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language-translation-rnn
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language-translation-rnn/dlnd_language_translation.html

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<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />
<title>dlnd_language_translation</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script>
<style type="text/css">
/*!
*
* Twitter Bootstrap
*
*/
/*!
* Bootstrap v3.3.7 (http://getbootstrap.com)
* Copyright 2011-2016 Twitter, Inc.
* Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
*/
/*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */
html {
font-family: sans-serif;
-ms-text-size-adjust: 100%;
-webkit-text-size-adjust: 100%;
}
body {
margin: 0;
}
article,
aside,
details,
figcaption,
figure,
footer,
header,
hgroup,
main,
menu,
nav,
section,
summary {
display: block;
}
audio,
canvas,
progress,
video {
display: inline-block;
vertical-align: baseline;
}
audio:not([controls]) {
display: none;
height: 0;
}
[hidden],
template {
display: none;
}
a {
background-color: transparent;
}
a:active,
a:hover {
outline: 0;
}
abbr[title] {
border-bottom: 1px dotted;
}
b,
strong {
font-weight: bold;
}
dfn {
font-style: italic;
}
h1 {
font-size: 2em;
margin: 0.67em 0;
}
mark {
background: #ff0;
color: #000;
}
small {
font-size: 80%;
}
sub,
sup {
font-size: 75%;
line-height: 0;
position: relative;
vertical-align: baseline;
}
sup {
top: -0.5em;
}
sub {
bottom: -0.25em;
}
img {
border: 0;
}
svg:not(:root) {
overflow: hidden;
}
figure {
margin: 1em 40px;
}
hr {
box-sizing: content-box;
height: 0;
}
pre {
overflow: auto;
}
code,
kbd,
pre,
samp {
font-family: monospace, monospace;
font-size: 1em;
}
button,
input,
optgroup,
select,
textarea {
color: inherit;
font: inherit;
margin: 0;
}
button {
overflow: visible;
}
button,
select {
text-transform: none;
}
button,
html input[type="button"],
input[type="reset"],
input[type="submit"] {
-webkit-appearance: button;
cursor: pointer;
}
button[disabled],
html input[disabled] {
cursor: default;
}
button::-moz-focus-inner,
input::-moz-focus-inner {
border: 0;
padding: 0;
}
input {
line-height: normal;
}
input[type="checkbox"],
input[type="radio"] {
box-sizing: border-box;
padding: 0;
}
input[type="number"]::-webkit-inner-spin-button,
input[type="number"]::-webkit-outer-spin-button {
height: auto;
}
input[type="search"] {
-webkit-appearance: textfield;
box-sizing: content-box;
}
input[type="search"]::-webkit-search-cancel-button,
input[type="search"]::-webkit-search-decoration {
-webkit-appearance: none;
}
fieldset {
border: 1px solid #c0c0c0;
margin: 0 2px;
padding: 0.35em 0.625em 0.75em;
}
legend {
border: 0;
padding: 0;
}
textarea {
overflow: auto;
}
optgroup {
font-weight: bold;
}
table {
border-collapse: collapse;
border-spacing: 0;
}
td,
th {
padding: 0;
}
/*! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css */
@media print {
*,
*:before,
*:after {
background: transparent !important;
color: #000 !important;
box-shadow: none !important;
text-shadow: none !important;
}
a,
a:visited {
text-decoration: underline;
}
a[href]:after {
content: " (" attr(href) ")";
}
abbr[title]:after {
content: " (" attr(title) ")";
}
a[href^="#"]:after,
a[href^="javascript:"]:after {
content: "";
}
pre,
blockquote {
border: 1px solid #999;
page-break-inside: avoid;
}
thead {
display: table-header-group;
}
tr,
img {
page-break-inside: avoid;
}
img {
max-width: 100% !important;
}
p,
h2,
h3 {
orphans: 3;
widows: 3;
}
h2,
h3 {
page-break-after: avoid;
}
.navbar {
display: none;
}
.btn > .caret,
.dropup > .btn > .caret {
border-top-color: #000 !important;
}
.label {
border: 1px solid #000;
}
.table {
border-collapse: collapse !important;
}
.table td,
.table th {
background-color: #fff !important;
}
.table-bordered th,
.table-bordered td {
border: 1px solid #ddd !important;
}
}
@font-face {
font-family: 'Glyphicons Halflings';
src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot');
src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot?#iefix') format('embedded-opentype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff2') format('woff2'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff') format('woff'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.ttf') format('truetype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.svg#glyphicons_halflingsregular') format('svg');
}
.glyphicon {
position: relative;
top: 1px;
display: inline-block;
font-family: 'Glyphicons Halflings';
font-style: normal;
font-weight: normal;
line-height: 1;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
}
.glyphicon-asterisk:before {
content: "\002a";
}
.glyphicon-plus:before {
content: "\002b";
}
.glyphicon-euro:before,
.glyphicon-eur:before {
content: "\20ac";
}
.glyphicon-minus:before {
content: "\2212";
}
.glyphicon-cloud:before {
content: "\2601";
}
.glyphicon-envelope:before {
content: "\2709";
}
.glyphicon-pencil:before {
content: "\270f";
}
.glyphicon-glass:before {
content: "\e001";
}
.glyphicon-music:before {
content: "\e002";
}
.glyphicon-search:before {
content: "\e003";
}
.glyphicon-heart:before {
content: "\e005";
}
.glyphicon-star:before {
content: "\e006";
}
.glyphicon-star-empty:before {
content: "\e007";
}
.glyphicon-user:before {
content: "\e008";
}
.glyphicon-film:before {
content: "\e009";
}
.glyphicon-th-large:before {
content: "\e010";
}
.glyphicon-th:before {
content: "\e011";
}
.glyphicon-th-list:before {
content: "\e012";
}
.glyphicon-ok:before {
content: "\e013";
}
.glyphicon-remove:before {
content: "\e014";
}
.glyphicon-zoom-in:before {
content: "\e015";
}
.glyphicon-zoom-out:before {
content: "\e016";
}
.glyphicon-off:before {
content: "\e017";
}
.glyphicon-signal:before {
content: "\e018";
}
.glyphicon-cog:before {
content: "\e019";
}
.glyphicon-trash:before {
content: "\e020";
}
.glyphicon-home:before {
content: "\e021";
}
.glyphicon-file:before {
content: "\e022";
}
.glyphicon-time:before {
content: "\e023";
}
.glyphicon-road:before {
content: "\e024";
}
.glyphicon-download-alt:before {
content: "\e025";
}
.glyphicon-download:before {
content: "\e026";
}
.glyphicon-upload:before {
content: "\e027";
}
.glyphicon-inbox:before {
content: "\e028";
}
.glyphicon-play-circle:before {
content: "\e029";
}
.glyphicon-repeat:before {
content: "\e030";
}
.glyphicon-refresh:before {
content: "\e031";
}
.glyphicon-list-alt:before {
content: "\e032";
}
.glyphicon-lock:before {
content: "\e033";
}
.glyphicon-flag:before {
content: "\e034";
}
.glyphicon-headphones:before {
content: "\e035";
}
.glyphicon-volume-off:before {
content: "\e036";
}
.glyphicon-volume-down:before {
content: "\e037";
}
.glyphicon-volume-up:before {
content: "\e038";
}
.glyphicon-qrcode:before {
content: "\e039";
}
.glyphicon-barcode:before {
content: "\e040";
}
.glyphicon-tag:before {
content: "\e041";
}
.glyphicon-tags:before {
content: "\e042";
}
.glyphicon-book:before {
content: "\e043";
}
.glyphicon-bookmark:before {
content: "\e044";
}
.glyphicon-print:before {
content: "\e045";
}
.glyphicon-camera:before {
content: "\e046";
}
.glyphicon-font:before {
content: "\e047";
}
.glyphicon-bold:before {
content: "\e048";
}
.glyphicon-italic:before {
content: "\e049";
}
.glyphicon-text-height:before {
content: "\e050";
}
.glyphicon-text-width:before {
content: "\e051";
}
.glyphicon-align-left:before {
content: "\e052";
}
.glyphicon-align-center:before {
content: "\e053";
}
.glyphicon-align-right:before {
content: "\e054";
}
.glyphicon-align-justify:before {
content: "\e055";
}
.glyphicon-list:before {
content: "\e056";
}
.glyphicon-indent-left:before {
content: "\e057";
}
.glyphicon-indent-right:before {
content: "\e058";
}
.glyphicon-facetime-video:before {
content: "\e059";
}
.glyphicon-picture:before {
content: "\e060";
}
.glyphicon-map-marker:before {
content: "\e062";
}
.glyphicon-adjust:before {
content: "\e063";
}
.glyphicon-tint:before {
content: "\e064";
}
.glyphicon-edit:before {
content: "\e065";
}
.glyphicon-share:before {
content: "\e066";
}
.glyphicon-check:before {
content: "\e067";
}
.glyphicon-move:before {
content: "\e068";
}
.glyphicon-step-backward:before {
content: "\e069";
}
.glyphicon-fast-backward:before {
content: "\e070";
}
.glyphicon-backward:before {
content: "\e071";
}
.glyphicon-play:before {
content: "\e072";
}
.glyphicon-pause:before {
content: "\e073";
}
.glyphicon-stop:before {
content: "\e074";
}
.glyphicon-forward:before {
content: "\e075";
}
.glyphicon-fast-forward:before {
content: "\e076";
}
.glyphicon-step-forward:before {
content: "\e077";
}
.glyphicon-eject:before {
content: "\e078";
}
.glyphicon-chevron-left:before {
content: "\e079";
}
.glyphicon-chevron-right:before {
content: "\e080";
}
.glyphicon-plus-sign:before {
content: "\e081";
}
.glyphicon-minus-sign:before {
content: "\e082";
}
.glyphicon-remove-sign:before {
content: "\e083";
}
.glyphicon-ok-sign:before {
content: "\e084";
}
.glyphicon-question-sign:before {
content: "\e085";
}
.glyphicon-info-sign:before {
content: "\e086";
}
.glyphicon-screenshot:before {
content: "\e087";
}
.glyphicon-remove-circle:before {
content: "\e088";
}
.glyphicon-ok-circle:before {
content: "\e089";
}
.glyphicon-ban-circle:before {
content: "\e090";
}
.glyphicon-arrow-left:before {
content: "\e091";
}
.glyphicon-arrow-right:before {
content: "\e092";
}
.glyphicon-arrow-up:before {
content: "\e093";
}
.glyphicon-arrow-down:before {
content: "\e094";
}
.glyphicon-share-alt:before {
content: "\e095";
}
.glyphicon-resize-full:before {
content: "\e096";
}
.glyphicon-resize-small:before {
content: "\e097";
}
.glyphicon-exclamation-sign:before {
content: "\e101";
}
.glyphicon-gift:before {
content: "\e102";
}
.glyphicon-leaf:before {
content: "\e103";
}
.glyphicon-fire:before {
content: "\e104";
}
.glyphicon-eye-open:before {
content: "\e105";
}
.glyphicon-eye-close:before {
content: "\e106";
}
.glyphicon-warning-sign:before {
content: "\e107";
}
.glyphicon-plane:before {
content: "\e108";
}
.glyphicon-calendar:before {
content: "\e109";
}
.glyphicon-random:before {
content: "\e110";
}
.glyphicon-comment:before {
content: "\e111";
}
.glyphicon-magnet:before {
content: "\e112";
}
.glyphicon-chevron-up:before {
content: "\e113";
}
.glyphicon-chevron-down:before {
content: "\e114";
}
.glyphicon-retweet:before {
content: "\e115";
}
.glyphicon-shopping-cart:before {
content: "\e116";
}
.glyphicon-folder-close:before {
content: "\e117";
}
.glyphicon-folder-open:before {
content: "\e118";
}
.glyphicon-resize-vertical:before {
content: "\e119";
}
.glyphicon-resize-horizontal:before {
content: "\e120";
}
.glyphicon-hdd:before {
content: "\e121";
}
.glyphicon-bullhorn:before {
content: "\e122";
}
.glyphicon-bell:before {
content: "\e123";
}
.glyphicon-certificate:before {
content: "\e124";
}
.glyphicon-thumbs-up:before {
content: "\e125";
}
.glyphicon-thumbs-down:before {
content: "\e126";
}
.glyphicon-hand-right:before {
content: "\e127";
}
.glyphicon-hand-left:before {
content: "\e128";
}
.glyphicon-hand-up:before {
content: "\e129";
}
.glyphicon-hand-down:before {
content: "\e130";
}
.glyphicon-circle-arrow-right:before {
content: "\e131";
}
.glyphicon-circle-arrow-left:before {
content: "\e132";
}
.glyphicon-circle-arrow-up:before {
content: "\e133";
}
.glyphicon-circle-arrow-down:before {
content: "\e134";
}
.glyphicon-globe:before {
content: "\e135";
}
.glyphicon-wrench:before {
content: "\e136";
}
.glyphicon-tasks:before {
content: "\e137";
}
.glyphicon-filter:before {
content: "\e138";
}
.glyphicon-briefcase:before {
content: "\e139";
}
.glyphicon-fullscreen:before {
content: "\e140";
}
.glyphicon-dashboard:before {
content: "\e141";
}
.glyphicon-paperclip:before {
content: "\e142";
}
.glyphicon-heart-empty:before {
content: "\e143";
}
.glyphicon-link:before {
content: "\e144";
}
.glyphicon-phone:before {
content: "\e145";
}
.glyphicon-pushpin:before {
content: "\e146";
}
.glyphicon-usd:before {
content: "\e148";
}
.glyphicon-gbp:before {
content: "\e149";
}
.glyphicon-sort:before {
content: "\e150";
}
.glyphicon-sort-by-alphabet:before {
content: "\e151";
}
.glyphicon-sort-by-alphabet-alt:before {
content: "\e152";
}
.glyphicon-sort-by-order:before {
content: "\e153";
}
.glyphicon-sort-by-order-alt:before {
content: "\e154";
}
.glyphicon-sort-by-attributes:before {
content: "\e155";
}
.glyphicon-sort-by-attributes-alt:before {
content: "\e156";
}
.glyphicon-unchecked:before {
content: "\e157";
}
.glyphicon-expand:before {
content: "\e158";
}
.glyphicon-collapse-down:before {
content: "\e159";
}
.glyphicon-collapse-up:before {
content: "\e160";
}
.glyphicon-log-in:before {
content: "\e161";
}
.glyphicon-flash:before {
content: "\e162";
}
.glyphicon-log-out:before {
content: "\e163";
}
.glyphicon-new-window:before {
content: "\e164";
}
.glyphicon-record:before {
content: "\e165";
}
.glyphicon-save:before {
content: "\e166";
}
.glyphicon-open:before {
content: "\e167";
}
.glyphicon-saved:before {
content: "\e168";
}
.glyphicon-import:before {
content: "\e169";
}
.glyphicon-export:before {
content: "\e170";
}
.glyphicon-send:before {
content: "\e171";
}
.glyphicon-floppy-disk:before {
content: "\e172";
}
.glyphicon-floppy-saved:before {
content: "\e173";
}
.glyphicon-floppy-remove:before {
content: "\e174";
}
.glyphicon-floppy-save:before {
content: "\e175";
}
.glyphicon-floppy-open:before {
content: "\e176";
}
.glyphicon-credit-card:before {
content: "\e177";
}
.glyphicon-transfer:before {
content: "\e178";
}
.glyphicon-cutlery:before {
content: "\e179";
}
.glyphicon-header:before {
content: "\e180";
}
.glyphicon-compressed:before {
content: "\e181";
}
.glyphicon-earphone:before {
content: "\e182";
}
.glyphicon-phone-alt:before {
content: "\e183";
}
.glyphicon-tower:before {
content: "\e184";
}
.glyphicon-stats:before {
content: "\e185";
}
.glyphicon-sd-video:before {
content: "\e186";
}
.glyphicon-hd-video:before {
content: "\e187";
}
.glyphicon-subtitles:before {
content: "\e188";
}
.glyphicon-sound-stereo:before {
content: "\e189";
}
.glyphicon-sound-dolby:before {
content: "\e190";
}
.glyphicon-sound-5-1:before {
content: "\e191";
}
.glyphicon-sound-6-1:before {
content: "\e192";
}
.glyphicon-sound-7-1:before {
content: "\e193";
}
.glyphicon-copyright-mark:before {
content: "\e194";
}
.glyphicon-registration-mark:before {
content: "\e195";
}
.glyphicon-cloud-download:before {
content: "\e197";
}
.glyphicon-cloud-upload:before {
content: "\e198";
}
.glyphicon-tree-conifer:before {
content: "\e199";
}
.glyphicon-tree-deciduous:before {
content: "\e200";
}
.glyphicon-cd:before {
content: "\e201";
}
.glyphicon-save-file:before {
content: "\e202";
}
.glyphicon-open-file:before {
content: "\e203";
}
.glyphicon-level-up:before {
content: "\e204";
}
.glyphicon-copy:before {
content: "\e205";
}
.glyphicon-paste:before {
content: "\e206";
}
.glyphicon-alert:before {
content: "\e209";
}
.glyphicon-equalizer:before {
content: "\e210";
}
.glyphicon-king:before {
content: "\e211";
}
.glyphicon-queen:before {
content: "\e212";
}
.glyphicon-pawn:before {
content: "\e213";
}
.glyphicon-bishop:before {
content: "\e214";
}
.glyphicon-knight:before {
content: "\e215";
}
.glyphicon-baby-formula:before {
content: "\e216";
}
.glyphicon-tent:before {
content: "\26fa";
}
.glyphicon-blackboard:before {
content: "\e218";
}
.glyphicon-bed:before {
content: "\e219";
}
.glyphicon-apple:before {
content: "\f8ff";
}
.glyphicon-erase:before {
content: "\e221";
}
.glyphicon-hourglass:before {
content: "\231b";
}
.glyphicon-lamp:before {
content: "\e223";
}
.glyphicon-duplicate:before {
content: "\e224";
}
.glyphicon-piggy-bank:before {
content: "\e225";
}
.glyphicon-scissors:before {
content: "\e226";
}
.glyphicon-bitcoin:before {
content: "\e227";
}
.glyphicon-btc:before {
content: "\e227";
}
.glyphicon-xbt:before {
content: "\e227";
}
.glyphicon-yen:before {
content: "\00a5";
}
.glyphicon-jpy:before {
content: "\00a5";
}
.glyphicon-ruble:before {
content: "\20bd";
}
.glyphicon-rub:before {
content: "\20bd";
}
.glyphicon-scale:before {
content: "\e230";
}
.glyphicon-ice-lolly:before {
content: "\e231";
}
.glyphicon-ice-lolly-tasted:before {
content: "\e232";
}
.glyphicon-education:before {
content: "\e233";
}
.glyphicon-option-horizontal:before {
content: "\e234";
}
.glyphicon-option-vertical:before {
content: "\e235";
}
.glyphicon-menu-hamburger:before {
content: "\e236";
}
.glyphicon-modal-window:before {
content: "\e237";
}
.glyphicon-oil:before {
content: "\e238";
}
.glyphicon-grain:before {
content: "\e239";
}
.glyphicon-sunglasses:before {
content: "\e240";
}
.glyphicon-text-size:before {
content: "\e241";
}
.glyphicon-text-color:before {
content: "\e242";
}
.glyphicon-text-background:before {
content: "\e243";
}
.glyphicon-object-align-top:before {
content: "\e244";
}
.glyphicon-object-align-bottom:before {
content: "\e245";
}
.glyphicon-object-align-horizontal:before {
content: "\e246";
}
.glyphicon-object-align-left:before {
content: "\e247";
}
.glyphicon-object-align-vertical:before {
content: "\e248";
}
.glyphicon-object-align-right:before {
content: "\e249";
}
.glyphicon-triangle-right:before {
content: "\e250";
}
.glyphicon-triangle-left:before {
content: "\e251";
}
.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 4.2.0 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=4.2.0');
src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#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;
}
.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;
}
@-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 {
filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
-webkit-transform: rotate(90deg);
-ms-transform: rotate(90deg);
transform: rotate(90deg);
}
.fa-rotate-180 {
filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
-webkit-transform: rotate(180deg);
-ms-transform: rotate(180deg);
transform: rotate(180deg);
}
.fa-rotate-270 {
filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
-webkit-transform: rotate(270deg);
-ms-transform: rotate(270deg);
transform: rotate(270deg);
}
.fa-flip-horizontal {
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 {
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:before {
content: "\f09a";
}
.fa-github:before {
content: "\f09b";
}
.fa-unlock:before {
content: "\f09c";
}
.fa-credit-card:before {
content: "\f09d";
}
.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 {
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: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-rebel:before {
content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
content: "\f1d1";
}
.fa-git-square:before {
content: "\f1d2";
}
.fa-git:before {
content: "\f1d3";
}
.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";
}
/*!
*
* 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;
}
/**
* 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 {
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;
}
@media (max-width: 991px) {
#ipython_notebook {
margin-left: 10px;
}
}
[dir="rtl"] #ipython_notebook {
float: right !important;
}
#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#login_widget {
float: right;
}
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;
}
@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;
}
/*!
*
* 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 {
text-align: center;
vertical-align: middle;
display: inline;
opacity: 0;
z-index: 2;
width: 12ex;
margin-right: -12ex;
}
.alternate_upload .btn-upload {
height: 22px;
}
/**
* Primary styles
*
* Author: Jupyter Development Team
*/
[dir="rtl"] #tabs li {
float: right;
}
ul#tabs {
margin-bottom: 4px;
}
[dir="rtl"] ul#tabs {
margin-right: 0px;
}
ul#tabs a {
padding-top: 6px;
padding-bottom: 4px;
}
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 {
float: left !important;
}
[dir="rtl"] .list_toolbar .pull-right {
padding-top: 1px;
float: left !important;
}
[dir="rtl"] .list_toolbar .pull-left {
float: right !important;
}
.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: baseline;
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;
}
.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_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;
}
.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;
}
#tree-selector {
padding-right: 0px;
}
[dir="rtl"] #tree-selector a {
float: right;
}
#button-select-all {
min-width: 50px;
}
#select-all {
margin-left: 7px;
margin-right: 2px;
}
.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.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.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.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.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;
}
[dir="rtl"] #new-menu {
text-align: right;
}
.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;
}
[dir="rtl"] #running .col-sm-8 {
float: right !important;
}
.delete-button {
display: none;
}
.duplicate-button {
display: none;
}
.rename-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.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.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.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.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);
}
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI colors. */
.ansibold {
font-weight: bold;
}
/* 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;
border-left-width: 1px;
padding-left: 5px;
background: linear-gradient(to right, transparent -40px, transparent 1px, transparent 1px, transparent 100%);
}
div.cell.jupyter-soft-selected {
border-left-color: #90CAF9;
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 {
border-color: #ababab;
border-left-width: 0px;
padding-left: 6px;
background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 5px, transparent 5px, transparent 100%);
}
@media print {
div.cell.selected {
border-color: transparent;
}
}
div.cell.selected.jupyter-soft-selected {
border-left-width: 0;
padding-left: 6px;
background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 7px, #E3F2FD 7px, #E3F2FD 100%);
}
.edit_mode div.cell.selected {
border-color: #66BB6A;
border-left-width: 0px;
padding-left: 6px;
background: linear-gradient(to right, #66BB6A -40px, #66BB6A 5px, transparent 5px, transparent 100%);
}
@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. */
padding: 0.4em;
}
.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. We need the 0 value because of how we size */
/* .CodeMirror-lines */
padding: 0;
border: 0;
border-radius: 0;
}
/*
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;
}
/* 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: 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 {
list-style: disc;
margin: 0em 2em;
padding-left: 0px;
}
.rendered_html ul ul {
list-style: square;
margin: 0em 2em;
}
.rendered_html ul ul ul {
list-style: circle;
margin: 0em 2em;
}
.rendered_html ol {
list-style: decimal;
margin: 0em 2em;
padding-left: 0px;
}
.rendered_html ol ol {
list-style: upper-alpha;
margin: 0em 2em;
}
.rendered_html ol ol ol {
list-style: lower-alpha;
margin: 0em 2em;
}
.rendered_html ol ol ol ol {
list-style: lower-roman;
margin: 0em 2em;
}
.rendered_html ol ol ol ol ol {
list-style: decimal;
margin: 0em 2em;
}
.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;
}
.rendered_html pre,
.rendered_html code {
border: 0;
background-color: #fff;
color: #000;
font-size: 100%;
padding: 0px;
}
.rendered_html blockquote {
margin: 1em 2em;
}
.rendered_html table {
margin-left: auto;
margin-right: auto;
border: 1px solid black;
border-collapse: collapse;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
border: 1px solid black;
border-collapse: collapse;
margin: 1em 2em;
}
.rendered_html td,
.rendered_html th {
text-align: left;
vertical-align: middle;
padding: 4px;
}
.rendered_html th {
font-weight: bold;
}
.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;
}
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.unrendered .text_cell_render {
display: none;
}
.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;
}
/* 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;
}
.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 {
float: right !important;
float: right;
}
#kernel_logo_widget .current_kernel_logo {
display: none;
margin-top: -1px;
margin-bottom: -1px;
width: 32px;
height: 32px;
}
#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;
}
.nav-wrapper {
border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
padding-top: 4px;
}
ul#help_menu li a {
overflow: hidden;
padding-right: 2.2em;
}
ul#help_menu li a i {
margin-right: -1.2em;
}
.dropdown-submenu {
position: relative;
}
.dropdown-submenu > .dropdown-menu {
top: 0;
left: 100%;
margin-top: -6px;
margin-left: -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.pull-left {
margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
margin-left: .3em;
}
.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;
}
.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;
}
#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;
}
#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;
}
#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.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.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.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.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.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.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,
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<h1 id="Language-Translation">Language Translation<a class="anchor-link" href="#Language-Translation">&#182;</a></h1><p>In this project, you’re going to take a peek into the realm of neural network machine translation. You’ll be training a sequence to sequence model on a dataset of English and French sentences that can translate new sentences from English to French.</p>
<h2 id="Get-the-Data">Get the Data<a class="anchor-link" href="#Get-the-Data">&#182;</a></h2><p>Since translating the whole language of English to French will take lots of time to train, we have provided you with a small portion of the English corpus.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">helper</span>
<span class="kn">import</span> <span class="nn">problem_unittests</span> <span class="k">as</span> <span class="nn">tests</span>
<span class="n">source_path</span> <span class="o">=</span> <span class="s1">&#39;/data/small_vocab_en&#39;</span>
<span class="n">target_path</span> <span class="o">=</span> <span class="s1">&#39;/data/small_vocab_fr&#39;</span>
<span class="n">source_text</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">load_data</span><span class="p">(</span><span class="n">source_path</span><span class="p">)</span>
<span class="n">target_text</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">load_data</span><span class="p">(</span><span class="n">target_path</span><span class="p">)</span>
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<h2 id="Explore-the-Data">Explore the Data<a class="anchor-link" href="#Explore-the-Data">&#182;</a></h2><p>Play around with view_sentence_range to view different parts of the data.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">view_sentence_range</span> <span class="o">=</span> <span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
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<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
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<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Dataset Stats&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Roughly the number of unique words: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">len</span><span class="p">({</span><span class="n">word</span><span class="p">:</span> <span class="kc">None</span> <span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">source_text</span><span class="o">.</span><span class="n">split</span><span class="p">()})))</span>
<span class="n">sentences</span> <span class="o">=</span> <span class="n">source_text</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)</span>
<span class="n">word_counts</span> <span class="o">=</span> <span class="p">[</span><span class="nb">len</span><span class="p">(</span><span class="n">sentence</span><span class="o">.</span><span class="n">split</span><span class="p">())</span> <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="n">sentences</span><span class="p">]</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Number of sentences: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">sentences</span><span class="p">)))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Average number of words in a sentence: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">average</span><span class="p">(</span><span class="n">word_counts</span><span class="p">)))</span>
<span class="nb">print</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;English sentences </span><span class="si">{}</span><span class="s1"> to </span><span class="si">{}</span><span class="s1">:&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="o">*</span><span class="n">view_sentence_range</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">source_text</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)[</span><span class="n">view_sentence_range</span><span class="p">[</span><span class="mi">0</span><span class="p">]:</span><span class="n">view_sentence_range</span><span class="p">[</span><span class="mi">1</span><span class="p">]]))</span>
<span class="nb">print</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;French sentences </span><span class="si">{}</span><span class="s1"> to </span><span class="si">{}</span><span class="s1">:&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="o">*</span><span class="n">view_sentence_range</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">target_text</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)[</span><span class="n">view_sentence_range</span><span class="p">[</span><span class="mi">0</span><span class="p">]:</span><span class="n">view_sentence_range</span><span class="p">[</span><span class="mi">1</span><span class="p">]]))</span>
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<pre>Dataset Stats
Roughly the number of unique words: 227
Number of sentences: 137861
Average number of words in a sentence: 13.225277634719028
English sentences 0 to 10:
new jersey is sometimes quiet during autumn , and it is snowy in april .
the united states is usually chilly during july , and it is usually freezing in november .
california is usually quiet during march , and it is usually hot in june .
the united states is sometimes mild during june , and it is cold in september .
your least liked fruit is the grape , but my least liked is the apple .
his favorite fruit is the orange , but my favorite is the grape .
paris is relaxing during december , but it is usually chilly in july .
new jersey is busy during spring , and it is never hot in march .
our least liked fruit is the lemon , but my least liked is the grape .
the united states is sometimes busy during january , and it is sometimes warm in november .
French sentences 0 to 10:
new jersey est parfois calme pendant l&#39; automne , et il est neigeux en avril .
les états-unis est généralement froid en juillet , et il gèle habituellement en novembre .
california est généralement calme en mars , et il est généralement chaud en juin .
les états-unis est parfois légère en juin , et il fait froid en septembre .
votre moins aimé fruit est le raisin , mais mon moins aimé est la pomme .
son fruit préféré est l&#39;orange , mais mon préféré est le raisin .
paris est relaxant en décembre , mais il est généralement froid en juillet .
new jersey est occupé au printemps , et il est jamais chaude en mars .
notre fruit est moins aimé le citron , mais mon moins aimé est le raisin .
les états-unis est parfois occupé en janvier , et il est parfois chaud en novembre .
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<h2 id="Implement-Preprocessing-Function">Implement Preprocessing Function<a class="anchor-link" href="#Implement-Preprocessing-Function">&#182;</a></h2><h3 id="Text-to-Word-Ids">Text to Word Ids<a class="anchor-link" href="#Text-to-Word-Ids">&#182;</a></h3><p>As you did with other RNNs, you must turn the text into a number so the computer can understand it. In the function <code>text_to_ids()</code>, you'll turn <code>source_text</code> and <code>target_text</code> from words to ids. However, you need to add the <code>&lt;EOS&gt;</code> word id at the end of <code>target_text</code>. This will help the neural network predict when the sentence should end.</p>
<p>You can get the <code>&lt;EOS&gt;</code> word id by doing:</p>
<div class="highlight"><pre><span></span><span class="n">target_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;EOS&gt;&#39;</span><span class="p">]</span>
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<p>You can get other word ids using <code>source_vocab_to_int</code> and <code>target_vocab_to_int</code>.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">text_to_ids</span><span class="p">(</span><span class="n">source_text</span><span class="p">,</span> <span class="n">target_text</span><span class="p">,</span> <span class="n">source_vocab_to_int</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Convert source and target text to proper word ids</span>
<span class="sd"> :param source_text: String that contains all the source text.</span>
<span class="sd"> :param target_text: String that contains all the target text.</span>
<span class="sd"> :param source_vocab_to_int: Dictionary to go from the source words to an id</span>
<span class="sd"> :param target_vocab_to_int: Dictionary to go from the target words to an id</span>
<span class="sd"> :return: A tuple of lists (source_id_text, target_id_text)</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="c1"># Process source text</span>
<span class="n">words</span> <span class="o">=</span> <span class="p">[[</span><span class="n">word</span> <span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">line</span><span class="o">.</span><span class="n">split</span><span class="p">()]</span> <span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="n">source_text</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)]</span>
<span class="n">source_word_ids</span> <span class="o">=</span> <span class="p">[[</span><span class="n">source_vocab_to_int</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">word</span><span class="p">,</span> <span class="n">source_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;UNK&gt;&#39;</span><span class="p">])</span> <span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">line</span><span class="o">.</span><span class="n">split</span><span class="p">()]</span> <span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="n">source_text</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)]</span> <span class="c1"># use get to replace ignored/unknown characters by &lt;UNK&gt;</span>
<span class="c1"># Process target text</span>
<span class="n">target_word_ids</span> <span class="o">=</span> <span class="p">[[</span><span class="n">target_vocab_to_int</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">word</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;UNK&gt;&#39;</span><span class="p">])</span> <span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">line</span><span class="o">.</span><span class="n">split</span><span class="p">()]</span> <span class="o">+</span> <span class="p">[</span><span class="n">target_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;EOS&gt;&#39;</span><span class="p">]]</span> <span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="n">target_text</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">)]</span>
<span class="k">return</span> <span class="n">source_word_ids</span><span class="p">,</span> <span class="n">target_word_ids</span>
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<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_text_to_ids</span><span class="p">(</span><span class="n">text_to_ids</span><span class="p">)</span>
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<pre>Tests Passed
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<h3 id="Preprocess-all-the-data-and-save-it">Preprocess all the data and save it<a class="anchor-link" href="#Preprocess-all-the-data-and-save-it">&#182;</a></h3><p>Running the code cell below will preprocess all the data and save it to file.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">helper</span><span class="o">.</span><span class="n">preprocess_and_save_data</span><span class="p">(</span><span class="n">source_path</span><span class="p">,</span> <span class="n">target_path</span><span class="p">,</span> <span class="n">text_to_ids</span><span class="p">)</span>
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<h1 id="Check-Point">Check Point<a class="anchor-link" href="#Check-Point">&#182;</a></h1><p>This is your first checkpoint. If you ever decide to come back to this notebook or have to restart the notebook, you can start from here. The preprocessed data has been saved to disk.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">helper</span>
<span class="kn">import</span> <span class="nn">problem_unittests</span> <span class="k">as</span> <span class="nn">tests</span>
<span class="p">(</span><span class="n">source_int_text</span><span class="p">,</span> <span class="n">target_int_text</span><span class="p">),</span> <span class="p">(</span><span class="n">source_vocab_to_int</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">),</span> <span class="n">_</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">load_preprocess</span><span class="p">()</span>
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<h3 id="Check-the-Version-of-TensorFlow-and-Access-to-GPU">Check the Version of TensorFlow and Access to GPU<a class="anchor-link" href="#Check-the-Version-of-TensorFlow-and-Access-to-GPU">&#182;</a></h3><p>This will check to make sure you have the correct version of TensorFlow and access to a GPU</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">distutils.version</span> <span class="k">import</span> <span class="n">LooseVersion</span>
<span class="kn">import</span> <span class="nn">warnings</span>
<span class="kn">import</span> <span class="nn">tensorflow</span> <span class="k">as</span> <span class="nn">tf</span>
<span class="kn">from</span> <span class="nn">tensorflow.python.layers.core</span> <span class="k">import</span> <span class="n">Dense</span>
<span class="c1"># Check TensorFlow Version</span>
<span class="k">assert</span> <span class="n">LooseVersion</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">__version__</span><span class="p">)</span> <span class="o">&gt;=</span> <span class="n">LooseVersion</span><span class="p">(</span><span class="s1">&#39;1.1&#39;</span><span class="p">),</span> <span class="s1">&#39;Please use TensorFlow version 1.1 or newer&#39;</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;TensorFlow Version: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">__version__</span><span class="p">))</span>
<span class="c1"># Check for a GPU</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">tf</span><span class="o">.</span><span class="n">test</span><span class="o">.</span><span class="n">gpu_device_name</span><span class="p">():</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span><span class="s1">&#39;No GPU found. Please use a GPU to train your neural network.&#39;</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Default GPU Device: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">test</span><span class="o">.</span><span class="n">gpu_device_name</span><span class="p">()))</span>
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<pre>TensorFlow Version: 1.2.1
Default GPU Device: /gpu:0
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<h2 id="Build-the-Neural-Network">Build the Neural Network<a class="anchor-link" href="#Build-the-Neural-Network">&#182;</a></h2><p>You'll build the components necessary to build a Sequence-to-Sequence model by implementing the following functions below:</p>
<ul>
<li><code>model_inputs</code></li>
<li><code>process_decoder_input</code></li>
<li><code>encoding_layer</code></li>
<li><code>decoding_layer_train</code></li>
<li><code>decoding_layer_infer</code></li>
<li><code>decoding_layer</code></li>
<li><code>seq2seq_model</code></li>
</ul>
<h3 id="Input">Input<a class="anchor-link" href="#Input">&#182;</a></h3><p>Implement the <code>model_inputs()</code> function to create TF Placeholders for the Neural Network. It should create the following placeholders:</p>
<ul>
<li>Input text placeholder named "input" using the TF Placeholder name parameter with rank 2.</li>
<li>Targets placeholder with rank 2.</li>
<li>Learning rate placeholder with rank 0.</li>
<li>Keep probability placeholder named "keep_prob" using the TF Placeholder name parameter with rank 0.</li>
<li>Target sequence length placeholder named "target_sequence_length" with rank 1</li>
<li>Max target sequence length tensor named "max_target_len" getting its value from applying tf.reduce_max on the target_sequence_length placeholder. Rank 0.</li>
<li>Source sequence length placeholder named "source_sequence_length" with rank 1</li>
</ul>
<p>Return the placeholders in the following the tuple (input, targets, learning rate, keep probability, target sequence length, max target sequence length, source sequence length)</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">model_inputs</span><span class="p">():</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create TF Placeholders for input, targets, learning rate, and lengths of source and target sequences.</span>
<span class="sd"> :return: Tuple (input, targets, learning rate, keep probability, target sequence length,</span>
<span class="sd"> max target sequence length, source sequence length)</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">input_text</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span> <span class="p">[</span><span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;input&#39;</span><span class="p">)</span>
<span class="n">targets</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span> <span class="p">[</span><span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;targets&#39;</span><span class="p">)</span>
<span class="n">lr</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;learning_rate&#39;</span> <span class="p">)</span>
<span class="n">keep</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;keep_prob&#39;</span><span class="p">)</span>
<span class="n">target_seq_len</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span> <span class="p">(</span><span class="kc">None</span><span class="p">,),</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;target_sequence_length&#39;</span><span class="p">)</span>
<span class="n">max_target_seq_len</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">reduce_max</span><span class="p">(</span><span class="n">target_seq_len</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;max_target_len&#39;</span><span class="p">)</span>
<span class="n">source_seq_len</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">placeholder</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span> <span class="p">(</span><span class="kc">None</span><span class="p">,),</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;source_sequence_length&#39;</span><span class="p">)</span>
<span class="k">return</span> <span class="n">input_text</span><span class="p">,</span> <span class="n">targets</span><span class="p">,</span> <span class="n">lr</span><span class="p">,</span> <span class="n">keep</span><span class="p">,</span> <span class="n">target_seq_len</span><span class="p">,</span> <span class="n">max_target_seq_len</span><span class="p">,</span> <span class="n">source_seq_len</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_model_inputs</span><span class="p">(</span><span class="n">model_inputs</span><span class="p">)</span>
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<pre>ERROR:tensorflow:==================================
Object was never used (type &lt;class &#39;tensorflow.python.framework.ops.Operation&#39;&gt;):
&lt;tf.Operation &#39;assert_rank_2/Assert/Assert&#39; type=Assert&gt;
If you want to mark it as used call its &#34;mark_used()&#34; method.
It was originally created here:
[&#39;File &#34;/usr/local/lib/python3.5/runpy.py&#34;, line 193, in _run_module_as_main\n &#34;__main__&#34;, mod_spec)&#39;, &#39;File &#34;/usr/local/lib/python3.5/runpy.py&#34;, line 85, in _run_code\n exec(code, run_globals)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/ipykernel_launcher.py&#34;, line 16, in &lt;module&gt;\n app.launch_new_instance()&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/traitlets/config/application.py&#34;, line 658, in launch_instance\n app.start()&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/ipykernel/kernelapp.py&#34;, line 477, in start\n ioloop.IOLoop.instance().start()&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/zmq/eventloop/ioloop.py&#34;, line 177, in start\n super(ZMQIOLoop, self).start()&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tornado/ioloop.py&#34;, line 888, in start\n handler_func(fd_obj, events)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tornado/stack_context.py&#34;, line 277, in null_wrapper\n return fn(*args, **kwargs)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py&#34;, line 440, in _handle_events\n self._handle_recv()&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py&#34;, line 472, in _handle_recv\n self._run_callback(callback, msg)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py&#34;, line 414, in _run_callback\n callback(*args, **kwargs)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tornado/stack_context.py&#34;, line 277, in null_wrapper\n return fn(*args, **kwargs)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/ipykernel/kernelbase.py&#34;, line 283, in dispatcher\n return self.dispatch_shell(stream, msg)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/ipykernel/kernelbase.py&#34;, line 235, in dispatch_shell\n handler(stream, idents, msg)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/ipykernel/kernelbase.py&#34;, line 399, in execute_request\n user_expressions, allow_stdin)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/ipykernel/ipkernel.py&#34;, line 196, in do_execute\n res = shell.run_cell(code, store_history=store_history, silent=silent)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/ipykernel/zmqshell.py&#34;, line 533, in run_cell\n return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/IPython/core/interactiveshell.py&#34;, line 2698, in run_cell\n interactivity=interactivity, compiler=compiler, result=result)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/IPython/core/interactiveshell.py&#34;, line 2808, in run_ast_nodes\n if self.run_code(code, result):&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/IPython/core/interactiveshell.py&#34;, line 2862, in run_code\n exec(code_obj, self.user_global_ns, self.user_ns)&#39;, &#39;File &#34;&lt;ipython-input-7-6c45c8fd5ae4&gt;&#34;, line 22, in &lt;module&gt;\n tests.test_model_inputs(model_inputs)&#39;, &#39;File &#34;/output/problem_unittests.py&#34;, line 106, in test_model_inputs\n assert tf.assert_rank(lr, 0, message=\&#39;Learning Rate has wrong rank\&#39;)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tensorflow/python/ops/check_ops.py&#34;, line 617, in assert_rank\n dynamic_condition, data, summarize)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tensorflow/python/ops/check_ops.py&#34;, line 571, in _assert_rank_condition\n return control_flow_ops.Assert(condition, data, summarize=summarize)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tensorflow/python/util/tf_should_use.py&#34;, line 170, in wrapped\n return _add_should_use_warning(fn(*args, **kwargs))&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tensorflow/python/util/tf_should_use.py&#34;, line 139, in _add_should_use_warning\n wrapped = TFShouldUseWarningWrapper(x)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tensorflow/python/util/tf_should_use.py&#34;, line 96, in __init__\n stack = [s.strip() for s in traceback.format_stack()]&#39;]
==================================
ERROR:tensorflow:==================================
Object was never used (type &lt;class &#39;tensorflow.python.framework.ops.Operation&#39;&gt;):
&lt;tf.Operation &#39;assert_rank_3/Assert/Assert&#39; type=Assert&gt;
If you want to mark it as used call its &#34;mark_used()&#34; method.
It was originally created here:
[&#39;File &#34;/usr/local/lib/python3.5/runpy.py&#34;, line 193, in _run_module_as_main\n &#34;__main__&#34;, mod_spec)&#39;, &#39;File &#34;/usr/local/lib/python3.5/runpy.py&#34;, line 85, in _run_code\n exec(code, run_globals)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/ipykernel_launcher.py&#34;, line 16, in &lt;module&gt;\n app.launch_new_instance()&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/traitlets/config/application.py&#34;, line 658, in launch_instance\n app.start()&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/ipykernel/kernelapp.py&#34;, line 477, in start\n ioloop.IOLoop.instance().start()&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/zmq/eventloop/ioloop.py&#34;, line 177, in start\n super(ZMQIOLoop, self).start()&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tornado/ioloop.py&#34;, line 888, in start\n handler_func(fd_obj, events)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tornado/stack_context.py&#34;, line 277, in null_wrapper\n return fn(*args, **kwargs)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py&#34;, line 440, in _handle_events\n self._handle_recv()&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py&#34;, line 472, in _handle_recv\n self._run_callback(callback, msg)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py&#34;, line 414, in _run_callback\n callback(*args, **kwargs)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tornado/stack_context.py&#34;, line 277, in null_wrapper\n return fn(*args, **kwargs)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/ipykernel/kernelbase.py&#34;, line 283, in dispatcher\n return self.dispatch_shell(stream, msg)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/ipykernel/kernelbase.py&#34;, line 235, in dispatch_shell\n handler(stream, idents, msg)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/ipykernel/kernelbase.py&#34;, line 399, in execute_request\n user_expressions, allow_stdin)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/ipykernel/ipkernel.py&#34;, line 196, in do_execute\n res = shell.run_cell(code, store_history=store_history, silent=silent)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/ipykernel/zmqshell.py&#34;, line 533, in run_cell\n return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/IPython/core/interactiveshell.py&#34;, line 2698, in run_cell\n interactivity=interactivity, compiler=compiler, result=result)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/IPython/core/interactiveshell.py&#34;, line 2808, in run_ast_nodes\n if self.run_code(code, result):&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/IPython/core/interactiveshell.py&#34;, line 2862, in run_code\n exec(code_obj, self.user_global_ns, self.user_ns)&#39;, &#39;File &#34;&lt;ipython-input-7-6c45c8fd5ae4&gt;&#34;, line 22, in &lt;module&gt;\n tests.test_model_inputs(model_inputs)&#39;, &#39;File &#34;/output/problem_unittests.py&#34;, line 107, in test_model_inputs\n assert tf.assert_rank(keep_prob, 0, message=\&#39;Keep Probability has wrong rank\&#39;)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tensorflow/python/ops/check_ops.py&#34;, line 617, in assert_rank\n dynamic_condition, data, summarize)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tensorflow/python/ops/check_ops.py&#34;, line 571, in _assert_rank_condition\n return control_flow_ops.Assert(condition, data, summarize=summarize)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tensorflow/python/util/tf_should_use.py&#34;, line 170, in wrapped\n return _add_should_use_warning(fn(*args, **kwargs))&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tensorflow/python/util/tf_should_use.py&#34;, line 139, in _add_should_use_warning\n wrapped = TFShouldUseWarningWrapper(x)&#39;, &#39;File &#34;/usr/local/lib/python3.5/site-packages/tensorflow/python/util/tf_should_use.py&#34;, line 96, in __init__\n stack = [s.strip() for s in traceback.format_stack()]&#39;]
==================================
Tests Passed
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<h3 id="Process-Decoder-Input">Process Decoder Input<a class="anchor-link" href="#Process-Decoder-Input">&#182;</a></h3><p>Implement <code>process_decoder_input</code> by removing the last word id from each batch in <code>target_data</code> and concat the GO ID to the begining of each batch.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">process_decoder_input</span><span class="p">(</span><span class="n">target_data</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Preprocess target data for encoding</span>
<span class="sd"> :param target_data: Target Placehoder</span>
<span class="sd"> :param target_vocab_to_int: Dictionary to go from the target words to an id</span>
<span class="sd"> :param batch_size: Batch Size</span>
<span class="sd"> :return: Preprocessed target data</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="c1"># TODO: Implement Function</span>
<span class="n">ending</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">strided_slice</span><span class="p">(</span><span class="n">target_data</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="p">[</span><span class="n">batch_size</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">])</span>
<span class="n">dec_input</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">concat</span><span class="p">([</span><span class="n">tf</span><span class="o">.</span><span class="n">fill</span><span class="p">([</span><span class="n">batch_size</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">target_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;GO&gt;&#39;</span><span class="p">]),</span> <span class="n">ending</span><span class="p">],</span> <span class="mi">1</span><span class="p">)</span>
<span class="k">return</span> <span class="n">dec_input</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_process_encoding_input</span><span class="p">(</span><span class="n">process_decoder_input</span><span class="p">)</span>
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<pre>Tests Passed
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<h3 id="Encoding">Encoding<a class="anchor-link" href="#Encoding">&#182;</a></h3><p>Implement <code>encoding_layer()</code> to create a Encoder RNN layer:</p>
<ul>
<li>Embed the encoder input using <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/layers/embed_sequence"><code>tf.contrib.layers.embed_sequence</code></a></li>
<li>Construct a <a href="https://github.com/tensorflow/tensorflow/blob/6947f65a374ebf29e74bb71e36fd82760056d82c/tensorflow/docs_src/tutorials/recurrent.md#stacking-multiple-lstms">stacked</a> <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/rnn/LSTMCell"><code>tf.contrib.rnn.LSTMCell</code></a> wrapped in a <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/rnn/DropoutWrapper"><code>tf.contrib.rnn.DropoutWrapper</code></a></li>
<li>Pass cell and embedded input to <a href="https://www.tensorflow.org/api_docs/python/tf/nn/dynamic_rnn"><code>tf.nn.dynamic_rnn()</code></a></li>
</ul>
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<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[9]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">imp</span> <span class="k">import</span> <span class="n">reload</span>
<span class="n">reload</span><span class="p">(</span><span class="n">tests</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">encoding_layer</span><span class="p">(</span><span class="n">rnn_inputs</span><span class="p">,</span> <span class="n">rnn_size</span><span class="p">,</span> <span class="n">num_layers</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">,</span>
<span class="n">source_sequence_length</span><span class="p">,</span> <span class="n">source_vocab_size</span><span class="p">,</span>
<span class="n">encoding_embedding_size</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create encoding layer</span>
<span class="sd"> :param rnn_inputs: Inputs for the RNN</span>
<span class="sd"> :param rnn_size: RNN Size</span>
<span class="sd"> :param num_layers: Number of layers</span>
<span class="sd"> :param keep_prob: Dropout keep probability</span>
<span class="sd"> :param source_sequence_length: a list of the lengths of each sequence in the batch</span>
<span class="sd"> :param source_vocab_size: vocabulary size of source data</span>
<span class="sd"> :param encoding_embedding_size: embedding size of source data</span>
<span class="sd"> :return: tuple (RNN output, RNN state)</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">enc_embed_input</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">layers</span><span class="o">.</span><span class="n">embed_sequence</span><span class="p">(</span><span class="n">rnn_inputs</span><span class="p">,</span> <span class="n">source_vocab_size</span><span class="p">,</span> <span class="n">encoding_embedding_size</span><span class="p">)</span>
<span class="c1">#Rnn cell</span>
<span class="k">def</span> <span class="nf">make_cell</span><span class="p">(</span><span class="n">rnn_size</span><span class="p">):</span>
<span class="n">cell</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">rnn</span><span class="o">.</span><span class="n">LSTMCell</span><span class="p">(</span><span class="n">rnn_size</span><span class="p">,</span>
<span class="n">initializer</span><span class="o">=</span><span class="n">tf</span><span class="o">.</span><span class="n">random_uniform_initializer</span><span class="p">(</span><span class="o">-</span><span class="mf">0.1</span><span class="p">,</span> <span class="mf">0.1</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="mi">2</span><span class="p">))</span>
<span class="c1"># add dropout layer</span>
<span class="n">enc_cell</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">rnn</span><span class="o">.</span><span class="n">DropoutWrapper</span><span class="p">(</span><span class="n">cell</span><span class="p">,</span> <span class="n">output_keep_prob</span><span class="o">=</span><span class="n">keep_prob</span><span class="p">)</span>
<span class="k">return</span> <span class="n">enc_cell</span>
<span class="n">enc_cell</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">rnn</span><span class="o">.</span><span class="n">MultiRNNCell</span><span class="p">([</span><span class="n">make_cell</span><span class="p">(</span><span class="n">rnn_size</span><span class="p">)</span> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_layers</span><span class="p">)])</span>
<span class="n">enc_output</span><span class="p">,</span> <span class="n">enc_state</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">dynamic_rnn</span><span class="p">(</span><span class="n">enc_cell</span><span class="p">,</span> <span class="n">enc_embed_input</span><span class="p">,</span> <span class="n">sequence_length</span><span class="o">=</span><span class="n">source_sequence_length</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>
<span class="k">return</span> <span class="n">enc_output</span><span class="p">,</span> <span class="n">enc_state</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_encoding_layer</span><span class="p">(</span><span class="n">encoding_layer</span><span class="p">)</span>
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<h3 id="Decoding---Training">Decoding - Training<a class="anchor-link" href="#Decoding---Training">&#182;</a></h3><p>Create a training decoding layer:</p>
<ul>
<li>Create a <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/seq2seq/TrainingHelper"><code>tf.contrib.seq2seq.TrainingHelper</code></a> </li>
<li>Create a <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/seq2seq/BasicDecoder"><code>tf.contrib.seq2seq.BasicDecoder</code></a></li>
<li>Obtain the decoder outputs from <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/seq2seq/dynamic_decode"><code>tf.contrib.seq2seq.dynamic_decode</code></a></li>
</ul>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">IPython.core.debugger</span> <span class="k">import</span> <span class="n">Tracer</span>
<span class="k">def</span> <span class="nf">decoding_layer_train</span><span class="p">(</span><span class="n">encoder_state</span><span class="p">,</span> <span class="n">dec_cell</span><span class="p">,</span> <span class="n">dec_embed_input</span><span class="p">,</span>
<span class="n">target_sequence_length</span><span class="p">,</span> <span class="n">max_summary_length</span><span class="p">,</span>
<span class="n">output_layer</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create a decoding layer for training</span>
<span class="sd"> :param encoder_state: Encoder State</span>
<span class="sd"> :param dec_cell: Decoder RNN Cell</span>
<span class="sd"> :param dec_embed_input: Decoder embedded input</span>
<span class="sd"> :param target_sequence_length: The lengths of each sequence in the target batch</span>
<span class="sd"> :param max_summary_length: The length of the longest sequence in the batch</span>
<span class="sd"> :param output_layer: Function to apply the output layer</span>
<span class="sd"> :param keep_prob: Dropout keep probability</span>
<span class="sd"> :return: BasicDecoderOutput containing training logits and sample_id</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="c1"># Question: Why are we receiving keep_prob here</span>
<span class="c1"># Where would we add dropout layer here</span>
<span class="c1"># Helper for the training process. Used by BasicDecoder to read inputs.</span>
<span class="n">training_helper</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">seq2seq</span><span class="o">.</span><span class="n">TrainingHelper</span><span class="p">(</span><span class="n">inputs</span><span class="o">=</span><span class="n">dec_embed_input</span><span class="p">,</span>
<span class="n">sequence_length</span><span class="o">=</span><span class="n">target_sequence_length</span><span class="p">,</span>
<span class="n">time_major</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="c1"># Basic decoder</span>
<span class="n">training_decoder</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">seq2seq</span><span class="o">.</span><span class="n">BasicDecoder</span><span class="p">(</span><span class="n">dec_cell</span><span class="p">,</span>
<span class="n">training_helper</span><span class="p">,</span>
<span class="n">encoder_state</span><span class="p">,</span>
<span class="n">output_layer</span><span class="p">)</span>
<span class="c1"># Perform dynamic decoding using the decoder</span>
<span class="n">training_decoder_output</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">seq2seq</span><span class="o">.</span><span class="n">dynamic_decode</span><span class="p">(</span><span class="n">training_decoder</span><span class="p">,</span>
<span class="n">impute_finished</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
<span class="n">maximum_iterations</span><span class="o">=</span><span class="n">max_summary_length</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
<span class="k">return</span> <span class="n">training_decoder_output</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_decoding_layer_train</span><span class="p">(</span><span class="n">decoding_layer_train</span><span class="p">)</span>
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<pre>Tests Passed
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<h3 id="Decoding---Inference">Decoding - Inference<a class="anchor-link" href="#Decoding---Inference">&#182;</a></h3><p>Create inference decoder:</p>
<ul>
<li>Create a <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/seq2seq/GreedyEmbeddingHelper"><code>tf.contrib.seq2seq.GreedyEmbeddingHelper</code></a></li>
<li>Create a <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/seq2seq/BasicDecoder"><code>tf.contrib.seq2seq.BasicDecoder</code></a></li>
<li>Obtain the decoder outputs from <a href="https://www.tensorflow.org/api_docs/python/tf/contrib/seq2seq/dynamic_decode"><code>tf.contrib.seq2seq.dynamic_decode</code></a></li>
</ul>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">decoding_layer_infer</span><span class="p">(</span><span class="n">encoder_state</span><span class="p">,</span> <span class="n">dec_cell</span><span class="p">,</span> <span class="n">dec_embeddings</span><span class="p">,</span> <span class="n">start_of_sequence_id</span><span class="p">,</span>
<span class="n">end_of_sequence_id</span><span class="p">,</span> <span class="n">max_target_sequence_length</span><span class="p">,</span>
<span class="n">vocab_size</span><span class="p">,</span> <span class="n">output_layer</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create a decoding layer for inference</span>
<span class="sd"> :param encoder_state: Encoder state</span>
<span class="sd"> :param dec_cell: Decoder RNN Cell</span>
<span class="sd"> :param dec_embeddings: Decoder embeddings</span>
<span class="sd"> :param start_of_sequence_id: GO ID</span>
<span class="sd"> :param end_of_sequence_id: EOS Id</span>
<span class="sd"> :param max_target_sequence_length: Maximum length of target sequences</span>
<span class="sd"> :param vocab_size: Size of decoder/target vocabulary</span>
<span class="sd"> :param decoding_scope: TenorFlow Variable Scope for decoding</span>
<span class="sd"> :param output_layer: Function to apply the output layer</span>
<span class="sd"> :param batch_size: Batch size</span>
<span class="sd"> :param keep_prob: Dropout keep probability</span>
<span class="sd"> :return: BasicDecoderOutput containing inference logits and sample_id</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="c1"># Start from GO</span>
<span class="n">start_tokens</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">tile</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">constant</span><span class="p">([</span><span class="n">start_of_sequence_id</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">tf</span><span class="o">.</span><span class="n">int32</span><span class="p">),</span> <span class="p">[</span><span class="n">batch_size</span><span class="p">],</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;start_tokens&#39;</span><span class="p">)</span>
<span class="c1"># Helper for the inference process.</span>
<span class="n">inference_helper</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">seq2seq</span><span class="o">.</span><span class="n">GreedyEmbeddingHelper</span><span class="p">(</span><span class="n">dec_embeddings</span><span class="p">,</span>
<span class="n">start_tokens</span><span class="p">,</span>
<span class="n">end_of_sequence_id</span><span class="p">)</span>
<span class="c1"># Basic decoder</span>
<span class="n">inference_decoder</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">seq2seq</span><span class="o">.</span><span class="n">BasicDecoder</span><span class="p">(</span><span class="n">dec_cell</span><span class="p">,</span>
<span class="n">inference_helper</span><span class="p">,</span>
<span class="n">encoder_state</span><span class="p">,</span>
<span class="n">output_layer</span><span class="p">)</span>
<span class="c1"># Perform dynamic decoding using the decoder</span>
<span class="n">inference_decoder_output</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">seq2seq</span><span class="o">.</span><span class="n">dynamic_decode</span><span class="p">(</span><span class="n">inference_decoder</span><span class="p">,</span>
<span class="n">impute_finished</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
<span class="n">maximum_iterations</span><span class="o">=</span><span class="n">max_target_sequence_length</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
<span class="k">return</span> <span class="n">inference_decoder_output</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_decoding_layer_infer</span><span class="p">(</span><span class="n">decoding_layer_infer</span><span class="p">)</span>
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<h3 id="Build-the-Decoding-Layer">Build the Decoding Layer<a class="anchor-link" href="#Build-the-Decoding-Layer">&#182;</a></h3><p>Implement <code>decoding_layer()</code> to create a Decoder RNN layer.</p>
<ul>
<li>Embed the target sequences</li>
<li>Construct the decoder LSTM cell (just like you constructed the encoder cell above)</li>
<li>Create an output layer to map the outputs of the decoder to the elements of our vocabulary</li>
<li>Use the your <code>decoding_layer_train(encoder_state, dec_cell, dec_embed_input, target_sequence_length, max_target_sequence_length, output_layer, keep_prob)</code> function to get the training logits.</li>
<li>Use your <code>decoding_layer_infer(encoder_state, dec_cell, dec_embeddings, start_of_sequence_id, end_of_sequence_id, max_target_sequence_length, vocab_size, output_layer, batch_size, keep_prob)</code> function to get the inference logits.</li>
</ul>
<p>Note: You'll need to use <a href="https://www.tensorflow.org/api_docs/python/tf/variable_scope">tf.variable_scope</a> to share variables between training and inference.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">decoding_layer</span><span class="p">(</span><span class="n">dec_input</span><span class="p">,</span> <span class="n">encoder_state</span><span class="p">,</span>
<span class="n">target_sequence_length</span><span class="p">,</span> <span class="n">max_target_sequence_length</span><span class="p">,</span>
<span class="n">rnn_size</span><span class="p">,</span>
<span class="n">num_layers</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">,</span> <span class="n">target_vocab_size</span><span class="p">,</span>
<span class="n">batch_size</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">,</span> <span class="n">decoding_embedding_size</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create decoding layer</span>
<span class="sd"> :param dec_input: Decoder input</span>
<span class="sd"> :param encoder_state: Encoder state</span>
<span class="sd"> :param target_sequence_length: The lengths of each sequence in the target batch</span>
<span class="sd"> :param max_target_sequence_length: Maximum length of target sequences</span>
<span class="sd"> :param rnn_size: RNN Size</span>
<span class="sd"> :param num_layers: Number of layers</span>
<span class="sd"> :param target_vocab_to_int: Dictionary to go from the target words to an id</span>
<span class="sd"> :param target_vocab_size: Size of target vocabulary</span>
<span class="sd"> :param batch_size: The size of the batch</span>
<span class="sd"> :param keep_prob: Dropout keep probability</span>
<span class="sd"> :param decoding_embedding_size: Decoding embedding size</span>
<span class="sd"> :return: Tuple of (Training BasicDecoderOutput, Inference BasicDecoderOutput)</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="c1"># 1. Decoder Embedding</span>
<span class="n">dec_embeddings</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">random_uniform</span><span class="p">([</span><span class="n">target_vocab_size</span><span class="p">,</span> <span class="n">decoding_embedding_size</span><span class="p">]))</span>
<span class="n">dec_embed_input</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">embedding_lookup</span><span class="p">(</span><span class="n">dec_embeddings</span><span class="p">,</span> <span class="n">dec_input</span><span class="p">)</span>
<span class="c1"># 2. Construct the decoder cell</span>
<span class="k">def</span> <span class="nf">make_cell</span><span class="p">(</span><span class="n">rnn_size</span><span class="p">):</span>
<span class="n">dec_cell</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">rnn</span><span class="o">.</span><span class="n">LSTMCell</span><span class="p">(</span><span class="n">rnn_size</span><span class="p">,</span>
<span class="n">initializer</span><span class="o">=</span><span class="n">tf</span><span class="o">.</span><span class="n">random_uniform_initializer</span><span class="p">(</span><span class="o">-</span><span class="mf">0.1</span><span class="p">,</span> <span class="mf">0.1</span><span class="p">,</span> <span class="n">seed</span><span class="o">=</span><span class="mi">2</span><span class="p">))</span>
<span class="c1"># Add dropout layer</span>
<span class="n">dec_cell</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">rnn</span><span class="o">.</span><span class="n">DropoutWrapper</span><span class="p">(</span><span class="n">dec_cell</span><span class="p">,</span> <span class="n">output_keep_prob</span><span class="o">=</span><span class="n">keep_prob</span><span class="p">)</span>
<span class="k">return</span> <span class="n">dec_cell</span>
<span class="n">dec_cell</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">rnn</span><span class="o">.</span><span class="n">MultiRNNCell</span><span class="p">([</span><span class="n">make_cell</span><span class="p">(</span><span class="n">rnn_size</span><span class="p">)</span> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_layers</span><span class="p">)])</span>
<span class="c1"># 3. Dense layer to translate the decoder&#39;s output at each time </span>
<span class="c1"># step into a choice from the target vocabulary</span>
<span class="n">output_layer</span> <span class="o">=</span> <span class="n">Dense</span><span class="p">(</span><span class="n">target_vocab_size</span><span class="p">,</span>
<span class="n">kernel_initializer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">truncated_normal_initializer</span><span class="p">(</span><span class="n">mean</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span> <span class="n">stddev</span><span class="o">=</span><span class="mf">0.1</span><span class="p">))</span>
<span class="c1"># 4. Get training and inference outputs</span>
<span class="c1">## In training mode</span>
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">variable_scope</span><span class="p">(</span><span class="s1">&#39;decode&#39;</span><span class="p">):</span>
<span class="n">training_decoder_output</span> <span class="o">=</span> <span class="n">decoding_layer_train</span><span class="p">(</span><span class="n">encoder_state</span><span class="p">,</span>
<span class="n">dec_cell</span><span class="p">,</span>
<span class="n">dec_embed_input</span><span class="p">,</span>
<span class="n">target_sequence_length</span><span class="p">,</span>
<span class="n">max_target_sequence_length</span><span class="p">,</span>
<span class="n">output_layer</span><span class="p">,</span>
<span class="n">keep_prob</span><span class="p">)</span>
<span class="c1">## In inference mode we reuse variables</span>
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">variable_scope</span><span class="p">(</span><span class="s1">&#39;decode&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">scope</span><span class="p">:</span>
<span class="n">scope</span><span class="o">.</span><span class="n">reuse_variables</span><span class="p">()</span>
<span class="n">inference_decoder_output</span> <span class="o">=</span> <span class="n">decoding_layer_infer</span><span class="p">(</span><span class="n">encoder_state</span><span class="p">,</span>
<span class="n">dec_cell</span><span class="p">,</span>
<span class="n">dec_embeddings</span><span class="p">,</span>
<span class="n">target_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;GO&gt;&#39;</span><span class="p">],</span> <span class="c1">#start of seq ID</span>
<span class="n">target_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;EOS&gt;&#39;</span><span class="p">],</span> <span class="c1"># end of seq ID</span>
<span class="n">max_target_sequence_length</span><span class="p">,</span>
<span class="n">target_vocab_size</span><span class="p">,</span>
<span class="n">output_layer</span><span class="p">,</span>
<span class="n">batch_size</span><span class="p">,</span>
<span class="n">keep_prob</span><span class="p">)</span>
<span class="k">return</span> <span class="n">training_decoder_output</span><span class="p">,</span> <span class="n">inference_decoder_output</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_decoding_layer</span><span class="p">(</span><span class="n">decoding_layer</span><span class="p">)</span>
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<pre>Tests Passed
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<h3 id="Build-the-Neural-Network">Build the Neural Network<a class="anchor-link" href="#Build-the-Neural-Network">&#182;</a></h3><p>Apply the functions you implemented above to:</p>
<ul>
<li>Encode the input using your <code>encoding_layer(rnn_inputs, rnn_size, num_layers, keep_prob, source_sequence_length, source_vocab_size, encoding_embedding_size)</code>.</li>
<li>Process target data using your <code>process_decoder_input(target_data, target_vocab_to_int, batch_size)</code> function.</li>
<li>Decode the encoded input using your <code>decoding_layer(dec_input, enc_state, target_sequence_length, max_target_sentence_length, rnn_size, num_layers, target_vocab_to_int, target_vocab_size, batch_size, keep_prob, dec_embedding_size)</code> function.</li>
</ul>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">seq2seq_model</span><span class="p">(</span><span class="n">input_data</span><span class="p">,</span> <span class="n">target_data</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span>
<span class="n">source_sequence_length</span><span class="p">,</span> <span class="n">target_sequence_length</span><span class="p">,</span>
<span class="n">max_target_sentence_length</span><span class="p">,</span>
<span class="n">source_vocab_size</span><span class="p">,</span> <span class="n">target_vocab_size</span><span class="p">,</span>
<span class="n">enc_embedding_size</span><span class="p">,</span> <span class="n">dec_embedding_size</span><span class="p">,</span>
<span class="n">rnn_size</span><span class="p">,</span> <span class="n">num_layers</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Build the Sequence-to-Sequence part of the neural network</span>
<span class="sd"> :param input_data: Input placeholder</span>
<span class="sd"> :param target_data: Target placeholder</span>
<span class="sd"> :param keep_prob: Dropout keep probability placeholder</span>
<span class="sd"> :param batch_size: Batch Size</span>
<span class="sd"> :param source_sequence_length: Sequence Lengths of source sequences in the batch</span>
<span class="sd"> :param target_sequence_length: Sequence Lengths of target sequences in the batch</span>
<span class="sd"> :param source_vocab_size: Source vocabulary size</span>
<span class="sd"> :param target_vocab_size: Target vocabulary size</span>
<span class="sd"> :param enc_embedding_size: Decoder embedding size</span>
<span class="sd"> :param dec_embedding_size: Encoder embedding size</span>
<span class="sd"> :param rnn_size: RNN Size</span>
<span class="sd"> :param num_layers: Number of layers</span>
<span class="sd"> :param target_vocab_to_int: Dictionary to go from the target words to an id</span>
<span class="sd"> :return: Tuple of (Training BasicDecoderOutput, Inference BasicDecoderOutput)</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="c1"># TODO: Implement Function</span>
<span class="c1"># Pass the input data through the encoder. We&#39;ll ignore the encoder output, but use the state</span>
<span class="n">_</span><span class="p">,</span> <span class="n">enc_state</span> <span class="o">=</span> <span class="n">encoding_layer</span><span class="p">(</span><span class="n">input_data</span><span class="p">,</span>
<span class="n">rnn_size</span><span class="p">,</span>
<span class="n">num_layers</span><span class="p">,</span>
<span class="n">keep_prob</span><span class="p">,</span>
<span class="n">source_sequence_length</span><span class="p">,</span>
<span class="n">source_vocab_size</span><span class="p">,</span>
<span class="n">enc_embedding_size</span><span class="p">)</span>
<span class="c1"># Prepare the target sequences we&#39;ll feed to the decoder in training mode</span>
<span class="n">dec_input</span> <span class="o">=</span> <span class="n">process_decoder_input</span><span class="p">(</span><span class="n">target_data</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">)</span>
<span class="c1"># Pass encoder state and decoder inputs to the decoders</span>
<span class="n">training_decoder_output</span><span class="p">,</span> <span class="n">inference_decoder_output</span> <span class="o">=</span> <span class="n">decoding_layer</span><span class="p">(</span><span class="n">dec_input</span><span class="p">,</span>
<span class="n">enc_state</span><span class="p">,</span>
<span class="n">target_sequence_length</span><span class="p">,</span>
<span class="n">max_target_sentence_length</span><span class="p">,</span>
<span class="n">rnn_size</span><span class="p">,</span>
<span class="n">num_layers</span><span class="p">,</span>
<span class="n">target_vocab_to_int</span><span class="p">,</span>
<span class="n">target_vocab_size</span><span class="p">,</span>
<span class="n">batch_size</span><span class="p">,</span>
<span class="n">keep_prob</span><span class="p">,</span>
<span class="n">dec_embedding_size</span><span class="p">)</span>
<span class="k">return</span> <span class="n">training_decoder_output</span><span class="p">,</span> <span class="n">inference_decoder_output</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_seq2seq_model</span><span class="p">(</span><span class="n">seq2seq_model</span><span class="p">)</span>
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<pre>Tests Passed
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<h2 id="Neural-Network-Training">Neural Network Training<a class="anchor-link" href="#Neural-Network-Training">&#182;</a></h2><h3 id="Hyperparameters">Hyperparameters<a class="anchor-link" href="#Hyperparameters">&#182;</a></h3><p>Tune the following parameters:</p>
<ul>
<li>Set <code>epochs</code> to the number of epochs.</li>
<li>Set <code>batch_size</code> to the batch size.</li>
<li>Set <code>rnn_size</code> to the size of the RNNs.</li>
<li>Set <code>num_layers</code> to the number of layers.</li>
<li>Set <code>encoding_embedding_size</code> to the size of the embedding for the encoder.</li>
<li>Set <code>decoding_embedding_size</code> to the size of the embedding for the decoder.</li>
<li>Set <code>learning_rate</code> to the learning rate.</li>
<li>Set <code>keep_probability</code> to the Dropout keep probability</li>
<li>Set <code>display_step</code> to state how many steps between each debug output statement</li>
</ul>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Number of Epochs</span>
<span class="n">epochs</span> <span class="o">=</span> <span class="mi">5</span>
<span class="c1"># Batch Size</span>
<span class="n">batch_size</span> <span class="o">=</span> <span class="mi">256</span>
<span class="c1"># RNN Size</span>
<span class="n">rnn_size</span> <span class="o">=</span> <span class="mi">256</span>
<span class="c1"># Number of Layers</span>
<span class="n">num_layers</span> <span class="o">=</span> <span class="mi">2</span>
<span class="c1"># Embedding Size</span>
<span class="n">encoding_embedding_size</span> <span class="o">=</span> <span class="mi">260</span>
<span class="n">decoding_embedding_size</span> <span class="o">=</span> <span class="mi">260</span>
<span class="c1"># Learning Rate</span>
<span class="n">learning_rate</span> <span class="o">=</span> <span class="mf">0.001</span>
<span class="c1"># Dropout Keep Probability</span>
<span class="n">keep_probability</span> <span class="o">=</span> <span class="mf">0.5</span>
<span class="n">display_step</span> <span class="o">=</span> <span class="mi">10</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">RUN_NUMBER</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">LOG_DIR</span> <span class="o">=</span> <span class="s1">&#39;/output/run_</span><span class="si">{}</span><span class="s1">/logs/&#39;</span>
<span class="n">CHECKPOINT_DIR</span> <span class="o">=</span> <span class="s1">&#39;/output/run_</span><span class="si">{}</span><span class="s1">/checkpoints/&#39;</span>
<span class="n">CHECKPOINT_PATH</span> <span class="o">=</span> <span class="n">CHECKPOINT_DIR</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">RUN_NUMBER</span><span class="p">)</span>
<span class="n">LOG_PATH</span> <span class="o">=</span> <span class="n">LOG_DIR</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">RUN_NUMBER</span><span class="p">)</span>
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<h3 id="Build-the-Graph">Build the Graph<a class="anchor-link" href="#Build-the-Graph">&#182;</a></h3><p>Build the graph using the neural network you implemented.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">save_path</span> <span class="o">=</span> <span class="n">CHECKPOINT_PATH</span>
<span class="p">(</span><span class="n">source_int_text</span><span class="p">,</span> <span class="n">target_int_text</span><span class="p">),</span> <span class="p">(</span><span class="n">source_vocab_to_int</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">),</span> <span class="n">_</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">load_preprocess</span><span class="p">()</span>
<span class="n">max_target_sentence_length</span> <span class="o">=</span> <span class="nb">max</span><span class="p">([</span><span class="nb">len</span><span class="p">(</span><span class="n">sentence</span><span class="p">)</span> <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="n">source_int_text</span><span class="p">])</span>
<span class="n">train_graph</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Graph</span><span class="p">()</span>
<span class="k">with</span> <span class="n">train_graph</span><span class="o">.</span><span class="n">as_default</span><span class="p">():</span>
<span class="n">input_data</span><span class="p">,</span> <span class="n">targets</span><span class="p">,</span> <span class="n">lr</span><span class="p">,</span> <span class="n">keep_prob</span><span class="p">,</span> <span class="n">target_sequence_length</span><span class="p">,</span> <span class="n">max_target_sequence_length</span><span class="p">,</span> <span class="n">source_sequence_length</span> <span class="o">=</span> <span class="n">model_inputs</span><span class="p">()</span>
<span class="c1">#sequence_length = tf.placeholder_with_default(max_target_sentence_length, None, name=&#39;sequence_length&#39;)</span>
<span class="n">input_shape</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">shape</span><span class="p">(</span><span class="n">input_data</span><span class="p">)</span>
<span class="n">train_logits</span><span class="p">,</span> <span class="n">inference_logits</span> <span class="o">=</span> <span class="n">seq2seq_model</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">reverse</span><span class="p">(</span><span class="n">input_data</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">targets</span><span class="p">,</span>
<span class="n">keep_prob</span><span class="p">,</span>
<span class="n">batch_size</span><span class="p">,</span>
<span class="n">source_sequence_length</span><span class="p">,</span>
<span class="n">target_sequence_length</span><span class="p">,</span>
<span class="n">max_target_sequence_length</span><span class="p">,</span>
<span class="nb">len</span><span class="p">(</span><span class="n">source_vocab_to_int</span><span class="p">),</span>
<span class="nb">len</span><span class="p">(</span><span class="n">target_vocab_to_int</span><span class="p">),</span>
<span class="n">encoding_embedding_size</span><span class="p">,</span>
<span class="n">decoding_embedding_size</span><span class="p">,</span>
<span class="n">rnn_size</span><span class="p">,</span>
<span class="n">num_layers</span><span class="p">,</span>
<span class="n">target_vocab_to_int</span><span class="p">)</span>
<span class="n">training_logits</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">identity</span><span class="p">(</span><span class="n">train_logits</span><span class="o">.</span><span class="n">rnn_output</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;logits&#39;</span><span class="p">)</span>
<span class="n">inference_logits</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">identity</span><span class="p">(</span><span class="n">inference_logits</span><span class="o">.</span><span class="n">sample_id</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;predictions&#39;</span><span class="p">)</span>
<span class="n">masks</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">sequence_mask</span><span class="p">(</span><span class="n">target_sequence_length</span><span class="p">,</span> <span class="n">max_target_sequence_length</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">tf</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;masks&#39;</span><span class="p">)</span>
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">name_scope</span><span class="p">(</span><span class="s2">&quot;optimization&quot;</span><span class="p">):</span>
<span class="c1"># Loss function</span>
<span class="n">cost</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">seq2seq</span><span class="o">.</span><span class="n">sequence_loss</span><span class="p">(</span>
<span class="n">training_logits</span><span class="p">,</span>
<span class="n">targets</span><span class="p">,</span>
<span class="n">masks</span><span class="p">)</span>
<span class="n">tf</span><span class="o">.</span><span class="n">summary</span><span class="o">.</span><span class="n">scalar</span><span class="p">(</span><span class="s1">&#39;cost&#39;</span><span class="p">,</span> <span class="n">cost</span><span class="p">)</span>
<span class="c1"># Optimizer</span>
<span class="n">optimizer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">train</span><span class="o">.</span><span class="n">AdamOptimizer</span><span class="p">(</span><span class="n">lr</span><span class="p">)</span>
<span class="c1"># Gradient Clipping</span>
<span class="n">gradients</span> <span class="o">=</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">compute_gradients</span><span class="p">(</span><span class="n">cost</span><span class="p">)</span>
<span class="n">capped_gradients</span> <span class="o">=</span> <span class="p">[(</span><span class="n">tf</span><span class="o">.</span><span class="n">clip_by_value</span><span class="p">(</span><span class="n">grad</span><span class="p">,</span> <span class="o">-</span><span class="mf">1.</span><span class="p">,</span> <span class="mf">1.</span><span class="p">),</span> <span class="n">var</span><span class="p">)</span> <span class="k">for</span> <span class="n">grad</span><span class="p">,</span> <span class="n">var</span> <span class="ow">in</span> <span class="n">gradients</span> <span class="k">if</span> <span class="n">grad</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">]</span>
<span class="n">train_op</span> <span class="o">=</span> <span class="n">optimizer</span><span class="o">.</span><span class="n">apply_gradients</span><span class="p">(</span><span class="n">capped_gradients</span><span class="p">)</span>
<span class="n">merged</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">summary</span><span class="o">.</span><span class="n">merge_all</span><span class="p">()</span>
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<p>Batch and pad the source and target sequences</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">pad_sentence_batch</span><span class="p">(</span><span class="n">sentence_batch</span><span class="p">,</span> <span class="n">pad_int</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Pad sentences with &lt;PAD&gt; so that each sentence of a batch has the same length&quot;&quot;&quot;</span>
<span class="n">max_sentence</span> <span class="o">=</span> <span class="nb">max</span><span class="p">([</span><span class="nb">len</span><span class="p">(</span><span class="n">sentence</span><span class="p">)</span> <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="n">sentence_batch</span><span class="p">])</span>
<span class="k">return</span> <span class="p">[</span><span class="n">sentence</span> <span class="o">+</span> <span class="p">[</span><span class="n">pad_int</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="n">max_sentence</span> <span class="o">-</span> <span class="nb">len</span><span class="p">(</span><span class="n">sentence</span><span class="p">))</span> <span class="k">for</span> <span class="n">sentence</span> <span class="ow">in</span> <span class="n">sentence_batch</span><span class="p">]</span>
<span class="k">def</span> <span class="nf">get_batches</span><span class="p">(</span><span class="n">sources</span><span class="p">,</span> <span class="n">targets</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">source_pad_int</span><span class="p">,</span> <span class="n">target_pad_int</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Batch targets, sources, and the lengths of their sentences together&quot;&quot;&quot;</span>
<span class="k">for</span> <span class="n">batch_i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">sources</span><span class="p">)</span><span class="o">//</span><span class="n">batch_size</span><span class="p">):</span>
<span class="n">start_i</span> <span class="o">=</span> <span class="n">batch_i</span> <span class="o">*</span> <span class="n">batch_size</span>
<span class="c1"># Slice the right amount for the batch</span>
<span class="n">sources_batch</span> <span class="o">=</span> <span class="n">sources</span><span class="p">[</span><span class="n">start_i</span><span class="p">:</span><span class="n">start_i</span> <span class="o">+</span> <span class="n">batch_size</span><span class="p">]</span>
<span class="n">targets_batch</span> <span class="o">=</span> <span class="n">targets</span><span class="p">[</span><span class="n">start_i</span><span class="p">:</span><span class="n">start_i</span> <span class="o">+</span> <span class="n">batch_size</span><span class="p">]</span>
<span class="c1"># Pad</span>
<span class="n">pad_sources_batch</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">pad_sentence_batch</span><span class="p">(</span><span class="n">sources_batch</span><span class="p">,</span> <span class="n">source_pad_int</span><span class="p">))</span>
<span class="n">pad_targets_batch</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">pad_sentence_batch</span><span class="p">(</span><span class="n">targets_batch</span><span class="p">,</span> <span class="n">target_pad_int</span><span class="p">))</span>
<span class="c1"># Need the lengths for the _lengths parameters</span>
<span class="n">pad_targets_lengths</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">target</span> <span class="ow">in</span> <span class="n">pad_targets_batch</span><span class="p">:</span>
<span class="n">pad_targets_lengths</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">target</span><span class="p">))</span>
<span class="n">pad_source_lengths</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">source</span> <span class="ow">in</span> <span class="n">pad_sources_batch</span><span class="p">:</span>
<span class="n">pad_source_lengths</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">source</span><span class="p">))</span>
<span class="k">yield</span> <span class="n">pad_sources_batch</span><span class="p">,</span> <span class="n">pad_targets_batch</span><span class="p">,</span> <span class="n">pad_source_lengths</span><span class="p">,</span> <span class="n">pad_targets_lengths</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># write out the graph for tensorboard</span>
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">(</span><span class="n">graph</span><span class="o">=</span><span class="n">train_graph</span><span class="p">)</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
<span class="n">train_writer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">summary</span><span class="o">.</span><span class="n">FileWriter</span><span class="p">(</span><span class="n">LOG_PATH</span> <span class="o">+</span> <span class="s1">&#39;/train&#39;</span><span class="p">,</span> <span class="n">sess</span><span class="o">.</span><span class="n">graph</span><span class="p">)</span>
<span class="n">test_writer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">summary</span><span class="o">.</span><span class="n">FileWriter</span><span class="p">(</span><span class="n">LOG_PATH</span> <span class="o">+</span> <span class="s1">&#39;/test&#39;</span><span class="p">)</span>
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<h3 id="Train">Train<a class="anchor-link" href="#Train">&#182;</a></h3><p>Train the neural network on the preprocessed data. If you have a hard time getting a good loss, check the forms to see if anyone is having the same problem.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">get_accuracy</span><span class="p">(</span><span class="n">target</span><span class="p">,</span> <span class="n">logits</span><span class="p">,</span> <span class="n">_type</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Calculate accuracy</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">max_seq</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">target</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">logits</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
<span class="k">if</span> <span class="n">max_seq</span> <span class="o">-</span> <span class="n">target</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]:</span>
<span class="n">target</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">target</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="mi">0</span><span class="p">,</span><span class="n">max_seq</span> <span class="o">-</span> <span class="n">target</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">])],</span>
<span class="s1">&#39;constant&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="n">max_seq</span> <span class="o">-</span> <span class="n">logits</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]:</span>
<span class="n">logits</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">logits</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="mi">0</span><span class="p">,</span><span class="n">max_seq</span> <span class="o">-</span> <span class="n">logits</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">])],</span>
<span class="s1">&#39;constant&#39;</span><span class="p">)</span>
<span class="n">acc</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">np</span><span class="o">.</span><span class="n">equal</span><span class="p">(</span><span class="n">target</span><span class="p">,</span> <span class="n">logits</span><span class="p">))</span>
<span class="k">if</span> <span class="n">_type</span> <span class="ow">is</span> <span class="s1">&#39;train&#39;</span><span class="p">:</span>
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">name_scope</span><span class="p">(</span><span class="s1">&#39;optimization&#39;</span><span class="p">):</span>
<span class="n">summary</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Summary</span><span class="p">(</span><span class="n">value</span><span class="o">=</span><span class="p">[</span><span class="n">tf</span><span class="o">.</span><span class="n">Summary</span><span class="o">.</span><span class="n">Value</span><span class="p">(</span><span class="n">tag</span><span class="o">=</span><span class="s2">&quot;accuracy&quot;</span><span class="p">,</span> <span class="n">simple_value</span><span class="o">=</span><span class="n">acc</span><span class="p">)])</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">name_scope</span><span class="p">(</span><span class="s1">&#39;validation&#39;</span><span class="p">):</span>
<span class="n">summary</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Summary</span><span class="p">(</span><span class="n">value</span><span class="o">=</span><span class="p">[</span><span class="n">tf</span><span class="o">.</span><span class="n">Summary</span><span class="o">.</span><span class="n">Value</span><span class="p">(</span><span class="n">tag</span><span class="o">=</span><span class="s2">&quot;accuracy&quot;</span><span class="p">,</span> <span class="n">simple_value</span><span class="o">=</span><span class="n">acc</span><span class="p">)])</span>
<span class="k">return</span> <span class="n">summary</span><span class="p">,</span> <span class="n">acc</span>
<span class="c1"># Split data to training and validation sets</span>
<span class="n">train_source</span> <span class="o">=</span> <span class="n">source_int_text</span><span class="p">[</span><span class="n">batch_size</span><span class="p">:]</span>
<span class="n">train_target</span> <span class="o">=</span> <span class="n">target_int_text</span><span class="p">[</span><span class="n">batch_size</span><span class="p">:]</span>
<span class="n">valid_source</span> <span class="o">=</span> <span class="n">source_int_text</span><span class="p">[:</span><span class="n">batch_size</span><span class="p">]</span>
<span class="n">valid_target</span> <span class="o">=</span> <span class="n">target_int_text</span><span class="p">[:</span><span class="n">batch_size</span><span class="p">]</span>
<span class="p">(</span><span class="n">valid_sources_batch</span><span class="p">,</span> <span class="n">valid_targets_batch</span><span class="p">,</span> <span class="n">valid_sources_lengths</span><span class="p">,</span> <span class="n">valid_targets_lengths</span> <span class="p">)</span> <span class="o">=</span> <span class="nb">next</span><span class="p">(</span><span class="n">get_batches</span><span class="p">(</span><span class="n">valid_source</span><span class="p">,</span>
<span class="n">valid_target</span><span class="p">,</span>
<span class="n">batch_size</span><span class="p">,</span>
<span class="n">source_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;PAD&gt;&#39;</span><span class="p">],</span>
<span class="n">target_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;PAD&gt;&#39;</span><span class="p">]))</span>
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">(</span><span class="n">graph</span><span class="o">=</span><span class="n">train_graph</span><span class="p">)</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
<span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">tf</span><span class="o">.</span><span class="n">global_variables_initializer</span><span class="p">())</span>
<span class="n">saver</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">train</span><span class="o">.</span><span class="n">Saver</span><span class="p">(</span><span class="n">keep_checkpoint_every_n_hours</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
<span class="k">for</span> <span class="n">epoch_i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">epochs</span><span class="p">):</span>
<span class="n">n_batches</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">train_source</span><span class="p">)</span><span class="o">//</span><span class="n">batch_size</span>
<span class="k">for</span> <span class="n">batch_i</span><span class="p">,</span> <span class="p">(</span><span class="n">source_batch</span><span class="p">,</span> <span class="n">target_batch</span><span class="p">,</span> <span class="n">sources_lengths</span><span class="p">,</span> <span class="n">targets_lengths</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span>
<span class="n">get_batches</span><span class="p">(</span><span class="n">train_source</span><span class="p">,</span> <span class="n">train_target</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span>
<span class="n">source_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;PAD&gt;&#39;</span><span class="p">],</span>
<span class="n">target_vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;PAD&gt;&#39;</span><span class="p">])):</span>
<span class="n">iteration</span> <span class="o">=</span> <span class="n">epoch_i</span><span class="o">*</span><span class="n">n_batches</span> <span class="o">+</span> <span class="n">batch_i</span>
<span class="n">summary</span><span class="p">,</span> <span class="n">_</span><span class="p">,</span> <span class="n">loss</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span>
<span class="p">[</span><span class="n">merged</span><span class="p">,</span> <span class="n">train_op</span><span class="p">,</span> <span class="n">cost</span><span class="p">],</span>
<span class="p">{</span><span class="n">input_data</span><span class="p">:</span> <span class="n">source_batch</span><span class="p">,</span>
<span class="n">targets</span><span class="p">:</span> <span class="n">target_batch</span><span class="p">,</span>
<span class="n">lr</span><span class="p">:</span> <span class="n">learning_rate</span><span class="p">,</span>
<span class="n">target_sequence_length</span><span class="p">:</span> <span class="n">targets_lengths</span><span class="p">,</span>
<span class="n">source_sequence_length</span><span class="p">:</span> <span class="n">sources_lengths</span><span class="p">,</span>
<span class="n">keep_prob</span><span class="p">:</span> <span class="n">keep_probability</span><span class="p">})</span>
<span class="n">train_writer</span><span class="o">.</span><span class="n">add_summary</span><span class="p">(</span><span class="n">summary</span><span class="p">,</span> <span class="n">iteration</span><span class="p">)</span>
<span class="k">if</span> <span class="n">epoch_i</span> <span class="o">%</span> <span class="mi">5</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">saver</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">sess</span><span class="p">,</span> <span class="n">save_path</span> <span class="o">+</span> <span class="s1">&#39;ckpt&#39;</span><span class="p">,</span> <span class="n">global_step</span><span class="o">=</span><span class="n">epoch_i</span><span class="p">)</span>
<span class="k">if</span> <span class="n">batch_i</span> <span class="o">%</span> <span class="n">display_step</span> <span class="o">==</span> <span class="mi">0</span> <span class="ow">and</span> <span class="n">batch_i</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">batch_train_logits</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span>
<span class="n">inference_logits</span><span class="p">,</span>
<span class="p">{</span><span class="n">input_data</span><span class="p">:</span> <span class="n">source_batch</span><span class="p">,</span>
<span class="n">source_sequence_length</span><span class="p">:</span> <span class="n">sources_lengths</span><span class="p">,</span>
<span class="n">target_sequence_length</span><span class="p">:</span> <span class="n">targets_lengths</span><span class="p">,</span>
<span class="n">keep_prob</span><span class="p">:</span> <span class="mf">1.0</span><span class="p">})</span>
<span class="n">batch_valid_logits</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span>
<span class="n">inference_logits</span><span class="p">,</span>
<span class="p">{</span><span class="n">input_data</span><span class="p">:</span> <span class="n">valid_sources_batch</span><span class="p">,</span>
<span class="n">source_sequence_length</span><span class="p">:</span> <span class="n">valid_sources_lengths</span><span class="p">,</span>
<span class="n">target_sequence_length</span><span class="p">:</span> <span class="n">valid_targets_lengths</span><span class="p">,</span>
<span class="n">keep_prob</span><span class="p">:</span> <span class="mf">1.0</span><span class="p">})</span>
<span class="n">train_acc_sum</span><span class="p">,</span> <span class="n">train_acc</span> <span class="o">=</span> <span class="n">get_accuracy</span><span class="p">(</span><span class="n">target_batch</span><span class="p">,</span> <span class="n">batch_train_logits</span><span class="p">,</span> <span class="n">_type</span><span class="o">=</span><span class="s1">&#39;train&#39;</span><span class="p">)</span>
<span class="n">valid_acc_sum</span><span class="p">,</span> <span class="n">valid_acc</span> <span class="o">=</span> <span class="n">get_accuracy</span><span class="p">(</span><span class="n">valid_targets_batch</span><span class="p">,</span> <span class="n">batch_valid_logits</span><span class="p">,</span> <span class="n">_type</span><span class="o">=</span><span class="s1">&#39;test&#39;</span><span class="p">)</span>
<span class="n">train_writer</span><span class="o">.</span><span class="n">add_summary</span><span class="p">(</span><span class="n">train_acc_sum</span><span class="p">,</span> <span class="n">iteration</span><span class="p">)</span>
<span class="n">test_writer</span><span class="o">.</span><span class="n">add_summary</span><span class="p">(</span><span class="n">valid_acc_sum</span><span class="p">,</span> <span class="n">iteration</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Epoch </span><span class="si">{:&gt;3}</span><span class="s1"> Batch </span><span class="si">{:&gt;4}</span><span class="s1">/</span><span class="si">{}</span><span class="s1"> - Train Accuracy: </span><span class="si">{:&gt;6.4f}</span><span class="s1">, Validation Accuracy: </span><span class="si">{:&gt;6.4f}</span><span class="s1">, Loss: </span><span class="si">{:&gt;6.4f}</span><span class="s1">&#39;</span>
<span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">epoch_i</span><span class="p">,</span> <span class="n">batch_i</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">source_int_text</span><span class="p">)</span> <span class="o">//</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">train_acc</span><span class="p">,</span> <span class="n">valid_acc</span><span class="p">,</span> <span class="n">loss</span><span class="p">))</span>
<span class="c1"># Save Model</span>
<span class="n">saver</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">sess</span><span class="p">,</span> <span class="n">save_path</span> <span class="o">+</span> <span class="s1">&#39;last-ckpt&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Model Trained and Saved&#39;</span><span class="p">)</span>
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<pre>Epoch 0 Batch 10/538 - Train Accuracy: 0.3002, Validation Accuracy: 0.3885, Loss: 3.6955
Epoch 0 Batch 20/538 - Train Accuracy: 0.3960, Validation Accuracy: 0.4355, Loss: 2.9661
Epoch 0 Batch 30/538 - Train Accuracy: 0.4240, Validation Accuracy: 0.4792, Loss: 2.8062
Epoch 0 Batch 40/538 - Train Accuracy: 0.4979, Validation Accuracy: 0.4789, Loss: 2.3624
Epoch 0 Batch 50/538 - Train Accuracy: 0.4619, Validation Accuracy: 0.4980, Loss: 2.3190
Epoch 0 Batch 60/538 - Train Accuracy: 0.4660, Validation Accuracy: 0.5165, Loss: 2.1668
Epoch 0 Batch 70/538 - Train Accuracy: 0.4650, Validation Accuracy: 0.4949, Loss: 1.9192
Epoch 0 Batch 80/538 - Train Accuracy: 0.4391, Validation Accuracy: 0.4949, Loss: 1.8879
Epoch 0 Batch 90/538 - Train Accuracy: 0.4801, Validation Accuracy: 0.5039, Loss: 1.6966
Epoch 0 Batch 100/538 - Train Accuracy: 0.4752, Validation Accuracy: 0.5099, Loss: 1.6296
Epoch 0 Batch 110/538 - Train Accuracy: 0.4352, Validation Accuracy: 0.4862, Loss: 1.5980
Epoch 0 Batch 120/538 - Train Accuracy: 0.4332, Validation Accuracy: 0.4838, Loss: 1.4634
Epoch 0 Batch 130/538 - Train Accuracy: 0.4494, Validation Accuracy: 0.4920, Loss: 1.3480
Epoch 0 Batch 140/538 - Train Accuracy: 0.4623, Validation Accuracy: 0.5130, Loss: 1.3912
Epoch 0 Batch 150/538 - Train Accuracy: 0.4697, Validation Accuracy: 0.5064, Loss: 1.2529
Epoch 0 Batch 160/538 - Train Accuracy: 0.5378, Validation Accuracy: 0.5508, Loss: 1.1481
Epoch 0 Batch 170/538 - Train Accuracy: 0.5491, Validation Accuracy: 0.5581, Loss: 1.1118
Epoch 0 Batch 180/538 - Train Accuracy: 0.5534, Validation Accuracy: 0.5476, Loss: 1.0687
Epoch 0 Batch 190/538 - Train Accuracy: 0.5234, Validation Accuracy: 0.5506, Loss: 1.0583
Epoch 0 Batch 200/538 - Train Accuracy: 0.5455, Validation Accuracy: 0.5676, Loss: 0.9990
Epoch 0 Batch 210/538 - Train Accuracy: 0.5406, Validation Accuracy: 0.5680, Loss: 0.9413
Epoch 0 Batch 220/538 - Train Accuracy: 0.5461, Validation Accuracy: 0.5843, Loss: 0.9197
Epoch 0 Batch 230/538 - Train Accuracy: 0.5428, Validation Accuracy: 0.5879, Loss: 0.9156
Epoch 0 Batch 240/538 - Train Accuracy: 0.5592, Validation Accuracy: 0.5795, Loss: 0.9008
Epoch 0 Batch 250/538 - Train Accuracy: 0.5785, Validation Accuracy: 0.5959, Loss: 0.8396
Epoch 0 Batch 260/538 - Train Accuracy: 0.5858, Validation Accuracy: 0.5989, Loss: 0.8275
Epoch 0 Batch 270/538 - Train Accuracy: 0.5781, Validation Accuracy: 0.5953, Loss: 0.8222
Epoch 0 Batch 280/538 - Train Accuracy: 0.6267, Validation Accuracy: 0.6154, Loss: 0.7569
Epoch 0 Batch 290/538 - Train Accuracy: 0.5830, Validation Accuracy: 0.6152, Loss: 0.7818
Epoch 0 Batch 300/538 - Train Accuracy: 0.6114, Validation Accuracy: 0.6170, Loss: 0.7352
Epoch 0 Batch 310/538 - Train Accuracy: 0.6029, Validation Accuracy: 0.6183, Loss: 0.7385
Epoch 0 Batch 320/538 - Train Accuracy: 0.6151, Validation Accuracy: 0.6255, Loss: 0.7263
Epoch 0 Batch 330/538 - Train Accuracy: 0.6170, Validation Accuracy: 0.6175, Loss: 0.6908
Epoch 0 Batch 340/538 - Train Accuracy: 0.5717, Validation Accuracy: 0.6213, Loss: 0.7202
Epoch 0 Batch 350/538 - Train Accuracy: 0.6075, Validation Accuracy: 0.6262, Loss: 0.6923
Epoch 0 Batch 360/538 - Train Accuracy: 0.6197, Validation Accuracy: 0.6333, Loss: 0.6942
Epoch 0 Batch 370/538 - Train Accuracy: 0.5906, Validation Accuracy: 0.6261, Loss: 0.6843
Epoch 0 Batch 380/538 - Train Accuracy: 0.6012, Validation Accuracy: 0.6374, Loss: 0.6539
Epoch 0 Batch 390/538 - Train Accuracy: 0.6603, Validation Accuracy: 0.6362, Loss: 0.6228
Epoch 0 Batch 400/538 - Train Accuracy: 0.6224, Validation Accuracy: 0.6440, Loss: 0.6205
Epoch 0 Batch 410/538 - Train Accuracy: 0.6279, Validation Accuracy: 0.6499, Loss: 0.6378
Epoch 0 Batch 420/538 - Train Accuracy: 0.6564, Validation Accuracy: 0.6273, Loss: 0.5990
Epoch 0 Batch 430/538 - Train Accuracy: 0.6490, Validation Accuracy: 0.6410, Loss: 0.5944
Epoch 0 Batch 440/538 - Train Accuracy: 0.6680, Validation Accuracy: 0.6566, Loss: 0.6338
Epoch 0 Batch 450/538 - Train Accuracy: 0.6522, Validation Accuracy: 0.6367, Loss: 0.5990
Epoch 0 Batch 460/538 - Train Accuracy: 0.6263, Validation Accuracy: 0.6557, Loss: 0.5675
Epoch 0 Batch 470/538 - Train Accuracy: 0.6847, Validation Accuracy: 0.6632, Loss: 0.5484
Epoch 0 Batch 480/538 - Train Accuracy: 0.6702, Validation Accuracy: 0.6550, Loss: 0.5310
Epoch 0 Batch 490/538 - Train Accuracy: 0.6851, Validation Accuracy: 0.6616, Loss: 0.5299
Epoch 0 Batch 500/538 - Train Accuracy: 0.7125, Validation Accuracy: 0.6777, Loss: 0.4948
Epoch 0 Batch 510/538 - Train Accuracy: 0.7161, Validation Accuracy: 0.6928, Loss: 0.5111
Epoch 0 Batch 520/538 - Train Accuracy: 0.6756, Validation Accuracy: 0.6717, Loss: 0.5343
Epoch 0 Batch 530/538 - Train Accuracy: 0.6719, Validation Accuracy: 0.6916, Loss: 0.5309
Epoch 1 Batch 10/538 - Train Accuracy: 0.6598, Validation Accuracy: 0.6651, Loss: 0.5121
Epoch 1 Batch 20/538 - Train Accuracy: 0.7059, Validation Accuracy: 0.6916, Loss: 0.5024
Epoch 1 Batch 30/538 - Train Accuracy: 0.6945, Validation Accuracy: 0.7005, Loss: 0.4938
Epoch 1 Batch 40/538 - Train Accuracy: 0.7244, Validation Accuracy: 0.7205, Loss: 0.4183
Epoch 1 Batch 50/538 - Train Accuracy: 0.7258, Validation Accuracy: 0.7227, Loss: 0.4692
Epoch 1 Batch 60/538 - Train Accuracy: 0.7250, Validation Accuracy: 0.7232, Loss: 0.4479
Epoch 1 Batch 70/538 - Train Accuracy: 0.7342, Validation Accuracy: 0.7106, Loss: 0.4234
Epoch 1 Batch 80/538 - Train Accuracy: 0.6930, Validation Accuracy: 0.7134, Loss: 0.4511
Epoch 1 Batch 90/538 - Train Accuracy: 0.7254, Validation Accuracy: 0.7244, Loss: 0.4251
Epoch 1 Batch 100/538 - Train Accuracy: 0.7746, Validation Accuracy: 0.7441, Loss: 0.3935
Epoch 1 Batch 110/538 - Train Accuracy: 0.7248, Validation Accuracy: 0.7354, Loss: 0.4242
Epoch 1 Batch 120/538 - Train Accuracy: 0.7604, Validation Accuracy: 0.7431, Loss: 0.3804
Epoch 1 Batch 130/538 - Train Accuracy: 0.7779, Validation Accuracy: 0.7353, Loss: 0.3716
Epoch 1 Batch 140/538 - Train Accuracy: 0.7469, Validation Accuracy: 0.7411, Loss: 0.4122
Epoch 1 Batch 150/538 - Train Accuracy: 0.7646, Validation Accuracy: 0.7475, Loss: 0.3716
Epoch 1 Batch 160/538 - Train Accuracy: 0.7413, Validation Accuracy: 0.7488, Loss: 0.3484
Epoch 1 Batch 170/538 - Train Accuracy: 0.7809, Validation Accuracy: 0.7473, Loss: 0.3566
Epoch 1 Batch 180/538 - Train Accuracy: 0.7853, Validation Accuracy: 0.7710, Loss: 0.3506
Epoch 1 Batch 190/538 - Train Accuracy: 0.7781, Validation Accuracy: 0.7884, Loss: 0.3540
Epoch 1 Batch 200/538 - Train Accuracy: 0.7994, Validation Accuracy: 0.7729, Loss: 0.3315
Epoch 1 Batch 210/538 - Train Accuracy: 0.7920, Validation Accuracy: 0.7990, Loss: 0.3154
Epoch 1 Batch 220/538 - Train Accuracy: 0.7798, Validation Accuracy: 0.7930, Loss: 0.3094
Epoch 1 Batch 230/538 - Train Accuracy: 0.8049, Validation Accuracy: 0.7884, Loss: 0.3151
Epoch 1 Batch 240/538 - Train Accuracy: 0.8084, Validation Accuracy: 0.7898, Loss: 0.3224
Epoch 1 Batch 250/538 - Train Accuracy: 0.8141, Validation Accuracy: 0.7791, Loss: 0.3067
Epoch 1 Batch 260/538 - Train Accuracy: 0.8039, Validation Accuracy: 0.7994, Loss: 0.3074
Epoch 1 Batch 270/538 - Train Accuracy: 0.8023, Validation Accuracy: 0.8104, Loss: 0.2979
Epoch 1 Batch 280/538 - Train Accuracy: 0.8402, Validation Accuracy: 0.8226, Loss: 0.2656
Epoch 1 Batch 290/538 - Train Accuracy: 0.8338, Validation Accuracy: 0.8349, Loss: 0.2634
Epoch 1 Batch 300/538 - Train Accuracy: 0.8153, Validation Accuracy: 0.8221, Loss: 0.2657
Epoch 1 Batch 310/538 - Train Accuracy: 0.8773, Validation Accuracy: 0.8292, Loss: 0.2728
Epoch 1 Batch 320/538 - Train Accuracy: 0.8304, Validation Accuracy: 0.8379, Loss: 0.2527
Epoch 1 Batch 330/538 - Train Accuracy: 0.8346, Validation Accuracy: 0.8303, Loss: 0.2402
Epoch 1 Batch 340/538 - Train Accuracy: 0.8539, Validation Accuracy: 0.8530, Loss: 0.2550
Epoch 1 Batch 350/538 - Train Accuracy: 0.8564, Validation Accuracy: 0.8331, Loss: 0.2609
Epoch 1 Batch 360/538 - Train Accuracy: 0.8438, Validation Accuracy: 0.8459, Loss: 0.2485
Epoch 1 Batch 370/538 - Train Accuracy: 0.8422, Validation Accuracy: 0.8427, Loss: 0.2579
Epoch 1 Batch 380/538 - Train Accuracy: 0.8684, Validation Accuracy: 0.8526, Loss: 0.2178
Epoch 1 Batch 390/538 - Train Accuracy: 0.8994, Validation Accuracy: 0.8661, Loss: 0.2011
Epoch 1 Batch 400/538 - Train Accuracy: 0.8687, Validation Accuracy: 0.8601, Loss: 0.2281
Epoch 1 Batch 410/538 - Train Accuracy: 0.8727, Validation Accuracy: 0.8610, Loss: 0.2327
Epoch 1 Batch 420/538 - Train Accuracy: 0.8832, Validation Accuracy: 0.8642, Loss: 0.2038
Epoch 1 Batch 430/538 - Train Accuracy: 0.8641, Validation Accuracy: 0.8608, Loss: 0.2079
Epoch 1 Batch 440/538 - Train Accuracy: 0.8586, Validation Accuracy: 0.8743, Loss: 0.2274
Epoch 1 Batch 450/538 - Train Accuracy: 0.8555, Validation Accuracy: 0.8489, Loss: 0.2110
Epoch 1 Batch 460/538 - Train Accuracy: 0.8590, Validation Accuracy: 0.8661, Loss: 0.2009
Epoch 1 Batch 470/538 - Train Accuracy: 0.8910, Validation Accuracy: 0.8786, Loss: 0.1802
Epoch 1 Batch 480/538 - Train Accuracy: 0.9007, Validation Accuracy: 0.8564, Loss: 0.1726
Epoch 1 Batch 490/538 - Train Accuracy: 0.8858, Validation Accuracy: 0.8729, Loss: 0.1721
Epoch 1 Batch 500/538 - Train Accuracy: 0.9032, Validation Accuracy: 0.8848, Loss: 0.1630
Epoch 1 Batch 510/538 - Train Accuracy: 0.8923, Validation Accuracy: 0.8812, Loss: 0.1686
Epoch 1 Batch 520/538 - Train Accuracy: 0.8877, Validation Accuracy: 0.8807, Loss: 0.1807
Epoch 1 Batch 530/538 - Train Accuracy: 0.8719, Validation Accuracy: 0.8919, Loss: 0.1775
Epoch 2 Batch 10/538 - Train Accuracy: 0.8943, Validation Accuracy: 0.8833, Loss: 0.1768
Epoch 2 Batch 20/538 - Train Accuracy: 0.9003, Validation Accuracy: 0.8975, Loss: 0.1649
Epoch 2 Batch 30/538 - Train Accuracy: 0.8777, Validation Accuracy: 0.8794, Loss: 0.1737
Epoch 2 Batch 40/538 - Train Accuracy: 0.9002, Validation Accuracy: 0.8903, Loss: 0.1366
Epoch 2 Batch 50/538 - Train Accuracy: 0.8979, Validation Accuracy: 0.9062, Loss: 0.1507
Epoch 2 Batch 60/538 - Train Accuracy: 0.9189, Validation Accuracy: 0.8782, Loss: 0.1457
Epoch 2 Batch 70/538 - Train Accuracy: 0.9040, Validation Accuracy: 0.8890, Loss: 0.1353
Epoch 2 Batch 80/538 - Train Accuracy: 0.8957, Validation Accuracy: 0.8880, Loss: 0.1490
Epoch 2 Batch 90/538 - Train Accuracy: 0.8865, Validation Accuracy: 0.8857, Loss: 0.1564
Epoch 2 Batch 100/538 - Train Accuracy: 0.9148, Validation Accuracy: 0.8975, Loss: 0.1301
Epoch 2 Batch 110/538 - Train Accuracy: 0.9000, Validation Accuracy: 0.8961, Loss: 0.1463
Epoch 2 Batch 120/538 - Train Accuracy: 0.9225, Validation Accuracy: 0.8929, Loss: 0.1330
Epoch 2 Batch 130/538 - Train Accuracy: 0.9167, Validation Accuracy: 0.8938, Loss: 0.1224
Epoch 2 Batch 140/538 - Train Accuracy: 0.8850, Validation Accuracy: 0.9027, Loss: 0.1490
Epoch 2 Batch 150/538 - Train Accuracy: 0.9227, Validation Accuracy: 0.9036, Loss: 0.1205
Epoch 2 Batch 160/538 - Train Accuracy: 0.8951, Validation Accuracy: 0.9013, Loss: 0.1173
Epoch 2 Batch 170/538 - Train Accuracy: 0.9022, Validation Accuracy: 0.8952, Loss: 0.1259
Epoch 2 Batch 180/538 - Train Accuracy: 0.9142, Validation Accuracy: 0.9048, Loss: 0.1225
Epoch 2 Batch 190/538 - Train Accuracy: 0.8973, Validation Accuracy: 0.8922, Loss: 0.1413
Epoch 2 Batch 200/538 - Train Accuracy: 0.9115, Validation Accuracy: 0.8938, Loss: 0.1011
Epoch 2 Batch 210/538 - Train Accuracy: 0.8906, Validation Accuracy: 0.9109, Loss: 0.1198
Epoch 2 Batch 220/538 - Train Accuracy: 0.9049, Validation Accuracy: 0.8967, Loss: 0.1083
Epoch 2 Batch 230/538 - Train Accuracy: 0.9115, Validation Accuracy: 0.9043, Loss: 0.1163
Epoch 2 Batch 240/538 - Train Accuracy: 0.8994, Validation Accuracy: 0.9043, Loss: 0.1244
Epoch 2 Batch 250/538 - Train Accuracy: 0.9187, Validation Accuracy: 0.9041, Loss: 0.1043
Epoch 2 Batch 260/538 - Train Accuracy: 0.8854, Validation Accuracy: 0.9167, Loss: 0.1173
Epoch 2 Batch 270/538 - Train Accuracy: 0.9098, Validation Accuracy: 0.9023, Loss: 0.1026
Epoch 2 Batch 280/538 - Train Accuracy: 0.9276, Validation Accuracy: 0.9128, Loss: 0.1005
Epoch 2 Batch 290/538 - Train Accuracy: 0.9283, Validation Accuracy: 0.9109, Loss: 0.0956
Epoch 2 Batch 300/538 - Train Accuracy: 0.9031, Validation Accuracy: 0.9087, Loss: 0.1090
Epoch 2 Batch 310/538 - Train Accuracy: 0.9424, Validation Accuracy: 0.9032, Loss: 0.1099
Epoch 2 Batch 320/538 - Train Accuracy: 0.9044, Validation Accuracy: 0.9102, Loss: 0.1009
Epoch 2 Batch 330/538 - Train Accuracy: 0.9115, Validation Accuracy: 0.9155, Loss: 0.0948
Epoch 2 Batch 340/538 - Train Accuracy: 0.9164, Validation Accuracy: 0.9162, Loss: 0.0972
Epoch 2 Batch 350/538 - Train Accuracy: 0.9336, Validation Accuracy: 0.9197, Loss: 0.1178
Epoch 2 Batch 360/538 - Train Accuracy: 0.9156, Validation Accuracy: 0.9112, Loss: 0.1010
Epoch 2 Batch 370/538 - Train Accuracy: 0.9375, Validation Accuracy: 0.9240, Loss: 0.0992
Epoch 2 Batch 380/538 - Train Accuracy: 0.9258, Validation Accuracy: 0.9103, Loss: 0.0927
Epoch 2 Batch 390/538 - Train Accuracy: 0.9306, Validation Accuracy: 0.9194, Loss: 0.0812
Epoch 2 Batch 400/538 - Train Accuracy: 0.9280, Validation Accuracy: 0.9132, Loss: 0.0971
Epoch 2 Batch 410/538 - Train Accuracy: 0.9201, Validation Accuracy: 0.9215, Loss: 0.1057
Epoch 2 Batch 420/538 - Train Accuracy: 0.9252, Validation Accuracy: 0.9132, Loss: 0.0920
Epoch 2 Batch 430/538 - Train Accuracy: 0.9156, Validation Accuracy: 0.9329, Loss: 0.0862
Epoch 2 Batch 440/538 - Train Accuracy: 0.9209, Validation Accuracy: 0.9165, Loss: 0.0949
Epoch 2 Batch 450/538 - Train Accuracy: 0.9089, Validation Accuracy: 0.9048, Loss: 0.1095
Epoch 2 Batch 460/538 - Train Accuracy: 0.9042, Validation Accuracy: 0.9219, Loss: 0.0971
Epoch 2 Batch 470/538 - Train Accuracy: 0.9312, Validation Accuracy: 0.9066, Loss: 0.0836
Epoch 2 Batch 480/538 - Train Accuracy: 0.9399, Validation Accuracy: 0.9205, Loss: 0.0793
Epoch 2 Batch 490/538 - Train Accuracy: 0.9373, Validation Accuracy: 0.9297, Loss: 0.0801
Epoch 2 Batch 500/538 - Train Accuracy: 0.9368, Validation Accuracy: 0.9114, Loss: 0.0709
Epoch 2 Batch 510/538 - Train Accuracy: 0.9474, Validation Accuracy: 0.9283, Loss: 0.0799
Epoch 2 Batch 520/538 - Train Accuracy: 0.9313, Validation Accuracy: 0.9176, Loss: 0.0847
Epoch 2 Batch 530/538 - Train Accuracy: 0.9039, Validation Accuracy: 0.9155, Loss: 0.0907
Epoch 3 Batch 10/538 - Train Accuracy: 0.9393, Validation Accuracy: 0.9096, Loss: 0.0886
Epoch 3 Batch 20/538 - Train Accuracy: 0.9271, Validation Accuracy: 0.9194, Loss: 0.0780
Epoch 3 Batch 30/538 - Train Accuracy: 0.9258, Validation Accuracy: 0.9027, Loss: 0.0883
Epoch 3 Batch 40/538 - Train Accuracy: 0.9295, Validation Accuracy: 0.9228, Loss: 0.0671
Epoch 3 Batch 50/538 - Train Accuracy: 0.9236, Validation Accuracy: 0.9137, Loss: 0.0772
Epoch 3 Batch 60/538 - Train Accuracy: 0.9363, Validation Accuracy: 0.9238, Loss: 0.0739
Epoch 3 Batch 70/538 - Train Accuracy: 0.9237, Validation Accuracy: 0.9215, Loss: 0.0715
Epoch 3 Batch 80/538 - Train Accuracy: 0.9256, Validation Accuracy: 0.9196, Loss: 0.0774
Epoch 3 Batch 90/538 - Train Accuracy: 0.9362, Validation Accuracy: 0.9132, Loss: 0.0828
Epoch 3 Batch 100/538 - Train Accuracy: 0.9453, Validation Accuracy: 0.9189, Loss: 0.0651
Epoch 3 Batch 110/538 - Train Accuracy: 0.9301, Validation Accuracy: 0.9206, Loss: 0.0758
Epoch 3 Batch 120/538 - Train Accuracy: 0.9428, Validation Accuracy: 0.9244, Loss: 0.0613
Epoch 3 Batch 130/538 - Train Accuracy: 0.9384, Validation Accuracy: 0.9256, Loss: 0.0720
Epoch 3 Batch 140/538 - Train Accuracy: 0.9145, Validation Accuracy: 0.9267, Loss: 0.0938
Epoch 3 Batch 150/538 - Train Accuracy: 0.9373, Validation Accuracy: 0.9366, Loss: 0.0668
Epoch 3 Batch 160/538 - Train Accuracy: 0.9202, Validation Accuracy: 0.9210, Loss: 0.0660
Epoch 3 Batch 170/538 - Train Accuracy: 0.9213, Validation Accuracy: 0.9288, Loss: 0.0789
Epoch 3 Batch 180/538 - Train Accuracy: 0.9343, Validation Accuracy: 0.9292, Loss: 0.0717
Epoch 3 Batch 190/538 - Train Accuracy: 0.9081, Validation Accuracy: 0.9174, Loss: 0.0896
Epoch 3 Batch 200/538 - Train Accuracy: 0.9447, Validation Accuracy: 0.9258, Loss: 0.0563
Epoch 3 Batch 210/538 - Train Accuracy: 0.9355, Validation Accuracy: 0.9412, Loss: 0.0726
Epoch 3 Batch 220/538 - Train Accuracy: 0.9167, Validation Accuracy: 0.9334, Loss: 0.0654
Epoch 3 Batch 230/538 - Train Accuracy: 0.9230, Validation Accuracy: 0.9192, Loss: 0.0697
Epoch 3 Batch 240/538 - Train Accuracy: 0.9172, Validation Accuracy: 0.9272, Loss: 0.0713
Epoch 3 Batch 250/538 - Train Accuracy: 0.9494, Validation Accuracy: 0.9274, Loss: 0.0620
Epoch 3 Batch 260/538 - Train Accuracy: 0.9172, Validation Accuracy: 0.9219, Loss: 0.0720
Epoch 3 Batch 270/538 - Train Accuracy: 0.9465, Validation Accuracy: 0.9347, Loss: 0.0710
Epoch 3 Batch 280/538 - Train Accuracy: 0.9488, Validation Accuracy: 0.9086, Loss: 0.0637
Epoch 3 Batch 290/538 - Train Accuracy: 0.9414, Validation Accuracy: 0.9258, Loss: 0.0536
Epoch 3 Batch 300/538 - Train Accuracy: 0.9362, Validation Accuracy: 0.9196, Loss: 0.0745
Epoch 3 Batch 310/538 - Train Accuracy: 0.9510, Validation Accuracy: 0.9286, Loss: 0.0677
Epoch 3 Batch 320/538 - Train Accuracy: 0.9353, Validation Accuracy: 0.9386, Loss: 0.0688
Epoch 3 Batch 330/538 - Train Accuracy: 0.9334, Validation Accuracy: 0.9338, Loss: 0.0605
Epoch 3 Batch 340/538 - Train Accuracy: 0.9221, Validation Accuracy: 0.9276, Loss: 0.0685
Epoch 3 Batch 350/538 - Train Accuracy: 0.9399, Validation Accuracy: 0.9332, Loss: 0.0599
Epoch 3 Batch 360/538 - Train Accuracy: 0.9377, Validation Accuracy: 0.9458, Loss: 0.0652
Epoch 3 Batch 370/538 - Train Accuracy: 0.9437, Validation Accuracy: 0.9284, Loss: 0.0641
Epoch 3 Batch 380/538 - Train Accuracy: 0.9459, Validation Accuracy: 0.9398, Loss: 0.0615
Epoch 3 Batch 390/538 - Train Accuracy: 0.9468, Validation Accuracy: 0.9490, Loss: 0.0536
Epoch 3 Batch 400/538 - Train Accuracy: 0.9464, Validation Accuracy: 0.9304, Loss: 0.0583
Epoch 3 Batch 410/538 - Train Accuracy: 0.9502, Validation Accuracy: 0.9426, Loss: 0.0672
Epoch 3 Batch 420/538 - Train Accuracy: 0.9510, Validation Accuracy: 0.9416, Loss: 0.0593
Epoch 3 Batch 430/538 - Train Accuracy: 0.9355, Validation Accuracy: 0.9370, Loss: 0.0615
Epoch 3 Batch 440/538 - Train Accuracy: 0.9391, Validation Accuracy: 0.9329, Loss: 0.0732
Epoch 3 Batch 450/538 - Train Accuracy: 0.9258, Validation Accuracy: 0.9483, Loss: 0.0722
Epoch 3 Batch 460/538 - Train Accuracy: 0.9278, Validation Accuracy: 0.9336, Loss: 0.0666
Epoch 3 Batch 470/538 - Train Accuracy: 0.9524, Validation Accuracy: 0.9382, Loss: 0.0591
Epoch 3 Batch 480/538 - Train Accuracy: 0.9464, Validation Accuracy: 0.9288, Loss: 0.0622
Epoch 3 Batch 490/538 - Train Accuracy: 0.9420, Validation Accuracy: 0.9208, Loss: 0.0564
Epoch 3 Batch 500/538 - Train Accuracy: 0.9673, Validation Accuracy: 0.9219, Loss: 0.0608
Epoch 3 Batch 510/538 - Train Accuracy: 0.9487, Validation Accuracy: 0.9396, Loss: 0.0625
Epoch 3 Batch 520/538 - Train Accuracy: 0.9352, Validation Accuracy: 0.9231, Loss: 0.0610
Epoch 3 Batch 530/538 - Train Accuracy: 0.9221, Validation Accuracy: 0.9405, Loss: 0.0664
Epoch 4 Batch 10/538 - Train Accuracy: 0.9418, Validation Accuracy: 0.9480, Loss: 0.0639
Epoch 4 Batch 20/538 - Train Accuracy: 0.9501, Validation Accuracy: 0.9364, Loss: 0.0593
Epoch 4 Batch 30/538 - Train Accuracy: 0.9477, Validation Accuracy: 0.9409, Loss: 0.0579
Epoch 4 Batch 40/538 - Train Accuracy: 0.9411, Validation Accuracy: 0.9490, Loss: 0.0446
Epoch 4 Batch 50/538 - Train Accuracy: 0.9486, Validation Accuracy: 0.9398, Loss: 0.0528
Epoch 4 Batch 60/538 - Train Accuracy: 0.9490, Validation Accuracy: 0.9338, Loss: 0.0595
Epoch 4 Batch 70/538 - Train Accuracy: 0.9611, Validation Accuracy: 0.9345, Loss: 0.0431
Epoch 4 Batch 80/538 - Train Accuracy: 0.9496, Validation Accuracy: 0.9467, Loss: 0.0569
Epoch 4 Batch 90/538 - Train Accuracy: 0.9548, Validation Accuracy: 0.9545, Loss: 0.0565
Epoch 4 Batch 100/538 - Train Accuracy: 0.9693, Validation Accuracy: 0.9416, Loss: 0.0468
Epoch 4 Batch 110/538 - Train Accuracy: 0.9477, Validation Accuracy: 0.9325, Loss: 0.0519
Epoch 4 Batch 120/538 - Train Accuracy: 0.9596, Validation Accuracy: 0.9471, Loss: 0.0380
Epoch 4 Batch 130/538 - Train Accuracy: 0.9542, Validation Accuracy: 0.9373, Loss: 0.0409
Epoch 4 Batch 140/538 - Train Accuracy: 0.9229, Validation Accuracy: 0.9272, Loss: 0.0687
Epoch 4 Batch 150/538 - Train Accuracy: 0.9510, Validation Accuracy: 0.9471, Loss: 0.0444
Epoch 4 Batch 160/538 - Train Accuracy: 0.9221, Validation Accuracy: 0.9252, Loss: 0.0451
Epoch 4 Batch 170/538 - Train Accuracy: 0.9345, Validation Accuracy: 0.9460, Loss: 0.0549
Epoch 4 Batch 180/538 - Train Accuracy: 0.9420, Validation Accuracy: 0.9416, Loss: 0.0512
Epoch 4 Batch 190/538 - Train Accuracy: 0.9241, Validation Accuracy: 0.9267, Loss: 0.0738
Epoch 4 Batch 200/538 - Train Accuracy: 0.9672, Validation Accuracy: 0.9430, Loss: 0.0420
Epoch 4 Batch 210/538 - Train Accuracy: 0.9472, Validation Accuracy: 0.9467, Loss: 0.0544
Epoch 4 Batch 220/538 - Train Accuracy: 0.9384, Validation Accuracy: 0.9377, Loss: 0.0508
Epoch 4 Batch 230/538 - Train Accuracy: 0.9449, Validation Accuracy: 0.9403, Loss: 0.0480
Epoch 4 Batch 240/538 - Train Accuracy: 0.9383, Validation Accuracy: 0.9325, Loss: 0.0475
Epoch 4 Batch 250/538 - Train Accuracy: 0.9588, Validation Accuracy: 0.9434, Loss: 0.0499
Epoch 4 Batch 260/538 - Train Accuracy: 0.9340, Validation Accuracy: 0.9384, Loss: 0.0525
Epoch 4 Batch 270/538 - Train Accuracy: 0.9498, Validation Accuracy: 0.9400, Loss: 0.0432
Epoch 4 Batch 280/538 - Train Accuracy: 0.9511, Validation Accuracy: 0.9373, Loss: 0.0405
Epoch 4 Batch 290/538 - Train Accuracy: 0.9777, Validation Accuracy: 0.9345, Loss: 0.0382
Epoch 4 Batch 300/538 - Train Accuracy: 0.9520, Validation Accuracy: 0.9569, Loss: 0.0495
Epoch 4 Batch 310/538 - Train Accuracy: 0.9652, Validation Accuracy: 0.9570, Loss: 0.0517
Epoch 4 Batch 320/538 - Train Accuracy: 0.9528, Validation Accuracy: 0.9485, Loss: 0.0477
Epoch 4 Batch 330/538 - Train Accuracy: 0.9621, Validation Accuracy: 0.9474, Loss: 0.0446
Epoch 4 Batch 340/538 - Train Accuracy: 0.9430, Validation Accuracy: 0.9425, Loss: 0.0472
Epoch 4 Batch 350/538 - Train Accuracy: 0.9555, Validation Accuracy: 0.9501, Loss: 0.0529
Epoch 4 Batch 360/538 - Train Accuracy: 0.9471, Validation Accuracy: 0.9567, Loss: 0.0441
Epoch 4 Batch 370/538 - Train Accuracy: 0.9637, Validation Accuracy: 0.9501, Loss: 0.0498
Epoch 4 Batch 380/538 - Train Accuracy: 0.9516, Validation Accuracy: 0.9565, Loss: 0.0451
Epoch 4 Batch 390/538 - Train Accuracy: 0.9461, Validation Accuracy: 0.9522, Loss: 0.0348
Epoch 4 Batch 400/538 - Train Accuracy: 0.9680, Validation Accuracy: 0.9600, Loss: 0.0426
Epoch 4 Batch 410/538 - Train Accuracy: 0.9588, Validation Accuracy: 0.9494, Loss: 0.0504
Epoch 4 Batch 420/538 - Train Accuracy: 0.9525, Validation Accuracy: 0.9542, Loss: 0.0439
Epoch 4 Batch 430/538 - Train Accuracy: 0.9389, Validation Accuracy: 0.9517, Loss: 0.0446
Epoch 4 Batch 440/538 - Train Accuracy: 0.9537, Validation Accuracy: 0.9510, Loss: 0.0538
Epoch 4 Batch 450/538 - Train Accuracy: 0.9299, Validation Accuracy: 0.9513, Loss: 0.0570
Epoch 4 Batch 460/538 - Train Accuracy: 0.9472, Validation Accuracy: 0.9576, Loss: 0.0453
Epoch 4 Batch 470/538 - Train Accuracy: 0.9550, Validation Accuracy: 0.9547, Loss: 0.0474
Epoch 4 Batch 480/538 - Train Accuracy: 0.9678, Validation Accuracy: 0.9487, Loss: 0.0453
Epoch 4 Batch 490/538 - Train Accuracy: 0.9528, Validation Accuracy: 0.9556, Loss: 0.0409
Epoch 4 Batch 500/538 - Train Accuracy: 0.9686, Validation Accuracy: 0.9627, Loss: 0.0355
Epoch 4 Batch 510/538 - Train Accuracy: 0.9513, Validation Accuracy: 0.9480, Loss: 0.0488
Epoch 4 Batch 520/538 - Train Accuracy: 0.9535, Validation Accuracy: 0.9565, Loss: 0.0444
Epoch 4 Batch 530/538 - Train Accuracy: 0.9363, Validation Accuracy: 0.9498, Loss: 0.0512
Model Trained and Saved
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<h3 id="Save-Parameters">Save Parameters<a class="anchor-link" href="#Save-Parameters">&#182;</a></h3><p>Save the <code>batch_size</code> and <code>save_path</code> parameters for inference.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
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<span class="c1"># Save parameters for checkpoint</span>
<span class="n">helper</span><span class="o">.</span><span class="n">save_params</span><span class="p">(</span><span class="n">save_path</span><span class="p">)</span>
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<h1 id="Checkpoint">Checkpoint<a class="anchor-link" href="#Checkpoint">&#182;</a></h1>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">tensorflow</span> <span class="k">as</span> <span class="nn">tf</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">helper</span>
<span class="kn">import</span> <span class="nn">problem_unittests</span> <span class="k">as</span> <span class="nn">tests</span>
<span class="n">_</span><span class="p">,</span> <span class="p">(</span><span class="n">source_vocab_to_int</span><span class="p">,</span> <span class="n">target_vocab_to_int</span><span class="p">),</span> <span class="p">(</span><span class="n">source_int_to_vocab</span><span class="p">,</span> <span class="n">target_int_to_vocab</span><span class="p">)</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">load_preprocess</span><span class="p">()</span>
<span class="n">load_path</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">load_params</span><span class="p">()</span>
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<h2 id="Sentence-to-Sequence">Sentence to Sequence<a class="anchor-link" href="#Sentence-to-Sequence">&#182;</a></h2><p>To feed a sentence into the model for translation, you first need to preprocess it. Implement the function <code>sentence_to_seq()</code> to preprocess new sentences.</p>
<ul>
<li>Convert the sentence to lowercase</li>
<li>Convert words into ids using <code>vocab_to_int</code><ul>
<li>Convert words not in the vocabulary, to the <code>&lt;UNK&gt;</code> word id.</li>
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</li>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">sentence_to_seq</span><span class="p">(</span><span class="n">sentence</span><span class="p">,</span> <span class="n">vocab_to_int</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Convert a sentence to a sequence of ids</span>
<span class="sd"> :param sentence: String</span>
<span class="sd"> :param vocab_to_int: Dictionary to go from the words to an id</span>
<span class="sd"> :return: List of word ids</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="p">[</span><span class="n">vocab_to_int</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">word</span><span class="p">,</span> <span class="n">vocab_to_int</span><span class="p">[</span><span class="s1">&#39;&lt;UNK&gt;&#39;</span><span class="p">])</span> <span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">sentence</span><span class="o">.</span><span class="n">lower</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>
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<span class="n">tests</span><span class="o">.</span><span class="n">test_sentence_to_seq</span><span class="p">(</span><span class="n">sentence_to_seq</span><span class="p">)</span>
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<pre>Tests Passed
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<h2 id="Translate">Translate<a class="anchor-link" href="#Translate">&#182;</a></h2><p>This will translate <code>translate_sentence</code> from English to French.</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">translate_sentence</span> <span class="o">=</span> <span class="s1">&#39;he saw a old yellow truck .&#39;</span>
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<span class="n">translate_sentence</span> <span class="o">=</span> <span class="n">sentence_to_seq</span><span class="p">(</span><span class="n">translate_sentence</span><span class="p">,</span> <span class="n">source_vocab_to_int</span><span class="p">)</span>
<span class="n">loaded_graph</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">Graph</span><span class="p">()</span>
<span class="k">with</span> <span class="n">tf</span><span class="o">.</span><span class="n">Session</span><span class="p">(</span><span class="n">graph</span><span class="o">=</span><span class="n">loaded_graph</span><span class="p">)</span> <span class="k">as</span> <span class="n">sess</span><span class="p">:</span>
<span class="c1"># Load saved model</span>
<span class="n">loader</span> <span class="o">=</span> <span class="n">tf</span><span class="o">.</span><span class="n">train</span><span class="o">.</span><span class="n">import_meta_graph</span><span class="p">(</span><span class="n">load_path</span> <span class="o">+</span> <span class="s1">&#39;last-ckpt.meta&#39;</span><span class="p">)</span>
<span class="n">loader</span><span class="o">.</span><span class="n">restore</span><span class="p">(</span><span class="n">sess</span><span class="p">,</span> <span class="n">load_path</span> <span class="o">+</span> <span class="s1">&#39;last-ckpt&#39;</span><span class="p">)</span>
<span class="n">input_data</span> <span class="o">=</span> <span class="n">loaded_graph</span><span class="o">.</span><span class="n">get_tensor_by_name</span><span class="p">(</span><span class="s1">&#39;input:0&#39;</span><span class="p">)</span>
<span class="n">logits</span> <span class="o">=</span> <span class="n">loaded_graph</span><span class="o">.</span><span class="n">get_tensor_by_name</span><span class="p">(</span><span class="s1">&#39;predictions:0&#39;</span><span class="p">)</span>
<span class="n">target_sequence_length</span> <span class="o">=</span> <span class="n">loaded_graph</span><span class="o">.</span><span class="n">get_tensor_by_name</span><span class="p">(</span><span class="s1">&#39;target_sequence_length:0&#39;</span><span class="p">)</span>
<span class="n">source_sequence_length</span> <span class="o">=</span> <span class="n">loaded_graph</span><span class="o">.</span><span class="n">get_tensor_by_name</span><span class="p">(</span><span class="s1">&#39;source_sequence_length:0&#39;</span><span class="p">)</span>
<span class="n">keep_prob</span> <span class="o">=</span> <span class="n">loaded_graph</span><span class="o">.</span><span class="n">get_tensor_by_name</span><span class="p">(</span><span class="s1">&#39;keep_prob:0&#39;</span><span class="p">)</span>
<span class="n">translate_logits</span> <span class="o">=</span> <span class="n">sess</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="n">logits</span><span class="p">,</span> <span class="p">{</span><span class="n">input_data</span><span class="p">:</span> <span class="p">[</span><span class="n">translate_sentence</span><span class="p">]</span><span class="o">*</span><span class="n">batch_size</span><span class="p">,</span>
<span class="n">target_sequence_length</span><span class="p">:</span> <span class="p">[</span><span class="nb">len</span><span class="p">(</span><span class="n">translate_sentence</span><span class="p">)</span><span class="o">*</span><span class="mi">2</span><span class="p">]</span><span class="o">*</span><span class="n">batch_size</span><span class="p">,</span>
<span class="n">source_sequence_length</span><span class="p">:</span> <span class="p">[</span><span class="nb">len</span><span class="p">(</span><span class="n">translate_sentence</span><span class="p">)]</span><span class="o">*</span><span class="n">batch_size</span><span class="p">,</span>
<span class="n">keep_prob</span><span class="p">:</span> <span class="mf">1.0</span><span class="p">})[</span><span class="mi">0</span><span class="p">]</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Input&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39; Word Ids: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">([</span><span class="n">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">translate_sentence</span><span class="p">]))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39; English Words: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">([</span><span class="n">source_int_to_vocab</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">translate_sentence</span><span class="p">]))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">Prediction&#39;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39; Word Ids: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">([</span><span class="n">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">translate_logits</span><span class="p">]))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39; French Words: </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="s2">&quot; &quot;</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="n">target_int_to_vocab</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">translate_logits</span><span class="p">])))</span>
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<pre>INFO:tensorflow:Restoring parameters from /output/run_1/checkpoints/last-ckpt
Input
Word Ids: [161, 156, 158, 103, 42, 112, 169]
English Words: [&#39;he&#39;, &#39;saw&#39;, &#39;a&#39;, &#39;old&#39;, &#39;yellow&#39;, &#39;truck&#39;, &#39;.&#39;]
Prediction
Word Ids: [224, 237, 230, 340, 282, 78, 64, 1]
French Words: il a un vieux camion jaune . &lt;EOS&gt;
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<h2 id="Imperfect-Translation">Imperfect Translation<a class="anchor-link" href="#Imperfect-Translation">&#182;</a></h2><p>You might notice that some sentences translate better than others. Since the dataset you're using only has a vocabulary of 227 English words of the thousands that you use, you're only going to see good results using these words. For this project, you don't need a perfect translation. However, if you want to create a better translation model, you'll need better data.</p>
<p>You can train on the <a href="http://www.statmt.org/wmt10/training-giga-fren.tar">WMT10 French-English corpus</a>. This dataset has more vocabulary and richer in topics discussed. However, this will take you days to train, so make sure you've a GPU and the neural network is performing well on dataset we provided. Just make sure you play with the WMT10 corpus after you've submitted this project.</p>
<h2 id="Submitting-This-Project">Submitting This Project<a class="anchor-link" href="#Submitting-This-Project">&#182;</a></h2><p>When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_language_translation.ipynb" and save it as a HTML file under "File" -&gt; "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.</p>
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