (1177,) (1177, 320) (1177, 320, 1) (1177, 320, 1) (1177, 320, 1) (0,)
Part 2...
(1177, 320, 1)
Part 3...
1817
Part 4...
173
End  157_4 ---------------------------------
Start  157_5 ---------------------------------
Part 1...
(1100,) (1100,) (1100, 320) (1100, 320, 1) (1100, 320, 1) (1100, 320, 1) (0,)
Part 2...
(1100, 320, 1)
Part 3...
1511
Part 4...
151
End  157_5 ---------------------------------
Start  157_8 ---------------------------------
Part 1...
(220,) (220,) (220, 320) (220, 320, 1) (220, 320, 1) (220, 320, 1) (0,)
Part 2...
(220, 320, 1)
Part 3...
580
Part 4...
68
End  157_8 ---------------------------------
Start  157_9 ---------------------------------
Part 1...
(528,) (528,) (528, 320) (528, 320, 1) (528, 320, 1) (528, 320, 1) (0,)
Part 2...
(528, 320, 1)
Part 3...
910
Part 4...
139
End  157_9 ---------------------------------
Start  158_1 ---------------------------------
Part 1...
(1342,) (1342,) (1342, 320) (1342, 320, 1) (1342, 320, 1) (1342, 320, 1) (0,)
Part 2...
(1342, 320, 1)
Part 3...
637
Part 4...
60
End  158_1 ---------------------------------
Start  158_10 ---------------------------------
Part 1...
(858,) (858,) (858, 320) (858, 320, 1) (858, 320, 1) (858, 320, 1) (0,)
Part 2...
(858, 320, 1)
Part 3...
838
Part 4...
147
End  158_10 ---------------------------------
Start  158_12 ---------------------------------
Part 1...
(374,) (374,) (374, 320) (374, 320, 1) (374, 320, 1) (374, 320, 1) (0,)
Part 2...
(374, 320, 1)
Part 3...
537
Part 4...
62
End  158_12 ---------------------------------
Start  158_17 ---------------------------------
Part 1...
(1087,) (1087,) (1087, 320) (1087, 320, 1) (1087, 320, 1) (1087, 320, 1) (0,)
Part 2...
(1087, 320, 1)
Part 3...
1805
Part 4...
146
End  158_17 ---------------------------------
Start  158_18 ---------------------------------
Part 1...
(2145,) (2145,) (2145, 320) (2145, 320, 1) (2145, 320, 1) (2145, 320, 1) (0,)
Part 2...
(2145, 320, 1)
Part 3...
3412
Part 4...
239
End  158_18 ---------------------------------
Start  158_19 ---------------------------------
Part 1...
(473,) (473,) (473, 320) (473, 320, 1) (473, 320, 1) (473, 320, 1) (0,)
Part 2...
(473, 320, 1)
Part 3...
958
Part 4...
170
End  158_19 ---------------------------------
Start  158_20 ---------------------------------
Part 1...
(2431,) (2431,) (2431, 320) (2431, 320, 1) (2431, 320, 1) (2431, 320, 1) (0,)
Part 2...
(2431, 320, 1)
Part 3...
3532
Part 4...
236
End  158_20 ---------------------------------
Start  158_3 ---------------------------------
Part 1...
(1661,) (1661,) (1661, 320) (1661, 320, 1) (1661, 320, 1) (1661, 320, 1) (0,)
Part 2...
(1661, 320, 1)
Part 3...
2517
Part 4...
242
End  158_3 ---------------------------------
Start  158_9 ---------------------------------
Part 1...
(1397,) (1397,) (1397, 320) (1397, 320, 1) (1397, 320, 1) (1397, 320, 1) (0,)
Part 2...
(1397, 320, 1)
Part 3...
1662
Part 4...
148
End  158_9 ---------------------------------
CPU times: user 35min 4s, sys: 54.6 s, total: 35min 59s
Wall time: 35min 43s
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">len</span><span class="p">(</span><span class="n">test_ann_file_list_dict</span><span class="p">),</span> <span class="nb">len</span><span class="p">(</span><span class="n">pre_final_dict</span><span class="p">)</span>
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<pre>(54, 54)</pre>
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<pre>&#39;s2_01_final_v4_1&#39;</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">MODEL_NAME</span> <span class="o">=</span> <span class="s1">&#39;s2_01_final_v4_b&#39;</span>
<span class="n">MODEL_NAME</span>
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<pre>&#39;s2_01_final_v4_b&#39;</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">for</span> <span class="n">file_k</span> <span class="ow">in</span> <span class="n">pre_final_dict</span><span class="p">:</span>
    <span class="n">_ann_result</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">test_ann_file_list_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">file_k</span><span class="p">),</span> <span class="n">sep</span><span class="o">=</span><span class="s1">&#39;</span><span class="se">\t</span><span class="s1">&#39;</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;id&#39;</span><span class="p">,</span> <span class="s1">&#39;p1&#39;</span><span class="p">,</span> <span class="s1">&#39;p2&#39;</span><span class="p">])</span>
    
    <span class="n">_ann_pre_final</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">pre_final_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">file_k</span><span class="p">))</span>
    <span class="n">_ann_pre_final_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;id&#39;</span><span class="p">,</span> <span class="s1">&#39;p1&#39;</span><span class="p">,</span> <span class="s1">&#39;p2&#39;</span><span class="p">])</span>
    <span class="n">_ann_pre_final_df</span><span class="p">[</span><span class="s1">&#39;id&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">_ann_pre_final</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span>
    <span class="n">_ann_pre_final_df</span><span class="p">[</span><span class="s1">&#39;p1&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">_ann_pre_final</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">]</span>
    
    <span class="n">_final_df</span> <span class="o">=</span> <span class="n">_ann_result</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_ann_pre_final_df</span><span class="p">,</span> <span class="n">ignore_index</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    
<span class="c1">#     _final_df.to_csv(&#39;./Demo/result/&#39; + MODEL_NAME + &#39;/&#39; + str(file_k) + &#39;.ann&#39;, index=False, header=None, sep=&#39;\t&#39;)</span>
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</div>{'Amount_Drug',
 'Anatomy_Disease',
 'Drug_Disease',
 'Duration_Drug',
 'Frequency_Drug',
 'Method_Drug',
 'SideEff-Drug',
 'Symptom_Disease',
 'Test_Disease',
 'Treatment_Disease'}最后将SideEff_Drug改为SideEff-Drug并保存
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">for</span> <span class="n">file_k</span> <span class="ow">in</span> <span class="n">pre_final_dict</span><span class="p">:</span>
    <span class="n">_ann_result</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">test_ann_file_list_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">file_k</span><span class="p">),</span> <span class="n">sep</span><span class="o">=</span><span class="s1">&#39;</span><span class="se">\t</span><span class="s1">&#39;</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;id&#39;</span><span class="p">,</span> <span class="s1">&#39;p1&#39;</span><span class="p">,</span> <span class="s1">&#39;p2&#39;</span><span class="p">])</span>
    
    <span class="n">_ann_pre_final</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">pre_final_dict</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">file_k</span><span class="p">))</span>
    <span class="n">_ann_pre_final_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;id&#39;</span><span class="p">,</span> <span class="s1">&#39;p1&#39;</span><span class="p">,</span> <span class="s1">&#39;p2&#39;</span><span class="p">])</span>
    <span class="n">_ann_pre_final_df</span><span class="p">[</span><span class="s1">&#39;id&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">_ann_pre_final</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span>
    <span class="n">_ann_pre_final_df</span><span class="p">[</span><span class="s1">&#39;p1&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">_ann_pre_final</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">]</span>
    <span class="n">_ann_pre_final_df</span><span class="p">[</span><span class="s1">&#39;p1&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">_ann_pre_final_df</span><span class="p">[</span><span class="s1">&#39;p1&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">&#39;SideEff_Drug&#39;</span><span class="p">,</span> <span class="s1">&#39;SideEff-Drug&#39;</span><span class="p">)</span>
    
    <span class="n">_final_df</span> <span class="o">=</span> <span class="n">_ann_result</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_ann_pre_final_df</span><span class="p">,</span> <span class="n">ignore_index</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    
    <span class="n">_final_df</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="s1">&#39;./Demo/result/&#39;</span> <span class="o">+</span> <span class="n">MODEL_NAME</span> <span class="o">+</span> <span class="s1">&#39;_raw/&#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">file_k</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;.ann&#39;</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">sep</span><span class="o">=</span><span class="s1">&#39;</span><span class="se">\t</span><span class="s1">&#39;</span><span class="p">)</span>
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</div>验证预测的结果合理性
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">pre_len_list_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">train_anno_dict</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    <span class="n">pre_len_list_dict</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">v</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">pre_len_list_dict</span><span class="o">.</span><span class="n">values</span><span class="p">())),</span> <span class="n">np</span><span class="o">.</span><span class="n">min</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">pre_len_list_dict</span><span class="o">.</span><span class="n">values</span><span class="p">())),</span> <span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">pre_len_list_dict</span><span class="o">.</span><span class="n">values</span><span class="p">()))</span>
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<pre>(376.14397905759165, 22, 1140)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">pre_len_list_dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">pre_final_dict</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    <span class="n">pre_len_list_dict</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">v</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">pre_len_list_dict</span><span class="o">.</span><span class="n">values</span><span class="p">())),</span> <span class="n">np</span><span class="o">.</span><span class="n">min</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">pre_len_list_dict</span><span class="o">.</span><span class="n">values</span><span class="p">())),</span> <span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">pre_len_list_dict</span><span class="o">.</span><span class="n">values</span><span class="p">()))</span>
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<pre>(165.40740740740742, 24, 405)</pre>
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</div>(165.40740740740742, 24, 405)

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">temp_k</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">pre_len_list_dict</span><span class="o">.</span><span class="n">items</span><span class="p">(),</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">])[:</span><span class="mi">5</span><span class="p">]</span>
<span class="n">temp_k</span>
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<pre>[(&#39;157_16&#39;, 24), (&#39;155_11&#39;, 32), (&#39;156_12&#39;, 42), (&#39;158_1&#39;, 60), (&#39;155_10&#39;, 62)]</pre>
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<pre>10739</pre>
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<pre>395</pre>
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<pre>[[&#39;R1&#39;, &#39;Anatomy_Disease Arg1:T346 Arg2:T78&#39;],
 [&#39;R2&#39;, &#39;Anatomy_Disease Arg1:T366 Arg2:T78&#39;],
 [&#39;R3&#39;, &#39;Anatomy_Disease Arg1:T367 Arg2:T78&#39;],
 [&#39;R4&#39;, &#39;Anatomy_Disease Arg1:T346 Arg2:T347&#39;],
 [&#39;R5&#39;, &#39;Drug_Disease Arg1:T79 Arg2:T81&#39;],
 [&#39;R6&#39;, &#39;Drug_Disease Arg1:T80 Arg2:T81&#39;],
 [&#39;R7&#39;, &#39;Test_Disease Arg1:T288 Arg2:T81&#39;],
 [&#39;R8&#39;, &#39;Test_Disease Arg1:T289 Arg2:T81&#39;],
 [&#39;R9&#39;, &#39;Drug_Disease Arg1:T290 Arg2:T81&#39;],
 [&#39;R10&#39;, &#39;Anatomy_Disease Arg1:T154 Arg2:T89&#39;]]</pre>
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<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>id</th>
      <th>label</th>
      <th>idx_0</th>
      <th>idx_1</th>
      <th>text</th>
    </tr>
  </thead>
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    <tr>
      <th>24</th>
      <td>T25</td>
      <td>Anatomy</td>
      <td>7645</td>
      <td>7649</td>
      <td>成骨细胞</td>
    </tr>
    <tr>
      <th>251</th>
      <td>T252</td>
      <td>Anatomy</td>
      <td>10379</td>
      <td>10382</td>
      <td>TAZ</td>
    </tr>
  </tbody>
</table>
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<pre>sphatase activity
(ALP) and calcium deposition. The mRNA expression of bone sialoprotein ( BSP) and osteo
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