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this.weblasTensor)}},{key:"replaceTensorData",value:function(e){if(e&&e.length&&e instanceof this._type)this.tensor.data=e;else{if(!(e&&e.length&&e instanceof Array))throw new Error("[Tensor] invalid input for replaceTensorData method.");this.tensor.data=new this._type(e)}}}]),e}();n.default=m},function(e,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var t=document.createElement("canvas"),a=t.getContext("webgl")||t.getContext("experimental-webgl");if(!a)throw new Error("Unable to initialize WebGL. Your browser may not support it.");n.MAX_TEXTURE_SIZE=a.getParameter(a.MAX_TEXTURE_SIZE)},function(e,n,t){n=e.exports=t(2)(),n.push([e.i,".demo-card {\n  width: 100%;\n  max-width: 1000px;\n  margin: 30px auto;\n  background: white;\n  border: 2px solid white;\n  border-radius: 10px;\n  -webkit-transition: border-color 0.2s ease-in;\n  transition: border-color 0.2s ease-in;\n  cursor: default;\n  -webkit-user-select: none;\n     -moz-user-select: none;\n      -ms-user-select: none;\n          user-select: none;\n  display: -webkit-box;\n  display: -ms-flexbox;\n  display: flex;\n  -webkit-box-orient: horizontal;\n  -webkit-box-direction: normal;\n      -ms-flex-direction: row;\n          flex-direction: row;\n  -webkit-box-align: center;\n      -ms-flex-align: center;\n          align-items: center;\n  -webkit-box-pack: justify;\n      -ms-flex-pack: justify;\n          justify-content: space-between;\n  overflow: hidden;\n}\n.demo-card .demo-card-heading {\n  -webkit-box-flex: 1;\n      -ms-flex: 1;\n          flex: 1;\n  padding: 20px;\n  text-align: center;\n  color: #69707a;\n  font-family: 'Fira Sans',sans-serif;\n  font-size: 20px;\n  -webkit-transition: color 0.2s ease-in;\n  transition: color 0.2s ease-in;\n}\n.demo-card .demo-card-image img {\n  width: 200px;\n  height: auto;\n}\n.demo-card:hover {\n  border-color: #1BBC9B;\n  cursor: pointer;\n}\n.demo-card:hover .demo-card-heading {\n  color: #1BBC9B;\n}\n",""])},function(e,n,t){n=e.exports=t(2)(),n.push([e.i,".demo.imdb-bidirectional-lstm .column {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n}\n.demo.imdb-bidirectional-lstm .column.input-column {\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n}\n.demo.imdb-bidirectional-lstm .column.input-column .input-container {\n    text-align: right;\n    margin: 5px 5px 5px 20px;\n    position: relative;\n}\n.demo.imdb-bidirectional-lstm .column.input-column .input-container .input-label {\n    font-family: 'Nothing You Could Do',cursive;\n    font-size: 18px;\n    color: #69707a;\n    text-align: left;\n}\n.demo.imdb-bidirectional-lstm .column.input-column .input-container .mdl-textfield {\n    width: 550px;\n}\n.demo.imdb-bidirectional-lstm .column.input-column .input-container .mdl-textfield textarea {\n    color: #393E46;\n    font-family: 'Fira Sans',sans-serif;\n    font-size: 16px;\n    padding: 10px;\n}\n.demo.imdb-bidirectional-lstm .column.input-column .input-container .input-buttons {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: justify;\n        -ms-flex-pack: justify;\n            justify-content: space-between;\n}\n.demo.imdb-bidirectional-lstm .column.input-column .input-container .input-buttons .input-load-button, .demo.imdb-bidirectional-lstm .column.input-column .input-container .input-buttons .input-clear-button {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    color: #69707a;\n    -webkit-transition: color 0.2s ease-in;\n    transition: color 0.2s ease-in;\n}\n.demo.imdb-bidirectional-lstm .column.input-column .input-container .input-buttons .input-load-button .material-icons, .demo.imdb-bidirectional-lstm .column.input-column .input-container .input-buttons .input-clear-button .material-icons {\n    margin-right: 5px;\n}\n.demo.imdb-bidirectional-lstm .column.input-column .input-container .input-buttons .input-load-button:hover, .demo.imdb-bidirectional-lstm .column.input-column .input-container .input-buttons .input-clear-button:hover {\n    color: rgba(27, 188, 155, 0.3);\n    cursor: pointer;\n}\n.demo.imdb-bidirectional-lstm .column.input-column .input-container .input-buttons .input-load-button {}\n.demo.imdb-bidirectional-lstm .column.input-column .input-container .input-buttons .input-load-button:hover {\n    color: #1BBC9B;\n}\n.demo.imdb-bidirectional-lstm .column.output-column {\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n}\n.demo.imdb-bidirectional-lstm .column.output-column .output {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: vertical;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: column;\n            flex-direction: column;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n    -webkit-user-select: none;\n       -moz-user-select: none;\n        -ms-user-select: none;\n            user-select: none;\n    cursor: default;\n}\n.demo.imdb-bidirectional-lstm .column.output-column .output .output-heading {\n    max-width: 200px;\n    color: #69707a;\n    font-family: 'Share Tech Mono',sans-serif;\n    font-size: 16px;\n    margin: 10px;\n}\n.demo.imdb-bidirectional-lstm .column.output-column .output .output-heading span.output-label.positive {\n    color: #1BBC9B;\n}\n.demo.imdb-bidirectional-lstm .column.output-column .output .output-heading span.output-label.negative {\n    color: #F22613;\n}\n.demo.imdb-bidirectional-lstm .column.output-column .output .output-value {\n    -webkit-transition: color 0.4s ease-in-out;\n    transition: color 0.4s ease-in-out;\n    font-family: 'Share Tech Mono',sans-serif;\n    font-size: 42px;\n    margin: 10px;\n}\n.demo.imdb-bidirectional-lstm .architecture-container {\n    position: relative;\n    width: 710px;\n    margin: 0 auto;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: horizontal;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: row;\n            flex-direction: row;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n}\n.demo.imdb-bidirectional-lstm .architecture-container .bg-line {\n    position: absolute;\n    top: 50%;\n    left: 0;\n    height: 5px;\n    width: 100%;\n    background: white;\n}\n.demo.imdb-bidirectional-lstm .architecture-container .layer {\n    display: inline-block;\n    width: 170px;\n    margin-right: 10px;\n    background: white;\n    border-radius: 5px;\n    padding: 2px 10px 0px;\n    z-index: 1;\n}\n.demo.imdb-bidirectional-lstm .architecture-container .layer .layer-class-name {\n    color: #1BBC9B;\n    font-size: 14px;\n    font-weight: bold;\n}\n.demo.imdb-bidirectional-lstm .architecture-container .layer .layer-details {\n    color: #999999;\n    font-size: 10px;\n    font-weight: bold;\n}\n.demo.imdb-bidirectional-lstm .architecture-container .layer:last-child {\n    margin-right: 0;\n}\n.demo.imdb-bidirectional-lstm .lstm-visualization-container {\n    min-width: 700px;\n    max-width: 900px;\n    margin: 20px auto;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: horizontal;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: row;\n            flex-direction: row;\n    -ms-flex-wrap: wrap;\n        flex-wrap: wrap;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    border: 1px solid #69707a;\n    border-radius: 5px;\n    padding: 10px;\n}\n.demo.imdb-bidirectional-lstm .lstm-visualization-container .lstm-visualization-word {\n    font-family: 'Share Tech Mono',sans-serif;\n    font-size: 14px;\n    color: #393E46;\n    padding: 3px 6px;\n}\n",""])},function(e,n,t){n=e.exports=t(2)(),n.push([e.i,".demo.inception-v3 .top-container {\n    margin: 10px;\n    position: relative;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n}\n.demo.inception-v3 .top-container .input-container .input-label {\n    font-family: 'Nothing You Could Do',cursive;\n    font-size: 16px;\n    color: #69707a;\n    text-align: left;\n    -webkit-user-select: none;\n       -moz-user-select: none;\n        -ms-user-select: none;\n            user-select: none;\n    cursor: default;\n}\n.demo.inception-v3 .top-container .input-container .image-url {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: horizontal;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: row;\n            flex-direction: row;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: start;\n        -ms-flex-pack: start;\n            justify-content: flex-start;\n    position: relative;\n}\n.demo.inception-v3 .top-container .input-container .image-url span {\n    margin: 0 10px;\n    font-family: 'Nothing You Could Do',cursive;\n    font-size: 16px;\n    color: #69707a;\n}\n.demo.inception-v3 .top-container .controls {\n    width: 250px;\n    margin-left: 40px;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: vertical;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: column;\n            flex-direction: column;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center\n}\n.demo.inception-v3 .top-container .controls > .mdl-switch {\n    margin-bottom: 5px;\n}\n.demo.inception-v3 .top-container .controls > .mdl-switch .mdl-switch__label {\n    font-size: 12px !important;\n}\n.demo.inception-v3 .columns.input-output {\n    max-width: 800px;\n    margin: 0 auto;\n}\n.demo.inception-v3 .columns.input-output .column {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n}\n.demo.inception-v3 .columns.input-output .column.input-column {\n    position: relative;\n}\n.demo.inception-v3 .columns.input-output .column.input-column .loading-indicator {\n    position: absolute;\n    top: 0;\n    left: -10px;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: vertical;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: column;\n            flex-direction: column;\n    -ms-flex-item-align: start;\n        align-self: flex-start;\n}\n.demo.inception-v3 .columns.input-output .column.input-column .loading-indicator .mdl-spinner {\n    margin: 20px;\n    -ms-flex-item-align: center;\n        -ms-grid-row-align: center;\n        align-self: center;\n}\n.demo.inception-v3 .columns.input-output .column.input-column .loading-indicator .error {\n    color: #D24D57;\n    font-size: 14px;\n    font-family: 'Fira Sans',sans-serif;\n    margin: 20px;\n}\n.demo.inception-v3 .columns.input-output .column.input-column .canvas-container {\n    display: -webkit-inline-box;\n    display: -ms-inline-flexbox;\n    display: inline-flex;\n    -webkit-box-pack: end;\n        -ms-flex-pack: end;\n            justify-content: flex-end;\n}\n.demo.inception-v3 .columns.input-output .column.input-column .canvas-container canvas {\n    background: white;\n}\n.demo.inception-v3 .columns.input-output .column.output-column .output {\n    width: 370px;\n    height: 160px;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: vertical;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: column;\n            flex-direction: column;\n    -webkit-box-align: start;\n        -ms-flex-align: start;\n            align-items: flex-start;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n}\n.demo.inception-v3 .columns.input-output .column.output-column .output .output-class {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: horizontal;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: row;\n            flex-direction: row;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n    padding: 6px 0;\n}\n.demo.inception-v3 .columns.input-output .column.output-column .output .output-class .output-label {\n    text-align: right;\n    width: 200px;\n    white-space: nowrap;\n    overflow: hidden;\n    text-overflow: ellipsis;\n    font-family: 'Share Tech Mono',sans-serif;\n    font-size: 18px;\n    color: #69707a;\n    padding: 0 6px;\n    border-right: 2px solid rgba(27, 188, 155, 0.3);\n}\n.demo.inception-v3 .columns.input-output .column.output-column .output .output-class .output-bar {\n    height: 8px;\n    -webkit-transition: width 0.2s ease-out;\n    transition: width 0.2s ease-out;\n}\n.demo.inception-v3 .columns.input-output .column.output-column .output .output-class .output-value {\n    text-align: left;\n    margin-left: 5px;\n    font-family: 'Share Tech Mono',sans-serif;\n    font-size: 14px;\n    color: #69707a;\n}\n.demo.inception-v3 .columns.input-output .column.output-column .output .output-class.predicted .output-label {\n    color: #1BBC9B;\n    border-left-color: #1BBC9B;\n}\n.demo.inception-v3 .columns.input-output .column.output-column .output .output-class.predicted .output-value {\n    color: #1BBC9B;\n}\n.demo.inception-v3 .architecture-container {\n    min-width: 800px;\n    max-width: 1200px;\n    margin: 0 auto;\n    position: relative;\n}\n.demo.inception-v3 .architecture-container .layers-row {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: horizontal;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: row;\n            flex-direction: row;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n    margin-bottom: 5px;\n    position: relative;\n    z-index: 1;\n}\n.demo.inception-v3 .architecture-container .layers-row .layer-column {\n    -webkit-box-flex: 1;\n        -ms-flex: 1;\n            flex: 1;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n    padding: 5px;\n}\n.demo.inception-v3 .architecture-container .layers-row .layer-column .layer {\n    display: inline-block;\n    background: white;\n    border: 2px solid white;\n    border-radius: 5px;\n    padding: 2px 10px 0px;\n    margin: 3px;\n}\n.demo.inception-v3 .architecture-container .layers-row .layer-column .layer .layer-class-name {\n    color: #1BBC9B;\n    font-size: 14px;\n    font-weight: bold;\n}\n.demo.inception-v3 .architecture-container .layers-row .layer-column .layer .layer-details {\n    color: #999999;\n    font-size: 12px;\n    font-weight: bold;\n}\n.demo.inception-v3 .architecture-container .layers-row .layer-column .layer.has-result {\n    border-color: #1BBC9B;\n}\n.demo.inception-v3 .architecture-container .architecture-connections {\n    position: absolute;\n    top: 0;\n    left: 0;\n    z-index: 0;\n}\n.demo.inception-v3 .architecture-container .architecture-connections path {\n    stroke-width: 4px;\n    stroke: #AAAAAA;\n    fill: none;\n}\n",""]);
},function(e,n,t){n=e.exports=t(2)(),n.push([e.i,"@import url(https://fonts.googleapis.com/css?family=Fira+Sans);",""]),n.push([e.i,"@import url(https://fonts.googleapis.com/css?family=Share+Tech+Mono);",""]),n.push([e.i,"@import url(https://fonts.googleapis.com/css?family=Nothing+You+Could+Do);",""]),n.push([e.i,"body {\n  background: -webkit-linear-gradient(bottom, #CCCCCC, #F0F0F0);\n  background: linear-gradient(0deg, #CCCCCC, #F0F0F0);\n  color: #393E46;\n  min-height: 100vh;\n  font-family: 'Fira Sans',sans-serif;\n}\n\n.title {\n  width: 100%;\n  display: -webkit-box;\n  display: -ms-flexbox;\n  display: flex;\n  -webkit-box-orient: horizontal;\n  -webkit-box-direction: normal;\n      -ms-flex-direction: row;\n          flex-direction: row;\n  -webkit-box-align: center;\n      -ms-flex-align: center;\n          align-items: center;\n}\n\n.title span {\n  color: #1BBC9B;\n  margin-right: 20px;\n}\n\n.subtitle {\n  color: #393E46;\n}\n\n.demo {\n  padding: 50px 30px;\n}\n\n.demo .loading-progress {\n  position: absolute;\n  top: 0;\n  right: 0;\n  padding: 30px;\n  color: #1BBC9B;\n  font-size: 18px;\n  font-family: 'Share Tech Mono',sans-serif;\n  padding: 20px 50px;\n  margin: 30px;\n  background: rgba(255, 255, 255, 0.5);\n  border-radius: 10px;\n}\n\n.demo .info-panel {\n  width: 100%;\n  max-width: 1200px;\n  border-radius: 5px;\n  background: white;\n  color: #393E46;\n  padding: 20px 20px 5px 20px;\n  margin: 20px auto;\n  box-shadow: 5px 5px #CCCCCC;\n}\n\n.demo .info-panel .info-panel-text {\n  width: 100%;\n  margin-bottom: 10px;\n  font-size: 12px;\n}\n\n.demo .info-panel .info-panel-text a {\n  color: #1BBC9B;\n  -webkit-transition: color 0.2s ease-in;\n  transition: color 0.2s ease-in\n}\n\n.demo .info-panel .info-panel-text a:hover{\n  color: rgba(27, 188, 155, 0.6);\n}\n\n.demo .info-panel .info-panel-close {\n  display: -webkit-box;\n  display: -ms-flexbox;\n  display: flex;\n  -webkit-box-align: center;\n      -ms-flex-align: center;\n          align-items: center;\n  -webkit-box-pack: end;\n      -ms-flex-pack: end;\n          justify-content: flex-end;\n}\n\n.demo .info-panel .info-panel-close .info-panel-close-btn {\n  display: -webkit-box;\n  display: -ms-flexbox;\n  display: flex;\n  -webkit-box-align: center;\n      -ms-flex-align: center;\n          align-items: center;\n  color: #69707a;\n  -webkit-transition: color 0.2s ease-in;\n  transition: color 0.2s ease-in\n}\n\n.demo .info-panel .info-panel-close .info-panel-close-btn:hover{\n  color: rgba(27, 188, 155, 0.3);\n  cursor: pointer;\n}\n\n/* MDL overrides */\n\n.demo .mdl-switch__label {\n  font-size: 14px !important;\n  color: #69707a;\n}\n\n/****************************************************************/\n\n.demo .mdl-switch.is-checked .mdl-switch__thumb {\n  background: rgba(27, 188, 155, 0.6);\n}\n\n.demo .mdl-switch.is-checked .mdl-switch__track {\n  background: rgba(27, 188, 155, 0.3);\n}\n\n.demo .mdl-textfield .mdl-textfield__input {\n  border-bottom-color: rgba(27, 188, 155, 0.6);\n  font-family: 'Share Tech Mono',sans-serif;\n  font-size: 14px;\n}\n\n.demo .mdl-textfield .mdl-textfield__label {\n  font-family: 'Share Tech Mono',sans-serif;\n  color: rgba(27, 188, 155, 0.6);\n}\n\n.demo .mdl-textfield .mdl-icon-toggle__label {\n  color: rgba(27, 188, 155, 0.6);\n}\n\n.demo .mdl-textfield.is-focused .mdl-textfield__input {\n  border-color: #1BBC9B;\n}\n\n.demo .mdl-textfield.is-focused .mdl-textfield__label {\n  color: #1BBC9B\n}\n\n.demo .mdl-textfield.is-focused .mdl-textfield__label::after{\n  background-color: #1BBC9B;\n}\n\n.demo .mdl-textfield.is-focused .mdl-icon-toggle__label {\n  color: #1BBC9B;\n}\n\n.demo .mdl-menu .mdl-menu__item {\n  font-family: 'Share Tech Mono',sans-serif;\n  font-size: 14px;\n  color: #69707a\n}\n\n.demo .mdl-menu .mdl-menu__item:hover{\n  background-color: rgba(27, 188, 155, 0.6);\n  color: white;\n}\n",""])},function(e,n,t){n=e.exports=t(2)(),n.push([e.i,".menu {\n  padding: 40px;\n  margin: 20px;\n  background: white;\n  border-radius: 10px;\n  box-shadow: 5px 5px #CCCCCC;\n}\n.menu h1 {\n  color: #CCCCCC;\n  font-family: 'Fira Sans',sans-serif;\n  font-size: 1.5rem;\n}\n.menu .menu-list li {\n  color: #69707a;\n  border-left: 2px solid white;\n  margin-bottom: 3px;\n}\n.menu .menu-list li.active {\n  border-left: 2px solid #1BBC9B;\n}\n.menu .menu-list a {\n  display: -webkit-box;\n  display: -ms-flexbox;\n  display: flex;\n  -webkit-box-orient: horizontal;\n  -webkit-box-direction: normal;\n      -ms-flex-direction: row;\n          flex-direction: row;\n  -webkit-box-align: center;\n      -ms-flex-align: center;\n          align-items: center;\n  -webkit-box-pack: justify;\n      -ms-flex-pack: justify;\n          justify-content: space-between;\n}\n.menu .menu-list a span.menu-item-heading {\n  margin-right: 10px;\n}\n.menu .menu-list a span.menu-item-subheading {\n  color: #999999;\n  font-size: 0.8em;\n}\n.menu .menu-list a:hover {\n  color: #1BBC9B;\n  background-color: whitesmoke;\n}\n.menu .menu-list a:hover .github-logo {\n  fill: #1BBC9B;\n}\n.menu .menu-list.github li, .menu .menu-list.contact li {\n  padding: 5px 10px;\n}\n.menu .menu-list.github a, .menu .menu-list.contact a {\n  color: #1BBC9B;\n  padding: 0;\n  display: -webkit-inline-box;\n  display: -ms-inline-flexbox;\n  display: inline-flex;\n  background-color: none;\n  -webkit-transition: color 0.2s ease-in;\n  transition: color 0.2s ease-in;\n}\n.menu .menu-list.github a .github-logo, .menu .menu-list.contact a .github-logo {\n  fill: #1BBC9B;\n  -webkit-transition: fill 0.2s ease-in;\n  transition: fill 0.2s ease-in;\n}\n.menu .menu-list.github a:hover, .menu .menu-list.contact a:hover {\n  color: rgba(27, 188, 155, 0.6);\n  background: none;\n}\n.menu .menu-list.github a:hover .github-logo, .menu .menu-list.contact a:hover .github-logo {\n  fill: rgba(27, 188, 155, 0.6);\n}\n",""])},function(e,n,t){n=e.exports=t(2)(),n.push([e.i,".demo.mnist-cnn .column {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n}\n.demo.mnist-cnn .column.input-column {\n    -webkit-box-pack: end;\n        -ms-flex-pack: end;\n            justify-content: flex-end;\n}\n.demo.mnist-cnn .column.input-column .input-container {\n    text-align: right;\n    margin: 20px;\n    position: relative;\n    -webkit-user-select: none;\n       -moz-user-select: none;\n        -ms-user-select: none;\n            user-select: none;\n}\n.demo.mnist-cnn .column.input-column .input-container .input-label {\n    font-family: 'Nothing You Could Do',cursive;\n    font-size: 18px;\n    color: #69707a;\n    text-align: right;\n}\n.demo.mnist-cnn .column.input-column .input-container .input-label span.arrow {\n    font-size: 36px;\n    color: #CCCCCC;\n    position: absolute;\n    right: -32px;\n    top: 8px;\n}\n.demo.mnist-cnn .column.input-column .input-container .canvas-container {\n    display: -webkit-inline-box;\n    display: -ms-inline-flexbox;\n    display: inline-flex;\n    -webkit-box-pack: end;\n        -ms-flex-pack: end;\n            justify-content: flex-end;\n    margin: 10px 0;\n    border: 15px solid rgba(27, 188, 155, 0.3);\n    -webkit-transition: border-color 0.2s ease-in;\n    transition: border-color 0.2s ease-in;\n}\n.demo.mnist-cnn .column.input-column .input-container .canvas-container canvas {\n    background: white\n}\n.demo.mnist-cnn .column.input-column .input-container .canvas-container canvas:hover {\n    cursor: crosshair;\n}\n.demo.mnist-cnn .column.input-column .input-container .canvas-container:hover {\n    border-color: rgba(27, 188, 155, 0.6);\n}\n.demo.mnist-cnn .column.input-column .input-container .input-buttons {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: end;\n        -ms-flex-pack: end;\n            justify-content: flex-end;\n}\n.demo.mnist-cnn .column.input-column .input-container .input-buttons .input-clear-button {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    color: #69707a;\n    -webkit-transition: color 0.2s ease-in;\n    transition: color 0.2s ease-in;\n}\n.demo.mnist-cnn .column.input-column .input-container .input-buttons .input-clear-button .material-icons {\n    margin-right: 5px;\n}\n.demo.mnist-cnn .column.input-column .input-container .input-buttons .input-clear-button:hover {\n    color: rgba(27, 188, 155, 0.3);\n    cursor: pointer;\n}\n.demo.mnist-cnn .column.controls-column {\n    -webkit-box-align: start;\n        -ms-flex-align: start;\n            align-items: flex-start;\n    -webkit-box-pack: start;\n        -ms-flex-pack: start;\n            justify-content: flex-start;\n    padding-top: 80px;\n}\n.demo.mnist-cnn .column.output-column {\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n}\n.demo.mnist-cnn .column.output-column .output {\n    height: 160px;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: horizontal;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: row;\n            flex-direction: row;\n    -webkit-box-align: end;\n        -ms-flex-align: end;\n            align-items: flex-end;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n    -webkit-user-select: none;\n       -moz-user-select: none;\n        -ms-user-select: none;\n            user-select: none;\n    cursor: default;\n}\n.demo.mnist-cnn .column.output-column .output .output-class {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: vertical;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: column;\n            flex-direction: column;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n    padding: 0 6px;\n    border-bottom: 2px solid rgba(27, 188, 155, 0.3);\n}\n.demo.mnist-cnn .column.output-column .output .output-class .output-label {\n    font-family: 'Share Tech Mono',sans-serif;\n    font-size: 1.5rem;\n    color: #69707a;\n}\n.demo.mnist-cnn .column.output-column .output .output-class .output-bar {\n    width: 8px;\n    background: #EEEEEE;\n    -webkit-transition: height 0.2s ease-out;\n    transition: height 0.2s ease-out;\n}\n.demo.mnist-cnn .column.output-column .output .output-class.predicted {\n    border-bottom-color: #1BBC9B;\n}\n.demo.mnist-cnn .column.output-column .output .output-class.predicted .output-label {\n    color: #1BBC9B;\n}\n.demo.mnist-cnn .layer-results-container {\n    position: relative;\n}\n.demo.mnist-cnn .layer-results-container .bg-line {\n    position: absolute;\n    z-index: 0;\n    top: 0;\n    left: 50%;\n    background: white;\n    width: 15px;\n    height: 100%;\n}\n.demo.mnist-cnn .layer-results-container .layer-result {\n    position: relative;\n    z-index: 1;\n    margin: 30px 20px;\n    background: white;\n    border-radius: 10px;\n    padding: 20px;\n    overflow-x: auto;\n}\n.demo.mnist-cnn .layer-results-container .layer-result .layer-result-heading {\n    font-size: 1rem;\n    color: #999999;\n    margin-bottom: 10px;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: vertical;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: column;\n            flex-direction: column;\n    font-size: 12px;\n}\n.demo.mnist-cnn .layer-results-container .layer-result .layer-result-heading span.layer-class {\n    color: #1BBC9B;\n    font-size: 14px;\n    font-weight: bold;\n}\n.demo.mnist-cnn .layer-results-container .layer-result .layer-result-canvas-container {\n    display: -webkit-inline-box;\n    display: -ms-inline-flexbox;\n    display: inline-flex;\n    -ms-flex-wrap: wrap;\n        flex-wrap: wrap;\n    background: white;\n}\n.demo.mnist-cnn .layer-results-container .layer-result .layer-result-canvas-container canvas {\n    border: 1px solid lightgray;\n    margin: 1px;\n}\n",""])},function(e,n,t){n=e.exports=t(2)(),n.push([e.i,".demo.mnist-vae .column {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n}\n.demo.mnist-vae .column.input-column {\n    -webkit-box-pack: end;\n        -ms-flex-pack: end;\n            justify-content: flex-end;\n}\n.demo.mnist-vae .column.input-column .input-container {\n    text-align: right;\n    margin: 20px;\n    position: relative;\n    -webkit-user-select: none;\n       -moz-user-select: none;\n        -ms-user-select: none;\n            user-select: none;\n}\n.demo.mnist-vae .column.input-column .input-container .input-label {\n    font-family: 'Nothing You Could Do',cursive;\n    font-size: 18px;\n    color: #69707a;\n    text-align: right;\n}\n.demo.mnist-vae .column.input-column .input-container .input-label span.arrow {\n    font-size: 36px;\n    color: #CCCCCC;\n    position: absolute;\n    right: -32px;\n    top: 8px;\n}\n.demo.mnist-vae .column.input-column .input-container .canvas-container {\n    position: relative;\n    display: -webkit-inline-box;\n    display: -ms-inline-flexbox;\n    display: inline-flex;\n    -webkit-box-pack: end;\n        -ms-flex-pack: end;\n            justify-content: flex-end;\n    margin: 10px 0;\n    border: 15px solid rgba(27, 188, 155, 0.3);\n    -webkit-transition: border-color 0.2s ease-in;\n    transition: border-color 0.2s ease-in;\n}\n.demo.mnist-vae .column.input-column .input-container .canvas-container canvas {\n    background: white\n}\n.demo.mnist-vae .column.input-column .input-container .canvas-container canvas:hover {\n    cursor: crosshair;\n}\n.demo.mnist-vae .column.input-column .input-container .canvas-container .axis {\n    position: absolute;\n    cursor: default;\n    -webkit-user-select: none;\n       -moz-user-select: none;\n        -ms-user-select: none;\n            user-select: none;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: justify;\n        -ms-flex-pack: justify;\n            justify-content: space-between;\n    font-family: 'Share Tech Mono',sans-serif;\n    font-size: 14px;\n    color: #1BBC9B;\n}\n.demo.mnist-vae .column.input-column .input-container .canvas-container .axis.x-axis {\n    right: 0;\n    bottom: -45px;\n    width: 200px;\n    -webkit-box-orient: horizontal;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: row;\n            flex-direction: row;\n}\n.demo.mnist-vae .column.input-column .input-container .canvas-container .axis.y-axis {\n    top: 0;\n    left: -55px;\n    height: 200px;\n    -webkit-box-orient: vertical;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: column;\n            flex-direction: column;\n}\n.demo.mnist-vae .column.input-column .input-container .canvas-container:hover {\n    border-color: rgba(27, 188, 155, 0.6);\n}\n.demo.mnist-vae .column.controls-column {\n    -webkit-box-orient: vertical;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: column;\n            flex-direction: column;\n    -webkit-box-align: start;\n        -ms-flex-align: start;\n            align-items: flex-start;\n    -webkit-box-pack: start;\n        -ms-flex-pack: start;\n            justify-content: flex-start;\n    padding-top: 80px;\n}\n.demo.mnist-vae .column.controls-column .coordinates {\n    margin-left: 5px;\n    margin-top: 45px;\n    font-family: 'Share Tech Mono',sans-serif;\n    font-size: 20px;\n    color: #69707a;\n}\n.demo.mnist-vae .column.output-column {\n    -webkit-box-pack: start;\n        -ms-flex-pack: start;\n            justify-content: flex-start;\n}\n.demo.mnist-vae .column.output-column .output {\n    border-radius: 10px;\n    overflow: hidden;\n}\n.demo.mnist-vae .column.output-column .output canvas {\n    background: white;\n}\n.demo.mnist-vae .layer-results-container {\n    position: relative;\n}\n.demo.mnist-vae .layer-results-container .bg-line {\n    position: absolute;\n    z-index: 0;\n    top: 0;\n    left: 50%;\n    background: white;\n    width: 15px;\n    height: 100%;\n}\n.demo.mnist-vae .layer-results-container .layer-result {\n    position: relative;\n    z-index: 1;\n    margin: 30px 20px;\n    background: white;\n    border-radius: 10px;\n    padding: 20px;\n    overflow-x: auto;\n}\n.demo.mnist-vae .layer-results-container .layer-result .layer-result-heading {\n    font-size: 1rem;\n    color: #999999;\n    margin-bottom: 10px;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: vertical;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: column;\n            flex-direction: column;\n    font-size: 12px;\n}\n.demo.mnist-vae .layer-results-container .layer-result .layer-result-heading span.layer-class {\n    color: #1BBC9B;\n    font-size: 14px;\n    font-weight: bold;\n}\n.demo.mnist-vae .layer-results-container .layer-result .layer-result-canvas-container {\n    display: -webkit-inline-box;\n    display: -ms-inline-flexbox;\n    display: inline-flex;\n    -ms-flex-wrap: wrap;\n        flex-wrap: wrap;\n    background: white;\n}\n.demo.mnist-vae .layer-results-container .layer-result .layer-result-canvas-container canvas {\n    border: 1px solid lightgray;\n    margin: 1px;\n}\n",""])},function(e,n,t){n=e.exports=t(2)(),n.push([e.i,".demo.resnet50 .top-container {\n    margin: 10px;\n    position: relative;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n}\n.demo.resnet50 .top-container .input-container .input-label {\n    font-family: 'Nothing You Could Do',cursive;\n    font-size: 16px;\n    color: #69707a;\n    text-align: left;\n    -webkit-user-select: none;\n       -moz-user-select: none;\n        -ms-user-select: none;\n            user-select: none;\n    cursor: default;\n}\n.demo.resnet50 .top-container .input-container .image-url {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: horizontal;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: row;\n            flex-direction: row;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: start;\n        -ms-flex-pack: start;\n            justify-content: flex-start;\n    position: relative;\n}\n.demo.resnet50 .top-container .input-container .image-url span {\n    margin: 0 10px;\n    font-family: 'Nothing You Could Do',cursive;\n    font-size: 16px;\n    color: #69707a;\n}\n.demo.resnet50 .top-container .controls {\n    width: 250px;\n    margin-left: 40px;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: vertical;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: column;\n            flex-direction: column;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center\n}\n.demo.resnet50 .top-container .controls > .mdl-switch {\n    margin-bottom: 5px;\n}\n.demo.resnet50 .top-container .controls > .mdl-switch .mdl-switch__label {\n    font-size: 12px !important;\n}\n.demo.resnet50 .columns.input-output {\n    max-width: 800px;\n    margin: 0 auto;\n}\n.demo.resnet50 .columns.input-output .column {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n}\n.demo.resnet50 .columns.input-output .column.input-column {\n    position: relative;\n}\n.demo.resnet50 .columns.input-output .column.input-column .loading-indicator {\n    position: absolute;\n    top: 0;\n    left: -10px;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: vertical;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: column;\n            flex-direction: column;\n    -ms-flex-item-align: start;\n        align-self: flex-start;\n}\n.demo.resnet50 .columns.input-output .column.input-column .loading-indicator .mdl-spinner {\n    margin: 20px;\n    -ms-flex-item-align: center;\n        -ms-grid-row-align: center;\n        align-self: center;\n}\n.demo.resnet50 .columns.input-output .column.input-column .loading-indicator .error {\n    color: #D24D57;\n    font-size: 14px;\n    font-family: 'Fira Sans',sans-serif;\n    margin: 20px;\n}\n.demo.resnet50 .columns.input-output .column.input-column .canvas-container {\n    display: -webkit-inline-box;\n    display: -ms-inline-flexbox;\n    display: inline-flex;\n    -webkit-box-pack: end;\n        -ms-flex-pack: end;\n            justify-content: flex-end;\n}\n.demo.resnet50 .columns.input-output .column.input-column .canvas-container canvas {\n    background: white;\n}\n.demo.resnet50 .columns.input-output .column.output-column .output {\n    width: 370px;\n    height: 160px;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: vertical;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: column;\n            flex-direction: column;\n    -webkit-box-align: start;\n        -ms-flex-align: start;\n            align-items: flex-start;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n}\n.demo.resnet50 .columns.input-output .column.output-column .output .output-class {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: horizontal;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: row;\n            flex-direction: row;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n    padding: 6px 0;\n}\n.demo.resnet50 .columns.input-output .column.output-column .output .output-class .output-label {\n    text-align: right;\n    width: 200px;\n    white-space: nowrap;\n    overflow: hidden;\n    text-overflow: ellipsis;\n    font-family: 'Share Tech Mono',sans-serif;\n    font-size: 18px;\n    color: #69707a;\n    padding: 0 6px;\n    border-right: 2px solid rgba(27, 188, 155, 0.3);\n}\n.demo.resnet50 .columns.input-output .column.output-column .output .output-class .output-bar {\n    height: 8px;\n    -webkit-transition: width 0.2s ease-out;\n    transition: width 0.2s ease-out;\n}\n.demo.resnet50 .columns.input-output .column.output-column .output .output-class .output-value {\n    text-align: left;\n    margin-left: 5px;\n    font-family: 'Share Tech Mono',sans-serif;\n    font-size: 14px;\n    color: #69707a;\n}\n.demo.resnet50 .columns.input-output .column.output-column .output .output-class.predicted .output-label {\n    color: #1BBC9B;\n    border-left-color: #1BBC9B;\n}\n.demo.resnet50 .columns.input-output .column.output-column .output .output-class.predicted .output-value {\n    color: #1BBC9B;\n}\n.demo.resnet50 .architecture-container {\n    min-width: 700px;\n    max-width: 900px;\n    margin: 0 auto;\n    position: relative;\n}\n.demo.resnet50 .architecture-container .layers-row {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: horizontal;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: row;\n            flex-direction: row;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n    margin-bottom: 5px;\n    position: relative;\n    z-index: 1;\n}\n.demo.resnet50 .architecture-container .layers-row .layer-column {\n    -webkit-box-flex: 1;\n        -ms-flex: 1;\n            flex: 1;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: center;\n        -ms-flex-pack: center;\n            justify-content: center;\n    padding: 5px;\n}\n.demo.resnet50 .architecture-container .layers-row .layer-column .layer {\n    display: inline-block;\n    background: white;\n    border: 2px solid white;\n    border-radius: 5px;\n    padding: 2px 10px 0px;\n}\n.demo.resnet50 .architecture-container .layers-row .layer-column .layer .layer-class-name {\n    color: #1BBC9B;\n    font-size: 14px;\n    font-weight: bold;\n}\n.demo.resnet50 .architecture-container .layers-row .layer-column .layer .layer-details {\n    color: #999999;\n    font-size: 12px;\n    font-weight: bold;\n}\n.demo.resnet50 .architecture-container .layers-row .layer-column .layer.has-result {\n    border-color: #1BBC9B;\n}\n.demo.resnet50 .architecture-container .architecture-connections {\n    position: absolute;\n    top: 0;\n    left: 0;\n    z-index: 0;\n}\n.demo.resnet50 .architecture-container .architecture-connections path {\n    stroke-width: 4px;\n    stroke: #AAAAAA;\n    fill: none;\n}\n",""])},function(e,n,t){n=e.exports=t(2)(),n.push([e.i,".demo.xception .top-container {\n    margin: 10px;\n    position: relative;\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n}\n.demo.xception .top-container .input-container .input-label {\n    font-family: 'Nothing You Could Do',cursive;\n    font-size: 16px;\n    color: #69707a;\n    text-align: left;\n    -webkit-user-select: none;\n       -moz-user-select: none;\n        -ms-user-select: none;\n            user-select: none;\n    cursor: default;\n}\n.demo.xception .top-container .input-container .image-url {\n    display: -webkit-box;\n    display: -ms-flexbox;\n    display: flex;\n    -webkit-box-orient: horizontal;\n    -webkit-box-direction: normal;\n        -ms-flex-direction: row;\n            flex-direction: row;\n    -webkit-box-align: center;\n        -ms-flex-align: center;\n            align-items: center;\n    -webkit-box-pack: 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l(e,n){this.fun=e,this.array=n}function c(){}var u,d,m=e.exports={};!function(){try{u="function"==typeof setTimeout?setTimeout:t}catch(e){u=t}try{d="function"==typeof clearTimeout?clearTimeout:a}catch(e){d=a}}();var p,f=[],h=!1,b=-1;m.nextTick=function(e){var n=new Array(arguments.length-1);if(arguments.length>1)for(var t=1;t<arguments.length;t++)n[t-1]=arguments[t];f.push(new l(e,n)),1!==f.length||h||o(s)},l.prototype.run=function(){this.fun.apply(null,this.array)},m.title="browser",m.browser=!0,m.env={},m.argv=[],m.version="",m.versions={},m.on=c,m.addListener=c,m.once=c,m.off=c,m.removeListener=c,m.removeAllListeners=c,m.emit=c,m.binding=function(e){throw new Error("process.binding is not supported")},m.cwd=function(){return"/"},m.chdir=function(e){throw new Error("process.chdir is not supported")},m.umask=function(){return 0}},function(e,n){e.exports='<div class="demo home">\n  <div class="title"><span>Home</span></div>\n  <a v-for="info in demoInfo" href="#/{{ info.path }}">\n    <div class="demo-card">\n      <div class="demo-card-heading">{{ info.title }}</div>\n      <div class="demo-card-image"><img :src="info.imagePath" /></div>\n    </div>\n  </a>\n</div>\n'},function(e,n){e.exports='<div class="demo imdb-bidirectional-lstm">\n  <div class="title">\n    <span>Bidirectional LSTM for IMDB sentiment classification</span>\n    <mdl-spinner v-if="modelLoading && loadingProgress < 100"></mdl-spinner>\n  </div>\n  <div class="loading-progress" v-if="modelLoading && loadingProgress < 100">\n    Loading...{{ loadingProgress }}%\n  </div>\n  <div class="info-panel" v-if="showInfoPanel">\n    <div class="info-panel-text">This demo is modified from the Keras <a target="_blank" href="https://github.com/fchollet/keras/blob/master/examples/imdb_bidirectional_lstm.py">example</a> demonstrating the Bidirectional wrapper class around an LSTM layer. Click on "load sample text" to populate the textbox with a sample IMDB movie review (preprocessed) from the test set (not used during training). You can also enter your own text into the textbox, but keep in mind the model was trained on IMDB movie reviews only (see the corresponding <a target="_blank" href="https://github.com/transcranial/keras-js/blob/master/demos/notebooks/imdb_bidirectional_lstm.ipynb">Jupyter notebook</a>). The result is a number from 0 (negative) to 1 (positive). We visualize the contributions from each word by running the forward+backward concatenated hidden state corresponding to each word through the final Dense layer.</div>\n    <div class="info-panel-close">\n      <div class="info-panel-close-btn" @click="closeInfoPanel"><i class="material-icons">close</i>CLOSE</div>\n    </div>\n  </div>\n  <div class="columns input-output" v-if="!modelLoading">\n    <div class="column input-column">\n      <div class="input-container">\n        <mdl-textfield\n          floating-label="input text"\n          :value.sync="inputText"\n          spellcheck="false"\n          textarea\n          rows="10"\n          @change="inputChanged"\n          @keyup="inputChanged"\n          @paste="inputChanged"\n        ></mdl-textfield>\n        <div class="input-buttons">\n          <div class="input-load-button" v-on:click="randomSample"><i class="material-icons">add_circle</i>LOAD SAMPLE TEXT</div>\n          <div class="input-clear-button" v-on:click="clear"><i class="material-icons">clear</i>CLEAR</div>\n        </div>\n      </div>\n    </div>\n    <div class="column output-column">\n      <div class="output">\n        <div class="output-heading">Result:</div>\n        <div class="output-value" style="color: {{ outputColor }};">{{ Math.round(output[0] * 100) }}%</div>\n        <div class="output-heading" v-if="isSampleText">Actual label for sample text: <span class="output-label" v-bind:class="sampleTextLabel">{{ sampleTextLabel }}</span></div>\n      </div>\n    </div>\n  </div>\n  <div class="architecture-container" v-if="!modelLoading">\n    <div class="bg-line"></div>\n    <div\n      v-for="layer in architectureDiagramLayers"\n      class="layer"\n      :id="layer.name"\n    >\n      <div class="layer-class-name">{{ layer.className }}</div>\n      <div class="layer-details"> {{ layer.details }}</div>\n    </div>\n  </div>\n  <div class="lstm-visualization-container" v-if="!modelLoading && !modelRunning && inputTextParsed.length">\n    <div\n      v-for="word in inputTextParsed"\n      class="lstm-visualization-word"\n      style="background: {{ stepwiseOutputColor[$index] }};"\n    >{{ word }}</div>\n  </div>\n</div>\n'},function(e,n){e.exports='<div class="demo inception-v3">\n  <div class="title">\n    <span>Inception V3, trained on ImageNet</span>\n    <mdl-spinner v-if="modelLoading && loadingProgress < 100"></mdl-spinner>\n  </div>\n  <div class="loading-progress" v-if="modelLoading && loadingProgress < 100">\n    Loading...{{ loadingProgress }}%\n  </div>\n  <div class="info-panel" v-if="showInfoPanel">\n    <div class="info-panel-text">\n      Note that ~100 MB of weights must be loaded. We use the Keras architecture from <a target="_blank" href="https://github.com/fchollet/keras/blob/master/keras/applications/inception_v3.py">here</a> and pretrained weights from <a target="_blank" href="https://github.com/fchollet/deep-learning-models">here</a>. Enter any valid image URL as input to the network. You can also select from a list of prepopulated image URLs. The endpoint must have CORS enabled, to enable us to extract the numeric data from the canvas element, so not all URLs will work. Imgur and <a target="_blank" href="https://www.flickr.com/search/?text=&license=2%2C3%2C4%2C5%2C6%2C9&sort=interestingness-desc">Flickr creative commons</a> all work, and are good places to start. After running the network, the top-5 classes are displayed. Keep in mind also we are limited to the <a target="_blank" href="https://github.com/transcranial/keras-js/blob/master/demos/src/utils/imagenet.js">1,000 classes of ImageNet</a>. Keep in mind that this is image classification and not object detection, so the network is forced to output a single class through softmax. Best results are on images where the classification target spans a large portion of the image. All computation performed entirely in your browser. Toggling GPU on should offer significant speedups compared to CPU. Running the network may still take several seconds (optimizations to come). With "show computational flow" toggled, computation through the network will be shown in the architecture diagram (scroll down as computation is performed layer by layer). Turning this feature off will also speed up computation.\n    </div>\n    <div class="info-panel-close">\n      <div class="info-panel-close-btn" @click="closeInfoPanel"><i class="material-icons">close</i>CLOSE</div>\n    </div>\n  </div>\n  <div class="top-container" v-if="!modelLoading">\n    <div class="input-container">\n      <div class="input-label">Enter a valid image URL or select an image from the dropdown:</div>\n      <div class="image-url">\n        <mdl-textfield\n          floating-label="enter image url"\n          :value.sync="imageURLInput"\n          spellcheck="false"\n          @change="imageURLInputChanged"\n        ></mdl-textfield>\n        <span>or</span>\n        <mdl-select\n          label="select image"\n          id="image-url-select"\n          :value.sync="imageURLSelect"\n          :options="imageURLSelectList"\n          style="width:200px;"\n          @change="imageURLSelectChanged"\n        ></mdl-select>\n      </div>\n    </div>\n    <div class="controls">\n      <mdl-switch\n        :checked.sync="useGpu"\n        :disabled="modelLoading || modelRunning || !hasWebgl"\n        @click="toggleGpu"\n      >Use GPU</mdl-switch>\n      <mdl-switch\n        :checked.sync="showComputationFlow"\n        :disabled="modelLoading || modelRunning"\n        @click="toggleComputationFlow"\n      >Show computation flow</mdl-switch>\n    </div>\n  </div>\n  <div class="columns input-output" v-if="!modelLoading">\n    <div class="column input-column">\n      <div class="loading-indicator">\n        <mdl-spinner v-if="imageLoading || modelRunning"></mdl-spinner>\n        <div class="error" v-if="imageLoadingError">Error loading URL</div>\n      </div>\n      <div class="canvas-container">\n        <canvas id="input-canvas" width="299" height="299"></canvas>\n      </div>\n    </div>\n    <div class="column output-column">\n      <div class="output">\n        <div class="output-class"\n          :class="{ \'predicted\': i === 0 && outputClasses[i].probability.toFixed(2) > 0 }"\n          v-for="i in [0, 1, 2, 3, 4]"\n        >\n          <div class="output-label">{{ outputClasses[i].name }}</div>\n          <div class="output-bar"\n            style="width: {{ Math.round(100 * outputClasses[i].probability) }}px; background: rgba(27, 188, 155, {{ outputClasses[i].probability.toFixed(2) }});"\n          ></div>\n          <div class="output-value">{{ Math.round(100 * outputClasses[i].probability) }}%</div>\n        </div>\n      </div>\n    </div>\n  </div>\n  <div class="architecture-container" v-if="!modelLoading">\n    <div v-for="row in architectureDiagramRows" class="layers-row">\n      <div v-for="layers in row" class="layer-column">\n        <div\n          v-for="layer in layers"\n          v-if="layer.className"\n          class="layer"\n          :class="{ \'has-result\': layersWithResults.includes(layer.name) }"\n          :id="layer.name"\n        >\n          <div class="layer-class-name">{{ layer.className }}</div>\n          <div class="layer-details"> {{ layer.details }}</div>\n        </div>\n      </div>\n    </div>\n    <svg class="architecture-connections" width="100%" height="100%">\n      <g>\n        <path v-for="path in architectureDiagramPaths" :d="path" />\n      </g>\n    </svg>\n  </div>\n</div>\n'},function(e,n){e.exports='<aside class="menu">\n  <h1>Keras.js Demos</h1>\n  <p class="menu-label">\n    Demos\n  </p>\n  <ul class="menu-list">\n    <li v-bind:class="{ \'active\': currentView === \'home\' }">\n      <a href="#/">Home</a>\n    </li>\n    <li v-bind:class="{ \'active\': currentView === \'mnist-cnn\' }">\n      <a href="#/mnist-cnn">\n        <span class="menu-item-heading">Basic Convnet</span>\n        <span class="menu-item-subheading">MNIST</span>\n      </a>\n    </li>\n    <li v-bind:class="{ \'active\': currentView === \'mnist-vae\' }">\n      <a href="#/mnist-vae">\n        <span class="menu-item-heading">Convolutional VAE</span>\n        <span class="menu-item-subheading">MNIST</span>\n      </a>\n    </li>\n    <li v-bind:class="{ \'active\': currentView === \'resnet50\' }">\n      <a href="#/resnet50">\n        <span class="menu-item-heading">Residual Network (50-layer)</span>\n        <span class="menu-item-subheading">ImageNet</span>\n      </a>\n    </li>\n    <li v-bind:class="{ \'active\': currentView === \'inception-v3\' }">\n      <a href="#/inception-v3">\n        <span class="menu-item-heading">Inception V3</span>\n        <span class="menu-item-subheading">ImageNet</span>\n      </a>\n    </li>\n    <li v-bind:class="{ \'active\': currentView === \'xception\' }">\n      <a href="#/xception">\n        <span class="menu-item-heading">Xception</span>\n        <span class="menu-item-subheading">ImageNet</span>\n      </a>\n    </li>\n    <li v-bind:class="{ \'active\': currentView === \'imdb-bidirectional-lstm\' }">\n      <a href="#/imdb-bidirectional-lstm">\n        <span class="menu-item-heading">Bidirectional LSTM</span>\n        <span class="menu-item-subheading">IMDB</span>\n      </a>\n    </li>\n  </ul>\n  <p class="menu-label">\n    Links\n  </p>\n  <ul class="menu-list github">\n    <li>\n      <a href="https://github.com/transcranial/keras-js" target="_blank">\n        <span class="menu-item-heading">\n          <svg height="24" width="24" class="github-logo" viewBox="0 0 16 16" version="1.1" aria-hidden="true"><path d="M8 0C3.58 0 0 3.58 0 8c0 3.54 2.29 6.53 5.47 7.59.4.07.55-.17.55-.38 0-.19-.01-.82-.01-1.49-2.01.37-2.53-.49-2.69-.94-.09-.23-.48-.94-.82-1.13-.28-.15-.68-.52-.01-.53.63-.01 1.08.58 1.23.82.72 1.21 1.87.87 2.33.66.07-.52.28-.87.51-1.07-1.78-.2-3.64-.89-3.64-3.95 0-.87.31-1.59.82-2.15-.08-.2-.36-1.02.08-2.12 0 0 .67-.21 2.2.82.64-.18 1.32-.27 2-.27.68 0 1.36.09 2 .27 1.53-1.04 2.2-.82 2.2-.82.44 1.1.16 1.92.08 2.12.51.56.82 1.27.82 2.15 0 3.07-1.87 3.75-3.65 3.95.29.25.54.73.54 1.48 0 1.07-.01 1.93-.01 2.2 0 .21.15.46.55.38A8.013 8.013 0 0 0 16 8c0-4.42-3.58-8-8-8z"></path></svg>\n          GitHub repo\n        </span>\n      </a>\n    </li>\n  </ul>\n  <p class="menu-label">\n    Contact\n  </p>\n  <ul class="menu-list contact">\n    <li><a href="https://github.com/transcranial" target="_blank">Leon Chen <@transcranial></a></li>\n    <li></li>\n  </ul>\n</aside>\n';
},function(e,n){e.exports='<div class="demo mnist-cnn">\n  <div class="title">\n    <span>Basic Convnet for MNIST</span>\n    <mdl-spinner v-if="modelLoading && loadingProgress < 100"></mdl-spinner>\n  </div>\n  <div class="loading-progress" v-if="modelLoading && loadingProgress < 100">\n    Loading...{{ loadingProgress }}%\n  </div>\n  <div class="info-panel" v-if="showInfoPanel">\n    <div class="info-panel-text">\n      Interactive demo of a simple convnet trained on MNIST (see <a target="_blank" href="https://github.com/transcranial/keras-js/blob/master/demos/notebooks/mnist_cnn.ipynb">Jupyter notebook</a>). All computation performed entirely in your browser. Toggling GPU on/off shouldn\'t reveal any significant speed differences, as this is a fairly small network. In the architecture diagram below, intermediate outputs at each layer are also visualized.\n    </div>\n    <div class="info-panel-close">\n      <div class="info-panel-close-btn" @click="closeInfoPanel"><i class="material-icons">close</i>CLOSE</div>\n    </div>\n  </div>\n  <div class="columns input-output" v-if="!modelLoading">\n    <div class="column input-column">\n      <div class="input-container">\n        <div class="input-label">Draw any digit (0-9) here <span class="arrow">⤸</span></div>\n        <div class="canvas-container">\n          <canvas\n            id="input-canvas" width="240" height="240"\n            @mousedown="activateDraw"\n            @mouseup="deactivateDrawAndPredict"\n            @mouseleave="deactivateDrawAndPredict"\n            @mousemove="draw"\n            @touchstart="activateDraw"\n            @touchend="deactivateDrawAndPredict"\n            @touchmove="draw"\n          ></canvas>\n          <canvas id="input-canvas-scaled" width="28" height="28" style="display:none;"></canvas>\n          <canvas id="input-canvas-centercrop" style="display:none;"></canvas>\n        </div>\n        <div class="input-buttons">\n          <div class="input-clear-button" v-on:click="clear"><i class="material-icons">clear</i>CLEAR</div>\n        </div>\n      </div>\n    </div>\n    <div class="column is-2 controls-column">\n      <mdl-switch\n        :checked.sync="useGpu"\n        :disabled="modelLoading || !hasWebgl"\n        @click="toggleGpu"\n      >use GPU</mdl-switch>\n    </div>\n    <div class="column output-column">\n      <div class="output">\n        <div class="output-class"\n          v-bind:class="{ \'predicted\': i === predictedClass }"\n          v-for="i in outputClasses"\n        >\n          <div class="output-label">{{ i }}</div>\n          <div class="output-bar"\n            style="height: {{ Math.round(100 * output[i]) }}px; background: rgba(27, 188, 155, {{ output[i].toFixed(2) }});"\n          ></div>\n        </div>\n      </div>\n    </div>\n  </div>\n  <div class="layer-results-container" v-if="!modelLoading">\n    <div class="bg-line"></div>\n    <div\n      v-for="layerResult in layerResultImages"\n      class="layer-result"\n    >\n      <div class="layer-result-heading">\n        <span class="layer-class">{{ layerResult.layerClass }}</span>\n        <span> {{ layerDisplayConfig[layerResult.name].heading }}</span>\n      </div>\n      <div class="layer-result-canvas-container">\n        <canvas v-for="image in layerResult.images"\n          id="intermediate-result-{{ $parent.$index }}-{{ $index }}"\n          width="{{ image.width }}"\n          height="{{ image.height }}"\n          style="display:none;"\n        ></canvas>\n        <canvas v-for="image in layerResult.images"\n          id="intermediate-result-{{ $parent.$index }}-{{ $index }}-scaled"\n          width="{{ layerDisplayConfig[layerResult.name].scalingFactor * image.width }}"\n          height="{{ layerDisplayConfig[layerResult.name].scalingFactor * image.height }}"\n        ></canvas>\n      </div>\n    </div>\n  </div>\n</div>\n'},function(e,n){e.exports='<div class="demo mnist-vae">\n  <div class="title">\n    <span>Convolutional Variational Autoencoder, trained on MNIST</span>\n    <mdl-spinner v-if="modelLoading && loadingProgress < 100"></mdl-spinner>\n  </div>\n  <div class="loading-progress" v-if="modelLoading && loadingProgress < 100">\n    Loading...{{ loadingProgress }}%\n  </div>\n  <div class="info-panel" v-if="showInfoPanel">\n    <div class="info-panel-text">\n      Modified from the MNIST convolution/deconvolution variational autoencoder example <a target="_blank" href="https://github.com/fchollet/keras/blob/master/examples/variational_autoencoder_deconv.py">here</a>. The network demonstrated here is the generative decoder portion (see <a target="_blank" href="https://github.com/transcranial/keras-js/blob/master/demos/notebooks/mnist_vae.ipynb">Jupyter notebook</a>). The network generates an image through a series of Deconvolution2D layers from coordinates in the 2D latent space. All computation performed entirely in your browser. Toggling GPU on/off shouldn\'t reveal any significant speed differences, as this is a fairly small network. In the architecture diagram below, intermediate outputs at each layer are also visualized.\n    </div>\n    <div class="info-panel-close">\n      <div class="info-panel-close-btn" @click="closeInfoPanel"><i class="material-icons">close</i>CLOSE</div>\n    </div>\n  </div>\n  <div class="columns input-output" v-if="!modelLoading">\n    <div class="column input-column">\n      <div class="input-container">\n        <div class="input-label">Click around the latent space <span class="arrow">⤸</span></div>\n        <div class="canvas-container">\n          <canvas\n            id="input-canvas" width="200" height="200"\n            @mouseenter="activateCrosshairs"\n            @mouseleave="deactivateCrosshairs"\n            @mousemove="draw"\n            @click="selectCoordinates"\n            @touchend="selectCoordinates"\n          ></canvas>\n          <div class="axis x-axis">\n            <span>-1.5</span>\n            <span>x</span>\n            <span>1.5</span>\n          </div>\n          <div class="axis y-axis">\n            <span>-1.5</span>\n            <span>y</span>\n            <span>1.5</span>\n          </div>\n        </div>\n      </div>\n    </div>\n    <div class="column is-2 controls-column">\n      <mdl-switch\n        :checked.sync="useGpu"\n        :disabled="modelLoading || !hasWebgl"\n        @click="toggleGpu"\n      >use GPU</mdl-switch>\n      <div class="coordinates">\n        <div class="coordinates-x">x: {{ inputCoordinates[0] < 0 ? inputCoordinates[0].toFixed(2) : inputCoordinates[0].toFixed(3) }}</div>\n        <div class="coordinates-y">y: {{ inputCoordinates[1] < 0 ? inputCoordinates[1].toFixed(2) : inputCoordinates[1].toFixed(3) }}</div>\n      </div>\n    </div>\n    <div class="column output-column">\n      <div class="output">\n        <canvas id="output-canvas-scaled" width="150" height="150"></canvas>\n        <canvas id="output-canvas" width="27" height="27" style="display:none;"></canvas>\n      </div>\n    </div>\n  </div>\n  <div class="layer-results-container" v-if="!modelLoading">\n    <div class="bg-line"></div>\n    <div\n      v-for="layerResult in layerResultImages"\n      class="layer-result"\n    >\n      <div class="layer-result-heading">\n        <span class="layer-class">{{ layerResult.layerClass }}</span>\n        <span> {{ layerDisplayConfig[layerResult.name].heading }}</span>\n      </div>\n      <div class="layer-result-canvas-container">\n        <canvas v-for="image in layerResult.images"\n          id="intermediate-result-{{ $parent.$index }}-{{ $index }}"\n          width="{{ image.width }}"\n          height="{{ image.height }}"\n          style="display:none;"\n        ></canvas>\n        <canvas v-for="image in layerResult.images"\n          id="intermediate-result-{{ $parent.$index }}-{{ $index }}-scaled"\n          width="{{ layerDisplayConfig[layerResult.name].scalingFactor * image.width }}"\n          height="{{ layerDisplayConfig[layerResult.name].scalingFactor * image.height }}"\n        ></canvas>\n      </div>\n    </div>\n  </div>\n</div>\n'},function(e,n){e.exports='<div class="demo resnet50">\n  <div class="title">\n    <span>50-layer Residual Network, trained on ImageNet</span>\n    <mdl-spinner v-if="modelLoading && loadingProgress < 100"></mdl-spinner>\n  </div>\n  <div class="loading-progress" v-if="modelLoading && loadingProgress < 100">\n    Loading...{{ loadingProgress }}%\n  </div>\n  <div class="info-panel" v-if="showInfoPanel">\n    <div class="info-panel-text">\n      Note that ~100 MB of weights must be loaded. We use the Keras architecture from <a target="_blank" href="https://github.com/fchollet/keras/blob/master/keras/applications/resnet50.py">here</a> and pretrained weights from <a target="_blank" href="https://github.com/fchollet/deep-learning-models">here</a>. Enter any valid image URL as input to the network. You can also select from a list of prepopulated image URLs. The endpoint must have CORS enabled, to enable us to extract the numeric data from the canvas element, so not all URLs will work. Imgur and <a target="_blank" href="https://www.flickr.com/search/?text=&license=2%2C3%2C4%2C5%2C6%2C9&sort=interestingness-desc">Flickr creative commons</a> all work, and are good places to start. After running the network, the top-5 classes are displayed. Keep in mind also we are limited to the <a target="_blank" href="https://github.com/transcranial/keras-js/blob/master/demos/src/utils/imagenet.js">1,000 classes of ImageNet</a>. Keep in mind that this is image classification and not object detection, so the network is forced to output a single class through softmax. Best results are on images where the classification target spans a large portion of the image. All computation performed entirely in your browser. Toggling GPU on should offer significant speedups compared to CPU. Running the network may still take several seconds (optimizations to come). With "show computational flow" toggled, computation through the network will be shown in the architecture diagram (scroll down as computation is performed layer by layer). Turning this feature off will also speed up computation.\n    </div>\n    <div class="info-panel-close">\n      <div class="info-panel-close-btn" @click="closeInfoPanel"><i class="material-icons">close</i>CLOSE</div>\n    </div>\n  </div>\n  <div class="top-container" v-if="!modelLoading">\n    <div class="input-container">\n      <div class="input-label">Enter a valid image URL or select an image from the dropdown:</div>\n      <div class="image-url">\n        <mdl-textfield\n          floating-label="enter image url"\n          :value.sync="imageURLInput"\n          spellcheck="false"\n          @change="imageURLInputChanged"\n        ></mdl-textfield>\n        <span>or</span>\n        <mdl-select\n          label="select image"\n          id="image-url-select"\n          :value.sync="imageURLSelect"\n          :options="imageURLSelectList"\n          style="width:200px;"\n          @change="imageURLSelectChanged"\n        ></mdl-select>\n      </div>\n    </div>\n    <div class="controls">\n      <mdl-switch\n        :checked.sync="useGpu"\n        :disabled="modelLoading || modelRunning || !hasWebgl"\n        @click="toggleGpu"\n      >Use GPU</mdl-switch>\n      <mdl-switch\n        :checked.sync="showComputationFlow"\n        :disabled="modelLoading || modelRunning"\n        @click="toggleComputationFlow"\n      >Show computation flow</mdl-switch>\n    </div>\n  </div>\n  <div class="columns input-output" v-if="!modelLoading">\n    <div class="column input-column">\n      <div class="loading-indicator">\n        <mdl-spinner v-if="imageLoading || modelRunning"></mdl-spinner>\n        <div class="error" v-if="imageLoadingError">Error loading URL</div>\n      </div>\n      <div class="canvas-container">\n        <canvas id="input-canvas" width="224" height="224"></canvas>\n      </div>\n    </div>\n    <div class="column output-column">\n      <div class="output">\n        <div class="output-class"\n          :class="{ \'predicted\': i === 0 && outputClasses[i].probability.toFixed(2) > 0 }"\n          v-for="i in [0, 1, 2, 3, 4]"\n        >\n          <div class="output-label">{{ outputClasses[i].name }}</div>\n          <div class="output-bar"\n            style="width: {{ Math.round(100 * outputClasses[i].probability) }}px; background: rgba(27, 188, 155, {{ outputClasses[i].probability.toFixed(2) }});"\n          ></div>\n          <div class="output-value">{{ Math.round(100 * outputClasses[i].probability) }}%</div>\n        </div>\n      </div>\n    </div>\n  </div>\n  <div class="architecture-container" v-if="!modelLoading">\n    <div v-for="row in architectureDiagramRows" class="layers-row">\n      <div v-for="layer in row" class="layer-column">\n        <div\n          v-if="layer.className"\n          class="layer"\n          :class="{ \'has-result\': layersWithResults.includes(layer.name) }"\n          :id="layer.name"\n        >\n          <div class="layer-class-name">{{ layer.className }}</div>\n          <div class="layer-details"> {{ layer.details }}</div>\n        </div>\n      </div>\n    </div>\n    <svg class="architecture-connections" width="100%" height="100%">\n      <g>\n        <path v-for="path in architectureDiagramPaths" :d="path" />\n      </g>\n    </svg>\n  </div>\n</div>\n'},function(e,n){e.exports='<div class="demo xception">\n  <div class="title">\n    <span>Xception, trained on ImageNet</span>\n    <mdl-spinner v-if="modelLoading && loadingProgress < 100"></mdl-spinner>\n  </div>\n  <div class="loading-progress" v-if="modelLoading && loadingProgress < 100">\n    Loading...{{ loadingProgress }}%\n  </div>\n  <div class="info-panel" v-if="showInfoPanel">\n    <div class="info-panel-text">\n      Controls currently disabled as network is very slow - SeparableConvolution2D layer implementation needs heavy optimization. Note that ~100 MB of weights must be loaded. We use the Keras architecture from <a target="_blank" href="https://github.com/fchollet/keras/blob/master/keras/applications/xception.py">here</a> and pretrained weights from <a target="_blank" href="https://github.com/fchollet/deep-learning-models">here</a>. Enter any valid image URL as input to the network. You can also select from a list of prepopulated image URLs. The endpoint must have CORS enabled, to enable us to extract the numeric data from the canvas element, so not all URLs will work. Imgur and <a target="_blank" href="https://www.flickr.com/search/?text=&license=2%2C3%2C4%2C5%2C6%2C9&sort=interestingness-desc">Flickr creative commons</a> all work, and are good places to start. After running the network, the top-5 classes are displayed. Keep in mind also we are limited to the <a target="_blank" href="https://github.com/transcranial/keras-js/blob/master/demos/src/utils/imagenet.js">1,000 classes of ImageNet</a>. Keep in mind that this is image classification and not object detection, so the network is forced to output a single class through softmax. Best results are on images where the classification target spans a large portion of the image. All computation performed entirely in your browser. Toggling GPU on should offer significant speedups compared to CPU. Running the network may still take several seconds (optimizations to come). With "show computational flow" toggled, computation through the network will be shown in the architecture diagram (scroll down as computation is performed layer by layer). Turning this feature off will also speed up computation.\n    </div>\n    <div class="info-panel-close">\n      <div class="info-panel-close-btn" @click="closeInfoPanel"><i class="material-icons">close</i>CLOSE</div>\n    </div>\n  </div>\n  <!--<div class="top-container" v-if="!modelLoading">\n    <div class="input-container">\n      <div class="input-label">Enter a valid image URL or select an image from the dropdown:</div>\n      <div class="image-url">\n        <mdl-textfield\n          floating-label="enter image url"\n          :value.sync="imageURLInput"\n          spellcheck="false"\n          @change="imageURLInputChanged"\n        ></mdl-textfield>\n        <span>or</span>\n        <mdl-select\n          label="select image"\n          id="image-url-select"\n          :value.sync="imageURLSelect"\n          :options="imageURLSelectList"\n          style="width:200px;"\n          @change="imageURLSelectChanged"\n        ></mdl-select>\n      </div>\n    </div>\n    <div class="controls">\n      <mdl-switch\n        :checked.sync="useGpu"\n        :disabled="modelLoading || modelRunning || !hasWebgl"\n        @click="toggleGpu"\n      >Use GPU</mdl-switch>\n      <mdl-switch\n        :checked.sync="showComputationFlow"\n        :disabled="modelLoading || modelRunning"\n        @click="toggleComputationFlow"\n      >Show computation flow</mdl-switch>\n    </div>\n  </div>-->\n  <div class="columns input-output" v-if="!modelLoading">\n    <div class="column input-column">\n      <div class="loading-indicator">\n        <mdl-spinner v-if="imageLoading || modelRunning"></mdl-spinner>\n        <div class="error" v-if="imageLoadingError">Error loading URL</div>\n      </div>\n      <div class="canvas-container">\n        <canvas id="input-canvas" width="299" height="299"></canvas>\n      </div>\n    </div>\n    <div class="column output-column">\n      <div class="output">\n        <div class="output-class"\n          :class="{ \'predicted\': i === 0 && outputClasses[i].probability.toFixed(2) > 0 }"\n          v-for="i in [0, 1, 2, 3, 4]"\n        >\n          <div class="output-label">{{ outputClasses[i].name }}</div>\n          <div class="output-bar"\n            style="width: {{ Math.round(100 * outputClasses[i].probability) }}px; background: rgba(27, 188, 155, {{ outputClasses[i].probability.toFixed(2) }});"\n          ></div>\n          <div class="output-value">{{ Math.round(100 * outputClasses[i].probability) }}%</div>\n        </div>\n      </div>\n    </div>\n  </div>\n  <div class="architecture-container" v-if="!modelLoading">\n    <div v-for="row in architectureDiagramRows" class="layers-row">\n      <div v-for="layers in row" class="layer-column">\n        <div\n          v-for="layer in layers"\n          v-if="layer.className"\n          class="layer"\n          :class="{ \'has-result\': layersWithResults.includes(layer.name) }"\n          :id="layer.name"\n        >\n          <div class="layer-class-name">{{ layer.className }}</div>\n          <div class="layer-details"> {{ layer.details }}</div>\n        </div>\n      </div>\n    </div>\n    <svg class="architecture-connections" width="100%" height="100%">\n      <g>\n        <path v-for="path in architectureDiagramPaths" :d="path" />\n      </g>\n    </svg>\n  </div>\n</div>\n'},function(e,n,t){var a=t(96);"string"==typeof a&&(a=[[e.i,a,""]]);t(4)(a,{});a.locals&&(e.exports=a.locals)},function(e,n,t){var a=t(97);"string"==typeof a&&(a=[[e.i,a,""]]);t(4)(a,{});a.locals&&(e.exports=a.locals)},function(e,n,t){var a=t(98);"string"==typeof a&&(a=[[e.i,a,""]]);t(4)(a,{});a.locals&&(e.exports=a.locals)},function(e,n,t){var a=t(99);"string"==typeof a&&(a=[[e.i,a,""]]);t(4)(a,{});a.locals&&(e.exports=a.locals)},function(e,n,t){var a=t(100);"string"==typeof a&&(a=[[e.i,a,""]]);t(4)(a,{});a.locals&&(e.exports=a.locals)},function(e,n,t){var a=t(101);"string"==typeof a&&(a=[[e.i,a,""]]);t(4)(a,{});a.locals&&(e.exports=a.locals)},function(e,n,t){var a=t(102);"string"==typeof a&&(a=[[e.i,a,""]]);t(4)(a,{});a.locals&&(e.exports=a.locals)},function(e,n,t){var a=t(103);"string"==typeof a&&(a=[[e.i,a,""]]);t(4)(a,{});a.locals&&(e.exports=a.locals)},function(e,n,t){var a=t(104);"string"==typeof a&&(a=[[e.i,a,""]]);t(4)(a,{});a.locals&&(e.exports=a.locals)},function(e,n,t){e.exports=t(63)}]);