Quant_Code/5.课程代码/4.Stock-Prediction-Models/使用文档/Stock-Prediction-Models-master/stock-forecasting-js/js/tf.js

!function(e,t){"object"==typeof exports&&"undefined"!=typeof module?t(exports):"function"==typeof define&&define.amd?define(["exports"],t):t(e.tf=e.tf||{})}(this,function(exports){"use strict";function isMobile(){var e=navigator.userAgent||navigator.vendor||window.opera;return/(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i.test(e)||/1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\-(n|u)|c55\/|capi|ccwa|cdm\-|cell|chtm|cldc|cmd\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\-s|devi|dica|dmob|do(c|p)o|ds(12|\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\-|_)|g1 u|g560|gene|gf\-5|g\-mo|go(\.w|od)|gr(ad|un)|haie|hcit|hd\-(m|p|t)|hei\-|hi(pt|ta)|hp( i|ip)|hs\-c|ht(c(\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\-(20|go|ma)|i230|iac( |\-|\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\/)|klon|kpt |kwc\-|kyo(c|k)|le(no|xi)|lg( g|\/(k|l|u)|50|54|\-[a-w])|libw|lynx|m1\-w|m3ga|m50\/|ma(te|ui|xo)|mc(01|21|ca)|m\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\-2|po(ck|rt|se)|prox|psio|pt\-g|qa\-a|qc(07|12|21|32|60|\-[2-7]|i\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\-|oo|p\-)|sdk\/|se(c(\-|0|1)|47|mc|nd|ri)|sgh\-|shar|sie(\-|m)|sk\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\-|v\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\-|tdg\-|tel(i|m)|tim\-|t\-mo|to(pl|sh)|ts(70|m\-|m3|m5)|tx\-9|up(\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\-|your|zeto|zte\-/i.test(e.substr(0,4))}function doc(e){return function(){for(var e=[],t=0;t<arguments.length;t++)e[t]=arguments[t]}}function assertArgumentIsTensor(e,t,r){assert(e instanceof Tensor,"Argument '"+t+"' passed to '"+r+"' must be a Tensor, but got "+typeof e+".")}function assertArgumentsAreTensors(e,t){for(var r in e)!function(r){var n=e[r];Array.isArray(n)?n.forEach(function(e,n){assertArgumentIsTensor(e,r+"["+n+"]",t)}):assertArgumentIsTensor(n,r,t)}(r)}function shuffle(e){for(var t=e.length,r=0,n=0;t>0;)n=Math.random()*t|0,r=e[--t],e[t]=e[n],e[n]=r}function clamp(e,t,r){return Math.max(e,Math.min(t,r))}function randUniform(e,t){return Math.random()*(t-e)+e}function distSquared(e,t){for(var r=0,n=0;n<e.length;n++){var a=Number(e[n])-Number(t[n]);r+=a*a}return r}function assert(e,t){if(!e)throw new Error(t)}function assertShapesMatch(e,t,r){void 0===r&&(r=""),assert(arraysEqual(e,t),r+" Shapes "+e+" and "+t+" must match")}function assertTypesMatch(e,t){assert(e.dtype===t.dtype," The dtypes of the first("+e.dtype+") and second("+t.dtype+") input must match")}function flatten(e,t){if(void 0===t&&(t=[]),Array.isArray(e))for(var r=0;r<e.length;++r)flatten(e[r],t);else t.push(e);return t}function inferShape(e){if(isTypedArray(e))return[e.length];if(!Array.isArray(e))return[];for(var t=[];e instanceof Array;)t.push(e.length),e=e[0];return t}function sizeFromShape(e){if(0===e.length)return 1;for(var t=e[0],r=1;r<e.length;r++)t*=e[r];return t}function isScalarShape(e){return 0===e.length}function arraysEqual(e,t){if(e.length!==t.length)return!1;for(var r=0;r<e.length;r++)if(e[r]!==t[r])return!1;return!0}function isInt(e){return e%1==0}function tanh(e){if(null!=Math.tanh)return Math.tanh(e);if(e===1/0)return 1;if(e===-1/0)return-1;var t=Math.exp(2*e);return(t-1)/(t+1)}function sizeToSquarishShape(e){for(var t=Math.floor(Math.sqrt(e));t>1;--t)if(e%t==0)return[t,e/t];return[1,e]}function createShuffledIndices(e){for(var t=new Uint32Array(e),r=0;r<e;++r)t[r]=r;return shuffle(t),t}function rightPad(e,t){return t<=e.length?e:e+" ".repeat(t-e.length)}function repeatedTry(e,t,r){return void 0===t&&(t=function(e){return 0}),new Promise(function(n,a){var o=0,i=function(){if(e())n();else{var s=t(++o);null!=r&&o>=r?a():setTimeout(i,s)}};i()})}function getQueryParams(e){var t={};return e.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g,function(e){for(var r=[],n=1;n<arguments.length;n++)r[n-1]=arguments[n];return decodeParam(t,r[0],r[1]),r.join("=")}),t}function decodeParam(e,t,r){e[decodeURIComponent(t)]=decodeURIComponent(r||"")}function inferFromImplicitShape(e,t){for(var r=1,n=-1,a=0;a<e.length;++a)if(e[a]>0)r*=e[a];else if(-1===e[a]){if(-1!==n)throw Error("Shapes can only have 1 implicit size. Found - 1 at dim "+n+" and dim "+a);n=a}else if(e[a]<=0)throw Error("Shapes can not be <= 0. Found "+e[a]+" at dim "+a);if(-1===n){if(t>0&&t!==r)throw Error("Size("+t+") must match the product of shape "+e);return e}if(t%r!=0)throw Error("The implicit shape can't be a fractional number. 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Got axes "+t+" and rank-"+r+" input.")}function getAxesPermutation(e,t){if(axesAreInnerMostDims(e,t))return null;for(var r=[],n=0;n<t;++n)-1===e.indexOf(n)&&r.push(n);return e.forEach(function(e){return r.push(e)}),r}function getUndoAxesPermutation(e){return e.map(function(e,t){return[t,e]}).sort(function(e,t){return e[1]-t[1]}).map(function(e){return e[0]})}function getInnerMostAxes(e,t){for(var r=[],n=t-e;n<t;++n)r.push(n);return r}function assertParams(e,t,r){var n=e.length,a=t.length;assert(e.length===t.length,"Error in concat"+n+"D: rank of x1 ("+n+") and x2 ("+a+") must be the same."),assert(r>=0&&r<n,"Error in concat"+n+"D: axis must be between 0 and "+(n-1)+".");for(var o=0;o<n;o++)assert(o===r||e[o]===t[o],"Error in concat"+n+"D: Shape ("+e+") does not match ("+t+") along the non-concatenated axis "+o+".")}function computeOutShape(e,t,r){assert(e.length===t.length,"x1 and x2 should have the same rank.");var n=e.slice();return n[r]+=t[r],n}function computeGradientSliceShapes(e,t){return{aBegin:[0,0],aSize:e,bBegin:[0,e[1]],bSize:t}}function operation(e,t,r){var n=r.value;return r.value=function(){for(var e=[],r=0;r<arguments.length;r++)e[r]=arguments[r];return tidy(t,function(){return n.apply(void 0,e)})},r}function concat2Tensors(e,t,r){assertParams(e.shape,t.shape,r);var n=computeOutShape(e.shape,t.shape,r),a=e.as2D(-1,sizeFromShape(e.shape.slice(r))),o=t.as2D(-1,sizeFromShape(t.shape.slice(r))),i=computeGradientSliceShapes(a.shape,o.shape),s=i.aBegin,u=i.aSize,l=i.bBegin,c=i.bSize;return ENV.engine.runKernel(function(e){return e.concat(a,o)},{a:a,b:o},function(e){return{a:function(){return e.slice(s,u)},b:function(){return e.slice(l,c)}}}).reshape(n)}function createCommonjsModule(e,t){return t={exports:{}},e(t,t.exports),t.exports}function makeZerosTypedArray(e,t){if(null==t||"float32"===t)return new Float32Array(e);if("int32"===t)return new Int32Array(e);if("bool"===t)return new Uint8Array(e);throw new Error("Unknown data type $ {dtype}")}function makeOnesTypedArray(e,t){for(var r=makeZerosTypedArray(e,t),n=0;n<r.length;n++)r[n]=1;return r}function toTypedArray(e,t){return noConversionNeeded(e,t)?e:(Array.isArray(e)&&(e=flatten(e)),copyTypedArray(e,t))}function noConversionNeeded(e,t){return e instanceof Float32Array&&"float32"===t||e instanceof Int32Array&&"int32"===t||e instanceof Uint8Array&&"bool"===t}function getBroadcastDims(e,t){for(var r=e.length,n=[],a=0;a<r;a++){var o=r-1-a,i=e[o]||1;(t[t.length-1-a]||1)>1&&1===i&&n.unshift(o)}return n}function getReductionAxes(e,t){for(var r=[],n=0;n<t.length;n++){var a=e[e.length-n-1],o=t.length-n-1,i=t[o];(null==a||1===a&&i>1)&&r.unshift(o)}return r}function broadcastDimsAreOuter(e){for(var t=0;t<e.length;t++)if(e[t]!==t)return!1;return!0}function assertAndGetBroadcastShape(e,t){for(var r=[],n="Operands could not be broadcast together with shapes "+e+" and "+t+".",a=Math.max(e.length,t.length),o=0;o<a;o++){var i=e[e.length-o-1]||1,s=t[t.length-o-1]||1;if(i>1&&s>1&&i!==s)throw Error(n);r.unshift(Math.max(i,s))}return r}function batchnormReshape4D(e){return null==e?null:0===e.rank?e.as1D():1===e.rank?e:2===e.rank?e.as4D(1,1,e.shape[0],e.shape[1]):3===e.rank?e.as4D(1,e.shape[0],e.shape[1],e.shape[2]):e}function upcastType(e,t){return upcastTypeMap[e][t]}function sumOutType(e){return upcastType(e,"int32")}function computePool2DInfo(e,t,r,n,a,o){void 0===o&&(o="channelsLast");var i,s=parseTupleParam(t),u=s[0],l=s[1];if("channelsLast"===o)i=[u,l,e[3],e[3]];else{if("channelsFirst"!==o)throw new Error("Unknown dataFormat "+o);i=[u,l,e[1],e[1]]}return computeConv2DInfo(e,i,r,1,n,a,!1,o)}function computeConv2DInfo(e,t,r,n,a,o,i,s){void 0===i&&(i=!1),void 0===s&&(s="channelsLast");var u=[-1,-1,-1,-1],l=u[0],c=u[1],p=u[2],d=u[3];if("channelsLast"===s)l=e[0],c=e[1],p=e[2],d=e[3];else{if("channelsFirst"!==s)throw new Error("Unknown dataFormat "+s);l=e[0],d=e[1],c=e[2],p=e[3]}var h,f=t[0],m=t[1],g=t[3],y=parseTupleParam(r),v=y[0],b=y[1],x=parseTupleParam(n),w=x[0],_=x[1],S=getPadAndOutInfo(a,c,p,v,b,getEffectiveFilterSize(f,w),getEffectiveFilterSize(m,_),o),N=S.padInfo,A=S.outHeight,E=S.outWidth,T=i?g*d:g;return"channelsFirst"===s?h=[l,T,A,E]:"channelsLast"===s&&(h=[l,A,E,T]),{batchSize:l,dataFormat:s,inHeight:c,inWidth:p,inChannels:d,outHeight:A,outWidth:E,outChannels:T,padInfo:N,strideHeight:v,strideWidth:b,filterHeight:f,filterWidth:m,dilationHeight:w,dilationWidth:_,inShape:e,outShape:h,filterShape:t}}function computeOutputShape3D(e,t,r,n,a,o){null==a&&(a=computeDefaultPad(e,t,n));var i=e[0],s=e[1],u=conditionalRound((i-t+2*a)/n+1,o);assert(isInt(u),"The output # of rows ("+u+") must be an integer. Change the stride and/or zero pad parameters");var l=conditionalRound((s-t+2*a)/n+1,o);return assert(isInt(l),"The output # of columns ("+l+") must be an integer. Change the stride and/or zero pad parameters"),[u,l,r]}function computeDefaultPad(e,t,r,n){void 0===n&&(n=1);var a=getEffectiveFilterSize(t,n);return Math.floor((e[0]*(r-1)-r+a)/2)}function parseTupleParam(e){return"number"==typeof e?[e,e]:e}function getEffectiveFilterSize(e,t){return t<=1?e:e+(e-1)*(t-1)}function getPadAndOutInfo(e,t,r,n,a,o,i,s){var u,l,c;if("number"==typeof e){u={top:e,bottom:e,left:e,right:e,type:0===e?"VALID":"NUMBER"};var p=computeOutputShape3D([t,r,1],o,1,n,e,s);l=p[0],c=p[1]}else if("same"===e){var d=((l=Math.ceil(t/n))-1)*n+o-t,h=((c=Math.ceil(r/a))-1)*a+i-r,f=Math.floor(d/2),m=d-f,g=Math.floor(h/2);u={top:f,bottom:m,left:g,right:h-g,type:"SAME"}}else{if("valid"!==e)throw Error("Unknown padding parameter: "+e);u={top:0,bottom:0,left:0,right:0,type:"VALID"},l=Math.ceil((t-o+1)/n),c=Math.ceil((r-i+1)/a)}return{padInfo:u,outHeight:l,outWidth:c}}function conditionalRound(e,t){if(!t)return e;switch(t){case"round":return Math.round(e);case"ceil":return Math.ceil(e);case"floor":return Math.floor(e);default:throw new Error("Unknown roundingMode "+t)}}function parseTupleParam$1(e){return"number"==typeof e?[e,e]:e}function tupleValuesAreOne(e){var t=parseTupleParam$1(e),r=t[0],n=t[1];return 1===r&&1===n}function eitherStridesOrDilationsAreOne(e,t){return tupleValuesAreOne(e)||tupleValuesAreOne(t)}function depthwiseConv2dDerInput(e,t,r,n){var a=t,o=!1;3===t.rank&&(o=!0,a=t.as4D(1,t.shape[0],t.shape[1],t.shape[2]));var i=ENV.engine.runKernel(function(e){return e.depthwiseConv2DDerInput(a,r,n)},{dy4D:a});return o?i.as3D(i.shape[1],i.shape[2],i.shape[3]):i}function depthwiseConv2dDerFilter(e,t,r,n){var a=e;3===e.rank&&(a=e.as4D(1,e.shape[0],e.shape[1],e.shape[2]));var o=t;return 3===o.rank&&(o=t.as4D(1,t.shape[0],t.shape[1],t.shape[2])),ENV.engine.runKernel(function(e){return e.depthwiseConv2DDerFilter(a,o,n)},{x4D:a,dy4D:o})}function normImpl(e,t,r){if(void 0===r&&(r=null),0===e.rank)return e.abs();if(1!==e.rank&&null===r)return normImpl(e.reshape([-1]),t,r);if(1===e.rank||"number"==typeof r||r instanceof Array&&1===r.length){if(1===t)return e.abs().sum(r);if(t===1/0)return e.abs().max(r);if(t===-1/0)return e.abs().min(r);if("euclidean"===t||2===t)return e.abs().pow(scalar(2,"int32")).sum(r).sqrt();throw new Error("Error in norm: invalid ord value: "+t)}if(r instanceof Array&&2===r.length){if(1===t)return e.abs().sum(r[0]).max(r[1]-1);if(t===1/0)return e.abs().sum(r[1]).max(r[0]);if(t===-1/0)return e.abs().sum(r[1]).min(r[0]);if("fro"===t||"euclidean"===t)return e.square().sum(r).sqrt();throw new Error("Error in norm: invalid ord value: "+t)}throw new Error("Error in norm: invalid axis: "+r)}function assertParamsValid(e,t,r){assert(e.rank===t.length,"Error in slice"+e.rank+"D: Length of begin "+t+" must match the rank of the array ("+e.rank+")."),assert(e.rank===r.length,"Error in slice"+e.rank+"D: Length of size "+r+" must match the rank of the array ("+e.rank+").");for(var n=0;n<e.rank;++n)assert(t[n]+r[n]<=e.shape[n],"Error in slice"+e.rank+"D: begin["+n+"] + size["+n+"] ("+(t[n]+r[n])+") would overflow input.shape["+n+"] ("+e.shape[n]+")")}function getStridedSlicedInfo(e,t,r,n,a,o){void 0===a&&(a=0),void 0===o&&(o=0);for(var i=[],s=[],u=0;u<e.length;u++)i[u]=startForAxis(a,t,n,e,u),s[u]=stopForAxis(o,r,n,e,u);var l=new Array(e.length).fill(0);return l=l.map(function(e,t){for(var r=0,a=i[t];!(n[t]>0?a>=s[t]:a<=s[t]);a+=n[t])r+=1;return r}),[i,l]}function startForAxis(e,t,r,n,a){var o=t[a];e&1<<a&&(o=r[a]>0?Number.MIN_SAFE_INTEGER:Number.MAX_SAFE_INTEGER);var i=n[a];return o<0&&(o+=i),o=clamp(0,o,i-1)}function stopForAxis(e,t,r,n,a){var o=t[a];e&1<<a&&(o=r[a]>0?Number.MAX_SAFE_INTEGER:Number.MIN_SAFE_INTEGER);var i=n[a];return o<0&&(o+=i),o=r[a]>0?clamp(0,o,i):clamp(-1,o,i-1)}function computeStrides(e){var t=e.length;if(t<2)return[];var r=new Array(t-1);r[t-2]=e[t-1];for(var n=t-3;n>=0;--n)r[n]=r[n+1]*e[n+1];return r}function checkGrads(e){if(e.filter(function(e){return null==e}).length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that\n    the f you passed encloses all operations that lead from x to y.")}function getFilteredNodesXToY(e,t,r){for(var n={},a={},o=0;o<t.length;o++)n[t[o].id]=!0;for(o=0;o<e.length;o++){d=(m=e[o]).inputs;for(var i in d){for(var s=d[i],u=!1,l=0;l<t.length;l++)if(n[s.id]){n[m.output.id]=!0,u=!0,a[m.id]=!0;break}if(u)break}}var c={};c[r.id]=!0;for(var p={},o=e.length-1;o>=0;o--){var d=(m=e[o]).inputs,h=[];h.push(m.output);for(l=0;l<h.length;l++)if(c[h[l].id]){for(var i in d)c[d[i].id]=!0,p[m.id]=!0;break}}for(var f=[],o=0;o<e.length;o++){var m=e[o];if(a[m.id]&&p[m.id]){var g={};for(var i in m.inputs){var y=m.inputs[i];n[y.id]&&(g[i]=y)}var v=Object.assign({},m);v.inputs=g,v.output=m.output,f.push(v)}}return f}function backpropagateGradients(e,t){for(var r=t.length-1;r>=0;r--){var n=t[r],a=e[n.output.id];if(null==n.gradient)throw new Error("Cannot compute gradient: gradient function not found for "+n.name+".");var o=n.gradient(a);for(var i in n.inputs){if(!(i in o))throw new Error("Cannot backprop through input "+i+". Available gradients found: "+Object.keys(o)+".");var s=o[i](),u=n.inputs[i];if(!arraysEqual(s.shape,u.shape))throw new Error("Error in gradient for op "+n.name+". The gradient of input '"+i+"' has shape '"+s.shape+"', which does not match the shape of the input '"+u.shape+"'");if(null==e[u.id])e[u.id]=s;else{var l=e[u.id];e[u.id]=l.add(s),l.dispose()}}}}function hasExtension(e,t){return null!=e.getExtension(t)}function getWebGLRenderingContext(e){if(0===e||!ENV.get("IS_BROWSER"))throw new Error("Cannot get WebGL rendering context, WebGL is disabled.");var t=document.createElement("canvas");return 1===e?t.getContext("webgl")||t.getContext("experimental-webgl"):t.getContext("webgl2")}function loseContext(e){if(null!=e){var t=e.getExtension("WEBGL_lose_context");if(null==t)throw new Error("Extension WEBGL_lose_context not supported on this browser.");t.loseContext()}}function isWebGLVersionEnabled(e){var t=getWebGLRenderingContext(e);return null!=t&&(loseContext(t),!0)}function getWebGLDisjointQueryTimerVersion(e){if(0===e)return 0;var t,r=getWebGLRenderingContext(e);return t=hasExtension(r,"EXT_disjoint_timer_query_webgl2")&&2===e?2:hasExtension(r,"EXT_disjoint_timer_query")?1:0,null!=r&&loseContext(r),t}function isFloatTextureReadPixelsEnabled(e){if(0===e)return!1;var t=getWebGLRenderingContext(e);if(1===e){if(!hasExtension(t,"OES_texture_float"))return!1}else if(!hasExtension(t,"EXT_color_buffer_float"))return!1;var r=t.createFramebuffer(),n=t.createTexture();t.bindTexture(t.TEXTURE_2D,n);var a=2===e?t.RGBA32F:t.RGBA;t.texImage2D(t.TEXTURE_2D,0,a,1,1,0,t.RGBA,t.FLOAT,null),t.bindFramebuffer(t.FRAMEBUFFER,r),t.framebufferTexture2D(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.TEXTURE_2D,n,0);var o=t.checkFramebufferStatus(t.FRAMEBUFFER)===t.FRAMEBUFFER_COMPLETE;t.readPixels(0,0,1,1,t.RGBA,t.FLOAT,new Float32Array(4));var i=t.getError()===t.NO_ERROR;return loseContext(t),o&&i}function isWebGLGetBufferSubDataAsyncExtensionEnabled(e){if(e>0)return!1;if(2!==e)return!1;var t=getWebGLRenderingContext(e),r=hasExtension(t,"WEBGL_get_buffer_sub_data_async");return loseContext(t),r}function getFeaturesFromURL(){var e={};if("undefined"==typeof window||void 0===window.location)return e;var t=getQueryParams(window.location.search);if(TENSORFLOWJS_FLAGS_PREFIX in t){var r={};t[TENSORFLOWJS_FLAGS_PREFIX].split(",").forEach(function(e){var t=e.split(":"),n=t[0],a=t[1];r[n]=a}),URL_PROPERTIES.forEach(function(t){t.name in r&&(console.log("Setting feature override from URL "+t.name+": "+r[t.name]),t.type===Type.NUMBER?e[t.name]=+r[t.name]:t.type===Type.BOOLEAN?e[t.name]="true"===r[t.name]:t.type===Type.STRING?e[t.name]=r[t.name]:console.warn("Unknown URL param: "+t.name+"."))})}return e}function getGlobalNamespace(){var e;if("undefined"!=typeof window)e=window;else{if("undefined"==typeof global)throw new Error("Could not find a global object");e=global}return e}function getOrMakeEnvironment(){var e=getGlobalNamespace();return e.ENV=e.ENV||new Environment(getFeaturesFromURL()),e.ENV}function computeOptimalWindowSize(e){return e<=PARALLELIZE_THRESHOLD?e:nearestDivisor(e,Math.floor(Math.sqrt(e)))}function nearestDivisor(e,t){for(var r=t;r<e;++r)if(e%r==0)return r;return e}function castTensor(e,t,r){if(!hasEncodingLoss(e.dtype,t))return Tensor.make(e.shape,{dataId:e.dataId},t);if("int32"===t)return r.int(e);if("bool"===t)return r.notEqual(e,ArrayOps.scalar(0,e.dtype));throw new Error("Error in Cast: unknown dtype argument ("+t+")")}function reshapeTensor(e,t){return Tensor.make(t,{dataId:e.dataId},e.dtype)}function getUnpackedMatrixTextureShapeWidthHeight(e,t){return[t,e]}function getUnpackedArraySizeFromMatrixSize(e,t){return e*t}function getColorMatrixTextureShapeWidthHeight(e,t){return[4*t,e]}function getMatrixSizeFromUnpackedArraySize(e,t){if(e%t!=0)throw new Error("unpackedSize ("+e+") must be a multiple of "+t);return e/t}function encodeMatrixToUnpackedArray(e,t,r){var n=getUnpackedArraySizeFromMatrixSize(e.length,r);if(t.length<n)throw new Error("unpackedArray length ("+t.length+") must be >= "+n);for(var a=0,o=0;o<e.length;++o)t[a]=e[o],a+=r}function encodeFloatArray(e){for(var t=new Uint8Array(4*e.length),r=0;r<t.length;r+=4)!function(r){var n=e[r/4];if(isNaN(n))return t[r]=BYTE_NAN_VALUE,t[r+1]=BYTE_NAN_VALUE,t[r+2]=BYTE_NAN_VALUE,t[r+3]=BYTE_NAN_VALUE,"continue";var a=(n-FLOAT_MIN)/FLOAT_RANGE,o=FLOAT_POWERS.map(function(e){return e*a}).map(function(e){return Math.floor(e%1*255)});t[r]=Math.floor(a),t[r+1]=o[0],t[r+2]=o[1],t[r+3]=o[2]}(r);return t}function decodeToFloatArray(e){for(var t=new Float32Array(e.length/4),r=0;r<e.length;r+=4)!function(r){if(e[r]===BYTE_NAN_VALUE&&e[r+1]===BYTE_NAN_VALUE&&e[r+2]===BYTE_NAN_VALUE&&e[r+3]===BYTE_NAN_VALUE)return t[r/4]=NaN,"continue";var n=0;FLOAT_DELTAS.forEach(function(t,a){n+=t*e[r+a]});var a=n*FLOAT_RANGE+FLOAT_MIN;t[r/4]=a}(r);return t}function decodeMatrixFromUnpackedArray(e,t,r){var n=getMatrixSizeFromUnpackedArraySize(e.length,r);if(t.length<n)throw new Error("matrix length ("+t.length+") must be >= "+n);for(var a=0,o=0;o<e.length;o+=r)t[a++]=e[o]}function decodeMatrixFromUnpackedColorRGBAArray(e,t,r){var n=e.length*r/4;if(t.length<n)throw new Error("matrix length ("+t.length+") must be >= "+n);for(var a=0,o=0;o<e.length;o+=4)for(var i=0;i<r;i++)t[a++]=e[o+i]}function getPackedMatrixTextureShapeWidthHeight(e,t){return[Math.ceil(t/2),Math.ceil(e/2)]}function getPackedRGBAArraySizeFromMatrixShape(e,t){var r=getPackedMatrixTextureShapeWidthHeight(e,t);return r[0]*r[1]*4}function encodeMatrixToPackedRGBA(e,t,r,n){var a=getPackedRGBAArraySizeFromMatrixShape(t,r);if(n.length<a)throw new Error("packedRGBA length ("+n.length+") must be >= "+a);for(var o=getPackedMatrixTextureShapeWidthHeight(t,r),i=o[0],s=o[1],u=r%2==1,l=t%2==1,c=Math.floor(r/2),p=Math.floor(t/2),d=u?4:0,h=r,f=0,m=0;m<p;++m){for(var g=2*m*r,y=0;y<c;++y){v=g+2*y;n[f]=e[v],n[f+1]=e[v+1],n[f+2]=e[v+h],n[f+3]=e[v+h+1],f+=4}f+=d}if(u)for(var v=r-1,f=4*(i-1),b=2*r,d=4*i,m=0;m<p;++m)n[f]=e[v],n[f+2]=e[v+r],v+=b,f+=d;if(l)for(var v=(t-1)*r,f=(s-1)*i*4,y=0;y<c;++y)n[f++]=e[v++],n[f++]=e[v++],f+=2;return u&&l&&(n[n.length-4]=e[e.length-1]),n}function decodeMatrixFromPackedRGBA(e,t,r,n){var a=t*r;if(a<n.length)throw new Error("matrix length ("+n.length+") must be >= "+a);for(var o=r%2==1,i=t%2==1,s=Math.floor(r/2),u=Math.floor(t/2),l=getPackedMatrixTextureShapeWidthHeight(t,r),c=l[0],p=l[1],d=o?4:0,h=r+(o?1:0),f=0,m=0,g=r,y=0;y<u;++y){for(b=0;b<s;++b)n[m++]=e[f++],n[m++]=e[f++],n[g++]=e[f++],n[g++]=e[f++];f+=d,m+=h,g+=h}if(o)for(var f=4*(c-1),v=r-1,d=4*c,h=2*r,y=0;y<u;++y)n[v]=e[f],n[v+r]=e[f+2],f+=d,v+=h;if(i)for(var f=(p-1)*c*4,v=(t-1)*r,b=0;b<s;++b)n[v++]=e[f++],n[v++]=e[f++],f+=2;return o&&i&&(n[n.length-1]=e[e.length-4]),n}function makeShader(e,t,r,n){var a=getSampleSnippet(),o=getSetOutputSnippet(),i=e.map(function(e){return"uniform sampler2D "+e.name+";"}).join("\n"),s=e.map(function(e){return getInputSamplingSnippet(e,t,n)}).join("\n"),u=t.texShape,l=getOutputSamplingSnippet(t.logicalShape,u);return[SHADER_PREFIX,a,o,i,l,s,r].join("\n")}function getSampleSnippet(){return ENV.get("WEBGL_FLOAT_TEXTURE_ENABLED")?FLOAT_TEXTURE_SAMPLE_SNIPPET:UNSIGNED_BYTE_TEXTURE_SAMPLE_SNIPPET}function getSetOutputSnippet(){return ENV.get("WEBGL_FLOAT_TEXTURE_ENABLED")?FLOAT_TEXTURE_SETOUTPUT_SNIPPET:UNSIGNED_BYTE_TEXTURE_SETOUTPUT_SNIPPET}function getSamplerFromInInfo(e){var t=e.shapeInfo.logicalShape;switch(t.length){case 0:return getSamplerScalar(e);case 1:return getSampler1D(e);case 2:return getSampler2D(e);case 3:return getSampler3D(e);case 4:return getSampler4D(e);case 5:return getSampler5D(e);default:throw new Error(t.length+"-D input sampling is not yet supported")}}function getInputSamplingSnippet(e,t,r){var n=getSamplerFlat(e);return n+=getSamplerFromInInfo(e),(r||arraysEqual(e.shapeInfo.logicalShape,t.logicalShape))&&(n+=getSamplerAtOutputCoords(e,t,r)),n}function getOutputSamplingSnippet(e,t){switch(e.length){case 0:return"\n    int getOutputCoords() {\n      return 0;\n    }\n  ";case 1:return getOutput1DCoords(e,t);case 2:return getOutput2DCoords(e,t);case 3:return getOutput3DCoords(e,t);case 4:return getOutput4DCoords(e,t);case 5:return getOutput5DCoords(e,t);default:throw new Error(e.length+"-D output sampling is not yet supported")}}function getOutputScalarCoords(){return"\n    int getOutputCoords() {\n      return 0;\n    }\n  "}function getOutput1DCoords(e,t){return 1===t[0]?"\n      int getOutputCoords() {\n        return int(resultUV.x * "+t[1]+".0);\n      }\n    ":1===t[1]?"\n      int getOutputCoords() {\n        return int(resultUV.y * "+t[0]+".0);\n      }\n    ":"\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+t[0]+", "+t[1]+"));\n      return resTexRC.x * "+t[1]+" + resTexRC.y;\n    }\n  "}function getOutput3DCoords(e,t){var r=e[1]*e[2],n=e[2];return"\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+t[0]+", "+t[1]+"));\n      int index = resTexRC.x * "+t[1]+" + resTexRC.y;\n      int r = index / "+r+";\n      index -= r * "+r+";\n      int c = index / "+n+";\n      int d = index - c * "+n+";\n      return ivec3(r, c, d);\n    }\n  "}function getOutput4DCoords(e,t){var r=e[3],n=e[2]*r,a=e[1]*n;return"\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2("+t[0]+", "+t[1]+"));\n      int index = resTexRC.x * "+t[1]+" + resTexRC.y;\n\n      int r = index / "+a+";\n      index -= r * "+a+";\n\n      int c = index / "+n+";\n      index -= c * "+n+";\n\n      int d = index / "+r+";\n      int d2 = index - d * "+r+";\n\n      return ivec4(r, c, d, d2);\n    }\n  "}function getOutput5DCoords(e,t){var r=e[4],n=e[3]*r,a=e[2]*n,o=e[1]*a;return"\n    ivec5 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx * vec2("+t[0]+",\n                             "+t[1]+"));\n\n      int index = resTexRC.x * "+t[1]+" + resTexRC.y;\n\n      int r = index / "+o+";\n      index -= r * "+o+";\n\n      int c = index / "+a+";\n      index -= c * "+a+";\n\n      int d = index / "+n+";\n      index -= d * "+n+";\n\n      int d2 = index  / "+r+";\n      int d3 = index - d2 * "+r+";\n\n      ivec5 outShape = ivec5(r, c, d, d2, d3);\n      return outShape;\n    }\n  "}function getOutput2DCoords(e,t){return arraysEqual(e,t)?"\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2("+t[0]+", "+t[1]+"));\n      }\n    ":1===e[1]?"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2("+t[0]+", "+t[1]+"));\n        int index = resTexRC.x * "+t[1]+" + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    ":1===e[0]?"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2("+t[0]+", "+t[1]+"));\n        int index = resTexRC.x * "+t[1]+" + resTexRC.y;\n        return ivec2(0, index);\n      }\n    ":"\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+t[0]+", "+t[1]+"));\n      int index = resTexRC.x * "+t[1]+" + resTexRC.y;\n      int r = index / "+e[1]+";\n      int c = index - r * "+e[1]+";\n      return ivec2(r, c);\n    }\n  "}function getSamplerScalar(e){var t=e.name;return"\n    float "+("get"+t.charAt(0).toUpperCase()+t.slice(1))+"() {\n      return sampleTexture("+t+", halfCR);\n    }\n  "}function getSampler1D(e){var t=e.name,r="get"+t.charAt(0).toUpperCase()+t.slice(1);return"\n    float "+r+"(int index) {\n      return "+r+"Flat(index);\n    }\n  "}function getSampler2D(e){var t=e.shapeInfo.logicalShape,r=e.shapeInfo.texShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),o=r[0],i=r[1];if(arraysEqual(t,r))return"\n    float "+a+"(int row, int col) {\n      vec2 uv = (vec2(col, row) + halfCR) / vec2("+i+".0, "+o+".0);\n      return sampleTexture("+n+", uv);\n    }\n  ";var s=squeezeShape(t),u=s.newShape,l=s.keptDims,c=u;if(c.length<t.length){var p=["row","col"];return"\n      "+getSamplerFromInInfo(squeezeInputInfo(e,c))+"\n      float "+a+"(int row, int col) {\n        return "+a+"("+getSqueezedParams(p,l)+");\n      }\n    "}return 1===i?"\n    float "+a+"(int row, int col) {\n      int index = row * "+t[1]+" + col;\n      vec2 uv = vec2(0.5, (float(index) + 0.5) / "+o+".0);\n      return sampleTexture("+n+", uv);\n    }\n  ":1===o?"\n    float "+a+"(int row, int col) {\n      int index = row * "+t[1]+" + col;\n      vec2 uv = vec2((float(index) + 0.5) / "+i+".0, 0.5);\n      return sampleTexture("+n+", uv);\n    }\n  ":"\n  float "+a+"(int row, int col) {\n    vec2 uv = UVfrom2D("+o+", "+i+", "+t[1]+", row, col);\n    return sampleTexture("+n+", uv);\n  }\n"}function getSampler3D(e){var t=e.shapeInfo.texShape,r=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),o=t[0],i=t[1],s=r[1]*r[2],u=r[2],l=squeezeShape(r),c=l.newShape,p=l.keptDims,d=c;if(d.length<r.length){var h=["row","col","depth"];return"\n        "+getSamplerFromInInfo(squeezeInputInfo(e,d))+"\n        float "+a+"(int row, int col, int depth) {\n          return "+a+"("+getSqueezedParams(h,p)+");\n        }\n      "}return i===s?"\n        float "+a+"(int row, int col, int depth) {\n          int texR = row;\n          int texC = col * "+u+" + depth;\n          vec2 uv = (vec2(texC, texR) + halfCR) /\n                     vec2("+i+".0, "+o+".0);\n          return sampleTexture("+n+", uv);\n        }\n      ":i===u?"\n    float "+a+"(int row, int col, int depth) {\n      int texR = row * "+r[1]+" + col;\n      int texC = depth;\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+i+".0, "+o+".0);\n      return sampleTexture("+n+", uv);\n    }\n  ":"\n      float "+a+"(int row, int col, int depth) {\n        vec2 uv = UVfrom3D(\n            "+o+", "+i+", "+s+", "+u+", row, col, depth);\n        return sampleTexture("+n+", uv);\n      }\n  "}function getSampler4D(e){var t=e.shapeInfo.logicalShape,r=e.shapeInfo.texShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),o=r[0],i=r[1],s=t[3],u=t[2]*s,l=t[1]*u,c=squeezeShape(t),p=c.newShape,d=c.keptDims;if(p.length<t.length){var h=["row","col","depth","depth2"];return"\n      "+getSamplerFromInInfo(squeezeInputInfo(e,p))+"\n      float "+a+"(int row, int col, int depth, int depth2) {\n        return "+a+"("+getSqueezedParams(h,d)+");\n      }\n    "}return i===l?"\n      float "+a+"(int row, int col, int depth, int depth2) {\n        int texR = row;\n        int texC = col * "+u+" + depth * "+s+" + depth2;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+i+".0, "+o+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ":i===s?"\n      float "+a+"(int row, int col, int depth, int depth2) {\n        int texR = row * "+t[1]*t[2]+" + col * "+t[2]+" + depth;\n        int texC = depth2;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+i+".0, "+o+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ":"\n    float "+a+"(int row, int col, int depth, int depth2) {\n      vec2 uv = UVfrom4D("+o+", "+i+", "+l+", "+u+",\n          "+s+", row, col, depth, depth2);\n      return sampleTexture("+n+", uv);\n    }\n  "}function getSampler5D(e){var t=e.shapeInfo.logicalShape,r=e.shapeInfo.texShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),o=r[0],i=r[1],s=t[4],u=t[3]*s,l=t[2]*u,c=t[1]*l,p=squeezeShape(t),d=p.newShape,h=p.keptDims;if(d.length<t.length){var f=["row","col","depth","depth2","depth3"];return"\n      "+getSamplerFromInInfo(squeezeInputInfo(e,d))+"\n      float "+a+"(int row, int col, int depth, int depth2, int depth3) {\n        return "+a+"("+getSqueezedParams(f,h)+");\n      }\n    "}return i===c?"\n      float "+a+"(int row, int col, int depth, int depth2, int depth3) {\n        int texR = row;\n        int texC = col * "+l+" + depth * "+u+" +\n                   depth2 * "+s+" + depth3;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+i+".0, "+o+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ":i===s?"\n      float "+a+"(int row, int col, int depth, int depth2, int depth3) {\n        int texR = row * "+t[1]*t[2]+" + col * "+t[2]+" +\n                   depth * "+t[3]+" + depth2;\n        int texC = depth3;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+i+".0, "+o+".0);\n        return sampleTexture("+n+", uv);\n      }\n    ":"\n    float "+a+"(int row, int col, int depth, int depth2, int depth3) {\n      vec2 uv = UVfrom5D("+o+", "+i+", "+c+", "+l+",\n          "+u+", "+s+", row, col, depth, depth2, depth3);\n      return sampleTexture("+n+", uv);\n    }\n  "}function getSamplerFlat(e){var t=e.name,r=e.shapeInfo.texShape,n="get"+t.charAt(0).toUpperCase()+t.slice(1)+"Flat",a=r[0],o=r[1];return 1===o&&1===a?"\n      float "+n+"(int index) {\n        return sampleTexture("+t+", halfCR);\n      }\n    ":1===o?"\n      float "+n+"(int index) {\n        vec2 uv = vec2(0.5, (float(index) + 0.5) / "+a+".0);\n        return sampleTexture("+t+", uv);\n      }\n    ":1===a?"\n      float "+n+"(int index) {\n        vec2 uv = vec2((float(index) + 0.5) / "+o+".0, 0.5);\n        return sampleTexture("+t+", uv);\n      }\n    ":"\n    float "+n+"(int index) {\n      vec2 uv = UVfrom1D("+a+", "+o+", index);\n      return sampleTexture("+t+", uv);\n    }\n  "}function getBroadcastOutputCoordsSampler(e,t,r,n){var a=e.shapeInfo.logicalShape.length,o=t.logicalShape.length,i="int";2===o?i="ivec2":3===o?i="ivec3":4===o&&(i="ivec4");var s,u=getBroadcastDims(e.shapeInfo.logicalShape,t.logicalShape),l=o-a;s=0===a?"":o<2&&u.length>=1?"coords = 0;":u.map(function(e){return"coords["+(e+l)+"] = 0;"}).join("\n");var c="";return c=o<2&&a>0?"coords":e.shapeInfo.logicalShape.map(function(e,t){return"coords["+(t+l)+"]"}).join(", "),"\n    float "+n+"() {\n      "+i+" coords = getOutputCoords();\n      "+s+"\n      return get"+r+"("+c+");\n    }\n  "}function getSamplerAtOutputCoords(e,t,r){var n=e.shapeInfo.texShape,a=e.name,o=a.charAt(0).toUpperCase()+a.slice(1),i="get"+o+"AtOutCoords",s=getBroadcastDims(e.shapeInfo.logicalShape,t.logicalShape),u=e.shapeInfo.logicalShape.length,l=t.logicalShape.length,c=r&&(l>u||s.length>0),p=broadcastDimsAreOuter(s);if(c&&!p)return getBroadcastOutputCoordsSampler(e,t,o,i);var d=t.texShape;if(arraysEqual(n,d))return"\n      float "+i+"() {\n        return sampleTexture("+a+", resultUV);\n      }\n    ";var h=sizeFromShape(n),f="";return c&&p&&(f="\n        int mainPart = index / "+h+";\n        index -= mainPart * "+h+";\n      "),"\n    float "+i+"() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+d[0]+", "+d[1]+"));\n      int index = resTexRC.x * "+d[1]+" + resTexRC.y;\n      "+f+"\n      int texR = index / "+n[1]+";\n      int texC = index - texR * "+n[1]+";\n      vec2 uv = (vec2(texC, texR) + halfCR) /\n                 vec2("+n[1]+".0, "+n[0]+".0);\n\n      return sampleTexture("+a+", uv);\n    }\n  "}function getCoordsDataType(e){if(e<=1)return"int";if(2===e)return"ivec2";if(3===e)return"ivec3";if(4===e)return"ivec4";if(5===e)return"ivec5";throw Error("GPU for rank "+e+" is not yet supported")}function squeezeInputInfo(e,t){var r=JSON.parse(JSON.stringify(e));return r.shapeInfo.logicalShape=t,r}function getSqueezedParams(e,t){return t.map(function(t){return e[t]}).join(", ")}function getCoords(e,t){if(1===e)return""+t;if(2===e)return t+".x, "+t+".y";if(3===e)return t+".x, "+t+".y, "+t+".z";if(4===e)return t+".x, "+t+".y, "+t+".z, "+t+".w";throw Error("Cumulative sum for rank "+e+" is not yet supported")}function getFinalCoord(e,t){if(1===e)return""+t;if(2===e)return t+".y";if(3===e)return t+".z";if(4===e)return t+".w";throw Error("Cumulative sum for rank "+e+" is not yet supported")}function getSourceCoords(e,t){var r=e.length;if(r>4)throw Error("Gather for rank "+r+" is not yet supported");if(1===r)return"int(getIndices(resRC))";for(var n=["resRC.x","resRC.y","resRC.z","resRC.w"],a=[],o=0;o<e.length;o++)o===t?a.push("int(getIndices("+n[o]+"))"):a.push(""+n[o]);return a.join()}function createWebGLRenderingContext(e){var t=document.createElement("canvas");return t.width=1,t.height=1,createWebGLRenderingContextFromCanvas(t,e)}function createWebGLRenderingContextFromCanvas(e,t){var r,n=ENV.get("WEBGL_VERSION");if(2===n?r=e.getContext("webgl2",t):1===n&&(r=e.getContext("webgl",t)||e.getContext("experimental-webgl",t)),0===n||null==r)throw new Error("This browser does not support WebGL.");return r}function callAndCheck(e,t){var r=t();return checkWebGLError(e),r}function enableDebugWebGLErrorChecking(e){webGLDebugErrorCheckingEnabled=e}function checkWebGLError(e){if(webGLDebugErrorCheckingEnabled){var t=e.getError();if(t!==e.NO_ERROR)throw new Error("WebGL Error: "+getWebGLErrorMessage(e,t))}}function getWebGLErrorMessage(e,t){switch(t){case e.NO_ERROR:return"NO_ERROR";case e.INVALID_ENUM:return"INVALID_ENUM";case e.INVALID_VALUE:return"INVALID_VALUE";case e.INVALID_OPERATION:return"INVALID_OPERATION";case e.INVALID_FRAMEBUFFER_OPERATION:return"INVALID_FRAMEBUFFER_OPERATION";case e.OUT_OF_MEMORY:return"OUT_OF_MEMORY";case e.CONTEXT_LOST_WEBGL:return"CONTEXT_LOST_WEBGL";default:return"Unknown error code "+t}}function getExtensionOrThrow(e,t){return throwIfNull(e,function(){return e.getExtension(t)},'Extension "'+t+'" not supported on this browser.')}function createVertexShader(e,t){var r=throwIfNull(e,function(){return e.createShader(e.VERTEX_SHADER)},"Unable to create vertex WebGLShader.");if(callAndCheck(e,function(){return e.shaderSource(r,t)}),callAndCheck(e,function(){return e.compileShader(r)}),!1===e.getShaderParameter(r,e.COMPILE_STATUS))throw console.log(e.getShaderInfoLog(r)),new Error("Failed to compile vertex shader.");return r}function createFragmentShader(e,t){var r=throwIfNull(e,function(){return e.createShader(e.FRAGMENT_SHADER)},"Unable to create fragment WebGLShader.");if(callAndCheck(e,function(){return e.shaderSource(r,t)}),callAndCheck(e,function(){return e.compileShader(r)}),!1===e.getShaderParameter(r,e.COMPILE_STATUS))throw logShaderSourceAndInfoLog(t,e.getShaderInfoLog(r)),new Error("Failed to compile fragment shader.");return r}function logShaderSourceAndInfoLog(e,t){var r=lineNumberRegex.exec(t);if(null==r)return console.log("Couldn't parse line number in error: "+t),void console.log(e);for(var n=+r[1],a=e.split("\n"),o=a.length.toString().length+2,i=a.map(function(e,t){return rightPad((t+1).toString(),o)+e}),s=0,u=0;u<i.length;u++)s=Math.max(i[u].length,s);var l=i.slice(0,n-1),c=i.slice(n-1,n),p=i.slice(n);console.log(l.join("\n")),console.log(t.split("\n")[0]),console.log("%c "+rightPad(c[0],s),"border:1px solid red; background-color:#e3d2d2; color:#a61717"),console.log(p.join("\n"))}function createProgram(e){return throwIfNull(e,function(){return e.createProgram()},"Unable to create WebGLProgram.")}function linkProgram(e,t){if(callAndCheck(e,function(){return e.linkProgram(t)}),!1===e.getProgramParameter(t,e.LINK_STATUS))throw console.log(e.getProgramInfoLog(t)),new Error("Failed to link vertex and fragment shaders.")}function validateProgram(e,t){if(callAndCheck(e,function(){return e.validateProgram(t)}),!1===e.getProgramParameter(t,e.VALIDATE_STATUS))throw console.log(e.getProgramInfoLog(t)),new Error("Shader program validation failed.")}function createStaticVertexBuffer(e,t){var r=throwIfNull(e,function(){return e.createBuffer()},"Unable to create WebGLBuffer");return callAndCheck(e,function(){return e.bindBuffer(e.ARRAY_BUFFER,r)}),callAndCheck(e,function(){return e.bufferData(e.ARRAY_BUFFER,t,e.STATIC_DRAW)}),r}function createStaticIndexBuffer(e,t){var r=throwIfNull(e,function(){return e.createBuffer()},"Unable to create WebGLBuffer");return callAndCheck(e,function(){return e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,r)}),callAndCheck(e,function(){return e.bufferData(e.ELEMENT_ARRAY_BUFFER,t,e.STATIC_DRAW)}),r}function queryMaxTextureSize(e){return null!=MAX_TEXTURE_SIZE?MAX_TEXTURE_SIZE:MAX_TEXTURE_SIZE=callAndCheck(e,function(){return e.getParameter(e.MAX_TEXTURE_SIZE)})}function getChannelsPerTexture(){return ENV.get("WEBGL_FLOAT_TEXTURE_ENABLED")&&2===ENV.get("WEBGL_VERSION")?1:4}function createTexture(e){return throwIfNull(e,function(){return e.createTexture()},"Unable to create WebGLTexture.")}function validateTextureSize(e,t,r){var n=queryMaxTextureSize(e);if(t<=0||r<=0){a="["+t+"x"+r+"]";throw new Error("Requested texture size "+a+" is invalid.")}if(t>n||r>n){var a="["+t+"x"+r+"]",o="["+n+"x"+n+"]";throw new Error("Requested texture size "+a+" greater than WebGL maximum on this browser / GPU "+o+".")}}function createFramebuffer(e){return throwIfNull(e,function(){return e.createFramebuffer()},"Unable to create WebGLFramebuffer.")}function bindVertexBufferToProgramAttribute(e,t,r,n,a,o,i){var s=e.getAttribLocation(t,r);return-1!==s&&(callAndCheck(e,function(){return e.bindBuffer(e.ARRAY_BUFFER,n)}),callAndCheck(e,function(){return e.vertexAttribPointer(s,a,e.FLOAT,!1,o,i)}),callAndCheck(e,function(){return e.enableVertexAttribArray(s)}),!0)}function bindTextureUnit(e,t,r){validateTextureUnit(e,r),callAndCheck(e,function(){return e.activeTexture(e.TEXTURE0+r)}),callAndCheck(e,function(){return e.bindTexture(e.TEXTURE_2D,t)})}function unbindTextureUnit(e,t){validateTextureUnit(e,t),callAndCheck(e,function(){return e.activeTexture(e.TEXTURE0+t)}),callAndCheck(e,function(){return e.bindTexture(e.TEXTURE_2D,null)})}function getProgramUniformLocationOrThrow(e,t,r){return throwIfNull(e,function(){return e.getUniformLocation(t,r)},'uniform "'+r+'" not present in program.')}function getProgramUniformLocation(e,t,r){return e.getUniformLocation(t,r)}function bindTextureToProgramUniformSampler(e,t,r,n,a){callAndCheck(e,function(){return bindTextureUnit(e,r,a)}),callAndCheck(e,function(){return e.uniform1i(n,a)})}function bindCanvasToFramebuffer(e){callAndCheck(e,function(){return e.bindFramebuffer(e.FRAMEBUFFER,null)}),callAndCheck(e,function(){return e.viewport(0,0,e.canvas.width,e.canvas.height)}),callAndCheck(e,function(){return e.scissor(0,0,e.canvas.width,e.canvas.height)})}function bindColorTextureToFramebuffer(e,t,r){callAndCheck(e,function(){return e.bindFramebuffer(e.FRAMEBUFFER,r)}),callAndCheck(e,function(){return e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0)})}function unbindColorTextureFromFramebuffer(e,t){callAndCheck(e,function(){return e.bindFramebuffer(e.FRAMEBUFFER,t)}),callAndCheck(e,function(){return e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,null,0)})}function validateFramebuffer(e){var t=e.checkFramebufferStatus(e.FRAMEBUFFER);if(t!==e.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+getFramebufferErrorMessage(e,t))}function getFramebufferErrorMessage(e,t){switch(t){case e.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case e.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return"unknown error "+t}}function throwIfNull(e,t,r){var n=callAndCheck(e,function(){return t()});if(null==n)throw new Error(r);return n}function validateTextureUnit(e,t){var r=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,n=t+e.TEXTURE0;if(n<e.TEXTURE0||n>r){var a="[gl.TEXTURE0, gl.TEXTURE"+r+"]";throw new Error("textureUnit must be in "+a+".")}}function getTextureShapeFromLogicalShape(e,t){2!==t.length&&(t=squeezeShape(t).newShape);var r=queryMaxTextureSize(e),n=sizeFromShape(t);return t.length<=1&&n<=r?[n,1]:2===t.length&&t[0]<=r&&t[1]<=r?t:3===t.length&&t[0]<=r&&t[1]*t[2]<=r?[t[0],t[1]*t[2]]:4===t.length&&t[0]<=r&&t[1]*t[2]*t[3]<=r?[t[0],t[1]*t[2]*t[3]]:sizeToSquarishShape(n)}function getWebGLContextAttributes(){return{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!0}}function createWebGLContext(e){var t,r=getWebGLContextAttributes();return t=null!=e?createWebGLRenderingContextFromCanvas(e,r):createWebGLRenderingContext(r),callAndCheck(t,function(){return t.disable(t.DEPTH_TEST)}),callAndCheck(t,function(){return t.disable(t.STENCIL_TEST)}),callAndCheck(t,function(){return t.disable(t.BLEND)}),callAndCheck(t,function(){return t.disable(t.DITHER)}),callAndCheck(t,function(){return t.disable(t.POLYGON_OFFSET_FILL)}),callAndCheck(t,function(){return t.disable(t.SAMPLE_COVERAGE)}),callAndCheck(t,function(){return t.enable(t.SCISSOR_TEST)}),callAndCheck(t,function(){return t.enable(t.CULL_FACE)}),callAndCheck(t,function(){return t.cullFace(t.BACK)}),t}function createVertexShader$1(e){return createVertexShader(e,"\n    precision highp float;\n    attribute vec3 clipSpacePos;\n    attribute vec2 uv;\n    varying vec2 resultUV;\n\n    void main() {\n      gl_Position = vec4(clipSpacePos, 1);\n      resultUV = uv;\n    }")}function createVertexBuffer(e){return createStaticVertexBuffer(e,new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]))}function createIndexBuffer(e){return createStaticIndexBuffer(e,new Uint16Array([0,1,2,2,1,3]))}function getTextureInternalFormat(e,t){return ENV.get("WEBGL_FLOAT_TEXTURE_ENABLED")&&2===ENV.get("WEBGL_VERSION")?4===t?e.RGBA32F:e.R32F:e.RGBA}function getTextureFormat(e,t){return ENV.get("WEBGL_FLOAT_TEXTURE_ENABLED")&&2===ENV.get("WEBGL_VERSION")?4===t?e.RGBA:e.RED:e.RGBA}function getTextureType(e){return ENV.get("WEBGL_FLOAT_TEXTURE_ENABLED")?e.FLOAT:e.UNSIGNED_BYTE}function createAndConfigureTexture(e,t,r,n){validateTextureSize(e,t,r);var a=createTexture(e),o=e.TEXTURE_2D,i=getTextureInternalFormat(e,n),s=getTextureFormat(e,n);return callAndCheck(e,function(){return e.bindTexture(o,a)}),callAndCheck(e,function(){return e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)}),callAndCheck(e,function(){return e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)}),callAndCheck(e,function(){return e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)}),callAndCheck(e,function(){return e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)}),callAndCheck(e,function(){return e.texImage2D(o,0,i,t,r,0,s,getTextureType(e),null)}),callAndCheck(e,function(){return e.bindTexture(e.TEXTURE_2D,null)}),a}function createMatrixTexture(e,t,r){var n=getUnpackedMatrixTextureShapeWidthHeight(t,r);return createAndConfigureTexture(e,n[0],n[1],1)}function createColorMatrixTexture(e,t,r){var n=getColorMatrixTextureShapeWidthHeight(t,r);return createAndConfigureTexture(e,n[0],n[1],4)}function createPackedMatrixTexture(e,t,r){var n=getPackedMatrixTextureShapeWidthHeight(t,r);return createAndConfigureTexture(e,n[0],n[1],4)}function bindVertexProgramAttributeStreams(e,t,r){return callAndCheck(e,function(){return e.bindBuffer(e.ARRAY_BUFFER,r)}),bindVertexBufferToProgramAttribute(e,t,"clipSpacePos",r,3,20,0)&&bindVertexBufferToProgramAttribute(e,t,"uv",r,2,20,12)}function uploadPixelDataToTexture(e,t,r){callAndCheck(e,function(){return e.bindTexture(e.TEXTURE_2D,t)}),callAndCheck(e,function(){return e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,r)}),callAndCheck(e,function(){return e.bindTexture(e.TEXTURE_2D,null)})}function uploadDataToTexture(e,t,r,n,a,o){var i=getTextureFormat(e,o);validateTextureSize(e,r,n),callAndCheck(e,function(){return e.bindTexture(e.TEXTURE_2D,t)}),callAndCheck(e,function(){return e.texSubImage2D(e.TEXTURE_2D,0,0,0,r,n,i,getTextureType(e),a)}),callAndCheck(e,function(){return e.bindTexture(e.TEXTURE_2D,null)})}function uploadMatrixToTexture(e,t,r,n,a,o){var i,s=getUnpackedMatrixTextureShapeWidthHeight(r,n),u=s[0],l=s[1];if(ENV.get("WEBGL_FLOAT_TEXTURE_ENABLED")){var c=1===o?getChannelsPerTexture():o;1===c?i=a:encodeMatrixToUnpackedArray(a,i=new Float32Array(getUnpackedArraySizeFromMatrixSize(a.length,c)),c)}else i=encodeFloatArray(a);uploadDataToTexture(e,t,u,l,i,o)}function uploadMatrixToPackedTexture(e,t,r,n,a){var o=getPackedMatrixTextureShapeWidthHeight(r,n),i=o[0],s=o[1],u=new Float32Array(getPackedRGBAArraySizeFromMatrixShape(r,n));encodeMatrixToPackedRGBA(a,r,n,u);uploadDataToTexture(e,t,i,s,u,4)}function getDownloadTargetArrayBuffer(e,t,r){var n=ENV.get("WEBGL_FLOAT_TEXTURE_ENABLED"),a=e*t*r;return n?(null==floatDownloadBuffer||floatDownloadBuffer.length<a)&&(floatDownloadBuffer=new Float32Array(a)):(null==byteDownloadBuffer||byteDownloadBuffer.length<a)&&(byteDownloadBuffer=new Uint8Array(a)),(n?floatDownloadBuffer:byteDownloadBuffer).subarray(0,a)}function decodeDownloadTargetArrayBuffer(e,t,r,n){if(ENV.get("WEBGL_FLOAT_TEXTURE_ENABLED")){var a=new Float32Array(t*r);return decodeMatrixFromUnpackedArray(e,a,n),a}return decodeToFloatArray(e)}function downloadMatrixFromOutputTextureAsync(e,t,r,n){return __awaiter$3(this,void 0,void 0,function(){var a,o,i,s,u;return __generator$3(this,function(l){switch(l.label){case 0:return a=e,o=4,i=getDownloadTargetArrayBuffer(r,n,o),s=i instanceof Float32Array?4*i.length:i,u=e.createBuffer(),callAndCheck(e,function(){return e.bindBuffer(a.PIXEL_PACK_BUFFER,u)}),callAndCheck(e,function(){return e.bufferData(a.PIXEL_PACK_BUFFER,s,e.STATIC_DRAW)}),callAndCheck(e,function(){return a.readPixels(0,0,n,r,e.RGBA,getTextureType(e),0)}),[4,t.getBufferSubDataAsync(a.PIXEL_PACK_BUFFER,0,i)];case 1:return l.sent(),[2,decodeDownloadTargetArrayBuffer(i,r,n,o)]}})})}function downloadMatrixFromOutputTexture(e,t,r){var n=getUnpackedMatrixTextureShapeWidthHeight(t,r),a=n[0],o=n[1],i=getDownloadTargetArrayBuffer(t,r,4);return callAndCheck(e,function(){return e.readPixels(0,0,a,o,e.RGBA,getTextureType(e),i)}),decodeDownloadTargetArrayBuffer(i,t,r,4)}function downloadMatrixFromRGBAColorTexture(e,t,r,n){var a=t*r*4,o=new Uint8Array(a);callAndCheck(e,function(){return e.readPixels(0,0,r,t,e.RGBA,e.UNSIGNED_BYTE,o)});for(var i=new Float32Array(a),s=0;s<o.length;s++)i[s]=o[s];var u=new Float32Array(t*r*n);return decodeMatrixFromUnpackedColorRGBAArray(i,u,n),u}function downloadMatrixFromPackedOutputTexture(e,t,r){var n=getPackedMatrixTextureShapeWidthHeight(t,r),a=n[0],o=n[1],i=new Float32Array(getPackedRGBAArraySizeFromMatrixShape(t,r));callAndCheck(e,function(){return e.readPixels(0,0,a,o,e.RGBA,getTextureType(e),i)});var s=new Float32Array(t*r);return decodeMatrixFromPackedRGBA(i,t,r,s)}function binSearchLastTrue(e){for(var t=0,r=e.length-1,n=-1;t<=r;){var a=t+r>>1;e[a]()?(n=a,t=a+1):r=a-1}return n}function shouldUploadNaNUniform(){return!ENV.get("WEBGL_FLOAT_TEXTURE_ENABLED")}function compileProgram(e,t,r,n){for(var a=t.userCode,o=r.map(function(e,r){var n={logicalShape:e.tensor.shape,texShape:e.texData.texShape};return{name:t.variableNames[r],shapeInfo:n}}),i=o.map(function(e){return e.shapeInfo}),s={logicalShape:n.tensor.shape,texShape:n.texData.texShape},u=makeShader(o,s,a,!0===t.supportsBroadcasting),l=e.createProgram(u),c={},p=0;p<t.variableNames.length;p++){var d=t.variableNames[p];c[d]=e.getUniformLocation(l,d)}if(shouldUploadNaNUniform()){c[NAN_UNIFORM_NAME]=e.getUniformLocation(l,NAN_UNIFORM_NAME,!1)}return{program:t,source:u,webGLProgram:l,uniformLocations:c,gpgpu:e,inShapeInfos:i,outShapeInfo:s}}function validateBinaryAndProgram(e,t){if(e.length!==t.length)throw Error("Binary was compiled with "+e.length+" inputs, but was executed with "+t.length+" inputs");e.forEach(function(e,r){var n=e.logicalShape,a=e.texShape,o=t[r].tensor.shape,i=t[r].texData.texShape;if(!arraysEqual(n,o))throw Error("Binary was compiled with different shapes than the current args. Shapes "+n+" and "+o+" must match");if(!arraysEqual(a,i))throw Error("Binary was compiled with different texture shapes than the current args. Shape "+a+" and "+i+" must match")})}function runProgram(e,t,r,n){validateBinaryAndProgram(e.inShapeInfos,t),validateBinaryAndProgram([e.outShapeInfo],[r]);var a=r.texData.texture,o=r.texData.texShape,i=e.gpgpu;i.setOutputMatrixTexture(a,o[0],o[1]),i.setProgram(e.webGLProgram),t.forEach(function(t,r){var n=t.texData.texture,a=e.program.variableNames[r],o=e.uniformLocations[a];i.setInputMatrixTexture(n,o,r)}),shouldUploadNaNUniform()&&i.gl.uniform1f(e.uniformLocations[NAN_UNIFORM_NAME],NaN),null!=n&&n(i,e.webGLProgram),i.executeProgram()}function makeShaderKey(e,t,r){var n="";t.concat(r).forEach(function(e){n+=e.tensor.shape+"_"+e.texData.texShape});var a=e.userCode,o=(!0===e.supportsBroadcasting).toString(),i=e.constructor.name;return i+="_"+o+"_"+n+"_"+a}function getCoords$1(e){if(1===e)return"sourceLoc";if(2===e)return"sourceLoc.x, sourceLoc.y";if(3===e)return"sourceLoc.x, sourceLoc.y, sourceLoc.z";if(4===e)return"sourceLoc.x, sourceLoc.y, sourceLoc.z, sourceLoc.w";throw Error("Slicing for rank "+e+" is not yet supported")}function getKeyFromTextureShape(e,t){return e[0]+"_"+e[1]+"_"+t}function getSourceCoords$1(e){var t=e.length;if(t>5)throw Error("Tile for rank "+t+" is not yet supported");if(1===t)return"imod(resRC, "+e[0]+")";for(var r=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],n=[],a=0;a<e.length;a++)n.push("imod("+r[a]+", "+e[a]+")");return n.join()}function getSwitchedCoords(e){var t=e.length;if(t>5)throw Error("Transpose for rank "+t+" is not yet supported");for(var r=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],n=new Array(t),a=0;a<e.length;a++)n[e[a]]=r[a];return n.join()}function STEP(e){return void 0===e&&(e=0),CHECK_NAN_SNIPPET$1+"\n    return x > 0.0 ? 1.0 : float("+e+");\n  "}function float32ToTypedArray(e,t){if("float32"===t)return e;if("int32"===t||"bool"===t){for(var r="int32"===t?new Int32Array(e.length):new Uint8Array(e.length),n=0;n<r.length;++n)r[n]=Math.round(e[n]);return r}throw new Error("Unknown dtype "+t)}function typedArrayToFloat32(e,t){return e instanceof Float32Array?e:new Float32Array(e)}function encodeWeights(e){return __awaiter$7(this,void 0,void 0,function(){var t,r,n,a,o;return __generator$7(this,function(i){switch(i.label){case 0:t=[],r=[];for(n in e){if("float32"!==(a=e[n]).dtype&&"int32"!==a.dtype&&"bool"!==a.dtype)throw new Error("Unsupported dtype in weight '"+n+"': "+a.dtype);t.push({name:n,shape:a.shape,dtype:a.dtype}),r.push(a.data())}return[4,Promise.all(r)];case 1:return o=i.sent(),[2,{data:concatenateTypedArrays(o),specs:t}]}})})}function decodeWeights(e,t){for(var r={},n=0,a=0,o=t;a<o.length;a++){var i=o[a],s=i.name,u=i.dtype,l=i.shape;if(null!=i.quantization)throw new Error("decodeWeights does not support quantization yet, but encountered weight '"+s+" with quantization.'");var c=sizeFromShape(l),p=void 0;if("float32"===u)p=ArrayOps.tensor(new Float32Array(e,n,c),l,"float32");else if("int32"===u)p=ArrayOps.tensor(new Int32Array(e,n,c),l,"int32");else{if("bool"!==u)throw new Error("Unsupported dtype in weight '"+s+"': "+u);p=ArrayOps.tensor(new Uint8Array(e,n,c),l,"bool")}r[s]=p,n+=c*DTYPE_VALUE_SIZE_MAP[u]}return r}function concatenateTypedArrays(e){if(null===e)throw new Error("Invalid input value: "+JSON.stringify(e));var t=0;e.forEach(function(e){if(e instanceof Float32Array||e instanceof Int32Array)t+=4*e.length;else{if(!(e instanceof Uint8Array))throw new Error("Unsupported TypedArray subtype: "+e.constructor.name);t+=e.length}});var r=new Uint8Array(t),n=0;return e.forEach(function(e){r.set(new Uint8Array(e.buffer),n),e instanceof Float32Array||e instanceof Int32Array?n+=4*e.length:n+=e.length}),r.buffer}function stringByteLength(e){return new Blob([e]).size}function arrayBufferToBase64String(e){return btoa(String.fromCharCode.apply(null,new Uint8Array(e)))}function base64StringToArrayBuffer(e){for(var t=atob(e),r=new Uint8Array(t.length),n=0;n<t.length;++n)r.set([t.charCodeAt(n)],n);return r.buffer}function concatenateArrayBuffers(e){var t=0;e.forEach(function(e){t+=e.byteLength});var r=new Uint8Array(t),n=0;return e.forEach(function(e){r.set(new Uint8Array(e),n),n+=e.byteLength}),r.buffer}function basename(e){for(e=e.trim();e.endsWith("/");)e=e.slice(0,e.length-1);var t=e.split("/");return t[t.length-1]}function getModelArtifactsInfoForJSON(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("Expected JSON model topology, received ArrayBuffer.");return{dateSaved:new Date,modelTopologyType:"JSON",modelTopologyBytes:null==e.modelTopology?0:stringByteLength(JSON.stringify(e.modelTopology)),weightSpecsBytes:null==e.weightSpecs?0:stringByteLength(JSON.stringify(e.weightSpecs)),weightDataBytes:null==e.weightData?0:e.weightData.byteLength}}function parseURL(e){if(-1===e.indexOf(URL_SCHEME_SUFFIX))throw new Error("The url string provided does not contain a scheme. Supported schemes are: "+ModelStoreManagerRegistry.getSchemes().join(","));return{scheme:e.split(URL_SCHEME_SUFFIX)[0],path:e.split(URL_SCHEME_SUFFIX)[1]}}function cloneModelInternal(e,t,r){return void 0===r&&(r=!1),__awaiter$8(this,void 0,void 0,function(){var n,a,o,i,s,u,l,c,p;return __generator$8(this,function(d){switch(d.label){case 0:return assert(e!==t,"Old path and new path are the same: '"+e+"'"),n=IORouterRegistry.getLoadHandlers(e),assert(n.length>0,"Copying failed because no load handler is found for source URL "+e+"."),assert(n.length<2,"Copying failed because more than one ("+n.length+") load handlers for source URL "+e+"."),a=n[0],o=IORouterRegistry.getSaveHandlers(t),assert(o.length>0,"Copying failed because no save handler is found for destination URL "+t+"."),assert(o.length<2,"Copying failed because more than one ("+n.length+") save handlers for destination URL "+t+"."),i=o[0],s=parseURL(e).scheme,u=parseURL(e).path,l=s===parseURL(e).scheme,[4,a.load()];case 1:return c=d.sent(),r&&l?[4,ModelStoreManagerRegistry.getManager(s).removeModel(u)]:[3,3];case 2:d.sent(),d.label=3;case 3:return[4,i.save(c)];case 4:return p=d.sent(),!r||l?[3,6]:[4,ModelStoreManagerRegistry.getManager(s).removeModel(u)];case 5:d.sent(),d.label=6;case 6:return[2,p.modelArtifactsInfo]}})})}function getIndexedDBFactory(){if(!ENV.get("IS_BROWSER"))throw new Error("Failed to obtain IndexedDB factory because the current environmentis not a web browser.");var e=window,t=e.indexedDB||e.mozIndexedDB||e.webkitIndexedDB||e.msIndexedDB||e.shimIndexedDB;if(null==t)throw new Error("The current browser does not appear to support IndexedDB.");return t}function setUpDatabase(e){var t=e.result;t.createObjectStore(MODEL_STORE_NAME,{keyPath:"modelPath"}),t.createObjectStore(INFO_STORE_NAME,{keyPath:"modelPath"})}function browserIndexedDB(e){return new BrowserIndexedDB(e)}function maybeStripScheme(e){return e.startsWith(BrowserIndexedDB.URL_SCHEME)?e.slice(BrowserIndexedDB.URL_SCHEME.length):e}function getModelKeys(e){return{info:[PATH_PREFIX,e,INFO_SUFFIX].join(PATH_SEPARATOR),topology:[PATH_PREFIX,e,MODEL_TOPOLOGY_SUFFIX].join(PATH_SEPARATOR),weightSpecs:[PATH_PREFIX,e,WEIGHT_SPECS_SUFFIX].join(PATH_SEPARATOR),weightData:[PATH_PREFIX,e,WEIGHT_DATA_SUFFIX].join(PATH_SEPARATOR)}}function getModelPathFromKey(e){var t=e.split(PATH_SEPARATOR);if(t.length<3)throw new Error("Invalid key format: "+e);return t.slice(1,t.length-1).join(PATH_SEPARATOR)}function maybeStripScheme$1(e){return e.startsWith(BrowserLocalStorage.URL_SCHEME)?e.slice(BrowserLocalStorage.URL_SCHEME.length):e}function browserLocalStorage(e){return new BrowserLocalStorage(e)}function browserDownloads(e){return void 0===e&&(e="model"),new BrowserDownloads(e)}function browserFiles(e){return new BrowserFiles(e)}function loadWeightsAsArrayBuffer(e,t){return __awaiter$12(this,void 0,void 0,function(){var r,n,a;return __generator$12(this,function(o){switch(o.label){case 0:return r=e.map(function(e){return fetch(e,t)}),[4,Promise.all(r)];case 1:return n=o.sent(),[4,Promise.all(n.map(function(e){return e.arrayBuffer()}))];case 2:return a=o.sent(),[2,a]}})})}function loadWeights(e,t,r,n){return void 0===t&&(t=""),__awaiter$12(this,void 0,void 0,function(){var a,o,i,s,u,l,c,p,d,h;return __generator$12(this,function(f){switch(f.label){case 0:if(a=e.map(function(){return!1}),o={},i=null!=r?r.map(function(){return!1}):[],s=[],e.forEach(function(e,t){var n=0;e.weights.forEach(function(e){var u="quantization"in e?e.quantization.dtype:e.dtype,l=DTYPE_VALUE_SIZE_MAP[u]*sizeFromShape(e.shape),c=function(){a[t]=!0,null==o[t]&&(o[t]=[]),o[t].push({manifestEntry:e,groupOffset:n,sizeBytes:l})};null!=r?r.forEach(function(t,r){t===e.name&&(c(),i[r]=!0)}):c(),s.push(e.name),n+=l})}),!i.every(function(e){return e}))throw u=r.filter(function(e,t){return!i[t]}),new Error("Could not find weights in manifest with names: "+u.join(", ")+". \nManifest JSON has weights with names: "+s.join(", ")+".");return l=a.reduce(function(e,t,r){return t&&e.push(r),e},[]),c=[],l.forEach(function(r){e[r].paths.forEach(function(e){var r=t+(t.endsWith("/")?"":"/")+e;c.push(r)})}),[4,loadWeightsAsArrayBuffer(c,n)];case 1:return p=f.sent(),d={},h=0,l.forEach(function(t){for(var r=e[t].paths.length,n=0,a=0;a<r;a++)n+=p[h+a].byteLength;for(var i=new ArrayBuffer(n),s=new Uint8Array(i),u=0,l=0;l<r;l++){var c=new Uint8Array(p[h+l]);s.set(c,u),u+=c.byteLength}o[t].forEach(function(e){var t,r=i.slice(e.groupOffset,e.groupOffset+e.sizeBytes),n=e.manifestEntry.dtype;if("quantization"in e.manifestEntry){var a=e.manifestEntry.quantization;if("uint8"!==a.dtype&&"uint16"!==a.dtype)throw new Error("Weight "+e.manifestEntry.name+" has unknown quantization dtype "+a.dtype+".");var o="uint8"===a.dtype?new Uint8Array(r):new Uint16Array(r);if("float32"===n)t=Float32Array.from(o,function(e){return e*a.scale+a.min});else{if("int32"!==n)throw new Error("Weight "+e.manifestEntry.name+" has a dtype not supported by quantization: "+n);t=Int32Array.from(o,function(e){return Math.round(e*a.scale+a.min)})}}else if("float32"===n)t=new Float32Array(r);else{if("int32"!==n)throw new Error("Weight "+e.manifestEntry.name+" has unknown dtype "+n+".");t=new Int32Array(r)}var s=e.manifestEntry.name;if(null!=d[s])throw new Error("Duplicate weight with name "+s+". Please make sure weights names are unique in the manifest JSON.");d[s]=tensor(t,e.manifestEntry.shape,e.manifestEntry.dtype)}),h+=r}),[2,d]}})})}function browserHTTPRequest(e,t){return new BrowserHTTPRequest(e,t)}function expectArraysClose(e,t,r){if(void 0===r&&(r=TEST_EPSILON),e instanceof Tensor||t instanceof Tensor){if(e instanceof Tensor&&t instanceof Tensor){if(e.dtype!==t.dtype)throw new Error("Arrays are of different type actual: "+e.dtype+" vs expected: "+t.dtype+".");if(!arraysEqual(e.shape,t.shape))throw new Error("Arrays are of different shape actual: "+e.shape+" vs expected: "+t.shape+".")}}else{var n=e.constructor.name,a=t.constructor.name;if(n!==a)throw new Error("Arrays are of different type actual: "+n+" vs expected: "+a)}var o,i;if(o=e instanceof Tensor?e.dataSync():e,i=t instanceof Tensor?t.dataSync():t,o.length!==i.length)throw new Error("Arrays have different lengths actual: "+o.length+" vs expected: "+i.length+".\nActual:   "+o+".\nExpected: "+i+".");for(var s=0;s<i.length;++s){var u=o[s],l=i[s];if(!areClose(u,Number(l),r))throw new Error("Arrays differ: actual["+s+"] = "+u+", expected["+s+"] = "+l+".\nActual:   "+o+".\nExpected: "+i+".")}}function expectPromiseToFail(e,t){e().then(function(){return t.fail()},function(){return t()})}function expectArraysEqual(e,t){return expectArraysClose(e,t,0)}function expectNumbersClose(e,t,r){if(void 0===r&&(r=TEST_EPSILON),!areClose(e,t,r))throw new Error("Numbers differ: actual === "+e+", expected === "+t)}function areClose(e,t,r){return!(!isNaN(e)||!isNaN(t))||!(isNaN(e)||isNaN(t)||Math.abs(e-t)>r)}function expectValuesInRange(e,t,r){var n;n=e instanceof Tensor?e.dataSync():e;for(var a=0;a<n.length;a++)if(n[a]<t||n[a]>r)throw new Error("Value out of range:"+n[a]+" low: "+t+", high: "+r)}function pyListRepeat(e,t){if(Array.isArray(e)){for(var r=[],n=0;n<t;n++)r=r.concat(e);return r}return(r=new Array(t)).fill(e),r}function assert$1(e,t){if(!e)throw new AssertionError(t)}function count(e,t){for(var r=0,n=0,a=e;n<a.length;n++)a[n]===t&&r++;return r}function singletonOrArray(e){return 1===e.length?e[0]:e}function toList(e){return Array.isArray(e)?e:[e]}function isArrayOfShapes(e){return Array.isArray(e)&&Array.isArray(e[0])}function normalizeShapeList(e){return 0===e.length?[]:Array.isArray(e[0])?e:[e]}function toSnakeCase(e){var t=e.replace(/(.)([A-Z][a-z0-9]+)/g,"$1_$2").replace(/([a-z])([A-Z])/g,"$1_$2").toLowerCase();return"_"!==t[0]?t:"private"+t}function toCamelCase(e){return e.length<=1?e:-1===e.indexOf("_")?e:e.replace(/[_]+(\w|$)/g,function(e,t){return t.toUpperCase()})}function serializeKerasObject(e){return null===e||void 0===e?null:{className:e.getClassName(),config:e.getConfig()}}function deserializeKerasObject(e,t,r,n){if(void 0===t&&(t={}),void 0===r&&(r={}),void 0===n&&(n="object"),"string"==typeof e){var a=e,o=void 0;if(a in r)o=r[a];else if(a in _GLOBAL_CUSTOM_OBJECTS)o=_GLOBAL_CUSTOM_OBJECTS[a];else if(null==(o=t[a]))throw new ValueError("Unknown "+n+": "+e);return o}var i=e;if(null==i.className||null==i.config)throw new ValueError(n+": Improper config format: "+JSON.stringify(i)+".\n'className' and 'config' must set.");var s=i.className,u=void 0,l=void 0;if(s in r?(u=(_=r.get(s))[0],l=_[1]):s in _GLOBAL_CUSTOM_OBJECTS?(u=(S=_GLOBAL_CUSTOM_OBJECTS.className)[0],l=S[1]):s in t&&(u=(N=t[s])[0],l=N[1]),null==u)throw new ValueError("Unknown "+n+": "+s);if(null!=l){for(var c={},p=0,d=Object.keys(_GLOBAL_CUSTOM_OBJECTS);p<d.length;p++)c[x=d[p]]=_GLOBAL_CUSTOM_OBJECTS[x];for(var h=0,f=Object.keys(r);h<f.length;h++)c[x=f[h]]=r[x];i.config.customObjects=c;for(var m=__assign({},_GLOBAL_CUSTOM_OBJECTS),g=0,y=Object.keys(r);g<y.length;g++){x=y[g];_GLOBAL_CUSTOM_OBJECTS[x]=r[x]}w=l(u,i.config);return _GLOBAL_CUSTOM_OBJECTS=__assign({},m),w}for(var m=__assign({},_GLOBAL_CUSTOM_OBJECTS),v=0,b=Object.keys(r);v<b.length;v++){var x=b[v];_GLOBAL_CUSTOM_OBJECTS[x]=r[x]}var w=new u(i.config);return _GLOBAL_CUSTOM_OBJECTS=__assign({},m),w;var _,S,N}function getExactlyOneTensor(e){var t;if(Array.isArray(e)){if(1!==e.length)throw new ValueError("Expected Tensor length to be 1; got "+e.length);t=e[0]}else t=e;return t}function getExactlyOneShape(e){if(Array.isArray(e)&&Array.isArray(e[0])){if(1===e.length)return(e=e)[0];throw new ValueError("Expected exactly 1 Shape; got "+e.length)}return e}function numberCompare(e,t){return e<t?-1:e>t?1:0}function reverseNumberCompare(e,t){return-1*numberCompare(e,t)}function stringToDType(e){switch(e){case"float32":return"float32";default:throw new ValueError("Invalid dtype: "+e)}}function unique(e){if(null==e)return e;for(var t=[],r=0,n=e;r<n.length;r++){var a=n[r];-1===t.indexOf(a)&&t.push(a)}return t}function isObjectEmpty(e){if(null==e)throw new ValueError("Invalid value in obj: "+JSON.stringify(e));for(var t in e)if(e.hasOwnProperty(t))return!1;return!0}function checkStringTypeUnionValue(e,t,r){if(null!=r&&e.indexOf(r)<0)throw new ValueError(r+" is not a valid "+t+".  Valid values are "+e+" or null/undefined.")}function checkDataFormat(e){checkStringTypeUnionValue(VALID_DATA_FORMAT_VALUES,"DataFormat",e)}function checkPaddingMode(e){checkStringTypeUnionValue(VALID_PADDING_MODE_VALUES,"PaddingMode",e)}function checkPoolMode(e){checkStringTypeUnionValue(VALID_POOL_MODE_VALUES,"PoolMode",e)}function nameScope(e,t){_nameScopeStack.push(e);try{var r=t();return _nameScopeStack.pop(),r}catch(e){throw _nameScopeStack.pop(),e}}function currentNameScopePrefix(){return 0===_nameScopeStack.length?"":_nameScopeStack.join(_nameScopeDivider)+_nameScopeDivider}function getScopedTensorName(e){if(!isValidTensorName(e))throw new Error("Not a valid tensor name: '"+e+"'");return currentNameScopePrefix()+e}function getUniqueTensorName(e){if(!isValidTensorName(e))throw new Error("Not a valid tensor name: '"+e+"'");nameMap.has(e)||nameMap.set(e,0);var t=nameMap.get(e);if(nameMap.set(e,nameMap.get(e)+1),t>0){var r=e+"_"+t;return nameMap.set(r,1),r}return e}function isValidTensorName(e){return!!e.match(tensorNameRegex)}function isInteger(e){return e===parseInt(e.toString(),10)}function arrayProd(e,t,r){null==t&&(t=0),null==r&&(r=e.length);for(var n=1,a=t;a<r;++a)n*=e[a];return n}function toArray1D(e){return e=Array.isArray(e)?new Float32Array(e):e,tensor1d(e)}function min$1(e){return min(toArray1D(e)).dataSync()[0]}function max$1(e){return max(toArray1D(e)).dataSync()[0]}function range$1(e,t){if(t<e)throw new ValueError("end ("+t+") < begin ("+e+") is forbidden.");for(var r=[],n=e;n<t;++n)r.push(n);return r}function getNextUniqueTensorId(){return _nextUniqueTensorId++}function checkShapesMatch(e,t){if(e.shape.toString()!==t.shape.toString())throw new Error("Shape mismatch: "+JSON.stringify(e.shape)+" vs. "+JSON.stringify(t.shape))}function batchGetValue(e){return e.map(function(e){return e.read()})}function batchSetValue(e){e.map(function(e){e[0].write(e[1])})}function epsilon(){return _epsilon}function imageDataFormat(){return"channelsLast"}function getScalar(e,t){return void 0===t&&(t=DEFAULT_DTYPE),null==scalarCache[t][e]&&(scalarCache[t][e]=scalar(e,t),keep(scalarCache[t][e])),scalarCache[t][e]}function shape(e){return e.shape}function intShape(e){return e.shape}function dtype(e){return e instanceof Tensor?DEFAULT_DTYPE:e.dtype}function cast$1(e,t){return e.asType(t)}function expandDims$1(e,t){void 0===t&&(t=-1);var r=shape(e).slice();return t<0&&(t=r.length+t+1),r.splice(t,0,1),e.reshape(r)}function repeat(e,t){return tidy(function(){if(2!==e.shape.length)throw new ValueError("repeat() expects a rank-2 tensor, but received a rank-"+e.shape.length+" tensor.");return tile$1(expandDims$1(e,1),[1,t,1])})}function flatten$1(e){var t=[arrayProd(e.shape)];return e.reshape(t)}function batchFlatten(e){if(e.rank<=1)throw new ValueError("batchFlatten requires a minimum rank of 2. Got rank: "+e.rank+".");var t=[e.shape[0],arrayProd(e.shape,1)];return e.reshape(t)}function sliceAlongFirstAxis(e,t,r){return tidy(function(){switch(e.rank){case 1:return slice1d(e,t,r);case 2:return slice2d(e,[t,0],[r,e.shape[1]]);case 3:return slice3d(e,[t,0,0],[r,e.shape[1],e.shape[2]]);case 4:return slice4d(e,[t,0,0,0],[r,e.shape[1],e.shape[2],e.shape[3]]);default:throw new ValueError("sliceAlongFirstAxis() received an unsupported tensor rank: "+e.rank)}})}function sliceAlongLastAxis(e,t,r){return tidy(function(){switch(e.rank){case 1:return slice1d(e,t,r);case 2:return slice2d(e,[0,t],[e.shape[0],r]);case 3:return slice3d(e,[0,0,t],[e.shape[0],e.shape[1],r]);case 4:return slice4d(e,[0,0,0,t],[e.shape[0],e.shape[1],e.shape[2],r]);default:throw new ValueError("sliceAlongLastAxis() received an unsupported tensor rank: "+e.rank)}})}function sliceAlongAxis(e,t,r,n){return tidy(function(){switch(e.rank){case 1:return slice1d(e,t,r);case 2:switch(n){case 1:return sliceAlongFirstAxis(e,t,r);case 2:return sliceAlongLastAxis(e,t,r);default:throw new ValueError("The axis is not within the rank of the tensor "+n)}case 3:switch(n){case 1:return sliceAlongFirstAxis(e,t,r);case 2:return slice3d(e,[0,t,0],[e.shape[0],r,e.shape[2]]);case 3:return sliceAlongLastAxis(e,t,r);default:throw new ValueError("The axis is not within the rank of the tensor "+n)}case 4:switch(n){case 1:return sliceAlongFirstAxis(e,t,r);case 2:return slice4d(e,[0,t,0,0],[e.shape[0],r,e.shape[2],e.shape[3]]);case 3:return slice4d(e,[0,0,t,0],[e.shape[0],e.shape[1],r,e.shape[3]]);case 4:return sliceAlongLastAxis(e,t,r);default:throw new ValueError("The axis is not within the rank of the tensor "+n)}default:throw new ValueError("sliceAlongLastAxis() received an unsupported tensor rank: "+e.rank)}})}function concatenate(e,t){void 0===t&&(t=-1);var r;return t<0&&(t=0!==(r=e[0].rank)?r:0),t===e[0].rank&&(t=-1),concat(e,t)}function concatAlongFirstAxis(e,t){switch(e.rank){case 1:return concat1d([e,t]);case 2:return concat2d([e,t],0);case 3:return concat3d([e,t],0);case 4:return concat4d([e,t],0);default:throw new ValueError("concatAlongFirstAxis() received an unsupported tensor rank: "+e.rank)}}function tile$1(e,t){if(Array.isArray(t)||(t=[t]),e.rank!==t.length)throw new ValueError("The length of input n ("+t.length+") does not match the number of dimensions in input x ("+e.rank+")");return tile(e,t)}function identity(e){return e.clone()}function scalarTimesArray(e,t){return mul(e,t)}function scalarPlusArray(e,t){return add(e,t)}function randomNormal$1(e,t,r,n,a){return void 0===t&&(t=0),void 0===r&&(r=1),randomNormal(e,t,r,n,a)}function dot$1(e,t){if(2!==t.rank)throw new NotImplementedError("dot support for y other than rank 2 is not yet implemented: y shape = "+shape);if(2===e.rank)return matMul(e,t);if(3===e.rank){var r=e.shape[0],n=e.shape[1],a=e.shape[2];return e=e.reshape([r*n,a]),matMul(e,t).reshape([r,n,t.shape[1]])}throw new NotImplementedError("dot support for x of rank "+e.rank+" is not yet implemented: x shape = "+shape)}function gather$1(e,t,r){return tidy(function(){return t=Array.isArray(t)?tensor1d(t,"int32"):t.toInt(),gather(e,t,r)})}function square$1(e){return mulStrict(e,e)}function biasAdd(e,t,r){return tidy(function(){if(null==r&&(r=imageDataFormat()),checkDataFormat(r),1!==t.rank&&t.rank!==e.rank)throw new ValueError("Unexpected bias dimensions: "+t.rank+"; expected it to be 1 or "+e.rank);var n,a=t.shape;if(5===e.rank)"channelsFirst"===r?n=1===a.length?e.add(t.reshape([1,a[0],1,1,1])):e.add(t.reshape([1,a[3],a[0],a[1],a[2]])):"channelsLast"===r&&(n=1===a.length?e.add(t.reshape([1,1,1,1,a[0]])):e.add(t.reshape([1].concat(a))));else if(4===e.rank)"channelsFirst"===r?n=1===a.length?e.add(t.reshape([1,a[0],1,1])):e.add(t.reshape([1,a[2],a[0],a[1]])):"channelsLast"===r&&(n=1===a.length?e.add(t.reshape([1,1,1,a[0]])):e.add(t.reshape([1].concat(a))));else if(3===e.rank)"channelsFirst"===r?n=1===a.length?e.add(t.reshape([1,a[0],1])):e.add(t.reshape([1,a[1],a[0]])):"channelsLast"===r&&(n=1===a.length?e.add(t.reshape([1,1,a[0]])):e.add(t.reshape([1].concat(a))));else{if(!(e.rank<3))throw new ValueError("Unsupported input rank by biasAdd: "+e.rank);n=e.add(t)}return n})}function elu$1(e,t){if(void 0===t&&(t=1),1!==t)throw new NotImplementedError("Support for alpha values other than 1 ("+t+") is not implemented yet.");return elu(e)}function softsign(e){return tidy(function(){return div(e,add(getScalar(1),abs(e)))})}function dropout(e,t,r,n){return tidy(function(){if(null!=r&&!arraysEqual(e.shape,r))throw new NotImplementedError("Non-default noise shape is not implemented yet: "+JSON.stringify(r));if(null!=n)throw new NotImplementedError("seed is not implemented for dropout yet.");var a=step(add(neg(t),randomUniform(e.shape,0,1,"float32")));return a=mul(div(getScalar(1),sub(getScalar(1),t)),a),mul(e,a)})}function nameScope$1(e,t){return nameScope(e,t)}function floatx(){return"float32"}function getUid(e){return void 0===e&&(e=""),e in _uidPrefixes||(_uidPrefixes[e]=0),_uidPrefixes[e]+=1,e+_uidPrefixes[e].toString()}function hardSigmoid(e){return tidy(function(){var t=scalarPlusArray(getScalar(.5),scalarTimesArray(getScalar(.2),e));return clipByValue(t,0,1)})}function inTrainPhase(e,t,r){return void 0===r&&(r=!1),r?e():t()}function calcL2Norms(e,t){return tidy(function(){return sqrt(sum(square$1(e),t,!0))})}function serializeConstraint(e){return serializeKerasObject(e)}function deserializeConstraint(e,t){return void 0===t&&(t={}),deserializeKerasObject(e,SerializationMap.getMap().classNameMap,t,"constraint")}function getConstraint(e){return null==e?null:"string"==typeof e?deserializeConstraint({className:e in CONSTRAINT_IDENTIFIER_REGISTRY_SYMBOL_MAP?CONSTRAINT_IDENTIFIER_REGISTRY_SYMBOL_MAP[e]:e,config:{}}):e instanceof Constraint?e:deserializeConstraint(e)}function deserialize(e,t){return void 0===t&&(t={}),deserializeKerasObject(e,SerializationMap.getMap().classNameMap,t,"layer")}function isArrayItemInputOrOutputName(e,t,r){return("inboundNodes"===e||"outputLayers"===e||"inputLayers"===e)&&0===t&&"string"==typeof r}function convertPythonicToTs(e,t){if(null===e)return null;if("string"==typeof e)return toCamelCase(e);if("number"==typeof e||"boolean"==typeof e)return e;if(e instanceof Array){for(var r=[],n=e.length,a=0;a<n;++a){var o=e[a];isArrayItemInputOrOutputName(t,a,o)?r.push(o):r.push(convertPythonicToTs(o,t))}return r}for(var i={},s=0,u=Object.keys(e);s<u.length;s++){var l=u[s],c=e[l];if("name"===l&&"string"==typeof c)i[l]=c;else{var p=toCamelCase(l);i[p]=convertPythonicToTs(c,p)}}return i}function convertTsToPythonic(e,t){if(null===e||void 0===e)return null;if("string"==typeof e)return toSnakeCase(e);if("number"==typeof e||"boolean"==typeof e)return e;if(e instanceof Array){for(var r=[],n=e.length,a=0;a<n;++a){var o=e[a];isArrayItemInputOrOutputName(t,a,o)?r.push(o):r.push(convertTsToPythonic(o,t))}return r}for(var i={},s=0,u=Object.keys(e);s<u.length;s++){var l=u[s],c=e[l],p=toSnakeCase(l);i[p]="name"!==l&&"className"!==l||"string"!=typeof c?convertTsToPythonic(c,l):c}return i}function collectInputShape(e){for(var t=[],r=0,n=e=toList(e);r<n.length;r++){var a=n[r];t.push(intShape(a))}return singletonOrArray(t)}function guessOutputDType(e){return"float32"}function Input(e){if(null==e.batchShape&&null==e.shape)throw new Error("Please provide to Input either a `shape` or a `batchShape` argument. Note that `shape` does not include the batch dimension.");if(null!=e.batchShape&&null!=e.shape)throw new ValueError("Please provide either a `shape` or `batchShape` argument to Input, but not both.");var t=e.batchShape;null!=e.shape&&null==t&&(t=[null].concat(e.shape));var r=e.dtype;return null==r&&(r=floatx()),new InputLayer({batchInputShape:t,name:e.name,dtype:r,sparse:e.sparse}).inboundNodes[0].outputTensors[0]}function getSourceInputs(e,t,r){if((null==t||null!=r&&r>0)&&(t=e.sourceLayer,r=e.nodeIndex),0===t.inboundNodes.length)return[e];var n=t.inboundNodes[r];if(0===n.inboundLayers.length)return n.inputTensors;for(var a=[],o=0;o<n.inboundLayers.length;o++)for(var i=0,s=getSourceInputs(n.inputTensors[o],n.inboundLayers[o],n.nodeIndices[o]);i<s.length;i++){var u=s[i];-1===a.indexOf(u)&&a.push(u)}return a}function loadTensor(e,t,r){var n=stringToDType(e);return Tensor.make(t,{values:0===t.length?r:flatten(r)},n)}function preprocessWeightsForLoading(e,t,r,n){if(!r.startsWith("2."))throw new ValueError("Unsupported Keras version in weights being loaded: "+r);return t}function loadWeightsFromNamedTensorMap(e,t){for(var r={},n=0,a=0,o=t;a<o.length;a++)for(var i=0,s=o[a].weights;i<s.length;i++){var u=s[i];if(null!=r[u.originalName])throw new ValueError("Duplicate weight name: "+u.originalName);r[u.originalName]=u,n++}var l=[];for(var c in e)l.push([r[c],e[c]]),delete r[c];var p=[];for(var d in r)p.push(d);if(p.length>0)throw new ValueError(p.length+" of "+n+" weights are not set: "+p);batchSetValue(l)}function loadWeightsFromJson(e,t,r){void 0===r&&(r=!1);for(var n=e.keras_version,a=e.backend,o=t.map(function(e){return e.name}),i={},s=0,u=t;s<u.length;s++)null!=(b=u[s]).name&&(null==i[b.name]&&(i[b.name]=[]),i[b.name].push(b));for(var l=e.weights,c=[],p=0;p<o.length;++p){var d=o[p],h=l[d];null==h&&(h=[]);for(var f=[],m=0;m<h.length;++m){var g=h[m];f.push(new LayerVariable(loadTensor(g.dtype,g.shape,g.value)))}for(var y=0,v=i[d];y<v.length;y++){var b=v[y],x=b.weights;if((f=preprocessWeightsForLoading(b,f,n,a)).length!==x.length){if(!r)throw new ValueError("Layer #"+p+' (named "'+b.name+'") expects '+x.length+" weight(s), but the saved weights have "+f.length+" element(s).");console.warn("Skipping loading of weights of layer "+b.name+" due to mismatch in number of weights: ("+f.length+" vs "+x.length+").")}for(var w=0;w<f.length;++w)!r||arraysEqual(x[w].shape,f[w].shape)?c.push([x[w],f[w].read()]):console.warn("Skipping loading of weights for layer "+b.name+" due to mismatch in shape ("+x[w].shape+" vs "+f[w].shape+")")}}batchSetValue(c)}function resolveScalarsInLogs(e){return __awaiter$14(this,void 0,void 0,function(){var t,r,n,a,o,i,s;return __generator$14(this,function(u){switch(u.label){case 0:if(null==e)return[2];t=[],r=[];for(n in e)"number"!=typeof(a=e[n])&&(o=a,t.push(o.data()),r.push(n));return[4,Promise.all(t)];case 1:for(i=u.sent(),s=0;s<i.length;++s)e[r[s]]=i[s][0];return[2]}})})}function disposeTensorsInLogs(e){if(null!=e)for(var t in e){var r=e[t];"number"!=typeof r&&r.dispose()}}function standardizeCallbacks(e){return null==e?null:e instanceof Callback?[e]:Array.isArray(e)&&e[0]instanceof Callback?e:toList(e).map(function(e){return new CustomCallback(e)})}function l2Normalize(e,t){return tidy(function(){var r=sum(square$1(e),t,!0),n=scalarTimesArray(scalar(epsilon$1()),onesLike(e)),a=sqrt(maximum(r,n));return div(e,a)})}function meanSquaredError(e,t){return tidy(function(){return mean(square$1(sub(t,e)),-1)})}function meanAbsoluteError(e,t){return tidy(function(){return mean(abs(sub(t,e)),-1)})}function meanAbsolutePercentageError(e,t){return tidy(function(){var r=sub(e,t),n=clipByValue(abs(e),epsilon$1(),Number.MAX_VALUE),a=abs(div(r,n));return scalarTimesArray(getScalar(100),mean(a,-1))})}function meanSquaredLogarithmicError(e,t){return tidy(function(){var r=getScalar(1),n=clipByValue(t,epsilon$1(),Number.MAX_VALUE),a=log(scalarPlusArray(r,n)),o=clipByValue(e,epsilon$1(),Number.MAX_VALUE),i=log(scalarPlusArray(r,o));return mean(square$1(sub(a,i)),-1)})}function squaredHinge(e,t){return tidy(function(){var r=getScalar(0),n=getScalar(1),a=maximum(r,sub(n,mul(e,t)));return mean(square$1(a),-1)})}function hinge(e,t){return tidy(function(){var r=getScalar(0),n=getScalar(1),a=maximum(r,sub(n,mul(e,t)));return mean(a,-1)})}function categoricalHinge(e,t){return tidy(function(){var r=getScalar(0),n=getScalar(1),a=sum(mul(e,t),-1),o=max(mul(sub(n,e),t),-1);return maximum(r,scalarPlusArray(n,sub(o,a)))})}function logcosh(e,t){return tidy(function(){var r=getScalar(Math.log(2)),n=sub(t,e),a=sub(add(n,softplus(scalarTimesArray(getScalar(-2),n))),r);return mean(a,-1)})}function categoricalCrossentropy(e,t,r){return void 0===r&&(r=!1),tidy(function(){if(r)t=softmax(t);else{var n=sum(t,shape(t).length-1,!0);t=div(t,n)}return t=clipByValue(t,epsilon$1(),1-epsilon$1()),neg(sum(mul(e.toFloat(),log(t)),shape(t).length-1))})}function sparseCategoricalCrossentropy(e,t,r){return void 0===r&&(r=!1),tidy(function(){var n=floor(flatten$1(e)).toInt(),a=shape(t);return categoricalCrossentropy(oneHot(n,a[a.length-1]).reshape(a),t,r)})}function sigmoidCrossEntropyWithLogits(e,t){return tidy(function(){var r=maximum(t,zerosLike(t)),n=mul(t,e),a=log(add(getScalar(1),exp(neg(abs(t)))));return add(sub(r,n),a)})}function binaryCrossentropy(e,t){return tidy(function(){var r;return r=clipByValue(t,epsilon$1(),1-epsilon$1()),r=log(div(r,sub(onesLike(r),r))),mean(sigmoidCrossEntropyWithLogits(e,r),-1)})}function kullbackLeiblerDivergence(e,t){return tidy(function(){var r=clipByValue(e,epsilon$1(),1),n=clipByValue(t,epsilon$1(),1);return sum(mul(e,log(div(r,n))),-1)})}function poisson(e,t){return tidy(function(){var r=log(scalarPlusArray(getScalar(epsilon$1()),t));return mean(sub(t,mul(e,r)),-1)})}function cosineProximity(e,t){return tidy(function(){var r=l2Normalize(e,-1),n=l2Normalize(t,-1),a=mul(r,n);return neg(sum(a,-1))})}function get(e){var t={meanSquaredError:meanSquaredError,meanAbsoluteError:meanAbsoluteError,meanAbsolutePercentageError:meanAbsolutePercentageError,meanSquaredLogarithmicError:meanSquaredLogarithmicError,squaredHinge:squaredHinge,hinge:hinge,categoricalHinge:categoricalHinge,logcosh:logcosh,categoricalCrossentropy:categoricalCrossentropy,sparseCategoricalCrossentropy:sparseCategoricalCrossentropy,binaryCrossentropy:binaryCrossentropy,kullbackLeiblerDivergence:kullbackLeiblerDivergence,poisson:poisson,cosineProximity:cosineProximity};if("string"==typeof e){if(e in t)return t[e];throw new ValueError("Unknown loss "+e)}return e}function binaryAccuracy(e,t){return tidy(function(){var r=scalarTimesArray(getScalar(.5),onesLike(t)),n=cast$1(greater(t,r),e.dtype);return mean(equal(e,n),-1)})}function categoricalAccuracy(e,t){return tidy(function(){return cast$1(equal(argMax(e,-1),argMax(t,-1)),"float32")})}function binaryCrossentropy$1(e,t){return binaryCrossentropy(e,t)}function sparseCategoricalAccuracy(e,t){throw new NotImplementedError}function get$1(e){var t={binaryAccuracy:binaryAccuracy,categoricalAccuracy:categoricalAccuracy,categoricalCrossentropy:categoricalCrossentropy$1,sparseCategoricalCrossentropy:sparseCategoricalCrossentropy$1,mse:mse$1,MSE:MSE$1,mae:mae$1,MAE:MAE$1,mape:mape$1,MAPE:MAPE$1,cosine:cosine$1};if("string"==typeof e&&e in t)return t[e];if("string"!=typeof e&&null!=e)return e;throw new ValueError("Unknown metric "+e)}function getOptimizer(e){var t={Adagrad:function(){return train.adagrad(.01)},Adam:function(){return train.adam(.001,.9,.999,epsilon$1())},RMSProp:function(){return train.rmsprop(.001,.9,null,epsilon$1())},SGD:function(){return train.sgd(.01)}};if(t.adagrad=t.Adagrad,t.adam=t.Adam,t.rmsprop=t.RMSProp,t.sgd=t.SGD,e in t)return t[e]();throw new ValueError("Unknown Optimizer "+e)}function assertFeedCompatibility(e,t){if(null!=e.dtype&&e.dtype!==t.dtype)throw new ValueError("The dtype of the feed ("+t.dtype+") is incompatible with that of the key '"+e.name+"' ("+e.dtype+").");if(null!=e.shape){if(e.shape.length!==t.shape.length)throw new ValueError("The rank of feed ("+t.shape.length+") does not match the rank of the key ("+e.shape.length+").");for(var r=0;r<e.shape.length;++r)if(null!=e.shape[r]&&e.shape[r]!==t.shape[r])throw new ValueError("The "+r+"-th dimension of the feed ("+t.shape[r]+") is incompatible with that of the key ("+e.shape[r]+").")}}function execute(e,t,r){for(var n=Array.isArray(e),a=n?e:[e],o=[],i=new FeedDict(t),s=0,u=a;s<u.length;s++){var l=u[s];o.push(executeInternal(l,i,r))}return n?o:o[0]}function executeInternal(e,t,r){if(t.hasKey(e))return t.getValue(e);if(e.sourceLayer instanceof InputLayer)throw new ValueError("Missing a feed value for SymbolicTensor from InputLayer '"+InputLayer.name+"'");for(var n=[],a=0,o=e.inputs;a<o.length;a++){var i=executeInternal(o[a],t,r);n.push(i)}var s=e.sourceLayer.apply(n,r);Array.isArray(s)||(s=[s]);for(var u=getNodeOutputs(e),l=Array.isArray(u)?u:[u],c=0;c<l.length;++c)t.add(l[c],s[c]);return 1===s.length?s[0]:s[e.outputTensorIndex]}function getNodeOutputs(e){var t;if(1===e.sourceLayer.inboundNodes.length)t=e.sourceLayer.output;else{for(var r=null,n=0;n<e.sourceLayer.inboundNodes.length;++n)for(var a=0,o=e.sourceLayer.inboundNodes[n].outputTensors;a<o.length;a++)if(o[a].id===e.id){r=n;break}t=e.sourceLayer.getOutputAt(r)}return t}function isDataTensor(e){return e instanceof Tensor}function isDataArray(e){return Array.isArray(e)}function isDataDict(e){return!isDataTensor(e)&&!isDataArray(e)}function standardizeInputData(e,t,r,n,a){if(void 0===n&&(n=!0),void 0===a&&(a=""),null==t||0===t.length){if(null!=e){var o=!1;if(isDataArray(e)&&e.length>0)o=!0;else if(isDataDict(e)){for(var i in e)if(e.hasOwnProperty(i)){o=!0;break}}else o=!0;if(o)throw new ValueError("Error when checking model "+a+" expected no data, but got "+e)}return[]}if(null==e)return t.map(function(e){return null});var s;if(isDataDict(e)){e=e,s=[];for(var u=0,l=t;u<l.length;u++){var c=l[u];if(null==e[c])throw new ValueError('No data provided for "'+c+'". Need data for each key in: '+t);s.push(e[c])}}else if(isDataArray(e)){if((e=e).length!==t.length)throw new ValueError("Error when checking model "+a+": the Array of Tensors that you are passing to your model is not the size the model expected. Expected to see "+t.length+" Tensor(s), but instead got the following list of Tensor(s): "+e);s=e}else{if(e=e,t.length>1)throw new ValueError("The model "+a+" expects "+t.length+" Tensor(s), but only received one Tensor. Found: Tensor with shape "+e.shape);s=[e]}for(p=0;p<t.length;++p)1===(d=s[p]).shape.length&&(s[p]=expandDims$1(d,1));if(null!=r)for(var p=0;p<t.length;++p)if(null!=r[p]){var d=s[p];if(d.shape.length!==r[p].length)throw new ValueError("Error when checking "+a+": expected "+t[p]+" to have "+r[p].length+" dimension(s). but got array with shape "+d.shape);for(var h=0;h<r[p].length;++h)if(0!==h||n){var f=d.shape[h],m=r[p][h];if(null!=m&&m>=0&&f!==m)throw new ValueError("Error when checking "+a+": expected "+t[p]+" to have shape ["+r[p]+"], but got array with shape ["+d.shape+"].")}}return s}function checkArrayLengths(e,t,r){var n=unique(e.map(function(e){return e.shape[0]}));n.sort();var a=unique(t.map(function(e){return e.shape[0]}));if(a.sort(),n.length>1)throw new ValueError("All input Tensors (x) should have the same number of samples. Got array shapes: "+JSON.stringify(e.map(function(e){return e.shape})));if(a.length>1)throw new ValueError("All target Tensors (y) should have the same number of samples. Got array shapes: "+JSON.stringify(t.map(function(e){return e.shape})));if(n.length>0&&a.length>0&&!arraysEqual(n,a))throw new ValueError("Input Tensors should have the same number of samples as target Tensors. Found "+n[0]+" input sample(s) and "+a[0]+" target sample(s).")}function checkLossAndTargetCompatibility(e,t,r){for(var n=[meanSquaredError,binaryCrossentropy,categoricalCrossentropy],a=0;a<e.length;++a){var o=e[a],i=t[a],s=r[a];if(null!=i){if(i===categoricalCrossentropy&&1===o.shape[o.shape.length-1])throw new ValueError("You are passing a target array of shape "+o.shape+" while using a loss 'categorical_crossentropy'. 'categorical_crossentropy'expects targets to be binary matrices (1s and 0s) of shape [samples, classes].");if(-1!==n.indexOf(i))for(var u=o.shape.slice(1),l=s.slice(1),c=0;c<u.length;++c){var p=u[c],d=l[c];if(null!=d&&p!==d)throw new ValueError("A target Tensor with shape "+o.shape+" was passed for an output of shape "+s+", while using a loss function that expects targets to have the same shape as the output.")}}}}function makeBatches(e,t){for(var r=[],n=0,a=null;n<e;)(a=n+t)>=e&&(a=e),r.push([n,a]),n=a;return r}function sliceArrays(e,t,r){return null==e?[null]:Array.isArray(e)?e.map(function(e){return sliceAlongFirstAxis(e,t,r-t)}):sliceAlongFirstAxis(e,t,r-t)}function sliceArraysByIndices(e,t){return tidy(function(){return null==e?null:Array.isArray(e)?e.map(function(e){return sliceArraysByIndices(e,t)}):gather$1(e,"int32"===t.dtype?t:t.toInt())})}function checkInputData(e,t,r,n,a){void 0===n&&(n=!0),void 0===a&&(a="");var o;if(Array.isArray(e)){if(e.length!==t.length)throw new ValueError("Error when checking model "+a+": the Array of Tensors that you are passing to your model is not the size the the model expected. Expected to see "+t.length+" Tensor(s), but instead got "+e.length+" Tensors(s).");o=e}else{if(t.length>1)throw new ValueError("The model expects "+t.length+" "+a+" Tensors, but only received one Tensor. Found: array with shape "+JSON.stringify(e.shape)+".");o=[e]}if(null!=r)for(var i=0;i<t.length;++i)if(null!=r[i]){var s=o[i];if(s.shape.length!==r[i].length)throw new ValueError("Error when checking "+a+": expected "+t[i]+" to have "+r[i].length+" dimension(s), but got array with shape "+JSON.stringify(s.shape));for(var u=0;u<r[i].length;++u)if(0!==u||n){var l=s.shape[u],c=r[i][u];if(null!=c&&c!==l)throw new ValueError("Error when checking "+a+": expected "+t[i]+" to have shape "+JSON.stringify(r[i])+" but got array with shape "+JSON.stringify(s.shape)+".")}}}function collectMetrics(e,t){if(null==e||Array.isArray(e)&&0===e.length)return t.map(function(e){return[]});if(Array.isArray(e))return t.map(function(t){return e});if(null!=e){for(var r=[],n=0,a=t;n<a.length;n++){var o=a[n],i=e.hasOwnProperty(o)?e[o]:[];Array.isArray(i)||(i=[i]),r.push(i)}return r}throw new TypeError("Type of metrics argument not understood. Expected an Array or Object, found: "+e)}function checkFanMode(e){checkStringTypeUnionValue(VALID_FAN_MODE_VALUES,"FanMode",e)}function checkDistribution(e){checkStringTypeUnionValue(VALID_DISTRIBUTION_VALUES,"Distribution",e)}function computeFans(e,t){void 0===t&&(t="channelsLast");var r,n;if(checkDataFormat(t),2===e.length)r=e[0],n=e[1];else if(-1!==[3,4,5].indexOf(e.length)){if("channelsFirst"===t){a=arrayProd(e,2);r=e[1]*a,n=e[0]*a}else if("channelsLast"===t){var a=arrayProd(e,0,e.length-2);r=e[e.length-2]*a,n=e[e.length-1]*a}}else{var o=arrayProd(e);r=Math.sqrt(o),n=Math.sqrt(o)}return[r,n]}function deserializeInitializer(e,t){return void 0===t&&(t={}),deserializeKerasObject(e,SerializationMap.getMap().classNameMap,t,"initializer")}function serializeInitializer(e){return serializeKerasObject(e)}function getInitializer(e){if("string"==typeof e){var t=e in INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP?INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP[e]:e;return"GlorotUniform"===t?new GlorotUniform:"GlorotNormal"===t?new GlorotNormal:"HeNormal"===t?new HeNormal:"LeCunNormal"===t?new LeCunNormal:deserializeInitializer({className:t,config:{}})}return e instanceof Initializer?e:deserializeInitializer(e)}function serializeActivation(e){return e.getClassName()}function deserializeActivation(e,t){return void 0===t&&(t={}),deserializeKerasObject(e,SerializationMap.getMap().classNameMap,t,"activation")}function getActivation(e){if(null==e)return deserializeActivation(t={className:"linear",config:{}});if("string"==typeof e){var t={className:e,config:{}};return deserializeActivation(t)}return e instanceof Activation?e:deserializeActivation(e)}function l1(e){return new L1L2({l1:null!=e?e.l1:null,l2:0})}function l2(e){return new L1L2({l2:null!=e?e.l2:null,l1:0})}function serializeRegularizer(e){return serializeKerasObject(e)}function deserializeRegularizer(e,t){return void 0===t&&(t={}),deserializeKerasObject(e,SerializationMap.getMap().classNameMap,t,"regularizer")}function getRegularizer(e){return null==e?null:"string"==typeof e?deserializeRegularizer({className:e in REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP?REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP[e]:e,config:{}}):e instanceof Regularizer?e:deserializeRegularizer(e)}function normalizeArray(e,t,r){if("number"==typeof e)return pyListRepeat(e,t);if(e.length!==t)throw new ValueError("The "+r+" argument must be a tuple of "+t+" integers. Received: "+e.length+" elements.");for(var n=0;n<t;++n){var a=e[n];if(!isInteger(a))throw new ValueError("The "+r+" argument must be a tuple of "+t+" integers. Received: "+JSON.stringify(e)+" including a non-integer number "+a)}return e}function convOutputLength(e,t,r,n,a){if(void 0===a&&(a=1),null==e)return e;var o,i=t+(t-1)*(a-1);return o="same"===r?e:e-i+1,Math.floor((o+n-1)/n)}function deconvLength(e,t,r,n){if(null==e)return null;if("valid"===n)e=e*t+max$1([r-t,0]);else{if("same"!==n)throw new ValueError("Unsupport padding mode: "+n+".");e*=t}return e}function preprocessConv2DInput(e,t){return tidy(function(){return checkDataFormat(t),"channelsFirst"===t?transpose(e,[0,2,3,1]):e})}function conv1dWithBias(e,t,r,n,a,o,i){return void 0===n&&(n=1),void 0===a&&(a="valid"),void 0===i&&(i=1),tidy(function(){if(null==o&&(o=imageDataFormat()),checkDataFormat(o),3!==e.shape.length)throw new ValueError("The input of a conv1dWithBias operation should be 3, but is "+e.shape.length+" instead.");if(3!==t.shape.length)throw new ValueError("The kernel for a conv1dWithBias operation should be 3, but is "+t.shape.length+" instead");if(null!=r&&1!==r.shape.length)throw new ValueError("The bias for a conv1dWithBias operation should be 1, but is "+t.shape.length+" instead");if("channelsFirst"===o&&(e=transpose(e,[0,2,1])),"causal"===a)throw new NotImplementedError("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");var s=conv1d(e,t,n,"same"===a?"same":"valid","NWC",i);return null!=r&&(s=biasAdd(s,r)),s})}function conv2dWithBias(e,t,r,n,a,o,i){return void 0===n&&(n=[1,1]),void 0===a&&(a="valid"),tidy(function(){if(null==o&&(o=imageDataFormat()),checkDataFormat(o),3!==e.rank&&4!==e.rank)throw new ValueError("conv2dWithBias expects input to be of rank 3 or 4, but received "+e.rank+".");if(3!==t.rank&&4!==t.rank)throw new ValueError("conv2dWithBias expects kernel to be of rank 3 or 4, but received "+e.rank+".");var s=preprocessConv2DInput(e,o);if("causal"===a)throw new NotImplementedError("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return s=conv2d(s,t,n,"same"===a?"same":"valid","NHWC",i),null!=r&&(s=biasAdd(s,r)),"channelsFirst"===o&&(s=transpose(s,[0,3,1,2])),s})}function depthwiseConv2d$1(e,t,r,n,a,o){return void 0===r&&(r=[1,1]),void 0===n&&(n="valid"),tidy(function(){null==a&&(a=imageDataFormat()),checkDataFormat(a);var i=preprocessConv2DInput(e,a);if(4!==e.rank)throw new ValueError("Input for depthwiseConv2d is required to be 4-D, but is instead "+e.rank+"-D");if(4!==t.rank)throw new ValueError("depthwiseKernel is required to be 4-D, but is instead "+t.rank+"-D");return i=depthwiseConv2d(i,t,r,"same"===n?"same":"valid","NHWC",o),"channelsFirst"===a&&(i=transpose(i,[0,3,1,2])),i})}function batchNormalization$1(e,t,r,n,a,o){void 0===o&&(o=.001);var i;if(2===e.rank)i=batchNormalization2d(e,t,r,o,a,n);else if(3===e.rank)i=batchNormalization3d(e,t,r,o,a,n);else{if(4!==e.rank)throw new NotImplementedError("batchNormalization is not implememnted for array of rank "+e.rank+" yet");i=batchNormalization4d(e,t,r,o,a,n)}return i}function regularNormalizeBatchInTraining(e,t,r,n,a){return void 0===a&&(a=.001),tidy(function(){var o=moments(e,n),i=o.mean,s=o.variance;return[batchNormalization$1(e,i,s,r,t,a),i,s]})}function broadcastNormalizeBatchInTraining(e,t,r,n,a){return void 0===a&&(a=.001),tidy(function(){for(var o=moments(e,n),i=o.mean,s=o.variance,u=[],l=0,c=range$1(0,e.rank);l<c.length;l++){var p=c[l];-1!==n.indexOf(p)?u.push(1):u.push(e.shape[p])}var d=i.reshape(u),h=s.reshape(u),f=null==t?null:t.reshape(u),m=null==r?null:r.reshape(u);return[batchNormalization$1(e,d,h,m,f,a),i,s]})}function normalizeBatchInTraining(e,t,r,n,a){return void 0===a&&(a=.001),arraysEqual(n.slice().sort(),range$1(0,e.rank-1))?regularNormalizeBatchInTraining(e,t,r,n,a):broadcastNormalizeBatchInTraining(e,t,r,n,a)}function spatial2dPadding(e,t,r){return tidy(function(){if(4!==e.rank)throw new ValueError("temporalPadding expects input tensor to be 4-D, but received a "+e.rank+"-D tensor.");if(null==t&&(t=[[1,1],[1,1]]),2!==t.length||2!==t[0].length||2!==t[1].length)throw new ValueError("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(null==r&&(r=imageDataFormat()),"channelsLast"!==r&&"channelsFirst"!==r)throw new ValueError("Unknown data format: "+r+". Supported data formats are 'channelsLast' and 'channelsFirst.");var n;return n="channelsFirst"===r?[[0,0],[0,0],t[0],t[1]]:[[0,0],t[0],t[1],[0,0]],pad(e,n)})}function pool2d(e,t,r,n,a,o){return tidy(function(){checkDataFormat(a),checkPoolMode(o),checkPaddingMode(n),null==r&&(r=[1,1]),null==n&&(n="valid"),null==a&&(a=imageDataFormat()),null==o&&(o="max"),e=preprocessConv2DInput(e,a);var i,s="same"===n?"same":"valid";return i="max"===o?maxPool(e,t,r,s):avgPool(e,t,r,s),"channelsFirst"===a&&(i=transpose(i,[0,3,1,2])),i})}function rnn(e,t,r,n,a,o,i,s){void 0===n&&(n=!1),void 0===i&&(i=!1);var u=t.shape.length;if(u<3)throw new ValueError("Input should be at least 3D, but is "+u+"D.");var l=[1,0].concat(range$1(2,u));if(t=transpose(t,l),null!=a)throw new NotImplementedError("The rnn() function of the deeplearn.js backend does not support masking yet.");if(null!=o)throw new NotImplementedError("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),n&&(t=reverse(t,0));for(var c,p,d=r,h=t.shape[0],f=0;f<h;++f){var m=sliceAlongFirstAxis(t,f,1),g=e(m=m.reshape(m.shape.slice(1)),d);p=g[0],c=0===f?p.reshape([1].concat(p.shape)):concatAlongFirstAxis(c,p.reshape([1].concat(p.shape))),d=g[1]}return[p,transpose(c,[1,0].concat(range$1(2,c.shape.length))),d]}function checkBidirectionalMergeMode(e){checkStringTypeUnionValue(VALID_BIDIRECTIONAL_MERGE_MODES,"BidirectionalMergeMode",e)}function loadModelInternal(e){return __awaiter$16(this,void 0,void 0,function(){var t;return __generator$16(this,function(r){if("string"==typeof e){if(0===(t=getLoadHandlers(e)).length)t.push(browserHTTPRequest(e));else if(t.length>1)throw new ValueError("Found more than one ("+t.length+") load handlers for URL '"+e+"'");e=t[0]}return[2,loadModelFromIOHandler(e)]})})}function loadModelFromIOHandler(e,t){return __awaiter$16(this,void 0,void 0,function(){var r,n,a,o,i;return __generator$16(this,function(s){switch(s.label){case 0:if(null==e.load)throw new ValueError("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");return[4,e.load()];case 1:if(r=s.sent(),null!=(n=r.modelTopology).model_config&&(n=n.model_config),a=deserialize(convertPythonicToTs(n),t),null!=r.weightData){if(null==r.weightSpecs)throw new ValueError("Model artifacts contains weight data, but not weight specs. Therefore loading of weights cannot proceed.");o=!1,i=!0,a.loadWeights(decodeWeights(r.weightData,r.weightSpecs),o,i)}return[2,a]}})})}function hasOwnProperty(e,t){return Object.prototype.hasOwnProperty.call(e,t)}function Url(){this.protocol=null,this.slashes=null,this.auth=null,this.host=null,this.port=null,this.hostname=null,this.hash=null,this.search=null,this.query=null,this.pathname=null,this.path=null,this.href=null}function urlParse(e,t,r){if(e&&util$1.isObject(e)&&e instanceof Url)return e;var n=new Url;return n.parse(e,t,r),n}function urlFormat(e){return util$1.isString(e)&&(e=urlParse(e)),e instanceof Url?e.format():Url.prototype.format.call(e)}function asPromise(e,t){for(var r=new Array(arguments.length-1),n=0,a=2,o=!0;a<arguments.length;)r[n++]=arguments[a++];return new Promise(function(a,i){r[n]=function(e){if(o)if(o=!1,e)i(e);else{for(var t=new 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Uint8Array(o.buffer),s=128===i[7];e.writeDoubleLE=s?t:r,e.writeDoubleBE=s?r:t,e.readDoubleLE=s?n:a,e.readDoubleBE=s?a:n}():function(){function t(e,t,r,n,a,o){var i=n<0?1:0;if(i&&(n=-n),0===n)e(0,a,o+t),e(1/n>0?0:2147483648,a,o+r);else if(isNaN(n))e(0,a,o+t),e(2146959360,a,o+r);else if(n>1.7976931348623157e308)e(0,a,o+t),e((i<<31|2146435072)>>>0,a,o+r);else{var s;if(n<2.2250738585072014e-308)e((s=n/5e-324)>>>0,a,o+t),e((i<<31|s/4294967296)>>>0,a,o+r);else{var u=Math.floor(Math.log(n)/Math.LN2);1024===u&&(u=1023),e(4503599627370496*(s=n*Math.pow(2,-u))>>>0,a,o+t),e((i<<31|u+1023<<20|1048576*s&1048575)>>>0,a,o+r)}}}function r(e,t,r,n,a){var o=e(n,a+t),i=e(n,a+r),s=2*(i>>31)+1,u=i>>>20&2047,l=4294967296*(1048575&i)+o;return 2047===u?l?NaN:s*(1/0):0===u?5e-324*s*l:s*Math.pow(2,u-1075)*(l+4503599627370496)}e.writeDoubleLE=t.bind(null,writeUintLE,0,4),e.writeDoubleBE=t.bind(null,writeUintBE,4,0),e.readDoubleLE=r.bind(null,readUintLE,0,4),e.readDoubleBE=r.bind(null,readUintBE,4,0)}(),e}function writeUintLE(e,t,r){t[r]=255&e,t[r+1]=e>>>8&255,t[r+2]=e>>>16&255,t[r+3]=e>>>24}function writeUintBE(e,t,r){t[r]=e>>>24,t[r+1]=e>>>16&255,t[r+2]=e>>>8&255,t[r+3]=255&e}function readUintLE(e,t){return(e[t]|e[t+1]<<8|e[t+2]<<16|e[t+3]<<24)>>>0}function readUintBE(e,t){return(e[t]<<24|e[t+1]<<16|e[t+2]<<8|e[t+3])>>>0}function inquire(moduleName){try{var mod=eval("quire".replace(/^/,"re"))(moduleName);if(mod&&(mod.length||Object.keys(mod).length))return mod}catch(e){}return null}function pool(e,t,r){var n=r||8192,a=n>>>1,o=null,i=n;return function(r){if(r<1||r>a)return e(r);i+r>n&&(o=e(n),i=0);var s=t.call(o,i,i+=r);return 7&i&&(i=1+(7|i)),s}}function LongBits(e,t){this.lo=e>>>0,this.hi=t>>>0}function Op(e,t,r){this.fn=e,this.len=t,this.next=void 0,this.val=r}function noop(){}function State(e){this.head=e.head,this.tail=e.tail,this.len=e.len,this.next=e.states}function Writer(){this.len=0,this.head=new Op(noop,0,0),this.tail=this.head,this.states=null}function writeByte(e,t,r){t[r]=255&e}function writeVarint32(e,t,r){for(;e>127;)t[r++]=127&e|128,e>>>=7;t[r]=e}function VarintOp(e,t){this.len=e,this.next=void 0,this.val=t}function writeVarint64(e,t,r){for(;e.hi;)t[r++]=127&e.lo|128,e.lo=(e.lo>>>7|e.hi<<25)>>>0,e.hi>>>=7;for(;e.lo>127;)t[r++]=127&e.lo|128,e.lo=e.lo>>>7;t[r++]=e.lo}function writeFixed32(e,t,r){t[r]=255&e,t[r+1]=e>>>8&255,t[r+2]=e>>>16&255,t[r+3]=e>>>24}function BufferWriter$1(){writer.call(this)}function writeStringBuffer(e,t,r){e.length<40?minimal.utf8.write(e,t,r):t.utf8Write(e,r)}function indexOutOfRange(e,t){return RangeError("index out of range: "+e.pos+" + "+(t||1)+" > "+e.len)}function Reader(e){this.buf=e,this.pos=0,this.len=e.length}function readLongVarint(){var e=new LongBits$2(0,0),t=0;if(!(this.len-this.pos>4)){for(;t<3;++t){if(this.pos>=this.len)throw indexOutOfRange(this);if(e.lo=(e.lo|(127&this.buf[this.pos])<<7*t)>>>0,this.buf[this.pos++]<128)return e}return e.lo=(e.lo|(127&this.buf[this.pos++])<<7*t)>>>0,e}for(;t<4;++t)if(e.lo=(e.lo|(127&this.buf[this.pos])<<7*t)>>>0,this.buf[this.pos++]<128)return e;if(e.lo=(e.lo|(127&this.buf[this.pos])<<28)>>>0,e.hi=(e.hi|(127&this.buf[this.pos])>>4)>>>0,this.buf[this.pos++]<128)return e;if(t=0,this.len-this.pos>4){for(;t<5;++t)if(e.hi=(e.hi|(127&this.buf[this.pos])<<7*t+3)>>>0,this.buf[this.pos++]<128)return e}else for(;t<5;++t){if(this.pos>=this.len)throw indexOutOfRange(this);if(e.hi=(e.hi|(127&this.buf[this.pos])<<7*t+3)>>>0,this.buf[this.pos++]<128)return e}throw Error("invalid varint encoding")}function readFixed32_end(e,t){return(e[t-4]|e[t-3]<<8|e[t-2]<<16|e[t-1]<<24)>>>0}function readFixed64(){if(this.pos+8>this.len)throw indexOutOfRange(this,8);return new LongBits$2(readFixed32_end(this.buf,this.pos+=4),readFixed32_end(this.buf,this.pos+=4))}function BufferReader$1(e){reader.call(this,e)}function Service(e,t,r){if("function"!=typeof e)throw TypeError("rpcImpl must be a function");minimal.EventEmitter.call(this),this.rpcImpl=e,this.requestDelimited=Boolean(t),this.responseDelimited=Boolean(r)}function getParamValue(e,t,r,n){var a=t.params[e];if(a&&void 0!==a.inputIndex){if("tensor"===a.type)return getTensor(t.inputNames[a.inputIndex],r,n);if("tensors"===a.type)return(0===a.inputIndex?0===a.inputParamLength?t.inputNames:t.inputNames.slice(a.inputIndex,-a.inputParamLength):t.inputNames.splice(a.inputIndex)).map(function(e){return getTensor(e,r,n)});var o=Array.prototype.slice.call(getTensor(t.inputNames.slice(a.inputIndex)[0],r,n).dataSync());return"number"===a.type?o[0]:o}return a&&a.value}function getTensor(e,t,r){var n=parseNodeName(e),a=n[0],o=n[1],i=r.currentContextIds.find(function(e){return!!t[getNodeNameWithContextId(a,e)]});return void 0!==i?t[getNodeNameWithContextId(a,i)][o]:void 0}function getNodeNameAndIndex(e,t){var r=parseNodeName(e),n=r[0],a=r[1];return[getNodeNameWithContextId(n,t&&t.currentContextId),a]}function getNodeNameWithContextId(e,t){return t?e+"-"+t:e}function parseNodeName(e){var t=e.lastIndexOf(":");return-1===t?[e,0]:[e.substring(0,t),Number(e.substring(t+1))]}function split$1(e,t){for(var r=[],n=0;n<e.length;n+=t)r.push(e.slice(n,n+t));return r}function executeOp$2(e,t,r){return __awaiter$17(this,void 0,void 0,function(){var n,a,o,i,s,u,l,c;return __generator$17(this,function(p){switch(p.label){case 0:switch(n=e.op){case"loopCond":return[3,1];case"switch":return[3,2];case"merge":return[3,4];case"enter":return[3,5];case"exit":return[3,6];case"nextIteration":return[3,7]}return[3,8];case 1:return[2,[getParamValue("pred",e,t,r)]];case 2:return a=getParamValue("pred",e,t,r),o=getParamValue("data",e,t,r),[4,a.data()];case 3:return[2,p.sent()[0]?[void 0,o]:[o,void 0]];case 4:return i=e.inputNames.find(function(e){return void 0!==getTensor(e,t,r)}),[2,i?[getTensor(i,t,r)]:void 0];case 5:return s=getParamValue("frameName",e,t,r),u=getParamValue("tensor",e,t,r),r.enterFrame(s),[2,[u]];case 6:return l=getParamValue("tensor",e,t,r),r.exitFrame(),[2,[l]];case 7:return c=getParamValue("tensor",e,t,r),r.nextIteration(),[2,[c]];case 8:throw TypeError("Node type "+e.op+" is not implemented")}})})}function executeOp$13(e,t,r){switch(e.category){case"arithmetic":return executeOp(e,t,r);case"basic_math":return executeOp$1(e,t,r);case"control":return executeOp$2(e,t,r);case"convolution":return executeOp$3(e,t,r);case"creation":return executeOp$4(e,t,r);case"image":return executeOp$6(e,t,r);case"graph":return executeOp$5(e,t,r);case"logical":return executeOp$7(e,t,r);case"matrices":return executeOp$8(e,t,r);case"normalization":return executeOp$9(e,t,r);case"reduction":return executeOp$10(e,t,r);case"slice_join":return executeOp$11(e,t,r);case"transformation":return 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= to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+t+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+n+".0;\n\n          if (dyR < 0.0 || dyR >= "+e.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < "+r+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+a+".0;\n\n            if (dyC < 0.0 || dyC >= "+e.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n\n            dotProd += dyValue * avgMultiplier;\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}}(),BatchNormProgram=function(){return function(e,t,r,n,a,o){this.outputShape=[],this.supportsBroadcasting=!0,this.variableNames=["x","mean","variance"],assertAndGetBroadcastShape(e,t),assertAndGetBroadcastShape(e,r);var i="0.0";null!=n&&(assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");var s="1.0";null!=a&&(assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),s="getScaleAtOutCoords()"),this.outputShape=e,this.userCode="\n      void main() {\n        float x = getXAtOutCoords();\n        float mean = getMeanAtOutCoords();\n        float variance = getVarianceAtOutCoords();\n        float offset = "+i+";\n        float scale = "+s+";\n        float inv = scale * inversesqrt(variance + float("+o+"));\n        setOutput((x - mean) * inv + offset);\n      }\n    "}}(),CHECK_NAN_SNIPPET="\n  if (isNaN(a)) return a;\n  if (isNaN(b)) return b;\n",ADD="return a + b;",SUB="return a - b;",MUL="return a * b;",DIV="return a / b;",INT_DIV="\n  float resultSign = sign(a) * sign(b);\n  int ia = round(a);\n  int ib = round(b);\n  int result = ia / ib;\n  int amodb = ia - ib * result;\n\n  if (resultSign < 0.0 && amodb != 0) {\n    result -= 1;\n  }\n  return float(result);\n",POW="\n  return (round(mod(b, 2.0)) == 0 || round(mod(b, 2.0)) == 2) ?\n      pow(abs(a), b) : sign(a) * pow(abs(a), b);\n",SQUARED_DIFFERENCE="return (a - b) * (a - b);",EQUAL="return float(a == b);",NOT_EQUAL="return float(a != b);",LESS="return float(a < b);",LESS_EQUAL="return float(a <= b);",GREATER="return float(a > b);",GREATER_EQUAL="return float(a >= b);",LOGICAL_AND="return float(a >= 1.0 && b >= 1.0);",LOGICAL_OR="return float(a >= 1.0 || b >= 1.0);",MAX=CHECK_NAN_SNIPPET+"\n  return max(a, b);\n",MIN=CHECK_NAN_SNIPPET+"\n  return min(a, b);\n",MOD="return mod(a, b);",ATAN2=CHECK_NAN_SNIPPET+"\n  return atan(a, b);\n",ELU_DER="return (b >= 1.0) ? a : a * (b + 1.0);",BinaryOpProgram=function(){return function(e,t,r){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.outputShape=assertAndGetBroadcastShape(t,r),this.userCode="\n      float binaryOperation(float a, float b) {\n        "+e+"\n      }\n\n      void main() {\n        float a = getAAtOutCoords();\n        float b = getBAtOutCoords();\n        setOutput(binaryOperation(a, b));\n      }\n    "}}(),ClipProgram=function(){return function(e,t,r){this.variableNames=["A"],this.outputShape=e;var n=t.toFixed(20),a=r.toFixed(20);this.userCode="\n      void main() {\n        float value = getAAtOutCoords();\n        if (isNaN(value)) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, "+n+", "+a+"));\n      }\n    "}}(),ConcatProgram=function(){return function(e,t){this.variableNames=["A","B"],this.outputShape=[],this.outputShape=computeOutShape(e,t,1),this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int yR = coords.x;\n        int yC = coords.y;\n\n        float value = 0.0;\n        if (yC < "+e[1]+") {\n          value = getA(yR, yC);\n        } else {\n          yC -= "+e[1]+";\n          value = getB(yR, yC);\n        }\n\n        setOutput(value);\n      }\n    "}}(),Conv2DDerFilterProgram=function(){return function(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;var t=e.strideHeight,r=e.strideWidth,n=e.padInfo.top,a=e.padInfo.left;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int d2 = coords.w;\n\n        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int b = 0; b < "+e.batchSize+"; b++) {\n          for (int yR = 0; yR < "+e.outHeight+"; yR++) {\n            int xR = wR + yR * "+t+" - "+n+";\n\n            if (xR < 0 || xR >= "+e.inHeight+") {\n              continue;\n            }\n\n            for (int yC = 0; yC < "+e.outWidth+"; yC++) {\n              int xC = wC + yC * "+r+" - "+a+";\n\n              if (xC < 0 || xC >= "+e.inWidth+") {\n                continue;\n              }\n\n              float dyValue = getDy(b, yR, yC, d2);\n              float xValue = getX(b, xR, xC, d1);\n              dotProd += (xValue * dyValue);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}}(),Conv2DDerInputProgram=function(){return function(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;var t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,a=e.strideWidth,o=t-1-e.padInfo.top,i=r-1-e.padInfo.left;this.userCode="\n      const ivec2 pads = ivec2("+o+", "+i+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[3];\n\n        ivec2 dyCorner = coords.yz - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+t+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+n+".0;\n\n          if (dyR < 0.0 || dyR >= "+e.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = "+t+" - 1 - wR;\n\n          for (int wC = 0; wC < "+r+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+a+".0;\n\n            if (dyC < 0.0 || dyC >= "+e.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = "+r+" - 1 - wC;\n\n            for (int d2 = 0; d2 < "+e.outChannels+"; d2++) {\n              float xValue = getDy(batch, idyR, idyC, d2);\n              float wValue = getW(wRPerm, wCPerm, d1, d2);\n              dotProd += xValue * wValue;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}}(),DepthwiseConv2DDerFilterProgram=function(){return function(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;var t=e.strideHeight,r=e.strideWidth,n=e.padInfo.top,a=e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int dm = coords.w;\n        int d2 = d1 * "+o+" + dm;\n\n        float dotProd = 0.0;\n\n        // TODO: Vec4 over the batch size\n        for (int b = 0; b < "+e.batchSize+"; b++) {\n          for (int yR = 0; yR < "+e.outHeight+"; yR++) {\n            int xR = wR + yR * "+t+" - "+n+";\n\n            if (xR < 0 || xR >= "+e.inHeight+") {\n              continue;\n            }\n\n            for (int yC = 0; yC < "+e.outWidth+"; yC++) {\n              int xC = wC + yC * "+r+" - "+a+";\n\n              if (xC < 0 || xC >= "+e.inWidth+") {\n                continue;\n              }\n\n              float dyValue = getDy(b, yR, yC, d2);\n              float xValue = getX(b, xR, xC, d1);\n              dotProd += (xValue * dyValue);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}}(),DepthwiseConv2DDerInputProgram=function(){return function(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;var t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,a=e.strideWidth,o=t-1-e.padInfo.top,i=r-1-e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode="\n      const ivec2 pads = ivec2("+o+", "+i+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[3];\n        ivec2 dyCorner = coords.yz - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        float dotProd = 0.0;\n\n        for (int wR = 0; wR < "+t+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+n+".0;\n\n          if (dyR < 0.0 || dyR >= "+e.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = "+t+" - 1 - wR;\n\n          for (int wC = 0; wC < "+r+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+a+".0;\n\n            if (dyC < 0.0 || dyC >= "+e.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = "+r+" - 1 - wC;\n\n            // TODO: Vec4 over the channelMul\n            for (int dm = 0; dm < "+s+"; dm++) {\n              int d2 = d1 * "+s+" + dm;\n              float xValue = getDy(batch, idyR, idyC, d2);\n              float wValue = getW(wRPerm, wCPerm, d1, dm);\n              dotProd += xValue * wValue;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}}(),Conv2DProgram=function(){return function(e){this.variableNames=["x","W"],this.outputShape=e.outShape;var t=e.padInfo.top,r=e.padInfo.left,n=e.strideHeight,a=e.strideWidth,o=e.dilationHeight,i=e.dilationWidth,s=e.filterHeight,u=e.filterWidth,l=4*Math.floor(e.inChannels/4),c=e.inChannels%4;this.userCode="\n      const ivec2 strides = ivec2("+n+", "+a+");\n      const ivec2 pads = ivec2("+t+", "+r+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d2 = coords[3];\n\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+s+"; wR++) {\n          int xR = xRCorner + wR * "+o+";\n\n          if (xR < 0 || xR >= "+e.inHeight+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+u+"; wC++) {\n            int xC = xCCorner + wC * "+i+";\n\n            if (xC < 0 || xC >= "+e.inWidth+") {\n              continue;\n            }\n\n            for (int d1 = 0; d1 < "+l+"; d1 += 4) {\n              vec4 xValues = vec4(\n                getX(batch, xR, xC, d1),\n                getX(batch, xR, xC, d1 + 1),\n                getX(batch, xR, xC, d1 + 2),\n                getX(batch, xR, xC, d1 + 3)\n              );\n              vec4 wValues = vec4(\n                getW(wR, wC, d1, d2),\n                getW(wR, wC, d1 + 1, d2),\n                getW(wR, wC, d1 + 2, d2),\n                getW(wR, wC, d1 + 3, d2)\n              );\n\n              dotProd += dot(xValues, wValues);\n            }\n\n            if ("+(1===c)+") {\n              dotProd +=\n                getX(batch, xR, xC, "+l+") *\n                getW(wR, wC, "+l+", d2);\n            } else if ("+(2===c)+") {\n              vec2 xValues = vec2(\n                getX(batch, xR, xC, "+l+"),\n                getX(batch, xR, xC, "+l+" + 1)\n              );\n              vec2 wValues = vec2(\n                getW(wR, wC, "+l+", d2),\n                getW(wR, wC, "+l+" + 1, d2)\n              );\n              dotProd += dot(xValues, wValues);\n            } else if ("+(3===c)+") {\n              vec3 xValues = vec3(\n                getX(batch, xR, xC, "+l+"),\n                getX(batch, xR, xC, "+l+" + 1),\n                getX(batch, xR, xC, "+l+" + 2)\n              );\n              vec3 wValues = vec3(\n                getW(wR, wC, "+l+", d2),\n                getW(wR, wC, "+l+" + 1, d2),\n                getW(wR, wC, "+l+" + 2, d2)\n              );\n              dotProd += dot(xValues, wValues);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}}(),DepthwiseConv2DProgram=function(){return function(e){this.variableNames=["x","W"],this.outputShape=e.outShape;var t=e.inHeight,r=e.inWidth,n=e.padInfo.top,a=e.padInfo.left,o=e.strideHeight,i=e.strideWidth,s=e.dilationHeight,u=e.dilationWidth,l=e.filterHeight,c=e.filterWidth,p=e.outChannels/e.inChannels;this.userCode="\n      const ivec2 strides = ivec2("+o+", "+i+");\n      const ivec2 pads = ivec2("+n+", "+a+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / "+p+";\n        int q = d2 - d1 * "+p+";\n\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        // TODO(dsmilkov): Flatten the two for loops and vec4 the operations.\n        for (int wR = 0; wR < "+l+"; wR++) {\n          int xR = xRCorner + wR * "+s+";\n\n          if (xR < 0 || xR >= "+t+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+c+"; wC++) {\n            int xC = xCCorner + wC * "+u+";\n\n            if (xC < 0 || xC >= "+r+") {\n              continue;\n            }\n\n            float xVal = getX(batch, xR, xC, d1);\n            float wVal = getW(wR, wC, d1, q);\n            dotProd += xVal * wVal;\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}}(),TextureType;!function(e){e[e.FLOAT=0]="FLOAT",e[e.UNSIGNED_BYTE=1]="UNSIGNED_BYTE"}(TextureType||(TextureType={}));var FLOAT_MAX=2e4,FLOAT_MIN=-FLOAT_MAX,FLOAT_RANGE=(FLOAT_MAX-FLOAT_MIN)/255,FLOAT_DELTAS=[1,1/255,1/65025,1/16581375],FLOAT_POWERS=[1,255,65025],BYTE_NAN_VALUE=0,SAMPLE_1D_SNIPPET="\nvec2 UVfrom1D(int texNumR, int texNumC, int index) {\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",SAMPLE_2D_SNIPPET="\nvec2 UVfrom2D(int texNumR, int texNumC, int numC, int row, int col) {\n  int index = row * numC + col;\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",SAMPLE_3D_SNIPPET="\nvec2 UVfrom3D(int texNumR, int texNumC, int stride0,\n    int stride1, int row, int col, int depth) {\n  // Explicitly use integer operations as dot() only works on floats.\n  int index = row * stride0 + col * stride1 + depth;\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",SAMPLE_4D_SNIPPET="\nvec2 UVfrom4D(int texNumR, int texNumC, int stride0,\n    int stride1, int stride2, int row, int col, int depth,\n    int depth2) {\n  // Explicitly use integer operations as dot() only works on floats.\n  int index = row * stride0 + col * stride1 + depth * stride2 + depth2;\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",SAMPLE_5D_SNIPPET="\nvec2 UVfrom5D(int texNumR, int texNumC, int stride0,\n    int stride1, int stride2, int stride3, int row, int col, int depth,\n    int depth2, int depth3) {\n  // Explicitly use integer operations as dot() only works on floats.\n  int index = row * stride0 + col * stride1 + \n              depth * stride2 + depth2 * stride3 + depth3;\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n",UNSIGNED_BYTE_TEXTURE_SAMPLE_SNIPPET="\n  uniform float NaN;\n\n  const vec4 floatDeltas = vec4(\n      1.0,\n      1.0 / 255.0,\n      1.0 / (255.0 * 255.0),\n      1.0 / (255.0 * 255.0 * 255.0)\n  );\n  const float minValue = "+FLOAT_MIN+".0;\n  const float maxValue = "+FLOAT_MAX+".0;\n  const float range = (maxValue - minValue) / 255.0;\n  const vec2 dotRange = vec2(1.0, range);\n\n  float sampleTexture(sampler2D textureSampler, vec2 uv) {\n    vec4 sampleValue = texture2D(textureSampler, uv);\n    if (all(equal(sampleValue, vec4("+BYTE_NAN_VALUE+")))) {\n      return NaN;\n    }\n\n    vec4 encValue = floor(sampleValue * 255.0 + 0.5);\n    float decodedValue = dot(encValue, floatDeltas);\n    return dot(vec2(minValue, decodedValue), dotRange);\n  }\n",UNSIGNED_BYTE_TEXTURE_SETOUTPUT_SNIPPET="\n  const vec4 floatPowers = vec4(\n    1.0,\n    255.0,\n    255.0 * 255.0,\n    255.0 * 255.0 * 255.0\n  );\n  const vec2 recipRange = vec2(1.0/range);\n  const vec2 recipRange255 = vec2(1.0/(maxValue - minValue));\n\n  void setOutput(float decodedValue) {\n    if (isNaN(decodedValue)) {\n      gl_FragColor = vec4("+BYTE_NAN_VALUE+");\n      return;\n    }\n\n    float a = dot(vec2(decodedValue, -minValue), recipRange);\n    float b = fract(a) * 255.0;\n    float c = fract(b) * 255.0;\n    float d = fract(c) * 255.0;\n    gl_FragColor = floor(vec4(a, b, c, d)) / 255.0;\n\n    // TODO(dsmilkov): Version above gets better accuracy but probably slower\n    // than the version below. Benchmark to determine if the accuracy is worth\n    // the cost.\n\n    // float normValue = dot(vec2(decodedValue, -minValue), recipRange255);\n    // vec4 f = normValue * floatPowers;\n    // gl_FragColor = floor(fract(f) * 255.0) / 255.0;\n  }\n",FLOAT_TEXTURE_SAMPLE_SNIPPET="\n  float sampleTexture(sampler2D textureSampler, vec2 uv) {\n    return texture2D(textureSampler, uv).r;\n  }\n",FLOAT_TEXTURE_SETOUTPUT_SNIPPET="\n  void setOutput(float val) {\n    gl_FragColor = vec4(val, 0, 0, 0);\n  }\n",SHADER_PREFIX="\n  precision highp float;\n  precision highp int;\n  varying vec2 resultUV;\n  const vec2 halfCR = vec2(0.5, 0.5);\n\n  struct ivec5\n  {\n    int x;\n    int y;\n    int z;\n    int w;\n    int u;\n  };\n\n  bool isNaN(float val) {\n    float v1 = val * val;\n    float v2 = val * val;\n    return v1 == v2 ? false : true;\n  }\n\n  bool hasNaN(vec4 values) {\n    vec4 v1 = values * values;\n    vec4 v2 = values * values;\n    return any(notEqual(v1, v2));\n  }\n\n  float getNaN(vec4 values) {\n    return dot(vec4(1), values);\n  }\n\n  int round(float value) {\n    return int(floor(value + 0.5));\n  }\n\n  int imod(int x, int y) {\n    return x - y * (x / y);\n  }\n\n  //Based on the work of Dave Hoskins\n  //https://www.shadertoy.com/view/4djSRW\n  #define HASHSCALE1 443.8975\n  float random(float seed){\n    vec2 p = resultUV * seed;\n    vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);\n    p3 += dot(p3, p3.yzx + 19.19);\n    return fract((p3.x + p3.y) * p3.z);\n  }\n\n  "+SAMPLE_1D_SNIPPET+"\n  "+SAMPLE_2D_SNIPPET+"\n  "+SAMPLE_3D_SNIPPET+"\n  "+SAMPLE_4D_SNIPPET+"\n  "+SAMPLE_5D_SNIPPET+"\n",CumSumProgram=function(){return function(e,t,r){this.variableNames=["x"],this.outputShape=e;var n=e.length,a=e[e.length-1],o=r?"<":">";this.userCode="\n      int getIndex(int i) {\n        "+(r?"return "+a+" -i - 1;":"return i;")+"\n      }\n\n      void main() {\n        "+getCoordsDataType(n)+" coords = getOutputCoords();\n        int end = "+getFinalCoord(n,"coords")+";\n        float val = 0.0;\n        for (int i = "+a+" - 1; i >= 0; i -= 1) {\n          int idx = getIndex(i);\n          if (idx "+o+" end) {\n            continue;\n          }\n          if (idx == end && "+t+") {\n            continue;\n          }\n          "+getFinalCoord(n,"coords")+" = idx;\n          val += getX("+getCoords(n,"coords")+");\n        }\n        setOutput(val);\n      }\n    "}}(),FromPixelsProgram=function(){return function(e){this.variableNames=["A"];var t=e[0],r=e[1];this.outputShape=e,this.userCode="\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n        vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+r+".0, "+t+".0);\n\n        vec4 values = texture2D(A, uv);\n        float value;\n        if (depth == 0) {\n          value = values.r;\n        } else if (depth == 1) {\n          value = values.g;\n        } else if (depth == 2) {\n          value = values.b;\n        } else if (depth == 3) {\n          value = values.a;\n        }\n\n        setOutput(floor(value * 255.0 + 0.5));\n      }\n    "}}(),GatherProgram=function(){return function(e,t,r){this.variableNames=["A","indices"];var n=e.slice();n[r]=t,this.outputShape=n,this.rank=n.length;var a=getCoordsDataType(this.rank),o=getSourceCoords(e,r);this.userCode="\n      void main() {\n        "+a+" resRC = getOutputCoords();\n        setOutput(getA("+o+"));\n      }\n    "}}(),MAX_TEXTURE_SIZE=null,webGLDebugErrorCheckingEnabled=!1,lineNumberRegex=/ERROR: 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e(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.autoDebugValidate=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[],this.gl=null!=e?e:createWebGLContext(),1===ENV.get("WEBGL_VERSION")?(this.textureFloatExtension=getExtensionOrThrow(this.gl,"OES_texture_float"),this.colorBufferFloatExtension=this.gl.getExtension("WEBGL_color_buffer_float")):this.colorBufferFloatExtension=getExtensionOrThrow(this.gl,"EXT_color_buffer_float"),this.loseContextExtension=getExtensionOrThrow(this.gl,"WEBGL_lose_context"),ENV.get("WEBGL_GET_BUFFER_SUB_DATA_ASYNC_EXTENSION_ENABLED")&&(this.getBufferSubDataAsyncExtension=this.gl.getExtension("WEBGL_get_buffer_sub_data_async")),this.vertexBuffer=createVertexBuffer(this.gl),this.indexBuffer=createIndexBuffer(this.gl),this.framebuffer=createFramebuffer(this.gl)}return e.prototype.dispose=function(){var e=this;if(!this.disposed){null!=this.program&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),null!=this.outputTexture&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");var t=this.gl;callAndCheck(t,function(){return t.finish()}),callAndCheck(t,function(){return t.bindFramebuffer(t.FRAMEBUFFER,null)}),callAndCheck(t,function(){return t.deleteFramebuffer(e.framebuffer)}),callAndCheck(t,function(){return t.bindBuffer(t.ARRAY_BUFFER,null)}),callAndCheck(t,function(){return t.deleteBuffer(e.vertexBuffer)}),callAndCheck(t,function(){return t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,null)}),callAndCheck(t,function(){return t.deleteBuffer(e.indexBuffer)}),this.loseContextExtension.loseContext(),this.disposed=!0}},e.prototype.enableAutomaticDebugValidation=function(e){this.autoDebugValidate=e,enableDebugWebGLErrorChecking(e)},e.prototype.createMatrixTexture=function(e,t){return this.throwIfDisposed(),createMatrixTexture(this.gl,e,t)},e.prototype.uploadPixelDataToTexture=function(e,t){this.throwIfDisposed(),uploadPixelDataToTexture(this.gl,e,t)},e.prototype.createPackedMatrixTexture=function(e,t){return this.throwIfDisposed(),createPackedMatrixTexture(this.gl,e,t)},e.prototype.deleteMatrixTexture=function(e){var t=this;this.throwIfDisposed(),this.outputTexture===e&&(unbindColorTextureFromFramebuffer(this.gl,this.framebuffer),this.outputTexture=null),callAndCheck(this.gl,function(){return t.gl.deleteTexture(e)})},e.prototype.uploadMatrixToTexture=function(e,t,r,n){this.throwIfDisposed();return uploadMatrixToTexture(this.gl,e,t,r,n,1)},e.prototype.uploadMatrixToPackedTexture=function(e,t,r,n){return this.throwIfDisposed(),uploadMatrixToPackedTexture(this.gl,e,t,r,n)},e.prototype.downloadMatrixFromTexture=function(e,t,r){var n=this;return this.downloadMatrixDriver(e,function(){return downloadMatrixFromOutputTexture(n.gl,t,r)})},e.prototype.downloadMatrixFromTextureAsync=function(e,t,r){return __awaiter$4(this,void 0,void 0,function(){var n=this;return __generator$4(this,function(a){if(null==this.getBufferSubDataAsyncExtension)throw new Error("Cannot download matrix from output texture asynchronously, WEBGL_get_buffer_sub_data_async is not enabled.");return[2,this.downloadMatrixDriverAsync(e,function(){return downloadMatrixFromOutputTextureAsync(n.gl,n.getBufferSubDataAsyncExtension,t,r)})]})})},e.prototype.downloadMatrixFromRGBAColorTexture=function(e,t,r,n){var a=this;return this.downloadMatrixDriver(e,function(){return downloadMatrixFromRGBAColorTexture(a.gl,t,r,n)})},e.prototype.downloadMatrixFromPackedTexture=function(e,t,r){var n=this;return this.downloadMatrixDriver(e,function(){return downloadMatrixFromPackedOutputTexture(n.gl,t,r)})},e.prototype.createProgram=function(e){this.throwIfDisposed();var t=this.gl,r=createFragmentShader(t,e),n=createVertexShader$1(t),a=createProgram(t);return callAndCheck(t,function(){return t.attachShader(a,n)}),callAndCheck(t,function(){return t.attachShader(a,r)}),linkProgram(t,a),this.autoDebugValidate&&validateProgram(t,a),this.vertexAttrsAreBound||(this.setProgram(a),this.vertexAttrsAreBound=bindVertexProgramAttributeStreams(t,this.program,this.vertexBuffer)),a},e.prototype.deleteProgram=function(e){var t=this;this.throwIfDisposed(),e===this.program&&(this.program=null),null!=e&&callAndCheck(this.gl,function(){return t.gl.deleteProgram(e)})},e.prototype.setProgram=function(e){var t=this;this.throwIfDisposed(),this.program=e,null!=this.program&&this.autoDebugValidate&&validateProgram(this.gl,this.program),callAndCheck(this.gl,function(){return t.gl.useProgram(e)})},e.prototype.getUniformLocation=function(e,t,r){return void 0===r&&(r=!0),this.throwIfDisposed(),r?getProgramUniformLocationOrThrow(this.gl,e,t):getProgramUniformLocation(this.gl,e,t)},e.prototype.getAttributeLocation=function(e,t){var r=this;return this.throwIfDisposed(),callAndCheck(this.gl,function(){return r.gl.getAttribLocation(e,t)})},e.prototype.getUniformLocationNoThrow=function(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)},e.prototype.setInputMatrixTexture=function(e,t,r){this.throwIfDisposed(),this.throwIfNoProgram(),bindTextureToProgramUniformSampler(this.gl,this.program,e,t,r)},e.prototype.setOutputMatrixTexture=function(e,t,r){this.setOutputMatrixTextureDriver(e,r,t)},e.prototype.setOutputPackedMatrixTexture=function(e,t,r){this.throwIfDisposed();var n=getPackedMatrixTextureShapeWidthHeight(t,r),a=n[0],o=n[1];this.setOutputMatrixTextureDriver(e,a,o)},e.prototype.setOutputMatrixWriteRegion=function(e,t,r,n){this.setOutputMatrixWriteRegionDriver(r,e,n,t)},e.prototype.setOutputPackedMatrixWriteRegion=function(e,t,r,n){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")},e.prototype.debugValidate=function(){null!=this.program&&validateProgram(this.gl,this.program),validateFramebuffer(this.gl)},e.prototype.executeProgram=function(){this.throwIfDisposed(),this.throwIfNoProgram();var e=this.gl;this.autoDebugValidate&&this.debugValidate(),callAndCheck(e,function(){return e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0)})},e.prototype.blockUntilAllProgramsCompleted=function(){var e=this;this.throwIfDisposed(),callAndCheck(this.gl,function(){return e.gl.finish()})},e.prototype.getQueryTimerExtension=function(){return null==this.disjointQueryTimerExtension&&(this.disjointQueryTimerExtension=getExtensionOrThrow(this.gl,2===ENV.get("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension},e.prototype.getQueryTimerExtensionWebGL2=function(){return this.getQueryTimerExtension()},e.prototype.getQueryTimerExtensionWebGL1=function(){return this.getQueryTimerExtension()},e.prototype.runQuery=function(e){var t=this.beginQuery();return e(),this.endQuery(),this.pollQueryTime(t)},e.prototype.beginQuery=function(){if(2===ENV.get("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){var e=this.gl,t=this.getQueryTimerExtensionWebGL2(),r=e.createQuery();return e.beginQuery(t.TIME_ELAPSED_EXT,r),r}var n=this.getQueryTimerExtensionWebGL1(),a=n.createQueryEXT();return n.beginQueryEXT(n.TIME_ELAPSED_EXT,a),a},e.prototype.endQuery=function(){if(2!==ENV.get("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){var e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}else{var t=this.gl,r=this.getQueryTimerExtensionWebGL2();t.endQuery(r.TIME_ELAPSED_EXT)}},e.prototype.isQueryAvailable=function(e,t){if(0===t)return!0;if(2===t){var r=this.gl,n=this.getQueryTimerExtensionWebGL2(),a=r.getQueryParameter(e,r.QUERY_RESULT_AVAILABLE);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),a&&!this.disjoint}a=(n=this.getQueryTimerExtensionWebGL1()).getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),a&&!this.disjoint},e.prototype.pollQueryTime=function(e){var t=this;return new Promise(function(r){var n=ENV.get("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION");t.addItemToPoll(function(){return t.isQueryAvailable(e,n)},function(){return r(t.getQueryTime(e,n))})})},e.prototype.pollItems=function(){for(var e=binSearchLastTrue(this.itemsToPoll.map(function(e){return e.isDoneFn})),t=0;t<=e;++t)(0,this.itemsToPoll[t].resolveFn)();this.itemsToPoll=this.itemsToPoll.slice(e+1)},e.prototype.addItemToPoll=function(e,t){var r=this;this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),this.itemsToPoll.length>1||repeatedTry(function(){return r.pollItems(),0===r.itemsToPoll.length})},e.prototype.getQueryTime=function(e,t){if(0===t)return null;if(2===t){var r=this.gl;return(a=r.getQueryParameter(e,r.QUERY_RESULT))/1e6}var n=this.getQueryTimerExtensionWebGL1(),a=n.getQueryObjectEXT(e,n.QUERY_RESULT_EXT);return a/1e6},e.prototype.downloadMatrixDriverSetup=function(e){this.throwIfDisposed(),bindColorTextureToFramebuffer(this.gl,e,this.framebuffer),this.autoDebugValidate&&validateFramebuffer(this.gl)},e.prototype.downloadMatrixDriverTeardown=function(){null!=this.outputTexture?(bindColorTextureToFramebuffer(this.gl,this.outputTexture,this.framebuffer),this.autoDebugValidate&&validateFramebuffer(this.gl)):unbindColorTextureFromFramebuffer(this.gl,this.framebuffer)},e.prototype.downloadMatrixDriver=function(e,t){this.downloadMatrixDriverSetup(e);var r=t();return this.downloadMatrixDriverTeardown(),r},e.prototype.downloadMatrixDriverAsync=function(e,t){return __awaiter$4(this,void 0,void 0,function(){var r;return __generator$4(this,function(n){switch(n.label){case 0:return this.downloadMatrixDriverSetup(e),[4,t()];case 1:return r=n.sent(),this.downloadMatrixDriverTeardown(),[2,r]}})})},e.prototype.setOutputMatrixTextureDriver=function(e,t,r){this.throwIfDisposed();var n=this.gl;bindColorTextureToFramebuffer(n,e,this.framebuffer),this.autoDebugValidate&&validateFramebuffer(n),this.outputTexture=e,callAndCheck(n,function(){return n.viewport(0,0,t,r)}),callAndCheck(n,function(){return n.scissor(0,0,t,r)})},e.prototype.setOutputMatrixWriteRegionDriver=function(e,t,r,n){var a=this;this.throwIfDisposed(),callAndCheck(this.gl,function(){return a.gl.scissor(e,t,r,n)})},e.prototype.throwIfDisposed=function(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")},e.prototype.throwIfNoProgram=function(){if(null==this.program)throw new Error("No GPU program is currently set.")},e}(),NAN_UNIFORM_NAME="NaN",WhereProgram=function(){return function(e,t,r){this.variableNames=["c","a","b"],this.outputShape=t;var n,a;if(r>4)throw Error("Where for rank "+r+" is not yet supported");if(1===r)a="resRC",n="resRC";else{for(var o=["resRC.x","resRC.y","resRC.z","resRC.w"],i=[],s=[],u=0;u<t.length;u++)s.push(""+o[u]),u<e&&i.push(""+o[u]);n=i.join(),a=s.join()}var l=getCoordsDataType(r);this.userCode="\n      void main() {\n        "+l+" resRC = getOutputCoords();\n        float cVal = getC("+n+");\n        if (cVal >= 1.0) {\n          setOutput(getA("+a+"));\n        } else {\n          setOutput(getB("+a+"));\n        }\n      }\n    "}}(),LRNProgram=function(){return function(e,t,r,n,a){this.variableNames=["x"],this.outputShape=[];var o=t,i=e[3]-1;this.outputShape=e;var s,u="float("+r+") + float("+n+") * sum";s=.5===a?"inversesqrt("+u+")":1===a?"1.0/("+u+")":"exp(log("+u+") * float(-"+a+"));",this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n        int d = coords[3];\n        float x = getX(b, r, c, d);\n        float sum = 0.0;\n        for (int j = -"+o+"; j <= "+o+"; j++) {\n          int idx = d + j;\n          if (idx >= 0 && idx <=  "+i+") {\n            float z = getX(b, r, c, idx);\n            sum += z * z;\n          }\n        }\n        float val = x * "+s+";\n        setOutput(val);\n      }\n    "}}(),MaxPool2DBackpropProgram=function(){return function(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;var t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,a=e.strideWidth,o=t-1-e.padInfo.top,i=r-1-e.padInfo.left,s=t*r-1;this.userCode="\n      const ivec2 pads = ivec2("+o+", "+i+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+t+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+n+".0;\n\n          if (dyR < 0.0 || dyR >= "+e.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < "+r+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+a+".0;\n\n            if (dyC < 0.0 || dyC >= "+e.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n            int maxPosValue = "+s+" - int(getMaxPos(b, idyR, idyC, d));\n\n            // Get the current value, check it against the value from the\n            // position matrix.\n            int curPosValue = wR * "+r+" + wC;\n            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n            dotProd += dyValue * mask;\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}}(),MatMulProgram=function(){return function(e,t,r,n){void 0===r&&(r=!1),void 0===n&&(n=!1),this.variableNames=["matrixA","matrixB"];var a=r?e[1]:e[0],o=n?t[0]:t[1],i=r?e[0]:e[1];this.outputShape=[a,o];var s=function(e,t){return r?t+" + "+e+", aRow":"aRow, "+t+" + "+e},u=function(e,t){return n?"bCol, "+t+" + "+e:t+" + "+e+", bCol"},l=4*Math.floor(i/4),c=i%4;this.userCode=" float dotARowBCol(int aRow, int bCol) {\n      float result = 0.0;\n      for (int i = 0; i < "+l+"; i += 4) {\n        vec4 a = vec4(\n          getMatrixA("+s(0,"i")+"),\n          getMatrixA("+s(1,"i")+"),\n          getMatrixA("+s(2,"i")+"),\n          getMatrixA("+s(3,"i")+")\n        );\n        vec4 b = vec4(\n          getMatrixB("+u(0,"i")+"),\n          getMatrixB("+u(1,"i")+"),\n          getMatrixB("+u(2,"i")+"),\n          getMatrixB("+u(3,"i")+")\n        );\n\n        result += dot(a, b);\n      }\n\n      if ("+(1===c)+") {\n        result += getMatrixA("+s(0,l)+") *\n          getMatrixB("+u(0,l)+");\n      } else if ("+(2===c)+") {\n        vec2 a = vec2(\n          getMatrixA("+s(0,l)+"),\n          getMatrixA("+s(1,l)+")\n        );\n        vec2 b = vec2(\n          getMatrixB("+u(0,l)+"),\n          getMatrixB("+u(1,l)+")\n        );\n        result += dot(a, b);\n      } else if ("+(3===c)+") {\n        vec3 a = vec3(\n          getMatrixA("+s(0,l)+"),\n          getMatrixA("+s(1,l)+"),\n          getMatrixA("+s(2,l)+")\n        );\n        vec3 b = vec3(\n          getMatrixB("+u(0,l)+"),\n          getMatrixB("+u(1,l)+"),\n          getMatrixB("+u(2,l)+")\n        );\n        result += dot(a, b);\n      }\n\n      return result;\n    }\n\n    void main() {\n      ivec2 resRC = getOutputCoords();\n      setOutput(dotARowBCol(resRC.x, resRC.y));\n    }\n    "}}(),MultinomialProgram=function(){function e(e,t,r){this.variableNames=["probs"],this.outputShape=[e,r],this.userCode="\n      uniform float seed;\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n\n        float r = random(seed);\n        float cdf = 0.0;\n\n        for (int i = 0; i < "+(t-1)+"; i++) {\n          cdf += getProbs(batch, i);\n\n          if (r < cdf) {\n            setOutput(float(i));\n            return;\n          }\n        }\n\n        // If no other event happened, last event happened.\n        setOutput(float("+(t-1)+"));\n      }\n    "}return e.prototype.getCustomSetupFunc=function(e){var t=this;return function(r,n){null==t.seedLoc&&(t.seedLoc=r.getUniformLocation(n,"seed")),r.gl.uniform1f(t.seedLoc,e)}},e}(),OneHotProgram=function(){return function(e,t,r,n){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int index = round(getIndices(coords.x));\n        setOutput(mix(float("+n+"), float("+r+"),\n                      float(index == coords.y)));\n      }\n    "}}(),PadProgram=function(){return function(e,t,r){this.variableNames=["x"],this.outputShape=t.map(function(t,r){return t[0]+e[r]+t[1]});var n=e.length,a=getCoordsDataType(n),o=t.map(function(e){return e[0]}).join(","),i=t.map(function(t,r){return t[0]+e[r]}).join(","),s=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n);this.userCode=1!==n?"\n      "+a+" start = "+a+"("+o+");\n      "+a+" end = "+a+"("+i+");\n\n      void main() {\n        "+a+" outC = getOutputCoords();\n        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\n          setOutput(float("+r+"));\n        } else {\n          "+a+" coords = outC - start;\n          setOutput(getX("+s+"));\n        }\n      }\n    ":"\n        int start = "+o+";\n        int end = "+i+";\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start || outC >= end) {\n            setOutput(float("+r+"));\n          } else {\n            setOutput(getX(outC - start));\n          }\n        }\n      "}}(),Pool2DProgram=function(){return function(e,t,r){if(this.variableNames=["x"],"avg"===t&&r)throw new Error("Cannot compute positions for average pool.");var n=e.filterHeight,a=e.filterWidth,o=e.strideHeight,i=e.strideWidth,s=e.padInfo.top,u=e.padInfo.left;this.outputShape=e.outShape;var l="avg"===t,c="0.0";if(l||(c="-1.0 / 0.0"),r)this.userCode="\n        const ivec2 strides = ivec2("+o+", "+i+");\n        const ivec2 pads = ivec2("+s+", "+u+");\n\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int batch = coords[0];\n          int d = coords[3];\n\n          ivec2 xRCCorner = coords.yz * strides - pads;\n          int xRCorner = xRCCorner.x;\n          int xCCorner = xRCCorner.y;\n\n          // max/min x(?, ?, d) to get y(yR, yC, d).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n          float avgValue = 0.0;\n\n          for (int wR = 0; wR < "+n+"; wR++) {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= "+e.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+a+"; wC++) {\n              int xC = xCCorner + wC;\n\n              if (xC < 0 || xC >= "+e.inWidth+") {\n                continue;\n              }\n\n              float value = getX(batch, xR, xC, d);\n\n              // If a min / max value has already been found, use it. If not,\n              // use the current value.\n              float currMinMaxValue = mix(\n                  value, minMaxValue, minMaxValueFound);\n              if (value >= currMinMaxValue) {\n                minMaxValue = value;\n                minMaxValueFound = 1.0;\n                minMaxPosition = wR * "+a+" + wC;\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      ";else{var p=t+"("+t+"("+t+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===t&&(p="avgValue / count");var d=4*Math.floor(a/4),h=a%4,f="\n      if ("+l+") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = max(values, minMaxValue);\n      }\n    ";this.userCode="\n      const ivec2 strides = ivec2("+o+", "+i+");\n      const ivec2 pads = ivec2("+s+", "+u+");\n      const float initializationValue = "+c+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xR, int xC, int d) {\n        if (xC < 0 || xC >= "+e.inWidth+") {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xR, xC, d);\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d = coords[3];\n\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // max/min x(?, ?, d) to get y(yR, yC, d).\n        // ? = to be determined\n        vec4 minMaxValue = vec4("+c+");\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wR = 0; wR < "+n+"; wR++) {\n          int xR = xRCorner + wR;\n\n          if (xR < 0 || xR >= "+e.inHeight+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+d+"; wC += 4) {\n            int xC = xCCorner + wC;\n\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + 1, d),\n              getValue(batch, xR, xC + 2, d),\n              getValue(batch, xR, xC + 3, d)\n            );\n\n            "+f+"\n          }\n\n          int xC = xCCorner + "+d+";\n          if ("+(1===h)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              initializationValue,\n              initializationValue,\n              initializationValue\n            );\n\n            "+f+"\n          } else if ("+(2===h)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + 1, d),\n              initializationValue,\n              initializationValue\n            );\n\n            "+f+"\n          } else if ("+(3===h)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + 1, d),\n              getValue(batch, xR, xC + 2, d),\n              initializationValue\n            );\n\n            "+f+"\n          }\n        }\n        setOutput("+p+");\n      }\n    "}}}(),ReduceProgram=function(){return function(e,t){this.variableNames=["x"];var r=e.windowSize,n=e.batchSize,a=e.inSize,o=Math.ceil(a/r);this.outputShape=[n,o];var i="sum"===t,s="0.0";i||(s="min"===t?"1.0 / 0.0":"-1.0 / 0.0");var u="min"===t?"min":"max",l=t+"("+t+"("+t+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"sum"===t&&(l="sumValue");var c=4*Math.floor(r/4),p=r%4,d="\n      if ("+i+") {\n        sumValue += dot(values, ones);\n      } else {\n        minMaxValue = "+u+"(values, minMaxValue);\n      }\n    ",h="";a%r>0&&(h="\n        if (inIdx < 0 || inIdx >= "+a+") {\n          return initializationValue;\n        }\n      "),this.userCode="\n      const float initializationValue = "+s+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        "+h+"\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * "+r+";\n\n        vec4 minMaxValue = vec4("+s+");\n        float sumValue = 0.0;\n\n        for (int i = 0; i < "+c+"; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          "+d+"\n        }\n\n        int inIdx = inOffset + "+c+";\n        if ("+(1===p)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n          "+d+"\n        } else if ("+(2===p)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n          "+d+"\n        } else if ("+(3===p)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n          "+d+"\n        }\n        setOutput("+l+");\n      }\n    "}}(),ResizeBilinearBackpropProgram=function(){return function(e,t,r){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t.shape;var n=t.shape,a=n[1],o=n[2],i=e.shape,s=i[1],u=i[2],l=[r&&s>1?a-1:a,r&&u>1?o-1:o],c=[r&&s>1?s-1:s,r&&u>1?u-1:u],p=l[0]/c[0],d=l[1]/c[1],h=1/p,f=1/d,m=2*Math.ceil(h)+2,g=2*Math.ceil(f)+2;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float("+p+");\n        const float widthScale = float("+d+");\n\n        const float invHeightScale = float("+h+");\n        const float invWidthScale = float("+f+");\n\n        const int winHeight = int("+m+");\n        const int winWidth = int("+g+");\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(startRLerp - float(winHeight / 2));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(startCLerp - float(winWidth / 2));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= "+s+") {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= "+u+") {\n              continue;\n            }\n\n            float dxR = float(dyR) * heightScale;\n            int topDxRIndex = int(floor(dxR));\n            int bottomDxRIndex = int(min(ceil(dxR), "+(a-1)+".0));\n            float dxRLerp = dxR - float(topDxRIndex);\n            float inverseDxRLerp = 1.0 - dxRLerp;\n\n            float dxC = float(dyC) * widthScale;\n            int leftDxCIndex = int(floor(dxC));\n            int rightDxCIndex = int(min(ceil(dxC), "+(o-1)+".0));\n            float dxCLerp = dxC - float(leftDxCIndex);\n            float inverseDxCLerp = 1.0 - dxCLerp;\n\n            if (r == topDxRIndex && c == leftDxCIndex) {\n              // topLeft\n              accumulator +=\n                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;\n            }\n\n            if (r == topDxRIndex && c == rightDxCIndex) {\n              // topRight\n              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == leftDxCIndex) {\n              // bottomLeft\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == rightDxCIndex) {\n              // bottomRight\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    "}}(),ResizeBilinearProgram=function(){return function(e,t,r,n){this.variableNames=["A"],this.outputShape=[];var a=e[0],o=e[1],i=e[2],s=e[3];this.outputShape=[a,t,r,s];var u=[n&&t>1?o-1:o,n&&r>1?i-1:i],l=[n&&t>1?t-1:t,n&&r>1?r-1:r];this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          "+u[0]/l[0]+",\n          "+u[1]/l[1]+");\n      const vec2 inputShapeRC = vec2("+o+".0, "+i+".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the four integer indices.\n        ivec2 sourceFloorRC = ivec2(sourceFracIndexRC);\n        ivec2 sourceCeilRC = ivec2(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);\n        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);\n        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);\n        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);\n\n        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);\n\n        float top = topLeft + (topRight - topLeft) * fracRC.y;\n        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\n        float newValue = top + (bottom - top) * fracRC.x;\n\n        setOutput(newValue);\n      }\n    "}}(),ResizeNearestNeighborProgram=function(){return function(e,t,r,n){this.variableNames=["A"],this.outputShape=[];var a=e[0],o=e[1],i=e[2],s=e[3];this.outputShape=[a,t,r,s];var u=n?[o-1,i-1]:[o,i],l=n?[t-1,r-1]:[t,r],c=n?"0.5":"0.0";this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          "+u[0]/l[0]+",\n          "+u[1]/l[1]+");\n      const vec2 inputShapeRC = vec2("+o+".0, "+i+".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec2 sourceNearestRC = ivec2(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + "+c+")));\n\n        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);\n\n        setOutput(newValue);\n      }\n    "}}(),ReverseProgram=function(){return function(e,t){this.variableNames=["x"];var r=e.length;if(r>4)throw new Error("WebGL backend: Reverse of rank-"+r+" tensor is not yet supported");if(this.outputShape=e,1!==r){var n=function(r){return-1!==t.indexOf(r)&&1!==e[r]?e[r]+" - coords["+r+"] - 1":"coords["+r+"]"},a=e.map(function(e,t){return n(t)}).join(","),o=getCoordsDataType(r);this.userCode="\n      void main() {\n        "+o+" coords = getOutputCoords();\n        setOutput(getX("+a+"));\n      }\n    "}else this.userCode="\n        void main() {\n          int coord = getOutputCoords();\n          setOutput(getX("+e[0]+" - coord - 1));\n        }\n      "}}(),SliceProgram=function(){function e(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;var t=getCoordsDataType(this.rank),r=getCoords$1(this.rank);this.userCode="\n      uniform "+t+" start;\n\n      void main() {\n        "+t+" sourceLoc = start + getOutputCoords();\n        setOutput(getSource("+r+"));\n      }\n    "}return e.prototype.getCustomSetupFunc=function(e){var t=this;if(e.length!==this.rank)throw Error("The rank ("+this.rank+") of the program must match the length of start ("+e.length+")");return function(r,n){if(null!=t.startLoc||(t.startLoc=r.getUniformLocationNoThrow(n,"start"),null!=t.startLoc))if(1===t.rank)r.gl.uniform1i(t.startLoc,e[0]);else if(2===t.rank)r.gl.uniform2i(t.startLoc,e[0],e[1]);else if(3===t.rank)r.gl.uniform3i(t.startLoc,e[0],e[1],e[2]);else{if(4!==t.rank)throw Error("Slicing for rank "+t.rank+" is not yet supported");r.gl.uniform4i(t.startLoc,e[0],e[1],e[2],e[3])}}},e}(),StridedSliceProgram=function(){return function(e,t,r){this.variableNames=["x"],this.outputShape=r,this.rank=r.length;var n=getCoordsDataType(this.rank),a="";a=1===this.rank?"coords * strides + begin":r.map(function(e,t){return"coords["+t+"] * strides["+t+"] + begin["+t+"]"}).join(","),this.userCode="\n      "+n+" begin = "+n+"("+e+");\n      "+n+" strides = "+n+"("+t+");\n\n      void main() {\n        "+n+" coords = getOutputCoords();\n        setOutput(getX("+a+"));\n      }\n    "}}(),TextureManager=function(){function e(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}return e.prototype.acquireTexture=function(e,t){void 0===t&&(t=TextureType.FLOAT);var r=getKeyFromTextureShape(e,t);if(r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]),this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this.log();var n=this.freeTextures[r].shift();return this.usedTextures[r].push(n),n}this.numUsedTextures++,this.log();var a=this.gpgpu.createMatrixTexture(e[0],e[1]);return this.usedTextures[r].push(a),a},e.prototype.releaseTexture=function(e,t,r){void 0===r&&(r=TextureType.FLOAT);var n=getKeyFromTextureShape(t,r);n in this.freeTextures||(this.freeTextures[n]=[]),this.freeTextures[n].push(e),this.numFreeTextures++,this.numUsedTextures--;var a=this.usedTextures[n],o=a.indexOf(e);if(o<0)throw new Error("Cannot release a texture that was never provided by this texture manager");a.splice(o,1),this.log()},e.prototype.log=function(){if(this.logEnabled){var e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",this.numFreeTextures+" / "+this.numUsedTextures,"("+e+")")}},e.prototype.getNumUsedTextures=function(){return this.numUsedTextures},e.prototype.getNumFreeTextures=function(){return this.numFreeTextures},e.prototype.dispose=function(){var e=this;if(null!=this.freeTextures){for(var t in this.freeTextures)this.freeTextures[t].forEach(function(t){e.gpgpu.deleteMatrixTexture(t)});for(var t in this.usedTextures)this.usedTextures[t].forEach(function(t){e.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0}},e}(),TileProgram=function(){return function(e,t){this.variableNames=["A"];for(var r=new Array(e.length),n=0;n<r.length;n++)r[n]=e[n]*t[n];this.outputShape=r,this.rank=r.length;var a=getCoordsDataType(this.rank),o=getSourceCoords$1(e);this.userCode="\n      void main() {\n        "+a+" resRC = getOutputCoords();\n        setOutput(getA("+o+"));\n      }\n    "}}(),TransposeProgram=function(){return function(e,t){this.variableNames=["A"];for(var r=new Array(e.length),n=0;n<r.length;n++)r[n]=e[t[n]];this.outputShape=r,this.rank=r.length;var a=getCoordsDataType(this.rank),o=getSwitchedCoords(t);this.userCode="\n    void main() {\n      "+a+" resRC = getOutputCoords();\n      setOutput(getA("+o+"));\n    }\n    "}}(),ERF_P=.3275911,ERF_A1=.254829592,ERF_A2=-.284496736,ERF_A3=1.421413741,ERF_A4=-1.453152027,ERF_A5=1.061405429,UnaryOpProgram=function(){return function(e,t){this.variableNames=["A"],this.outputShape=e,this.userCode="\n      float unaryOperation(float x) {\n        "+t+"\n      }\n\n      void main() {\n        float x = getAAtOutCoords();\n        float y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    "}}(),CHECK_NAN_SNIPPET$1="if (isNaN(x)) return x;",ABS="return abs(x);",RELU=CHECK_NAN_SNIPPET$1+"\n  return (x < 0.0) ? 0.0 : x;\n",ELU="return (x >= 0.0) ? x : (exp(x) - 1.0);",SELU="\n  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\n  // see: https://arxiv.org/abs/1706.02515\n  float scaleAlpha = "+SELU_SCALEALPHA+";\n  float scale = "+SELU_SCALE+";\n  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\n",NEG="return -x;",CEIL="return ceil(x);",FLOOR="return floor(x);",SIGN="\n  if (isNaN(x)) { return 0.0; }\n  return sign(x);\n",ROUND="\n  // OpenGL ES does not support round function.\n  // The algorithm is based on banker's rounding.\n  float base = floor(x);\n  if ((x - base) < 0.5) {\n    return floor(x);\n  } else if ((x - base) > 0.5) {\n    return ceil(x);\n  } else {\n    if (mod(base, 2.0) == 0.0) {\n      return base;\n    } else {\n      return base + 1.0;\n    }\n  }\n",EXP="return exp(x);",EXPM1="return exp(x) - 1.0;",LOG="return log(x);",LOG1P="return log(1.0 + x);",SQRT="return sqrt(x);",RSQRT="return inversesqrt(x);",SIGMOID="return 1.0 / (1.0 + exp(-1.0 * x));",SOFTPLUS="\n  float epsilon = 1.1920928955078125e-7;\n  float threshold = log(epsilon) + 2.0;\n\n  bool too_large = x > -threshold;\n  bool too_small = x < threshold;\n\n  float result;\n  float exp_x = exp(x);\n\n  if (too_large){\n    result = x;\n  }\n  else if (too_small){\n    result = exp_x;\n  }\n  else{\n    result = log(exp_x + 1.0);\n  }\n  return result;\n",SIN="return sin(x);",COS="return cos(x);",TAN="return tan(x);",ASIN="return asin(x);",ACOS="return acos(x);",ATAN=CHECK_NAN_SNIPPET$1+"\n  return atan(x);\n",SINH="\n  float e2x = exp(x);\n  return (e2x - 1.0 / e2x) / 2.0;\n",COSH="\n  float e2x = exp(-x);\n  return (e2x + 1.0 / e2x) / 2.0;\n",TANH="\n  float e2x = exp(-2.0 * abs(x));\n  return sign(x) * (1.0 - e2x) / (1.0 + e2x);\n",ASINH="return log(x + sqrt(x * x + 1.0));",ACOSH="return log(x + sqrt(x * x - 1.0));",ATANH="return (log(1.0 + x) - log(1.0 - x)) / 2.0;",ERF='\n  // Error function is calculated approximately with elementary function.\n  // See "Handbook of Mathematical Functions with Formulas,\n  // Graphs, and Mathematical Tables", Abramowitz and Stegun.\n  float p = '+ERF_P+";\n  float a1 = "+ERF_A1+";\n  float a2 = "+ERF_A2+";\n  float a3 = "+ERF_A3+";\n  float a4 = "+ERF_A4+";\n  float a5 = "+ERF_A5+";\n\n  float t = 1.0 / (1.0 + p * x);\n  return 1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x);\n",SQUARE="return x * x;",RECIPROCAL="return 1.0 / 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WeakSet,this.lruDataGPU=[],this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.binaryCache={},this.disposed=!1,ENV.get("WEBGL_VERSION")<1)throw new Error("WebGL is not supported on this device");ENV.get("IS_BROWSER")&&(this.canvas=document.createElement("canvas")),null==e?(this.gpgpu=new GPGPUContext(createWebGLContext(this.canvas)),this.gpgpuCreatedLocally=!0):this.gpgpuCreatedLocally=!1,this.NUM_BYTES_BEFORE_PAGING=window.screen.height*window.screen.width*window.devicePixelRatio*BEFORE_PAGING_CONSTANT,this.textureManager=new TextureManager(this.gpgpu)}return e.prototype.register=function(e,t,r){if(this.texData.has(e))throw new Error("Data buffer is already registered");this.texData.set(e,{shape:t,dtype:r,values:null,texture:null,texShape:null,texType:TextureType.FLOAT})},e.prototype.fromPixels=function(e,t){if(null==e)throw new Error("MathBackendWebGL.writePixels(): pixels can not be null");var r=[e.height,e.width],n=[e.height,e.width,t];if(e instanceof HTMLVideoElement){if(null==this.fromPixelsCanvas){if(!ENV.get("IS_BROWSER"))throw new Error("Can't read pixels from HTMLImageElement outside the browser.");if("complete"!==document.readyState)throw new Error("The DOM is not ready yet. Please call tf.fromPixels() once the DOM is ready. One way to do that is to add an event listener for `DOMContentLoaded` on the document object");this.fromPixelsCanvas=document.createElement("canvas")}this.fromPixelsCanvas.width=e.width,this.fromPixelsCanvas.height=e.height,this.fromPixelsCanvas.getContext("2d").drawImage(e,0,0,e.width,e.height),e=this.fromPixelsCanvas}var a=Tensor.make(r,{},"int32");this.texData.get(a.dataId).texType=TextureType.UNSIGNED_BYTE,this.gpgpu.uploadPixelDataToTexture(this.getTexture(a.dataId),e);var o=new FromPixelsProgram(n),i=this.compileAndRun(o,[a]);return a.dispose(),i},e.prototype.write=function(e,t){if(null==t)throw new Error("MathBackendWebGL.write(): values can not be null");this.throwIfNoData(e);var r=this.texData.get(e),n=r.texture,a=r.texShape,o=r.texType;null!=n&&(this.releaseTexture(e,n,a,o),r.texture=null,r.texShape=null),r.values=t,this.delayedStorage||this.uploadToGPU(e)},e.prototype.readSync=function(e){this.throwIfNoData(e);var t=this.texData.get(e),r=t.texture,n=t.values,a=t.texShape;if(null!=n)return this.cacheOnCPU(e),n;var o,i=null!=this.activeTimers;i&&(o=performance.now());var s=this.gpgpu.downloadMatrixFromTexture(r,a[0],a[1]);return i&&(this.downloadWaitMs+=performance.now()-o),this.cacheOnCPU(e,s),t.values},e.prototype.read=function(e){return __awaiter$5(this,void 0,void 0,function(){var t,r,n,a,o,i,s,u;return __generator$5(this,function(l){switch(l.label){case 0:return this.pendingRead.has(e)?(t=this.pendingRead.get(e),[2,new Promise(function(e){return t.push(e)})]):(this.throwIfNoData(e),r=this.texData.get(e),n=r.texture,a=r.values,o=r.texShape,null!=a?(this.cacheOnCPU(e),[2,a]):ENV.get("WEBGL_GET_BUFFER_SUB_DATA_ASYNC_EXTENSION_ENABLED")?[4,this.gpgpu.downloadMatrixFromTextureAsync(n,o[0],o[1])]:[3,2]);case 1:return i=l.sent(),this.cacheOnCPU(e,i),[2,r.values];case 2:return 0===ENV.get("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")?[2,this.readSync(e)]:(this.pendingRead.set(e,[]),[4,this.gpgpu.runQuery(function(){})]);case 3:return l.sent(),s=this.pendingRead.get(e),this.pendingRead.delete(e),u=this.readSync(e),s.forEach(function(e){return e(u)}),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)),[2,u]}})})},e.prototype.time=function(e){return __awaiter$5(this,void 0,void 0,function(){var t,r,n,a,o,i;return __generator$5(this,function(s){switch(s.label){case 0:return t=this.activeTimers,r=[],n=!1,null==this.programTimersStack?(this.programTimersStack=r,n=!0):this.activeTimers.push(r),this.activeTimers=r,e(),a=flatten(this.activeTimers),this.activeTimers=t,n&&(this.programTimersStack=null),[4,Promise.all(a).then(function(e){var t=0;return e.forEach(function(e){return t+=e}),t})];case 1:return o=s.sent(),i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:o,wallMs:null},this.uploadWaitMs=0,this.downloadWaitMs=0,[2,i]}})})},e.prototype.memory=function(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU}},e.prototype.startTimer=function(){return ENV.get("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?this.gpgpu.beginQuery():{startMs:performance.now(),endMs:null}},e.prototype.endTimer=function(e){return ENV.get("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(this.gpgpu.endQuery(),e):(e.endMs=performance.now(),e)},e.prototype.getQueryTime=function(e){return __awaiter$5(this,void 0,void 0,function(){var t;return __generator$5(this,function(r){return ENV.get("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?[2,this.gpgpu.pollQueryTime(e)]:(t=e,[2,t.endMs-t.startMs])})})},e.prototype.disposeData=function(e){if(!this.pendingDisposal.has(e))if(this.pendingRead.has(e))this.pendingDisposal.add(e);else if(this.texData.has(e)){var t=this.texData.get(e),r=t.texture,n=t.texShape,a=t.texType;null!=r&&this.releaseTexture(e,r,n,a),this.texData.delete(e)}},e.prototype.getTexture=function(e){return this.uploadToGPU(e),this.texData.get(e).texture},e.prototype.getGPGPUContext=function(){return this.gpgpu},e.prototype.getCanvas=function(){return this.canvas},e.prototype.slice=function(e,t,r){var n=new SliceProgram(r),a=n.getCustomSetupFunc(t);return this.compileAndRun(n,[e],null,a)},e.prototype.stridedSlice=function(e,t,r,n,a,o){var i=getStridedSlicedInfo(e.shape,t,r,n,a,o),s=i[0],u=i[1];if(u.some(function(e){return 0===e}))return tensor([],u);var l=new StridedSliceProgram(s,n,u);return this.compileAndRun(l,[e])},e.prototype.reverse=function(e,t){var r=new ReverseProgram(e.shape,t);return this.compileAndRun(r,[e])},e.prototype.concat=function(e,t){var r=new ConcatProgram(e.shape,t.shape);return this.compileAndRun(r,[e,t])},e.prototype.neg=function(e){var t=new UnaryOpProgram(e.shape,NEG);return this.compileAndRun(t,[e])},e.prototype.matMul=function(e,t,r,n){var a=new MatMulProgram(e.shape,t.shape,r,n);return this.compileAndRun(a,[e,t])},e.prototype.multiply=function(e,t){var r=new BinaryOpProgram(MUL,e.shape,t.shape),n=this.makeOutputArray(r.outputShape,upcastType(e.dtype,t.dtype));return this.compileAndRun(r,[e,t],n)},e.prototype.batchNormalization=function(e,t,r,n,a,o){var i=[e,t,r],s=null;null!=o&&(s=o.shape,i.push(o));var u=null;null!=a&&(u=a.shape,i.push(a));var l=new BatchNormProgram(e.shape,t.shape,r.shape,s,u,n);return this.compileAndRun(l,i)},e.prototype.localResponseNormalization4D=function(e,t,r,n,a){var o=new LRNProgram(e.shape,t,r,n,a);return this.compileAndRun(o,[e])},e.prototype.tile=function(e,t){var r=new TileProgram(e.shape,t);return this.compileAndRun(r,[e])},e.prototype.pad=function(e,t,r){var n=new PadProgram(e.shape,t,r);return this.compileAndRun(n,[e])},e.prototype.transpose=function(e,t){var r=new TransposeProgram(e.shape,t);return this.compileAndRun(r,[e])},e.prototype.gather=function(e,t,r){var n=new GatherProgram(e.shape,t.size,r);return this.compileAndRun(n,[e,t])},e.prototype.reduce=function(e,t,r){var n=e.shape[0],a=e.shape[1],o=computeOptimalWindowSize(a),i=new ReduceProgram({windowSize:o,inSize:a,batchSize:n},t),s=i.outputShape,u=s[0],l=s[1],c=this.makeOutputArray([u,l],r);return this.compileAndRun(i,[e],c),1===c.shape[1]?c:this.reduce(c,t,r)},e.prototype.argReduce=function(e,t,r){void 0===r&&(r=null);var n=e.shape[0],a=e.shape[1];null!=r&&(n=r.shape[0],a=r.shape[1]);var o=computeOptimalWindowSize(a),i=new ArgMinMaxProgram({windowSize:o,inSize:a,batchSize:n},t,null==r),s=i.outputShape,u=s[0],l=s[1],c=this.makeOutputArray([u,l],"int32"),p=[e];return null!=r&&p.push(r),this.compileAndRun(i,p,c),1===c.shape[1]?c:this.argReduce(e,t,c)},e.prototype.sum=function(e,t){assertAxesAreInnerMostDims("sum",t,e.rank);var r=computeOutAndReduceShapes(e.shape,t),n=r[0],a=sizeFromShape(r[1]),o=e.as2D(-1,a),i=sumOutType(e.dtype);return this.reduce(o,"sum",i).reshape(n)},e.prototype.argMin=function(e,t){var r=[t];assertAxesAreInnerMostDims("argMin",r,e.rank);var n=computeOutAndReduceShapes(e.shape,r),a=n[0],o=sizeFromShape(n[1]),i=e.as2D(-1,o);return this.argReduce(i,"min").reshape(a)},e.prototype.argMax=function(e,t){var r=[t];assertAxesAreInnerMostDims("argMax",r,e.rank);var n=computeOutAndReduceShapes(e.shape,r),a=n[0],o=sizeFromShape(n[1]),i=e.as2D(-1,o);return this.argReduce(i,"max").reshape(a)},e.prototype.cumsum=function(e,t,r,n){if(t!==e.rank-1)throw new Error("WebGL cumsum shader expects an inner-most axis="+(e.rank-1)+" but got axis="+t);var a=new CumSumProgram(e.shape,r,n);return this.compileAndRun(a,[e])},e.prototype.equal=function(e,t){var r=new BinaryOpProgram(EQUAL,e.shape,t.shape),n=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,t],n)},e.prototype.notEqual=function(e,t){var r=new BinaryOpProgram(NOT_EQUAL,e.shape,t.shape),n=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,t],n)},e.prototype.less=function(e,t){var r=new BinaryOpProgram(LESS,e.shape,t.shape),n=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,t],n)},e.prototype.lessEqual=function(e,t){var r=new BinaryOpProgram(LESS_EQUAL,e.shape,t.shape),n=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,t],n)},e.prototype.greater=function(e,t){var r=new BinaryOpProgram(GREATER,e.shape,t.shape),n=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,t],n)},e.prototype.greaterEqual=function(e,t){var r=new BinaryOpProgram(GREATER_EQUAL,e.shape,t.shape),n=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,t],n)},e.prototype.logicalNot=function(e){var t=new UnaryOpProgram(e.shape,LOGICAL_NOT);return this.compileAndRun(t,[e])},e.prototype.logicalAnd=function(e,t){var r=new BinaryOpProgram(LOGICAL_AND,e.shape,t.shape),n=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,t],n)},e.prototype.logicalOr=function(e,t){var r=new BinaryOpProgram(LOGICAL_OR,e.shape,t.shape),n=this.makeOutputArray(r.outputShape,"bool");return this.compileAndRun(r,[e,t],n)},e.prototype.where=function(e,t,r,n){var a=new WhereProgram(e.rank,t.shape,t.rank),o=this.makeOutputArray(a.outputShape,n);return this.compileAndRun(a,[e,t,r],o)},e.prototype.topKValues=function(e,t){throw new Error("topKValues GPU not yet implemented!")},e.prototype.topKIndices=function(e,t){throw new Error("topKIndices GPU not yet implemented!")},e.prototype.min=function(e,t){assertAxesAreInnerMostDims("min",t,e.rank);var r=computeOutAndReduceShapes(e.shape,t),n=r[0],a=sizeFromShape(r[1]),o=e.as2D(-1,a);return this.reduce(o,"min",o.dtype).reshape(n)},e.prototype.minimum=function(e,t){var r=new BinaryOpProgram(MIN,e.shape,t.shape);return this.compileAndRun(r,[e,t])},e.prototype.mod=function(e,t){var r=new BinaryOpProgram(MOD,e.shape,t.shape);return this.compileAndRun(r,[e,t])},e.prototype.max=function(e,t){assertAxesAreInnerMostDims("max",t,e.rank);var r=computeOutAndReduceShapes(e.shape,t),n=r[0],a=sizeFromShape(r[1]),o=e.as2D(-1,a);return this.reduce(o,"max",o.dtype).reshape(n)},e.prototype.maximum=function(e,t){var r=new BinaryOpProgram(MAX,e.shape,t.shape);return this.compileAndRun(r,[e,t])},e.prototype.squaredDifference=function(e,t){var r=new BinaryOpProgram(SQUARED_DIFFERENCE,e.shape,t.shape);return this.compileAndRun(r,[e,t])},e.prototype.realDivide=function(e,t){var r=new BinaryOpProgram(DIV,e.shape,t.shape),n=this.makeOutputArray(r.outputShape,"float32");return this.compileAndRun(r,[e,t],n)},e.prototype.floorDiv=function(e,t){var r=new BinaryOpProgram(INT_DIV,e.shape,t.shape),n=this.makeOutputArray(r.outputShape,"int32");return this.compileAndRun(r,[e,t],n)},e.prototype.add=function(e,t){var r=new BinaryOpProgram(ADD,e.shape,t.shape),n=this.makeOutputArray(r.outputShape,upcastType(e.dtype,t.dtype));return this.compileAndRun(r,[e,t],n)},e.prototype.subtract=function(e,t){var r=new BinaryOpProgram(SUB,e.shape,t.shape),n=this.makeOutputArray(r.outputShape,upcastType(e.dtype,t.dtype));return this.compileAndRun(r,[e,t],n)},e.prototype.pow=function(e,t){var r=new BinaryOpProgram(POW,e.shape,t.shape),n=this.makeOutputArray(r.outputShape,upcastType(e.dtype,t.dtype));return this.compileAndRun(r,[e,t],n)},e.prototype.ceil=function(e){var t=new UnaryOpProgram(e.shape,CEIL);return this.compileAndRun(t,[e])},e.prototype.floor=function(e){var t=new UnaryOpProgram(e.shape,FLOOR);return this.compileAndRun(t,[e])},e.prototype.sign=function(e){var t=new UnaryOpProgram(e.shape,SIGN);return this.compileAndRun(t,[e])},e.prototype.round=function(e){var t=new UnaryOpProgram(e.shape,ROUND);return this.compileAndRun(t,[e])},e.prototype.exp=function(e){var t=new UnaryOpProgram(e.shape,EXP);return this.compileAndRun(t,[e])},e.prototype.expm1=function(e){var t=new UnaryOpProgram(e.shape,EXPM1);return this.compileAndRun(t,[e])},e.prototype.log=function(e){var t=new UnaryOpProgram(e.shape,LOG);return this.compileAndRun(t,[e])},e.prototype.log1p=function(e){var t=new UnaryOpProgram(e.shape,LOG1P);return this.compileAndRun(t,[e])},e.prototype.sqrt=function(e){var t=new UnaryOpProgram(e.shape,SQRT);return this.compileAndRun(t,[e])},e.prototype.rsqrt=function(e){var t=new UnaryOpProgram(e.shape,RSQRT);return this.compileAndRun(t,[e])},e.prototype.square=function(e){var t=new UnaryOpProgram(e.shape,SQUARE);return this.compileAndRun(t,[e])},e.prototype.reciprocal=function(e){var t=new UnaryOpProgram(e.shape,RECIPROCAL);return this.compileAndRun(t,[e])},e.prototype.relu=function(e){var t=new UnaryOpProgram(e.shape,RELU);return this.compileAndRun(t,[e])},e.prototype.elu=function(e){var t=new UnaryOpProgram(e.shape,ELU);return this.compileAndRun(t,[e])},e.prototype.eluDer=function(e,t){var r=new BinaryOpProgram(ELU_DER,e.shape,t.shape);return this.compileAndRun(r,[e,t])},e.prototype.selu=function(e){var t=new UnaryOpProgram(e.shape,SELU);return this.compileAndRun(t,[e])},e.prototype.int=function(e){var t=new UnaryOpProgram(e.shape,TO_INT),r=this.makeOutputArray(t.outputShape,"int32");return this.compileAndRun(t,[e],r)},e.prototype.clip=function(e,t,r){var n=new ClipProgram(e.shape,t,r);return this.compileAndRun(n,[e])},e.prototype.abs=function(e){var t=new UnaryOpProgram(e.shape,ABS);return this.compileAndRun(t,[e])},e.prototype.sigmoid=function(e){var t=new UnaryOpProgram(e.shape,SIGMOID);return this.compileAndRun(t,[e])},e.prototype.softplus=function(e){var t=new UnaryOpProgram(e.shape,SOFTPLUS);return this.compileAndRun(t,[e])},e.prototype.sin=function(e){var t=new UnaryOpProgram(e.shape,SIN);return this.compileAndRun(t,[e])},e.prototype.cos=function(e){var t=new UnaryOpProgram(e.shape,COS);return this.compileAndRun(t,[e])},e.prototype.tan=function(e){var t=new UnaryOpProgram(e.shape,TAN);return this.compileAndRun(t,[e])},e.prototype.asin=function(e){var t=new UnaryOpProgram(e.shape,ASIN);return this.compileAndRun(t,[e])},e.prototype.acos=function(e){var t=new UnaryOpProgram(e.shape,ACOS);return this.compileAndRun(t,[e])},e.prototype.atan=function(e){var t=new UnaryOpProgram(e.shape,ATAN);return this.compileAndRun(t,[e])},e.prototype.atan2=function(e,t){var r=new BinaryOpProgram(ATAN2,e.shape,t.shape);return this.compileAndRun(r,[e,t])},e.prototype.sinh=function(e){var t=new UnaryOpProgram(e.shape,SINH);return this.compileAndRun(t,[e])},e.prototype.cosh=function(e){var t=new UnaryOpProgram(e.shape,COSH);return this.compileAndRun(t,[e])},e.prototype.tanh=function(e){var t=new UnaryOpProgram(e.shape,TANH);return this.compileAndRun(t,[e])},e.prototype.asinh=function(e){var t=new UnaryOpProgram(e.shape,ASINH);return this.compileAndRun(t,[e])},e.prototype.acosh=function(e){var t=new UnaryOpProgram(e.shape,ACOSH);return this.compileAndRun(t,[e])},e.prototype.atanh=function(e){var t=new UnaryOpProgram(e.shape,ATANH);return this.compileAndRun(t,[e])},e.prototype.erf=function(e){var t=new UnaryOpProgram(e.shape,ERF);return this.compileAndRun(t,[e])},e.prototype.step=function(e,t){var r=new UnaryOpProgram(e.shape,STEP(t));return this.compileAndRun(r,[e])},e.prototype.conv2d=function(e,t,r){var n=new Conv2DProgram(r);return this.compileAndRun(n,[e,t])},e.prototype.conv2dDerInput=function(e,t,r){var n=new Conv2DDerInputProgram(r);return this.compileAndRun(n,[e,t])},e.prototype.conv2dDerFilter=function(e,t,r){var n=new Conv2DDerFilterProgram(r);return this.compileAndRun(n,[e,t])},e.prototype.depthwiseConv2D=function(e,t,r){var n=new DepthwiseConv2DProgram(r);return this.compileAndRun(n,[e,t])},e.prototype.depthwiseConv2DDerInput=function(e,t,r){var n=new DepthwiseConv2DDerInputProgram(r);return this.compileAndRun(n,[e,t])},e.prototype.depthwiseConv2DDerFilter=function(e,t,r){var n=new DepthwiseConv2DDerFilterProgram(r);return this.compileAndRun(n,[e,t])},e.prototype.maxPool=function(e,t){var r=new Pool2DProgram(t,"max",!1),n=this.makeOutputArray(r.outputShape,e.dtype);return this.compileAndRun(r,[e],n)},e.prototype.avgPool=function(e,t){var r=new Pool2DProgram(t,"avg",!1),n=this.makeOutputArray(r.outputShape,"float32");return this.compileAndRun(r,[e],n)},e.prototype.maxPoolBackprop=function(e,t,r,n){var a=new Pool2DProgram(n,"max",!0),o=this.compileAndRun(a,[t]),i=new MaxPool2DBackpropProgram(n),s=this.makeOutputArray(i.outputShape,t.dtype),u=this.compileAndRun(i,[e,o],s);return o.dispose(),u},e.prototype.avgPoolBackprop=function(e,t,r){var n=new AvgPool2DBackpropProgram(r),a=this.makeOutputArray(n.outputShape,t.dtype);return this.compileAndRun(n,[e],a)},e.prototype.cast=function(e,t){return castTensor(e,t,this)},e.prototype.reshape=function(e,t){return reshapeTensor(e,t)},e.prototype.resizeBilinear=function(e,t,r,n){var a=new ResizeBilinearProgram(e.shape,t,r,n);return this.compileAndRun(a,[e])},e.prototype.resizeBilinearBackprop=function(e,t,r){var n=new ResizeBilinearBackpropProgram(e,t,r);return this.compileAndRun(n,[e])},e.prototype.resizeNearestNeighbor=function(e,t,r,n){var a=new ResizeNearestNeighborProgram(e.shape,t,r,n);return this.compileAndRun(a,[e])},e.prototype.multinomial=function(e,t,r,n){var a=t?e:softmax(e),o=a.shape[0],i=a.shape[1],s=new MultinomialProgram(o,i,r),u=this.makeOutputArray(s.outputShape,"int32"),l=s.getCustomSetupFunc(n);return this.compileAndRun(s,[a],u,l)},e.prototype.oneHot=function(e,t,r,n){var a=new OneHotProgram(e.size,t,r,n);return this.compileAndRun(a,[e])},e.prototype.makeOutputArray=function(e,t){return Tensor.make(e,{},t)},e.prototype.compileAndRun=function(e,t,r,n){var a=this;null==r&&(r=this.makeOutputArray(e.outputShape,t[0].dtype));var o=t.map(function(e){return a.uploadToGPU(e.dataId),{tensor:e,texData:a.texData.get(e.dataId)}});this.uploadToGPU(r.dataId);var i,s={tensor:r,texData:this.texData.get(r.dataId)},u=makeShaderKey(e,o,s),l=this.getAndSaveBinary(u,function(){return compileProgram(a.gpgpu,e,o,s)}),c=null!=this.activeTimers;if(c&&(i=this.startTimer()),runProgram(l,o,s,n),this.numBytesInGPU>this.NUM_BYTES_BEFORE_PAGING)for(var p=this.numBytesInGPU-this.NUM_BYTES_BEFORE_PAGING;p>0;){var d=this.lruDataGPU.shift(),h=this.texData.get(d),f=h.shape,m=h.dtype;p-=this.computeBytes(f,m),this.read(d)}return c&&(i=this.endTimer(i),this.activeTimers.push(this.getQueryTime(i))),r},e.prototype.getAndSaveBinary=function(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]},e.prototype.getTextureManager=function(){return this.textureManager},e.prototype.dispose=function(){if(!this.disposed){for(var e in this.binaryCache)this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram);this.textureManager.dispose(),this.canvas.remove(),null!=this.fromPixelsCanvas&&this.fromPixelsCanvas.remove(),this.gpgpuCreatedLocally&&this.gpgpu.dispose(),this.disposed=!0}},e.prototype.throwIfNoData=function(e){if(!this.texData.has(e))throw new Error("WebGL backend: No data found for this tensor. Did you change your backend in the middle of the program? 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x=m+b*i;if(!(x<0||x>=r.inWidth))for(var w=0;w<r.inChannels;++w)g+=e.get(c,v,x,w)*t.get(y,b,w,p)}}l.set(g,c,d,f,p)}return l.toTensor()},e.prototype.conv2dDerInput=function(e,t,r){for(var n=buffer(r.inShape,"float32"),a=n.values,o=n.strides,i=o[0],s=o[1],u=o[2],l=e.dataSync(),c=e.strides,p=c[0],d=c[1],h=c[2],f=t.dataSync(),m=t.strides,g=m[0],y=m[1],v=m[2],b=r.batchSize,x=r.filterHeight,w=r.filterWidth,_=r.inChannels,S=r.inHeight,N=r.inWidth,A=r.outChannels,E=r.outHeight,T=r.outWidth,I=r.strideHeight,O=r.strideWidth,P=x-1-r.padInfo.top,R=w-1-r.padInfo.left,C=0;C<b;++C)for(var k=0;k<_;++k)for(var D=0;D<S;++D)for(var M=D-P,L=Math.max(0,Math.ceil(M/I)),z=Math.min(E,(x+M)/I),V=0;V<N;++V){for(var F=V-R,$=Math.max(0,Math.ceil(F/O)),B=Math.min(T,(w+F)/O),U=0,j=L;j<z;++j)for(var G=j*I-M,W=$;W<B;++W)for(var q=p*C+d*j+h*W,H=g*(x-1-G)+y*(w-1-(W*O-F))+v*k,K=0;K<A;++K)U+=l[q+K]*f[H+K];a[i*C+s*D+u*V+k]=U}return n.toTensor()},e.prototype.conv2dDerFilter=function(e,t,r){for(var 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x=f+b*o;if(!(x<0||x>=r.inHeight))for(var w=0;w<a;++w){var _=g+w*i;_<0||_>=r.inWidth||(v+=e.get(p,x,_,d)*t.get(b,w,d,y))}}c.set(v,p,h,m,d*l+y)}return c.toTensor()},e.prototype.depthwiseConv2DDerInput=function(e,t,r){for(var n=buffer(r.inShape,"float32"),a=n.values,o=n.strides,i=o[0],s=o[1],u=o[2],l=e.dataSync(),c=e.strides,p=c[0],d=c[1],h=c[2],f=t.dataSync(),m=t.strides,g=m[0],y=m[1],v=m[2],b=r.batchSize,x=r.filterHeight,w=r.filterWidth,_=r.inChannels,S=r.inHeight,N=r.inWidth,A=r.outChannels,E=r.outHeight,T=r.outWidth,I=r.strideHeight,O=r.strideWidth,P=x-1-r.padInfo.top,R=w-1-r.padInfo.left,C=A/_,k=0;k<b;++k)for(var D=0;D<_;++D)for(var M=0;M<S;++M)for(var L=M-P,z=Math.max(0,Math.ceil(L/I)),V=Math.min(E,(x+L)/I),F=0;F<N;++F){for(var $=F-R,B=Math.max(0,Math.ceil($/O)),U=Math.min(T,(w+$)/O),j=0,G=z;G<V;++G)for(var W=G*I-L,q=B;q<U;++q)for(var H=p*k+d*G+h*q,K=g*(x-1-W)+y*(w-1-(q*O-$))+v*D,X=0;X<C;++X)j+=l[H+(D*C+X)]*f[K+X];a[i*k+s*M+u*F+D]=j}return 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n=t.strideHeight,a=t.strideWidth,o=t.filterHeight,i=t.filterWidth,s=buffer(t.outShape,"float32"),u=t.padInfo.top,l=t.padInfo.left,c=0;c<t.batchSize;++c)for(var p=0;p<t.inChannels;++p)for(var d=0;d<t.outHeight;++d)for(var h=d*n-u,f=Math.max(0,h),m=Math.min(t.inHeight,o+h),g=0;g<t.outWidth;++g){for(var y=g*a-l,v=Math.max(0,y),b=Math.min(t.inWidth,i+y),x="max"===r?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,w=0,_=0,S=f;S<m;++S){for(var N=v;N<b;++N){var A=e.get(c,S,N,p);"max"===r&&A>x?x=A:"avg"===r&&(w+=A,_++)}if(isNaN(x))break}s.set("avg"===r?w/_:x,c,d,g,p)}return s.toTensor()},e.prototype.maxPool=function(e,t){return this.pool(e,t,"max")},e.prototype.maxPoolPositions=function(e,t){for(var r=buffer(t.outShape,"int32"),n=t.strideHeight,a=t.strideWidth,o=t.filterHeight,i=t.filterWidth,s=t.padInfo.top,u=t.padInfo.left,l=0;l<t.batchSize;++l)for(var c=0;c<t.inChannels;++c)for(var p=0;p<t.outHeight;++p)for(var d=p*n-s,h=Math.max(0,d),f=Math.min(t.inHeight,o+d),m=0;m<t.outWidth;++m){for(var g=m*a-u,y=Math.max(0,g),v=Math.min(t.inWidth,i+g),b=Number.NEGATIVE_INFINITY,x=-1,w=h;w<f;++w)for(var _=w-d,S=y;S<v;++S){var N=S-g,A=e.get(l,w,S,c);A>b&&(b=A,x=_*i+N)}r.set(x,l,p,m,c)}return r.toTensor()},e.prototype.maxPoolBackprop=function(e,t,r,n){for(var a=this.maxPoolPositions(t,n),o=n.strideHeight,i=n.strideWidth,s=n.filterHeight,u=n.filterWidth,l=u-1-n.padInfo.left,c=s-1-n.padInfo.top,p=buffer(t.shape,"float32"),d=0;d<n.batchSize;++d)for(var h=0;h<n.inChannels;++h)for(var f=0;f<n.inHeight;++f)for(var m=0;m<n.inWidth;++m){for(var g=f-c,y=m-l,v=0,b=0;b<s;++b){var x=(g+b)/o;if(!(x<0||x>=n.outHeight||Math.floor(x)!==x))for(var w=0;w<u;++w){var _=(y+w)/i;if(!(_<0||_>=n.outWidth||Math.floor(_)!==_)){var S=s*u-1-a.get(d,x,_,h)===b*u+w?1:0;0!==S&&(v+=e.get(d,x,_,h)*S)}}}p.set(v,d,f,m,h)}return p.toTensor()},e.prototype.avgPoolBackprop=function(e,t,r){for(var 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Use `getOutputAt(nodeIndex)` instead.');return singletonOrArray(this.getNodeAtIndex(0,"output").outputTensors)},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"losses",{get:function(){return this._losses},enumerable:!0,configurable:!0}),t.prototype.calculateLosses=function(){return this.losses.map(function(e){return e()})},Object.defineProperty(t.prototype,"updates",{get:function(){return this._updates},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"built",{get:function(){return this._built},set:function(e){this._built=e},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"trainableWeights",{get:function(){return this.trainable?this._trainableWeights:[]},set:function(e){this._trainableWeights=e},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"nonTrainableWeights",{get:function(){return this.trainable?this._nonTrainableWeights:this._trainableWeights.concat(this._nonTrainableWeights)},set:function(e){this._nonTrainableWeights=e},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"weights",{get:function(){return this.trainableWeights.concat(this.nonTrainableWeights)},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"stateful",{get:function(){return this._stateful},enumerable:!0,configurable:!0}),t.prototype.assertInputCompatibility=function(e){if(e=toList(e),null!=this.inputSpec&&0!==this.inputSpec.length){var t=toList(this.inputSpec);if(e.length!==t.length)throw new ValueError("Layer "+this.name+" expects "+t.length+" inputs, but it received "+e.length+" input tensors. Input received: "+e);for(var r=0;r<e.length;r++){var n=e[r],a=t[r];if(null!=a){var o=n.rank;if(null!=a.ndim&&o!==a.ndim)throw new ValueError("Input "+r+" is incompatible with layer "+this.name+": expected ndim="+a.ndim+", found ndim="+o);if(null!=a.maxNDim&&o>a.maxNDim)throw new ValueError("Input "+r+" is incompatible with layer "+this.name+": expected max_ndim="+a.maxNDim+", found ndim="+o);if(null!=a.minNDim&&o<a.minNDim)throw new ValueError("Input "+r+" is incompatible with layer "+this.name+": expected min_ndim="+a.minNDim+", found ndim="+o+".");if(null!=a.dtype&&dtype(n)!==a.dtype){var i=dtype(n);throw new ValueError("Input "+r+" is incompatible with layer "+this.name+" : expected dtype="+a.dtype+", found dtype="+i+".")}if(a.axes){p=intShape(n);for(var s in a.axes){var u=Number(s),l=a.axes[s],c=u>=0?p[u]:p[p.length+u];if(null!=l&&-1===[l,null].indexOf(c))throw new ValueError("Input "+r+" is incompatible with layer "+this.name+": expected axis "+u+" of input shape to have value "+l+" but got shape "+p+".")}}if(null!=a.shape)for(var p=intShape(n),d=0;d<a.shape.length;++d){var h=a.shape[d],f=p[d];if(null!=h&&null!=f&&h!==f)throw new ValueError("Input "+r+" is incompatible with layer "+this.name+": expected shape="+a.shape+", found shape=${xShape}.")}}}}},t.prototype.call=function(e,t){return e},t.prototype.invokeCallHook=function(e,t){null!=this._callHook&&this._callHook(e,t)},t.prototype.setCallHook=function(e){this._callHook=e},t.prototype.clearCallHook=function(){this._callHook=null},t.prototype.apply=function(e,t){var r=this;t=t||{};for(var n=toList(e),a=!0,o=0,i=n;o<i.length;o++)if(!((c=i[o])instanceof SymbolicTensor)){a=!1;break}for(var s=!0,u=0,l=n;u<l.length;u++){var c=l[u];if(c instanceof SymbolicTensor){s=!1;break}}if(a===s)throw new ValueError("Arguments to apply() must be all SymbolicTensors or all Tensors");return nameScope$1(this.name,function(){if(!r.built){r.assertInputCompatibility(e);for(var a=[],o=0,i=toList(e);o<i.length;o++){var u=i[o];a.push(intShape(u))}r.build(singletonOrArray(a)),r.built=!0,r.initialWeights&&r.setWeights(r.initialWeights)}if(r.assertInputCompatibility(e),s){for(var l=[],c=0,p=toList(m=r.call(e,t));c<p.length;c++){var d=p[c];-1!==n.indexOf(d)&&(d=identity(d)),l.push(d)}if(m=singletonOrArray(l),null!=r.activityRegularizer)throw new NotImplementedError("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return m}var h=collectInputShape(e),f=r.computeOutputShape(h),m=void 0;if(m=null!=f&&f.length>0&&Array.isArray(f[0])?f.map(function(n,a){return new SymbolicTensor("float32",n,r,toList(e),t,r.name,a)}):new SymbolicTensor("float32",f,r,toList(e),t,r.name),r.addInboundNode(e,m,null,null,h,f,t),null!=r.activityRegularizer)throw new NotImplementedError("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return m})},t.prototype.build=function(e){this.built=!0},t.prototype.getWeights=function(e){return void 0===e&&(e=!1),batchGetValue(e?this.trainableWeights:this.weights)},t.prototype.setWeights=function(e){var t=this;tidy(function(){var r=t.weights;if(r.length!==e.length)throw new ValueError('You called setWeights(weights) on layer "'+t.name+'" with a weight list of length '+e.length+", but the layer was expecting "+r.length+" weights. Provided weights: "+e+"...");if(0!==r.length){for(var n=[],a=batchGetValue(r),o=0;o<a.length;++o){var i=a[o],s=r[o],u=e[o];if(!arraysEqual(i.shape,u.shape))throw new ValueError("Layer weight shape "+i.shape+" not compatible with provided weight shape "+u.shape);n.push([s,u])}batchSetValue(n)}})},t.prototype.addWeight=function(e,t,r,n,a,o,i){if(-1!==this._addedWeightNames.indexOf(e))throw new ValueError("Duplicate weight name "+e+" for layer "+this.name);this._addedWeightNames.push(e),null==r&&(r=floatx());var s=new LayerVariable(n.apply(t,r),r,e,o,i);return null!=a&&this.addLoss(function(){return a.apply(s.read())}),null==o&&(o=!0),o?this._trainableWeights.push(s):this._nonTrainableWeights.push(s),s},t.prototype.addLoss=function(e){if(!(null==e||Array.isArray(e)&&0===e.length)){e=toList(e),void 0!==this._losses&&null!==this._losses&&(t=this.losses).push.apply(t,e);var t}},t.prototype.computeOutputShape=function(e){return e},t.prototype.computeMask=function(e,t){var r=this;if(!this.supportsMasking){if(null!=t){if(!Array.isArray(t))throw new TypeError("Layer "+this.name+" does not support masking,but was passed an inputMask.");t.forEach(function(e){if(null!=e)throw new TypeError("Layer "+r.name+" does not support masking,but was passed an inputMask.")})}return null}return t},t.prototype.addInboundNode=function(e,t,r,n,a,o,i){void 0===i&&(i=null);var s=toList(e);t=toList(t),r=toList(r),n=toList(n),a=normalizeShapeList(a),o=normalizeShapeList(o);for(var u=[],l=[],c=[],p=0,d=s;p<d.length;p++){var h=d[p];u.push(h.sourceLayer),l.push(h.nodeIndex),c.push(h.tensorIndex)}new Node({outboundLayer:this,inboundLayers:u,nodeIndices:l,tensorIndices:c,inputTensors:s,outputTensors:t,inputMasks:r,outputMasks:n,inputShapes:a,outputShapes:o},i);for(var f=0;f<t.length;f++)t[f].sourceLayer=this,t[f].nodeIndex=this.inboundNodes.length-1,t[f].tensorIndex=f},t.prototype.getConfig=function(){var e={name:this.name,trainable:this.trainable};return null!=this.batchInputShape&&(e.batchInputShape=this.batchInputShape),null!=this.dtype&&(e.dtype=this.dtype),e},__decorate$33([doc()],t.prototype,"apply",null),t=__decorate$33([doc()],t)}(Serializable),InputLayer=function(e){function t(t){var r=e.call(this,{dtype:t.dtype,name:null!=t.name?t.name:getUid("input").toString()})||this;if(null==t.batchSize&&(t.batchSize=null),null==t.sparse&&(t.sparse=!1),r.trainable=!1,r.built=!0,r.sparse=t.sparse,null!=t.inputShape&&null!=t.batchInputShape)throw new ValueError("Only provide the inputShape OR batchInputShape argument to inputLayer, not both at the same time.");var n=t.batchInputShape;if(null==n){if(null==t.inputShape)throw new ValueError("An InputLayer should be passed either a `batchInputShape` or an `inputShape`.");n=[t.batchSize].concat(t.inputShape)}else if(null!=t.batchSize)throw new ValueError("Cannot specify batchSize if batchInputShape isspecified when creating an InputLayer.");var a=t.dtype||floatx();r.batchInputShape=n,r.dtype=a,r.inputSpec=[{shape:n}];var o=new SymbolicTensor(r.dtype,r.batchInputShape,r,[],{},r.name);return o.nodeIndex=0,o.tensorIndex=0,new Node({outboundLayer:r,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:[o],outputTensors:[o],inputMasks:[null],outputMasks:[null],inputShapes:[n],outputShapes:[n]}),r}return __extends$11(t,e),t.prototype.apply=function(e,t){throw new ValueError("Cannot pass any input to an InputLayer's apply() method. InputLayer name: "+this.name)},t.prototype.getConfig=function(){return{batchInputShape:this.batchInputShape,dtype:this.dtype,sparse:this.sparse,name:this.name}},t.className="InputLayer",t}(Layer);SerializationMap.register(InputLayer);var Container=function(e){function t(r){var n=e.call(this,{})||this;if(n.containerNodes=new Set,n.name=r.name,null==n.name){var a=n.getClassName().toLowerCase();n.name=getUid(a)}if(n.supportsMasking=!1,n.trainable=!0,n.updatable=!0,Array.isArray(r.inputs)?n.inputs=r.inputs.slice():n.inputs=[r.inputs],Array.isArray(r.outputs)?n.outputs=r.outputs.slice():n.outputs=[r.outputs],unique(n.inputs).length!==n.inputs.length)throw new ValueError("The list of inputs passed to the model is redundant. All inputs should only appear once. Found: "+n.inputs.map(function(e){return e.name}));unique(n.outputs).length!==n.outputs.length&&console.warn("The list of outputs passed to the model is redundant. All outputs should only appear once. Found: "+n.outputs.map(function(e){return e.name})),n.inputLayers=[],n.inputLayersNodeIndices=[],n.inputLayersTensorIndices=[],n.outputLayers=[],n.outputLayersNodeIndices=[],n.outputLayersTensorIndices=[],n.layers=[];for(var o=0,i=n.outputs;o<i.length;o++){var s=(ee=i[o]).sourceLayer,u=ee.nodeIndex,l=ee.tensorIndex;n.outputLayers.push(s),n.outputLayersNodeIndices.push(u),n.outputLayersTensorIndices.push(l)}for(var c=0,p=n.inputs;c<p.length;c++){var s=(ee=p[c]).sourceLayer,u=ee.nodeIndex,l=ee.tensorIndex;assert$1(0===u,"input layer has >1 nodes"),assert$1(0===l,"input layer has >1 tensors"),n.inputLayers.push(s),n.inputLayersNodeIndices.push(u),n.inputLayersTensorIndices.push(l)}n.inputNames=[],n.outputNames=[],n.feedInputShapes=[],n.feedInputNames=[],n.feedOutputNames=[];for(O=0;O<n.inputLayers.length;O++){if(!((s=n.inputLayers[O])instanceof InputLayer))throw new TypeError("Input layers to a Model must be InputLayer objects. Received inputs: "+r.inputs+". Input "+O+" (0-based) originates from layer type "+s.getClassName()+".");n.inputNames.push(s.name),n.feedInputShapes.push(s.batchInputShape),n.feedInputNames.push(s.name)}for(var d=0,h=n.outputLayers;d<h.length;d++){s=h[d];n.outputNames.push(s.name)}n.internalInputShapes=n.inputs.map(function(e){return e.shape}),n.internalOutputShapes=n.outputs.map(function(e){return e.shape});for(var f={},m={},g={},y={},v={},b=[],x=function(e,r,a,o,i,s){null!=o&&null!=i&&null!=s||(o=e.sourceLayer,i=e.nodeIndex,s=e.tensorIndex);var u=o.inboundNodes[i];if(-1!==a.indexOf(u))throw new RuntimeError("The tensor "+e.name+' at layer "'+o.name+'" is part of a cycle.');if(-1===r.indexOf(u)){n.containerNodes.add(t.nodeKey(o,i)),o.id in v||(v[o.id]=Object.keys(v).length),-1===a.indexOf(u)&&a.push(u);for(var l=u.inboundLayers.length,c=0;c<l;c++){var p=u.inputTensors[c],d=u.inboundLayers[c],h=u.nodeIndices[c],f=u.tensorIndices[c];x(p,r,a,d,h,f)}for(r.push(u);a.indexOf(u)>=0;)a.splice(a.indexOf(u),1);b.push(u)}},w=[],_=[],S=0,N=n.outputs;S<N.length;S++){ee=N[S];x(ee,w,_)}for(var A=0,E=b.slice().reverse();A<E.length;A++){m[(X=E[A]).id]=X,X.id in f||(f[X.id]=0);var T=f[X.id],I=null==g[X.outboundLayer.id]?0:g[X.outboundLayer.id];T=Math.max(T,I),g[X.outboundLayer.id]=T,y[X.outboundLayer.id]=X.outboundLayer,f[X.id]=T;for(var O=0;O<X.inboundLayers.length;O++){var P=X.inboundLayers[O],u=X.nodeIndices[O],R=P.inboundNodes[u],C=null==f[R.id]?0:f[R.id];f[R.id]=Math.max(T+1,C),m[R.id]=R}}var k={};for(var D in f)(T=f[D])in k||(k[T]=[]),k[T].push(m[D]);var M={};for(var L in g)(T=g[L])in M||(M[T]=[]),M[T].push(y[L]);var z=Object.keys(M).map(function(e){return parseInt(e,10)}).sort(reverseNumberCompare);n.layers=[];for(var V=0,F=z;V<F.length;V++){var $=M[T=F[V]];$.sort(function(e,t){var r=v[e.id],n=v[t.id];return r<n?-1:r>n?1:0});for(var B=0,U=$;B<U.length;B++){s=U[B];n.layers.push(s)}}n.layersByDepth=M,z=Object.keys(k).map(function(e){return parseInt(e,10)}).sort(reverseNumberCompare);for(var j=n.inputs.slice(),G=[],W=0,q=z;W<q.length;W++)for(var H=0,K=k[T=q[W]];H<K.length;H++){var X=K[H];if(null!=(s=X.outboundLayer)){for(var J=0,Y=X.inputTensors;J<Y.length;J++){ee=Y[J];if(-1===j.indexOf(ee))throw new RuntimeError("Graph disconnected: cannot obtain value for tensor "+ee+' at layer "'+s.name+'". The following previous layers were accessed without issue: '+G)}for(var Z=0,Q=X.outputTensors;Z<Q.length;Z++){var ee=Q[Z];j.push(ee)}G.push(s.name)}}n.nodesByDepth=k;for(var te=n.layers.map(function(e){return e.name}),re=0,ne=te;re<ne.length;re++)!function(e){var t=te.filter(function(t){return t===e}).length;if(1!==t)throw new RuntimeError('The name "'+e+'" is used '+t+" times in the model. All layer names should be unique. Layer names: "+JSON.stringify(te))}(ne[re]);return n.outboundNodes=[],n.inboundNodes=[],new Node({outboundLayer:n,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:n.inputs,outputTensors:n.outputs,inputMasks:n.inputs.map(function(e){return null}),outputMasks:n.outputs.map(function(e){return null}),inputShapes:n.inputs.map(function(e){return e.shape}),outputShapes:n.outputs.map(function(e){return e.shape})}),n.built=!0,n}return __extends$11(t,e),Object.defineProperty(t.prototype,"trainableWeights",{get:function(){if(this._trainableWeights.length>0)throw new ValueError("Container instance unexpectedly contains _trainableWeights.The trainable weights of a Container are a union of the trainable weights of its consituent Layers. Its own _trainableWeights must remain an empty Array.");if(!this.trainable)return[];for(var e=[],t=0,r=this.layers;t<r.length;t++){var n=r[t];e=e.concat(n.trainableWeights)}return e},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"nonTrainableWeights",{get:function(){for(var e=[],t=0,r=this.layers;t<r.length;t++){i=r[t];e.push.apply(e,i.nonTrainableWeights)}if(!this.trainable){for(var n=[],a=0,o=this.layers;a<o.length;a++){var i=o[a];n.push.apply(n,i.trainableWeights)}return n.concat(e)}return e},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"weights",{get:function(){return this.trainableWeights.concat(this.nonTrainableWeights)},enumerable:!0,configurable:!0}),t.prototype.loadWeights=function(e,t,r){void 0===t&&(t=!1),void 0===r&&(r=!1),r?loadWeightsFromNamedTensorMap(e,this.layers):loadWeightsFromJson(e,this.layers,t)},t.prototype.updatedConfig=function(){var e=this.getConfig();return{className:this.getClassName(),config:e,kerasVersion:"tfjs-layers "+version$1,backend:"TensorFlow.js"}},t.prototype.toJSON=function(e,t){void 0===t&&(t=!0);var r=convertTsToPythonic(this.updatedConfig());return t?JSON.stringify(r):r},t.prototype.call=function(e,t){var r=this;return tidy(function(){e=toList(e);var n;return n="mask"in t?toList(t.mask):pyListRepeat(null,e.length),r.runInternalGraph(e,n)[0]})},t.prototype.computeMask=function(e,t){var r=this;return tidy(function(){e=toList(e);var n;return n=null==t?pyListRepeat(null,e.length):toList(t),r.runInternalGraph(e,n)[1]})},t.prototype.computeOutputShape=function(e){var t=normalizeShapeList(e);if(t.length!==this.inputLayers.length)throw new ValueError("Invalid inputShape argument "+e+": model has "+this.inputLayers.length+" tensor inputs.");for(var r={},n=0;n<t.length;n++){var a=this.inputLayers[n],o=t[n];r[S=a.name+"_0_0"]=o}var i=Object.keys(this.nodesByDepth).map(function(e){return parseInt(e,10)}).sort(reverseNumberCompare);if(i.length>1)for(var s=0,u=i;s<u.length;s++)for(var l=u[s],c=0,p=this.nodesByDepth[l];c<p.length;c++){var d=p[c],a=d.outboundLayer;if(-1===this.inputLayers.map(function(e){return e.id}).indexOf(a.id)){for(var h=[],f=0;f<d.inboundLayers.length;f++){var m=d.inboundLayers[f],g=d.nodeIndices[f],y=d.tensorIndices[f],v=r[S=m.name+"_"+g+"_"+y];h.push(v)}for(var b=normalizeShapeList(a.computeOutputShape(singletonOrArray(h))),x=a.inboundNodes.indexOf(d),f=0;f<b.length;f++)r[S=a.name+"_"+x+"_"+f]=b[f]}}for(var w=[],_=[],n=0;n<this.outputLayers.length;n++){var a=this.outputLayers[n],x=this.outputLayersNodeIndices[n],y=this.outputLayersTensorIndices[n],S=a.name+"_"+x+"_"+y;_.push(S)}for(n=0;n<_.length;n++){var N=_[n];assert$1(N in r),w.push(r[N])}return singletonOrArray(w)},t.prototype.runInternalGraph=function(e,t){null==t&&(t=pyListRepeat(null,e.length));for(var r={},n=0;n<this.inputs.length;++n){var a=this.inputs[n],o=e[n],i=t[n];r[a.id]=[o,i]}for(var s=0,u=Object.keys(this.nodesByDepth).map(function(e){return parseInt(e,10)}).sort(reverseNumberCompare);s<u.length;s++)for(var l=u[s],c=0,p=this.nodesByDepth[l];c<p.length;c++){for(var d=p[c],h=d.outboundLayer,f=d.inputTensors,m=d.outputTensors,g=new Array,y=0,v=f;y<v.length;y++)(a=v[y]).id in r&&g.push(r[a.id]);if(g.length===f.length){var b={},x=void 0,w=void 0,_=void 0,S=void 0;if(null!=d.callArgs&&(b=d.callArgs),1===g.length){var N=g[0],A=N[0],E=N[1];null==b.mask&&(b.mask=E),_=toList(h.call(A,b)),S=toList(h.computeMask(A,E)),x=[A],w=[E]}else x=g.map(function(e){return e[0]}),w=g.map(function(e){return e[1]}),null==b.mask&&(b.mask=w),_=toList(h.call(x,b)),S=toList(h.computeMask(x,w));if(h.activityRegularizer)throw new NotImplementedError("Model invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(n=0;n<m.length;++n){var a=m[n],o=_[n],i=S[n];r[a.id]=[o,i]}}}for(var T=[],I=[],O=[],P=0,R=this.outputs;P<R.length;P++){assert$1((a=R[P]).id in r,"Could not compute output "+a.name+" : "+a.id);var C=r[a.id],k=C[0],i=C[1];O.push(k.shape),T.push(k),I.push(i)}return[T,I,O]},t.prototype.buildNodeConversionMap=function(e){for(var r,n={},a=0,o=this.layers;a<o.length;a++){var i=o[a];r=i instanceof t?1:0;for(var s=0;s<i.inboundNodes.length;s++){var u=t.nodeKey(i,s);u in this.containerNodes&&(n[u]=r,r+=1)}}return n},t.prototype.getLayer=function(e,t){if(null!=t){if(this.layers.length<=t)throw new ValueError("Was asked to retrieve layer at index "+t+", but model only has "+this.layers.length+" layer(s).");return this.layers[t]}if(null==e)throw new ValueError("Provide either a layer name or layer index");for(var r=0,n=this.layers;r<n.length;r++){var a=n[r];if(a.name===e)return a}throw new ValueError("No such layer: "+e)},t.prototype.calculateLosses=function(){var e=this;return tidy(function(){for(var r=[],n=0,a=e.layers;n<a.length;n++)for(var 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m=o.concat(i),this.checkTrainableWeightsConsistency(),g=function(e){var t=e.slice(0,_.inputs.length),r=e.slice(_.inputs.length,_.inputs.length+_.outputs.length),n=[],a=_.collectedTrainableWeights.map(function(e){return e.read()});return[_.optimizer.minimize(function(){for(var e=[],a=0;a<_.inputs.length;++a)e.push({key:_.inputs[a],value:t[a]});for(var o,i=new FeedDict(e),s=execute(_.outputs,i,{training:!0}),a=0;a<_.lossFunctions.length;++a){var u=(0,_.lossFunctions[a])(r[a],s[a]);mean(u),o=0===a?u:add(o,u)}for(a=0;a<_.metricsTensors.length;++a){var l=_.metricsTensors[a][0],c=_.metricsTensors[a][1],p=mean(l(r[c],s[c]));keep(p),n.push(p)}return 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__extends$14(t,e),t.prototype.getClassName=function(){return VarianceScaling.className},t}(VarianceScaling),GlorotNormal=function(e){function t(t){return e.call(this,{scale:1,mode:"fanAvg",distribution:"normal",seed:null==t?null:t.seed})||this}return __extends$14(t,e),t.prototype.getClassName=function(){return VarianceScaling.className},t}(VarianceScaling),HeNormal=function(e){function t(t){return e.call(this,{scale:2,mode:"fanIn",distribution:"normal",seed:null==t?null:t.seed})||this}return __extends$14(t,e),t.prototype.getClassName=function(){return VarianceScaling.className},t}(VarianceScaling),LeCunNormal=function(e){function t(t){return e.call(this,{scale:1,mode:"fanIn",distribution:"normal",seed:null==t?null:t.seed})||this}return __extends$14(t,e),t.prototype.getClassName=function(){return VarianceScaling.className},t}(VarianceScaling),Orthogonal=function(e){function t(t){var r=e.call(this)||this;if(r.DEFAULT_GAIN=1,r.gain=null==t.gain?r.DEFAULT_GAIN:t.gain,r.seed=t.seed,null!=r.seed)throw new NotImplementedError("Random seed is not implemented for Orthogonal Initializer yet.");return r}return __extends$14(t,e),t.prototype.apply=function(e,t){var r=this;return tidy(function(){if(2!==e.length)throw new NotImplementedError("The Orthogonal Initializer does not support non-2D shapes yet.");e[0]*e[1]>2e3&&console.warn("Orthogonal initializer is being called on a matrix with more than 2000 ("+e[0]*e[1]+") elements: Slowness may result.");var t=randomNormal$1(e[0]>e[1]?[e[1],e[0]]:e,0,1,"float32"),n=linalg.gramSchmidt(t);return e[0]>e[1]&&(n=n.transpose()),scalarTimesArray(getScalar(r.gain),n)})},t.prototype.getConfig=function(){return{gain:this.gain,seed:this.seed}},t.className="Orthogonal",t}(Initializer);SerializationMap.register(Orthogonal);var INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP={constant:"Constant",glorotNormal:"GlorotNormal",glorotUniform:"GlorotUniform",heNormal:"HeNormal",identity:"Identity",leCunNormal:"LeCunNormal",ones:"Ones",orthogonal:"Orthogonal",randomNormal:"RandomNormal",randomUniform:"RandomUniform",truncatedNormal:"TruncatedNormal",varianceScaling:"VarianceScaling",zeros:"Zeros"},__extends$15=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)t.hasOwnProperty(r)&&(e[r]=t[r])};return function(t,r){function n(){this.constructor=t}e(t,r),t.prototype=null===r?Object.create(r):(n.prototype=r.prototype,new n)}}(),Activation=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$15(t,e),t.prototype.getConfig=function(){return{}},t}(Serializable),Elu=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$15(t,e),t.prototype.apply=function(e,t){return void 0===t&&(t=1),elu$1(e,t)},t.className="elu",t}(Activation);SerializationMap.register(Elu);var Selu=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$15(t,e),t.prototype.apply=function(e){return selu(e)},t.className="selu",t}(Activation);SerializationMap.register(Selu);var Relu=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$15(t,e),t.prototype.apply=function(e){return relu(e)},t.className="relu",t}(Activation);SerializationMap.register(Relu);var Relu6=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$15(t,e),t.prototype.apply=function(e){return tidy(function(){return minimum(getScalar(6),relu(e))})},t.className="relu6",t}(Activation);SerializationMap.register(Relu6);var Linear=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$15(t,e),t.prototype.apply=function(e){return e},t.className="linear",t}(Activation);SerializationMap.register(Linear);var Sigmoid=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$15(t,e),t.prototype.apply=function(e){return sigmoid(e)},t.className="sigmoid",t}(Activation);SerializationMap.register(Sigmoid);var HardSigmoid=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$15(t,e),t.prototype.apply=function(e){return hardSigmoid(e)},t.className="hardSigmoid",t}(Activation);SerializationMap.register(HardSigmoid);var Softplus=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$15(t,e),t.prototype.apply=function(e){return softplus(e)},t.className="softplus",t}(Activation);SerializationMap.register(Softplus);var Softsign=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$15(t,e),t.prototype.apply=function(e){return softsign(e)},t.className="softsign",t}(Activation);SerializationMap.register(Softsign);var Tanh=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$15(t,e),t.prototype.apply=function(e){return tanh$1(e)},t.className="tanh",t}(Activation);SerializationMap.register(Tanh);var Softmax=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$15(t,e),t.prototype.apply=function(e,t){return void 0===t&&(t=-1),softmax(e,t)},t.className="softmax",t}(Activation);SerializationMap.register(Softmax);var __extends$16=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)t.hasOwnProperty(r)&&(e[r]=t[r])};return function(t,r){function n(){this.constructor=t}e(t,r),t.prototype=null===r?Object.create(r):(n.prototype=r.prototype,new n)}}(),LeakyReLU=function(e){function t(t){var r=e.call(this,null==t?{}:t)||this;return r.DEFAULT_ALPHA=.3,null==t&&(t={}),r.alpha=null==t.alpha?r.DEFAULT_ALPHA:t.alpha,r}return __extends$16(t,e),t.prototype.call=function(e,t){var r=getExactlyOneTensor(e);return leakyRelu(r,this.alpha)},t.prototype.computeOutputShape=function(e){return e},t.prototype.getConfig=function(){var t={alpha:this.alpha},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="LeakyReLU",t}(Layer);SerializationMap.register(LeakyReLU);var ELU$1=function(e){function t(t){var r=e.call(this,null==t?{}:t)||this;if(r.DEFAULT_ALPHA=1,null==t&&(t={}),null!=t.alpha&&t.alpha!==r.DEFAULT_ALPHA)throw new NotImplementedError("Non-default alpha value ("+t.alpha+") is not supported by the ELU layer yet.");return r.alpha=null==t.alpha?r.DEFAULT_ALPHA:t.alpha,r}return __extends$16(t,e),t.prototype.call=function(e,t){var r=getExactlyOneTensor(e);return elu(r)},t.prototype.computeOutputShape=function(e){return e},t.prototype.getConfig=function(){var t={alpha:this.alpha},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="ELU",t}(Layer);SerializationMap.register(ELU$1);var ThresholdedReLU=function(e){function t(t){var r=e.call(this,null==t?{}:t)||this;return r.DEFAULT_THETA=1,null==t&&(t={}),r.theta=null==t.theta?r.DEFAULT_THETA:t.theta,r.thetaTensor=getScalar(r.theta),r}return __extends$16(t,e),t.prototype.call=function(e,t){var r=getExactlyOneTensor(e);return r.mul(cast$1(r.greater(this.thetaTensor),"float32"))},t.prototype.computeOutputShape=function(e){return e},t.prototype.getConfig=function(){var t={theta:this.theta},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="ThresholdedReLU",t}(Layer);SerializationMap.register(ThresholdedReLU);var Softmax$1=function(e){function t(t){var r=e.call(this,null==t?{}:t)||this;return r.DEFAULT_AXIS=1,null==t&&(t={}),r.softmax=(new Softmax).apply,r.axis=null==t.axis?r.DEFAULT_AXIS:t.axis,r}return __extends$16(t,e),t.prototype.call=function(e,t){var r=getExactlyOneTensor(e);return this.softmax(r,this.axis)},t.prototype.computeOutputShape=function(e){return e},t.prototype.getConfig=function(){var t={axis:this.axis},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="Softmax",t}(Layer);SerializationMap.register(Softmax$1);var __extends$17=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)t.hasOwnProperty(r)&&(e[r]=t[r])};return function(t,r){function n(){this.constructor=t}e(t,r),t.prototype=null===r?Object.create(r):(n.prototype=r.prototype,new n)}}(),__decorate$36=function(e,t,r,n){var a,o=arguments.length,i=o<3?t:null===n?n=Object.getOwnPropertyDescriptor(t,r):n;if("object"==typeof Reflect&&"function"==typeof Reflect.decorate)i=Reflect.decorate(e,t,r,n);else for(var s=e.length-1;s>=0;s--)(a=e[s])&&(i=(o<3?a(i):o>3?a(t,r,i):a(t,r))||i);return o>3&&i&&Object.defineProperty(t,r,i),i},Regularizer=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$17(t,e),t}(Serializable),L1L2=function(e){function t(t){var r=e.call(this)||this,n=null==t||null==t.l1?.01:t.l1,a=null==t||null==t.l2?.01:t.l2;return r.hasL1=0!==n,r.hasL2=0!==a,r.l1=getScalar(n),r.l2=getScalar(a),r}return __extends$17(t,e),t.prototype.apply=function(e){var t=this;return tidy(function(){var r=zeros([1]);return t.hasL1&&(r=add(r,sum(scalarTimesArray(t.l1,abs(e))))),t.hasL2&&(r=add(r,sum(scalarTimesArray(t.l2,square$1(e))))),r.asScalar()})},t.prototype.getConfig=function(){return{l1:this.l1.dataSync()[0],l2:this.l2.dataSync()[0]}},t.fromConfig=function(e,t){return new e({l1:t.l1,l2:t.l2})},t.className="L1L2",t=__decorate$36([doc()],t)}(Regularizer);SerializationMap.register(L1L2);var REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP={l1l2:"L1L2"},__extends$18=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)t.hasOwnProperty(r)&&(e[r]=t[r])};return function(t,r){function n(){this.constructor=t}e(t,r),t.prototype=null===r?Object.create(r):(n.prototype=r.prototype,new n)}}(),Conv=function(e){function t(t,r){var n=e.call(this,r)||this;if(n.kernel=null,n.bias=null,n.DEFAULT_KERNEL_INITIALIZER="glorotNormal",n.DEFAULT_BIAS_INITIALIZER="zeros",n.rank=t,1!==n.rank&&2!==n.rank)throw new NotImplementedError("Convolution layer for rank other than 1 or 2 ("+n.rank+") is not implemented yet.");if(n.filters=r.filters,n.kernelSize=normalizeArray(r.kernelSize,t,"kernelSize"),n.strides=normalizeArray(null==r.strides?1:r.strides,t,"strides"),n.padding=null==r.padding?"valid":r.padding,checkPaddingMode(n.padding),n.dataFormat=null==r.dataFormat?"channelsLast":r.dataFormat,checkDataFormat(n.dataFormat),n.dilationRate=null==r.dilationRate?1:r.dilationRate,1===n.rank&&Array.isArray(n.dilationRate)&&1!==n.dilationRate.length)throw new ValueError("dilationRate must be a number or an array of a single number for 1D convolution, but received "+JSON.stringify(n.dilationRate));if(2===n.rank)if("number"==typeof n.dilationRate)n.dilationRate=[n.dilationRate,n.dilationRate];else if(2!==n.dilationRate.length)throw new ValueError("dilationRate must be a number or array of two numbers for 2D convolution, but received "+JSON.stringify(n.dilationRate));return n.activation=getActivation(r.activation),n.useBias=null==r.useBias||r.useBias,n.kernelInitializer=getInitializer(r.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.biasInitializer=getInitializer(r.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.kernelConstraint=getConstraint(r.kernelConstraint),n.biasConstraint=getConstraint(r.biasConstraint),n.kernelRegularizer=getRegularizer(r.kernelRegularizer),n.biasRegularizer=getRegularizer(r.biasRegularizer),n.activityRegularizer=getRegularizer(r.activityRegularizer),n}return __extends$18(t,e),t.prototype.build=function(e){e=getExactlyOneShape(e);var t="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[t])throw new ValueError("The channel dimension of the input should be defined. Found "+e[t]);var r=e[t],n=this.kernelSize.concat([r,this.filters]);this.kernel=this.addWeight("kernel",n,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:(a={},a[t]=r,a)}],this.built=!0;var a},t.prototype.call=function(e,t){var r=this;return tidy(function(){e=getExactlyOneTensor(e);var t,n=null==r.bias?null:r.bias.read();if(1===r.rank)t=conv1dWithBias(e,r.kernel.read(),n,r.strides[0],r.padding,r.dataFormat,r.dilationRate);else if(2===r.rank)t=conv2dWithBias(e,r.kernel.read(),n,r.strides,r.padding,r.dataFormat,r.dilationRate);else if(3===r.rank)throw new NotImplementedError("3D convolution is not implemented yet.");return null!=r.activation&&(t=r.activation.apply(t)),t})},t.prototype.computeOutputShape=function(e){e=getExactlyOneShape(e);for(var t=[],r="channelsLast"===this.dataFormat?e.slice(1,e.length-1):e.slice(2),n=0;n<r.length;++n){var a=convOutputLength(r[n],this.kernelSize[n],this.padding,this.strides[n],"number"==typeof this.dilationRate?this.dilationRate:this.dilationRate[n]);t.push(a)}var o=[e[0]];return"channelsLast"===this.dataFormat?(o=o.concat(t)).push(this.filters):(o.push(this.filters),o=o.concat(t)),o},t.prototype.getConfig=function(){var t={rank:this.rank,filters:this.filters,kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:serializeInitializer(this.kernelInitializer),biasInitializer:serializeInitializer(this.biasInitializer),kernelRegularizer:serializeRegularizer(this.kernelRegularizer),biasRegularizer:serializeRegularizer(this.biasRegularizer),activityRegularizer:serializeRegularizer(this.activityRegularizer),kernelConstraint:serializeConstraint(this.kernelConstraint),biasConstraint:serializeConstraint(this.biasConstraint)},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t}(Layer),Conv2D=function(e){function t(t){return e.call(this,2,t)||this}return __extends$18(t,e),t.prototype.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.rank,t},t.className="Conv2D",t}(Conv);SerializationMap.register(Conv2D);var Conv2DTranspose=function(e){function t(t){var r=e.call(this,t)||this;if(r.inputSpec=[new InputSpec({ndim:4})],"same"!==r.padding&&"valid"!==r.padding)throw new ValueError("Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode "+r.padding);return r}return __extends$18(t,e),t.prototype.build=function(e){if(4!==(e=getExactlyOneShape(e)).length)throw new ValueError("Input should have rank 4; Received input shape: "+JSON.stringify(e));var t="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[t])throw new ValueError("The channel dimension of the inputs should be defined. Found `None`.");var r=e[t],n=this.kernelSize.concat([this.filters,r]);this.kernel=this.addWeight("kernel",n,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new InputSpec({ndim:4,axes:(a={},a[t]=r,a)})],this.built=!0;var a},t.prototype.call=function(e,t){var r=this;return tidy(function(){var t=getExactlyOneTensor(e);if(4!==t.shape.length)throw new ValueError("Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-"+t.shape.length);var n,a,o=t.shape,i=o[0];"channelsFirst"===r.dataFormat?(n=2,a=3):(n=1,a=2);var s=o[n],u=o[a],l=r.kernelSize[0],c=r.kernelSize[1],p=r.strides[0],d=r.strides[1],h=[i,deconvLength(s,p,l,r.padding),deconvLength(u,d,c,r.padding),r.filters];"channelsLast"!==r.dataFormat&&(t=transpose(t,[0,2,3,1]));var f=conv2dTranspose(t,r.kernel.read(),h,r.strides,r.padding);return"channelsLast"!==r.dataFormat&&(f=transpose(f,[0,3,1,2])),null!=r.bias&&(f=biasAdd(f,r.bias.read(),r.dataFormat)),null!=r.activation&&(f=r.activation.apply(f)),f})},t.prototype.computeOutputShape=function(e){var t,r,n,a=(e=getExactlyOneShape(e)).slice();"channelsFirst"===this.dataFormat?(t=1,r=2,n=3):(t=3,r=1,n=2);var o=this.kernelSize[0],i=this.kernelSize[1],s=this.strides[0],u=this.strides[1];return a[t]=this.filters,a[r]=deconvLength(a[r],s,o,this.padding),a[n]=deconvLength(a[n],u,i,this.padding),a},t.prototype.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.dilationRate,t},t.className="Conv2DTranspose",t}(Conv2D);SerializationMap.register(Conv2DTranspose);var SeparableConv=function(e){function t(t,r){var n=e.call(this,t,r)||this;if(n.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",n.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",n.depthwiseKernel=null,n.pointwiseKernel=null,null==r.filters)throw new ValueError("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(null!=r.kernelInitializer||null!=r.kernelRegularizer||null!=r.kernelConstraint)throw new ValueError("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(null!=r.padding&&"same"!==r.padding&&"valid"!==r.padding)throw new ValueError("SeparableConv"+n.rank+"D supports only padding modes: 'same' and 'valid', but received "+JSON.stringify(r.padding));return n.depthMultiplier=null==r.depthMultiplier?1:r.depthMultiplier,n.depthwiseInitializer=getInitializer(r.depthwiseInitializer||n.DEFAULT_DEPTHWISE_INITIALIZER),n.depthwiseRegularizer=getRegularizer(r.depthwiseRegularizer),n.depthwiseConstraint=getConstraint(r.depthwiseConstraint),n.pointwiseInitializer=getInitializer(r.depthwiseInitializer||n.DEFAULT_POINTWISE_INITIALIZER),n.pointwiseRegularizer=getRegularizer(r.pointwiseRegularizer),n.pointwiseConstraint=getConstraint(r.pointwiseConstraint),n}return __extends$18(t,e),t.prototype.build=function(e){if((e=getExactlyOneShape(e)).length<this.rank+2)throw new ValueError("Inputs to SeparableConv"+this.rank+"D should have rank "+(this.rank+2)+", but received input shape: "+JSON.stringify(e));var t="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[t]||e[t]<0)throw new ValueError("The channel dimension of the inputs should be defined, but found "+JSON.stringify(e[t]));for(var r=e[t],n=this.kernelSize.concat([r,this.depthMultiplier]),a=[],o=0;o<this.rank;++o)a.push(1);a.push(r*this.depthMultiplier,this.filters);this.depthwiseKernel=this.addWeight("depthwise_kernel",n,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,!0,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.inputSpec=[new InputSpec({ndim:this.rank+2,axes:(i={},i[t]=r,i)})],this.built=!0;var i},t.prototype.call=function(e,t){var r=this;return tidy(function(){e=getExactlyOneTensor(e);var t;if(1===r.rank)throw new NotImplementedError("1D separable convolution is not implemented yet.");return 2===r.rank&&("channelsFirst"===r.dataFormat&&(e=transpose(e,[0,2,3,1])),t=separableConv2d(e,r.depthwiseKernel.read(),r.pointwiseKernel.read(),r.strides,r.padding,r.dilationRate,"NHWC")),r.useBias&&(t=biasAdd(t,r.bias.read(),r.dataFormat)),null!=r.activation&&(t=r.activation.apply(t)),"channelsFirst"===r.dataFormat&&(t=transpose(t,[0,3,1,2])),t})},t.prototype.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.rank,delete t.kernelInitializer,delete t.kernelRegularizer,delete t.kernelConstraint,t.depthwiseInitializer=serializeInitializer(this.depthwiseInitializer),t.pointwiseInitializer=serializeInitializer(this.pointwiseInitializer),t.depthwiseRegularizer=serializeRegularizer(this.depthwiseRegularizer),t.pointwiseRegularizer=serializeRegularizer(this.pointwiseRegularizer),t.depthwiseConstraint=serializeConstraint(this.depthwiseConstraint),t.pointwiseConstraint=serializeConstraint(this.pointwiseConstraint),t},t.className="SeparableConv",t}(Conv),SeparableConv2D=function(e){function t(t){return e.call(this,2,t)||this}return __extends$18(t,e),t.className="SeparableConv2D",t}(SeparableConv);SerializationMap.register(SeparableConv2D);var Conv1D=function(e){function t(t){var r=e.call(this,1,t)||this;return r.inputSpec=[{ndim:3}],r}return __extends$18(t,e),t.prototype.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.rank,delete t.dataFormat,t},t.className="Conv1D",t}(Conv);SerializationMap.register(Conv1D);var Cropping2D=function(e){function t(t){var r=e.call(this,t)||this;return"number"==typeof t.cropping?r.cropping=[[t.cropping,t.cropping],[t.cropping,t.cropping]]:"number"==typeof t.cropping[0]?r.cropping=[[t.cropping[0],t.cropping[0]],[t.cropping[1],t.cropping[1]]]:r.cropping=t.cropping,r.dataFormat=void 0===t.dataFormat?"channelsLast":t.dataFormat,r.inputSpec=[{ndim:4}],r}return __extends$18(t,e),t.prototype.computeOutputShape=function(e){return"channelsFirst"===this.dataFormat?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]},t.prototype.call=function(e,t){var r=this;return tidy(function(){if(e=getExactlyOneTensor(e),"channelsLast"===r.dataFormat)return sliceAlongAxis(t=sliceAlongAxis(e,r.cropping[0][0],e.shape[1]-r.cropping[0][0]-r.cropping[0][1],2),r.cropping[1][0],e.shape[2]-r.cropping[1][1]-r.cropping[1][0],3);var t=sliceAlongAxis(e,r.cropping[0][0],e.shape[2]-r.cropping[0][0]-r.cropping[0][1],3);return sliceAlongAxis(t,r.cropping[1][0],e.shape[3]-r.cropping[1][1]-r.cropping[1][0],4)})},t.prototype.getConfig=function(){var t={cropping:this.cropping,dataFormat:this.dataFormat},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="Cropping2D",t}(Layer);SerializationMap.register(Cropping2D);var UpSampling2D=function(e){function t(t){var r=e.call(this,t)||this;return r.DEFAULT_SIZE=[2,2],r.inputSpec=[{ndim:4}],r.size=void 0===t.size?r.DEFAULT_SIZE:t.size,r.dataFormat=void 0===t.dataFormat?"channelsLast":t.dataFormat,r}return __extends$18(t,e),t.prototype.computeOutputShape=function(e){if("channelsFirst"===this.dataFormat){var t=this.size[0]*e[2],r=this.size[1]*e[3];return[e[0],e[1],t,r]}var t=this.size[0]*e[1],r=this.size[1]*e[2];return[e[0],t,r,e[3]]},t.prototype.call=function(e,t){var r=this;return tidy(function(){var t=getExactlyOneTensor(e),n=t.shape;if("channelsFirst"===r.dataFormat){t=transpose(t,[0,2,3,1]);var a=r.size[0]*n[2],o=r.size[1]*n[3],i=t.resizeNearestNeighbor([a,o]);return transpose(i,[0,3,1,2])}var a=r.size[0]*n[1],o=r.size[1]*n[2];return t.resizeNearestNeighbor([a,o])})},t.prototype.getConfig=function(){var t={size:this.size,dataFormat:this.dataFormat},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="UpSampling2D",t}(Layer);SerializationMap.register(UpSampling2D);var __extends$19=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)t.hasOwnProperty(r)&&(e[r]=t[r])};return function(t,r){function n(){this.constructor=t}e(t,r),t.prototype=null===r?Object.create(r):(n.prototype=r.prototype,new n)}}(),DepthwiseConv2D=function(e){function t(t){var r=e.call(this,t)||this;return r.depthwiseKernel=null,r.depthMultiplier=null==t.depthMultiplier?1:t.depthMultiplier,r.depthwiseInitializer=getInitializer(t.depthwiseInitializer||r.DEFAULT_KERNEL_INITIALIZER),r.depthwiseConstraint=getConstraint(t.depthwiseConstraint),r.depthwiseRegularizer=getRegularizer(t.depthwiseRegularizer),r}return __extends$19(t,e),t.prototype.build=function(e){if((e=getExactlyOneShape(e)).length<4)throw new ValueError("Inputs to DepthwiseConv2D should have rank 4. Received input shape: "+JSON.stringify(e)+".");var t="channelsFirst"===this.dataFormat?1:3;if(null==e[t]||e[t]<0)throw new ValueError("The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not ("+e[t]+").");var r=e[t],n=[this.kernelSize[0],this.kernelSize[1],r,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",n,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[r*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0},t.prototype.call=function(e,t){var r=this;return tidy(function(){var t=depthwiseConv2d$1(e=getExactlyOneTensor(e),r.depthwiseKernel.read(),r.strides,r.padding,r.dataFormat,null);return r.useBias&&(t=biasAdd(t,r.bias.read(),r.dataFormat)),null!=r.activation&&(t=r.activation.apply(t)),t})},t.prototype.computeOutputShape=function(e){e=getExactlyOneShape(e);var t="channelsFirst"===this.dataFormat?e[2]:e[1],r="channelsFirst"===this.dataFormat?e[3]:e[2],n="channelsFirst"===this.dataFormat?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=convOutputLength(t,this.kernelSize[0],this.padding,this.strides[0]),o=convOutputLength(r,this.kernelSize[1],this.padding,this.strides[1]);return"channelsFirst"===this.dataFormat?[e[0],n,a,o]:[e[0],a,o,n]},t.className="DepthwiseConv2D",t}(Conv2D);SerializationMap.register(DepthwiseConv2D);var __extends$20=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)t.hasOwnProperty(r)&&(e[r]=t[r])};return function(t,r){function n(){this.constructor=t}e(t,r),t.prototype=null===r?Object.create(r):(n.prototype=r.prototype,new n)}}(),Dropout=function(e){function t(t){var r=e.call(this,t)||this;if(r.rate=Math.max(Math.min(t.rate,1),0),r.rateScalar=getScalar(r.rate),r.noiseShape=t.noiseShape,r.seed=t.seed,null!=r.seed)throw new NotImplementedError("Non-default seed is not implemented in Dropout layer yet: "+r.seed);return r.supportsMasking=!0,r}return __extends$20(t,e),t.prototype.getNoiseShape=function(e){if(null==this.noiseShape)return this.noiseShape;for(var t=e.shape,r=[],n=0;n<this.noiseShape.length;++n)r.push(null==this.noiseShape[n]?t[n]:this.noiseShape[n]);return r},t.prototype.call=function(e,t){var r=this;return tidy(function(){r.invokeCallHook(e,t);var n=getExactlyOneTensor(e);if(null!=r.noiseShape&&!arraysEqual(n.shape,r.noiseShape))throw new NotImplementedError("Non-default noise shape is not implemented in Dropout layer yet: "+JSON.stringify(r.noiseShape));if(0<r.rate&&r.rate<1){var a=null!=t.training&&t.training,o=r.getNoiseShape(n);return inTrainPhase(function(){return dropout(n,r.rateScalar,o,r.seed)},function(){return n},a)}return e})},t.prototype.getConfig=function(){var t={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="Dropout",t}(Layer);SerializationMap.register(Dropout);var Dense=function(e){function t(t){var r=e.call(this,t)||this;if(r.activation=null,r.useBias=!0,r.kernel=null,r.bias=null,r.DEFAULT_KERNEL_INITIALIZER="glorotNormal",r.DEFAULT_BIAS_INITIALIZER="zeros",null==t.batchInputShape&&null==t.inputShape&&null!=t.inputDim){var n=null;null!=t.batchSize&&(n=t.batchSize),r.batchInputShape=[n,t.inputDim]}return r.units=t.units,r.activation=getActivation(t.activation),null!=t.useBias&&(r.useBias=t.useBias),r.kernelInitializer=getInitializer(t.kernelInitializer||r.DEFAULT_KERNEL_INITIALIZER),r.biasInitializer=getInitializer(t.biasInitializer||r.DEFAULT_BIAS_INITIALIZER),r.kernelConstraint=getConstraint(t.kernelConstraint),r.biasConstraint=getConstraint(t.biasConstraint),r.kernelRegularizer=getRegularizer(t.kernelRegularizer),r.biasRegularizer=getRegularizer(t.biasRegularizer),r.activityRegularizer=getRegularizer(t.activityRegularizer),r.inputSpec=[{minNDim:2}],r}return __extends$20(t,e),t.prototype.build=function(e){var t=(e=getExactlyOneShape(e))[e.length-1];null==this.kernel&&(this.kernel=this.addWeight("kernel",[t,this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint))),this.inputSpec=[{minNDim:2,axes:(r={},r[-1]=t,r)}],this.built=!0;var r},t.prototype.computeOutputShape=function(e){var t=(e=getExactlyOneShape(e)).slice();return t[t.length-1]=this.units,t},t.prototype.call=function(e,t){var r=this;return tidy(function(){r.invokeCallHook(e,t);var n=dot$1(getExactlyOneTensor(e),r.kernel.read());return null!=r.bias&&(n=biasAdd(n,r.bias.read())),null!=r.activation&&(n=r.activation.apply(n)),n})},t.prototype.getConfig=function(){var t={units:this.units,activation:serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:serializeInitializer(this.kernelInitializer),biasInitializer:serializeInitializer(this.biasInitializer),kernelRegularizer:serializeRegularizer(this.kernelRegularizer),biasRegularizer:serializeRegularizer(this.biasRegularizer),activityRegularizer:serializeRegularizer(this.activityRegularizer),kernelConstraint:serializeConstraint(this.kernelConstraint),biasConstraint:serializeConstraint(this.biasConstraint)},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="Dense",t}(Layer);SerializationMap.register(Dense);var Flatten=function(e){function t(t){var r=e.call(this,t||{})||this;return r.inputSpec=[{minNDim:3}],r}return __extends$20(t,e),t.prototype.computeOutputShape=function(e){for(var t=0,r=(e=getExactlyOneShape(e)).slice(1);t<r.length;t++)if(null==r[t])throw new ValueError('The shape of the input to "Flatten" is not fully defined (got '+e.slice(1)+'). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.');return[e[0],arrayProd(e,1)]},t.prototype.call=function(e,t){var r=this;return tidy(function(){return r.invokeCallHook(e,t),batchFlatten(getExactlyOneTensor(e))})},t.className="Flatten",t}(Layer);SerializationMap.register(Flatten);var Activation$1=function(e){function t(t){var r=e.call(this,t)||this;return r.supportsMasking=!0,r.activation=getActivation(t.activation),r}return __extends$20(t,e),t.prototype.call=function(e,t){var r=this;return tidy(function(){r.invokeCallHook(e,t);var n=getExactlyOneTensor(e);return r.activation.apply(n)})},t.prototype.getConfig=function(){var t={activation:serializeActivation(this.activation)},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="Activation",t}(Layer);SerializationMap.register(Activation$1);var RepeatVector=function(e){function t(t){var r=e.call(this,t)||this;return r.n=t.n,r.inputSpec=[{ndim:2}],r}return __extends$20(t,e),t.prototype.computeOutputShape=function(e){return[e[0],this.n,e[1]]},t.prototype.call=function(e,t){var r=this;return tidy(function(){return e=getExactlyOneTensor(e),repeat(e,r.n)})},t.prototype.getConfig=function(){var t={n:this.n},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="RepeatVector",t}(Layer);SerializationMap.register(RepeatVector);var Reshape=function(e){function t(t){var r=e.call(this,t)||this;r.targetShape=t.targetShape;for(var n=0;n<r.targetShape.length;++n)r.isUnknown(r.targetShape[n])&&(r.targetShape[n]=null);return r}return __extends$20(t,e),t.prototype.isUnknown=function(e){return e<0||null==e},t.prototype.fixUnknownDimension=function(e,t){for(var r="Total size of new array must be unchanged.",n=t.slice(),a=1,o=null,i=0;i<n.length;++i){var s=n[i];if(this.isUnknown(s)){if(null!==o)throw new ValueError("Can only specifiy one unknown dimension.");o=i}else a*=s}var u=arrayProd(e);if(null!==o){if(0===a||u%a!=0)throw new ValueError(r);n[o]=u/a}else if(u!==a)throw new ValueError(r);return n},t.prototype.computeOutputShape=function(e){for(var t=!1,r=0;r<e.length;++r)if(this.isUnknown(e[r])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))},t.prototype.call=function(e,t){var r=this;return tidy(function(){r.invokeCallHook(e,t);var n=getExactlyOneTensor(e),a=shape(n),o=a.slice(0,1).concat(r.fixUnknownDimension(a.slice(1),r.targetShape));return n.reshape(o)})},t.prototype.getConfig=function(){var t={targetShape:this.targetShape},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="Reshape",t}(Layer);SerializationMap.register(Reshape);var __extends$21=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)t.hasOwnProperty(r)&&(e[r]=t[r])};return function(t,r){function n(){this.constructor=t}e(t,r),t.prototype=null===r?Object.create(r):(n.prototype=r.prototype,new n)}}(),Embedding=function(e){function t(t){var r=e.call(this,t)||this;if(r.embeddings=null,r.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",null==t.batchInputShape&&null==t.inputShape){var n=null;null!=t.batchSize&&(n=t.batchSize),null==t.inputLength?r.batchInputShape=[n,null]:r.batchInputShape=[n].concat(toList(t.inputLength))}return r.inputDim=t.inputDim,r.outputDim=t.outputDim,r.embeddingsInitializer=getInitializer(t.embeddingsInitializer||r.DEFAULT_EMBEDDINGS_INITIALIZER),r.embeddingsRegularizer=getRegularizer(t.embeddingsRegularizer),r.activityRegularizer=getRegularizer(t.activityRegularizer),r.embeddingsConstraint=getConstraint(t.embeddingsConstraint),r.maskZero=t.maskZero,r.inputLength=t.inputLength,r}return __extends$21(t,e),t.prototype.build=function(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0},t.prototype.computeMask=function(e,t){throw new NotImplementedError("computeMask has not been implemented for Embedding yet")},t.prototype.computeOutputShape=function(e){if(e=getExactlyOneShape(e),null==this.inputLength)return e.concat([this.outputDim]);var t=toList(this.inputLength);if(t.length!==e.length-1)throw new ValueError('"inputLength" is '+this.inputLength+", but received input shape has shape "+e);for(var r=0,n=0;n<t.length;++n){var a=t[n],o=e[n+1];if(null!=a&&null!=o&&a!==o)throw new ValueError('"inputLength" is '+this.inputLength+", but received input shape has shape "+e);null==a&&(t[r]=o),r++}return[e[0]].concat(t,[this.outputDim])},t.prototype.call=function(e,t){var r=this;return tidy(function(){r.invokeCallHook(e,t);var n=getExactlyOneTensor(e);return"int32"!==dtype(n)&&(n=cast$1(n,"int32")),gather$1(r.embeddings.read(),n.as1D()).reshape(getExactlyOneShape(r.computeOutputShape(n.shape)))})},t.prototype.getConfig=function(){var t={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:serializeInitializer(this.embeddingsInitializer),embeddingsRegularizer:serializeRegularizer(this.embeddingsRegularizer),activityRegularizer:serializeRegularizer(this.activityRegularizer),embeddingsConstraint:serializeConstraint(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="Embedding",t}(Layer);SerializationMap.register(Embedding);var __extends$22=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)t.hasOwnProperty(r)&&(e[r]=t[r])};return function(t,r){function n(){this.constructor=t}e(t,r),t.prototype=null===r?Object.create(r):(n.prototype=r.prototype,new n)}}(),Merge=function(e){function t(t){var r=e.call(this,t||{})||this;return r.supportsMasking=!0,r}return __extends$22(t,e),t.prototype.mergeFunction=function(e){throw new NotImplementedError},t.prototype.computeElementwiseOpOutputShape=function(e,t){if(null==e||null==t)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(0===t.length)return e;for(var r=e.slice(0,e.length-t.length),n=0;n<t.length;++n){var a=e[e.length-t.length+n],o=t[n];if(null==a||null==o||a<0||o<0)r.push(null);else if(1===a)r.push(o);else if(1===o)r.push(a);else{if(a!==o)throw new ValueError("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));r.push(a)}}return r},t.prototype.build=function(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[getExactlyOneShape(e)]),(e=e).length<2)throw new ValueError("A merge layer should be called on an Array of at least 2 inputs. Got "+e.length+" input(s).");for(var t=[],r=0,n=e;r<n.length;r++)null!=(i=n[r])&&null!==i[0]&&t.push(i[0]);if((t=unique(t)).length>1)throw new ValueError("Can not merge tensors with different batch sizes. Got tensors with shapes: "+JSON.stringify(e)+".");for(var a=null==e[0]?null:e[0].slice(1),o=1;o<e.length;++o){var i=null==e[o]?null:e[o].slice(1);a=this.computeElementwiseOpOutputShape(a,i)}var s=e.map(function(e){return e.length});-1===e.indexOf(null)&&1===unique(s).length?this.reshapeRequired=!1:this.reshapeRequired=!0},t.prototype.call=function(e,t){var r=this;return tidy(function(){if(e=e,r.reshapeRequired){var t=[],n=e.map(function(e){return e.rank});if(-1===n.indexOf(null)){for(var a=max$1(n),o=0,i=e;o<i.length;o++){for(var s=(d=i[o]).rank,u=0;u<a-s;++u)d=expandDims$1(d,1);t.push(d)}return r.mergeFunction(t)}for(var l=!1,c=0,p=e;c<p.length;c++){var d=p[c];if(null==(s=d.rank)){var h=shape(d),f=h[0],m=h.slice(1).concat([f]),g=d.reshape([f].concat(arrayProd(h.slice(1))));g=(g=transpose(g,[1,0])).reshape(m),t.push(g),l=!0}else if(s>1){x=range$1(1,s).concat([0]);t.push(transpose(d,x)),l=!0}else t.push(d)}var y=r.mergeFunction(t),v=y.rank;if(l)if(null==v){var b=shape(y),m=[f=b[b.length-1]].concat(b.slice(0,b.length-1));y=transpose(y.reshape([-1,f]),[1,0]).reshape(m)}else if(v>1){var x=[v-1].concat(range$1(0,v-1));y=transpose(y,x)}return y}return r.mergeFunction(e)})},t.prototype.computeOutputShape=function(e){var t;t=null==(e=e)[0]?null:e[0].slice(1);for(var r=1;r<e.length;++r){var n=null==e[r]?null:e[r].slice(1);t=this.computeElementwiseOpOutputShape(t,n)}for(var a=[],o=0,i=e;o<i.length;o++)null!=(n=i[o])&&null!==n[0]&&a.push(n[0]);return a=unique(a),t=1===a.length?a.concat(t):[null].concat(t)},t}(Layer),Add=function(e){function t(t){return e.call(this,t)||this}return __extends$22(t,e),t.prototype.mergeFunction=function(e){return tidy(function(){for(var t=zeros(e[0].shape),r=0,n=e;r<n.length;r++){var a=n[r];t=add(t,a)}return t})},t.className="Add",t}(Merge);SerializationMap.register(Add);var Multiply=function(e){function t(t){return e.call(this,t)||this}return __extends$22(t,e),t.prototype.mergeFunction=function(e){return tidy(function(){for(var t=ones(e[0].shape),r=0,n=e;r<n.length;r++){var a=n[r];t=mul(t,a)}return t})},t.className="Multiply",t}(Merge);SerializationMap.register(Multiply);var Average=function(e){function t(t){return e.call(this,t)||this}return __extends$22(t,e),t.prototype.mergeFunction=function(e){return tidy(function(){for(var t=zeros(e[0].shape),r=0,n=e;r<n.length;r++){var a=n[r];t=add(t,a)}return scalarTimesArray(getScalar(1/e.length),t)})},t.className="Average",t}(Merge);SerializationMap.register(Average);var Maximum=function(e){function t(t){return e.call(this,t)||this}return __extends$22(t,e),t.prototype.mergeFunction=function(e){return tidy(function(){for(var t=e[0],r=1;r<e.length;++r)t=maximum(t,e[r]);return t})},t.className="Maximum",t}(Merge);SerializationMap.register(Maximum);var Minimum=function(e){function t(t){return e.call(this,t)||this}return __extends$22(t,e),t.prototype.mergeFunction=function(e){return tidy(function(){for(var t=e[0],r=1;r<e.length;++r)t=minimum(t,e[r]);return t})},t.className="Minimum",t}(Merge);SerializationMap.register(Minimum);var Concatenate=function(e){function t(t){var r=e.call(this,t)||this;return r.DEFAULT_AXIS=-1,null==t&&(t={}),r.axis=null==t.axis?r.DEFAULT_AXIS:t.axis,r.supportsMasking=!0,r.reshapeRequired=!1,r}return __extends$22(t,e),t.prototype.build=function(e){if(!Array.isArray(e)||!Array.isArray(e[0])||1===e.length)throw new ValueError("A `Concatenate` layer should be called on a list of at least 2 inputs");for(var t=!0,r=0,n=e=e;r<n.length;r++)if(null!=(c=n[r])){t=!1;break}if(!t){for(var a=[],o=0;o<e.length;++o){var i=e[o].slice();i.splice(this.axis,1);for(var s=!1,u=0,l=a;u<l.length;u++){var c=l[u];if(arraysEqual(c,i)){s=!0;break}}s||a.push(i)}if(a.length>1)throw new ValueError("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}},t.prototype.mergeFunction=function(e){var t=this;return tidy(function(){return concatenate(e,t.axis)})},t.prototype.computeOutputShape=function(e){if(!Array.isArray(e)||!Array.isArray(e[0]))throw new ValueError("A `Concatenate` layer should be called on a list of inputs.");for(var t=e,r=t[0].slice(),n=this.axis<0?r.length+this.axis:this.axis,a=0,o=t.slice(1);a<o.length;a++){var i=o[a];if(null==r[n]||null==i[n]){r[n]=null;break}r[n]+=i[n]}return r},t.prototype.getConfig=function(){var t={axis:this.axis},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="Concatenate",t}(Merge);SerializationMap.register(Concatenate);var __extends$23=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)t.hasOwnProperty(r)&&(e[r]=t[r])};return function(t,r){function n(){this.constructor=t}e(t,r),t.prototype=null===r?Object.create(r):(n.prototype=r.prototype,new n)}}(),BatchNormalization=function(e){function t(t){var r=e.call(this,t)||this;return r.supportsMasking=!0,r.axis=null==t.axis?-1:t.axis,r.momentum=null==t.momentum?.99:t.momentum,r.epsilon=null==t.epsilon?.001:t.epsilon,r.center=null==t.center||t.center,r.scale=null==t.scale||t.scale,r.betaInitializer=getInitializer(t.betaInitializer||"zeros"),r.gammaInitializer=getInitializer(t.gammaInitializer||"ones"),r.movingMeanInitializer=getInitializer(t.movingMeanInitializer||"zeros"),r.movingVarianceInitializer=getInitializer(t.movingVarianceInitializer||"ones"),r.betaConstraint=getConstraint(t.betaConstraint),r.gammaConstraint=getConstraint(t.gammaConstraint),r.betaRegularizer=getRegularizer(t.betaRegularizer),r.gammaRegularizer=getRegularizer(t.gammaRegularizer),r.stepCount=0,r}return __extends$23(t,e),t.prototype.build=function(e){e=getExactlyOneShape(e);var t=this.axis>=0?this.axis:this.axis+e.length,r=e[t];if(null==r)throw new ValueError("Axis "+t+" of input tensor should have a defined dimension but the layer received an input with shape "+JSON.stringify(e)+".");this.inputSpec=[new InputSpec({ndim:e.length,axes:(a={},a[t]=r,a)})];var n=[r];this.scale&&(this.gamma=this.addWeight("gamma",n,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",n,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",n,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",n,null,this.movingVarianceInitializer,null,!1),this.built=!0;var a},t.prototype.call=function(e,t){var r=this;return tidy(function(){var n=null!=t.training&&t.training,a=getExactlyOneTensor(e),o=shape(a),i=o.length,s=range$1(0,i),u=r.axis>=0?r.axis:r.axis+i;s.splice(u,1);var l=pyListRepeat(1,i);l[u]=o[u];var c=s.slice();c.sort();var p=!arraysEqual(c,range$1(0,i).slice(0,i-1));if(!n)return function(){if(p){var e=r.movingMean.read().reshape(l),t=r.movingVariance.read().reshape(l),n=r.center?r.beta.read().reshape(l):null,o=r.scale?r.gamma.read().reshape(l):null;return batchNormalization$1(a,e,t,n,o,r.epsilon)}return batchNormalization$1(a,r.movingMean.read(),r.movingVariance.read(),null==r.beta?null:r.beta.read(),null==r.gamma?null:r.gamma.read(),r.epsilon)}();var d=normalizeBatchInTraining(a,r.gamma.read(),r.beta.read(),s,r.epsilon),h=d[0],f=d[1],m=d[2],g=arrayProd(s.map(function(e){return a.shape[e]})),y=m.mul(getScalar(g/(g-(1+r.epsilon))));return function(){r.stepCount++;var e=movingAverage(r.movingMean.read(),f,r.momentum,r.stepCount);r.movingMean.write(e);var t=movingAverage(r.movingVariance.read(),y,r.momentum,r.stepCount);r.movingVariance.write(t)}(),h})},t.prototype.getConfig=function(){var t={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:serializeInitializer(this.betaInitializer),gammaInitializer:serializeInitializer(this.gammaInitializer),movingMeanInitializer:serializeInitializer(this.movingMeanInitializer),movingVarianceInitializer:serializeInitializer(this.movingVarianceInitializer),betaRegularizer:serializeRegularizer(this.betaRegularizer),gammaRegularizer:serializeRegularizer(this.gammaRegularizer),betaConstraint:serializeConstraint(this.betaConstraint),gammaConstraint:serializeConstraint(this.gammaConstraint)},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="BatchNormalization",t}(Layer);SerializationMap.register(BatchNormalization);var __extends$24=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)t.hasOwnProperty(r)&&(e[r]=t[r])};return function(t,r){function n(){this.constructor=t}e(t,r),t.prototype=null===r?Object.create(r):(n.prototype=r.prototype,new n)}}(),ZeroPadding2D=function(e){function t(t){var r=this;if(null==t&&(t={}),r=e.call(this,t)||this,r.dataFormat=null==t.dataFormat?imageDataFormat():t.dataFormat,null==t.padding)r.padding=[[1,1],[1,1]];else if("number"==typeof t.padding)r.padding=[[t.padding,t.padding],[t.padding,t.padding]];else{if(t.padding=t.padding,2!==t.padding.length)throw new ValueError("ZeroPadding2D expects padding to be a length-2 array, but received a length-"+t.padding.length+" array.");var n=void 0,a=void 0;if("number"==typeof t.padding[0])n=[t.padding[0],t.padding[0]],a=[t.padding[1],t.padding[1]];else{if(t.padding=t.padding,2!==t.padding[0].length)throw new ValueError("ZeroPadding2D expects height padding to be a length-2 array, but received a length-"+t.padding[0].length+" array.");if(n=t.padding[0],2!==t.padding[1].length)throw new ValueError("ZeroPadding2D expects width padding to be a length-2 array, but received a length-"+t.padding[1].length+" array.");a=t.padding[1]}r.padding=[n,a]}return r.inputSpec=[new InputSpec({ndim:4})],r}return __extends$24(t,e),t.prototype.computeOutputShape=function(e){e=getExactlyOneShape(e);var t,r;return"channelsFirst"===this.dataFormat?(t=null!=e[2]&&e[2]>=0?e[2]+this.padding[0][0]+this.padding[0][1]:null,r=null!=e[3]&&e[3]>=0?e[3]+this.padding[1][0]+this.padding[1][1]:null,[e[0],e[1],t,r]):(t=null!=e[1]&&e[1]>=0?e[1]+this.padding[0][0]+this.padding[0][1]:null,r=null!=e[2]&&e[2]>=0?e[2]+this.padding[1][0]+this.padding[1][1]:null,[e[0],t,r,e[3]])},t.prototype.call=function(e,t){var r=this;return tidy(function(){return spatial2dPadding(getExactlyOneTensor(e),r.padding,r.dataFormat)})},t.prototype.getConfig=function(){var t={padding:this.padding,dataFormat:this.dataFormat},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="ZeroPadding2D",t}(Layer);SerializationMap.register(ZeroPadding2D);var __extends$25=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)t.hasOwnProperty(r)&&(e[r]=t[r])};return function(t,r){function n(){this.constructor=t}e(t,r),t.prototype=null===r?Object.create(r):(n.prototype=r.prototype,new n)}}(),Pooling1D=function(e){function t(t){var r=this;if(null==t.poolSize&&(t.poolSize=2),r=e.call(this,t)||this,"number"==typeof t.poolSize)r.poolSize=[t.poolSize];else{if(!Array.isArray(t.poolSize)||1!==t.poolSize.length||"number"!=typeof t.poolSize[0])throw new ValueError("poolSize for 1D convolutional layer must be a number or an Array of a single number, but received "+JSON.stringify(t.poolSize));r.poolSize=t.poolSize}if(null==t.strides)r.strides=r.poolSize;else if("number"==typeof t.strides)r.strides=[t.strides];else{if(!Array.isArray(t.strides)||1!==t.strides.length||"number"!=typeof t.strides[0])throw new ValueError("strides for 1D convolutional layer must be a number or an Array of a single number, but received "+JSON.stringify(t.strides));r.strides=t.strides}return r.padding=null==t.padding?"valid":t.padding,checkPaddingMode(r.padding),r.inputSpec=[new InputSpec({ndim:3})],r}return __extends$25(t,e),t.prototype.computeOutputShape=function(e){var t=convOutputLength((e=getExactlyOneShape(e))[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]},t.prototype.call=function(e,t){var r=this;return tidy(function(){r.invokeCallHook(e,t),e=expandDims$1(getExactlyOneTensor(e),2);var n=r.poolingFunction(getExactlyOneTensor(e),[r.poolSize[0],1],[r.strides[0],1],r.padding,"channelsLast");return squeeze(n,[2])})},t.prototype.getConfig=function(){var t={poolSize:this.poolSize,padding:this.padding,strides:this.strides},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t}(Layer),MaxPooling1D=function(e){function t(t){return e.call(this,t)||this}return __extends$25(t,e),t.prototype.poolingFunction=function(e,t,r,n,a){return checkDataFormat(a),checkPaddingMode(n),pool2d(e,t,r,n,a,"max")},t.className="MaxPooling1D",t}(Pooling1D);SerializationMap.register(MaxPooling1D);var AveragePooling1D=function(e){function t(t){return e.call(this,t)||this}return __extends$25(t,e),t.prototype.poolingFunction=function(e,t,r,n,a){return checkDataFormat(a),checkPaddingMode(n),pool2d(e,t,r,n,a,"avg")},t.className="AveragePooling1D",t}(Pooling1D);SerializationMap.register(AveragePooling1D);var Pooling2D=function(e){function t(t){var r=this;return null==t.poolSize&&(t.poolSize=[2,2]),r=e.call(this,t)||this,r.poolSize=Array.isArray(t.poolSize)?t.poolSize:[t.poolSize,t.poolSize],r.strides=null==t.strides?r.poolSize:t.strides,r.padding=null==t.padding?"valid":t.padding,r.dataFormat=null==t.dataFormat?"channelsLast":t.dataFormat,checkDataFormat(r.dataFormat),checkPaddingMode(r.padding),r.inputSpec=[new InputSpec({ndim:4})],r}return __extends$25(t,e),t.prototype.computeOutputShape=function(e){e=getExactlyOneShape(e);var t="channelsFirst"===this.dataFormat?e[2]:e[1],r="channelsFirst"===this.dataFormat?e[3]:e[2];return t=convOutputLength(t,this.poolSize[0],this.padding,this.strides[0]),r=convOutputLength(r,this.poolSize[1],this.padding,this.strides[1]),"channelsFirst"===this.dataFormat?[e[0],e[1],t,r]:[e[0],t,r,e[3]]},t.prototype.call=function(e,t){var r=this;return tidy(function(){return r.invokeCallHook(e,t),r.poolingFunction(getExactlyOneTensor(e),r.poolSize,r.strides,r.padding,r.dataFormat)})},t.prototype.getConfig=function(){var t={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t}(Layer),MaxPooling2D=function(e){function t(t){return e.call(this,t)||this}return __extends$25(t,e),t.prototype.poolingFunction=function(e,t,r,n,a){return checkDataFormat(a),checkPaddingMode(n),pool2d(e,t,r,n,a,"max")},t.className="MaxPooling2D",t}(Pooling2D);SerializationMap.register(MaxPooling2D);var AveragePooling2D=function(e){function t(t){return e.call(this,t)||this}return __extends$25(t,e),t.prototype.poolingFunction=function(e,t,r,n,a){return checkDataFormat(a),checkPaddingMode(n),pool2d(e,t,r,n,a,"avg")},t.className="AveragePooling2D",t}(Pooling2D);SerializationMap.register(AveragePooling2D);var GlobalPooling1D=function(e){function t(t){var r=e.call(this,t)||this;return r.inputSpec=[new InputSpec({ndim:3})],r}return __extends$25(t,e),t.prototype.computeOutputShape=function(e){return[e[0],e[2]]},t.prototype.call=function(e,t){throw new NotImplementedError},t}(Layer),GlobalAveragePooling1D=function(e){function t(t){return e.call(this,t)||this}return __extends$25(t,e),t.prototype.call=function(e,t){return tidy(function(){var t=getExactlyOneTensor(e);return mean(t,1)})},t.className="GlobalAveragePooling1D",t}(GlobalPooling1D);SerializationMap.register(GlobalAveragePooling1D);var GlobalMaxPooling1D=function(e){function t(t){return e.call(this,t)||this}return __extends$25(t,e),t.prototype.call=function(e,t){return tidy(function(){var t=getExactlyOneTensor(e);return max(t,1)})},t.className="GlobalMaxPooling1D",t}(GlobalPooling1D);SerializationMap.register(GlobalMaxPooling1D);var GlobalPooling2D=function(e){function t(t){var r=e.call(this,t)||this;return r.dataFormat=null==t.dataFormat?"channelsLast":t.dataFormat,checkDataFormat(r.dataFormat),r.inputSpec=[new InputSpec({ndim:4})],r}return __extends$25(t,e),t.prototype.computeOutputShape=function(e){return e=e,"channelsLast"===this.dataFormat?[e[0],e[3]]:[e[0],e[1]]},t.prototype.call=function(e,t){throw new NotImplementedError},t.prototype.getConfig=function(){var t={dataFormat:this.dataFormat},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t}(Layer),GlobalAveragePooling2D=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$25(t,e),t.prototype.call=function(e,t){var r=this;return tidy(function(){var t=getExactlyOneTensor(e);return"channelsLast"===r.dataFormat?mean(t,[1,2]):mean(t,[2,3])})},t.className="GlobalAveragePooling2D",t}(GlobalPooling2D);SerializationMap.register(GlobalAveragePooling2D);var GlobalMaxPooling2D=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$25(t,e),t.prototype.call=function(e,t){var r=this;return tidy(function(){var t=getExactlyOneTensor(e);return"channelsLast"===r.dataFormat?max(t,[1,2]):max(t,[2,3])})},t.className="GlobalMaxPooling2D",t}(GlobalPooling2D);SerializationMap.register(GlobalMaxPooling2D);var __extends$26=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)t.hasOwnProperty(r)&&(e[r]=t[r])};return function(t,r){function n(){this.constructor=t}e(t,r),t.prototype=null===r?Object.create(r):(n.prototype=r.prototype,new n)}}(),__decorate$37=function(e,t,r,n){var a,o=arguments.length,i=o<3?t:null===n?n=Object.getOwnPropertyDescriptor(t,r):n;if("object"==typeof Reflect&&"function"==typeof Reflect.decorate)i=Reflect.decorate(e,t,r,n);else for(var s=e.length-1;s>=0;s--)(a=e[s])&&(i=(o<3?a(i):o>3?a(t,r,i):a(t,r))||i);return o>3&&i&&Object.defineProperty(t,r,i),i},RNN=function(e){function t(t){var r,n=e.call(this,t)||this;if(null==t.cell)throw new ValueError("cell property is missing for the constructor of RNN.");if(null==(r=Array.isArray(t.cell)?new StackedRNNCells({cells:t.cell}):t.cell).stateSize)throw new ValueError("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");return n.cell=r,n.returnSequences=null!=t.returnSequences&&t.returnSequences,n.returnState=null!=t.returnState&&t.returnState,n.goBackwards=null!=t.goBackwards&&t.goBackwards,n._stateful=null!=t.stateful&&t.stateful,n.unroll=null!=t.unroll&&t.unroll,n.supportsMasking=!0,n.inputSpec=[new InputSpec({ndim:3})],n.stateSpec=null,n.states=null,n.numConstants=null,n}return __extends$26(t,e),t.prototype.getStates=function(){return null==this.states?range$1(0,Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1).map(function(e){return null}):this.states},t.prototype.setStates=function(e){this.states=e},t.prototype.computeOutputShape=function(e){isArrayOfShapes(e)&&(e=e[0]),e=e;var t=this.cell.stateSize;Array.isArray(t)||(t=[t]);var r,n=t[0];if(r=this.returnSequences?[e[0],e[1],n]:[e[0],n],this.returnState){for(var a=[],o=0,i=t;o<i.length;o++){var s=i[o];a.push([e[0],s])}return[r].concat(a)}return r},t.prototype.computeMask=function(e,t){throw new NotImplementedError("computeMask has not been implemented for RNN yet")},t.prototype.build=function(e){if(null!=this.numConstants)throw new NotImplementedError("Constants support is not implemented in RNN yet.");isArrayOfShapes(e)&&(e=e[0]),e=e;var t=this.stateful?e[0]:null,r=e[e.length-1];this.inputSpec[0]=new InputSpec({shape:[t,null,r]});var n=[e[0]].concat(e.slice(2));this.cell.build(n);var a;if(a=Array.isArray(this.cell.stateSize)?this.cell.stateSize:[this.cell.stateSize],null!=this.stateSpec){if(!arraysEqual(this.stateSpec.map(function(e){return e.shape[e.shape.length-1]}),a))throw new ValueError("An initialState was passed that is not compatible with cell.stateSize. Received stateSpec="+this.stateSpec+"; However cell.stateSize is "+this.cell.stateSize)}else this.stateSpec=a.map(function(e){return new InputSpec({shape:[null,e]})});if(this.stateful)throw new NotImplementedError("stateful RNN layer is not implemented yet")},t.prototype.resetStates=function(e){var t=this;tidy(function(){if(!t.stateful)throw new AttributeError("Cannot call resetState() on an RNN Layer that is not stateful.");var r=t.inputSpec[0].shape[0];if(null==r)throw new ValueError("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(null==t.states)Array.isArray(t.cell.stateSize)?t.states=t.cell.stateSize.map(function(e){return zeros([r,e])}):t.states=[zeros([r,t.cell.stateSize])];else if(null==e)Array.isArray(t.cell.stateSize)?t.states=t.cell.stateSize.map(function(e){return zeros([r,e])}):t.states[0]=zeros([r,t.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==t.states.length)throw new ValueError("Layer "+t.name+" expects "+t.states.length+" state(s), but it received "+e.length+" state value(s). Input received: "+e);for(var n=0;n<t.states.length;++n){var a=e[n],o=Array.isArray(t.cell.stateSize)?t.cell.stateSize[n]:t.cell.stateSize,i=[r,o];if(!arraysEqual(a.shape,i))throw new ValueError("State "+n+" is incompatible with layer "+t.name+": expected shape="+i+", received shape="+a.shape);t.states[n]=a}}})},t.prototype.standardizeArgs=function(e,t,r){function n(e){return null==e||Array.isArray(e)?e:[e]}if(Array.isArray(e)){if(null!=t||null!=r)throw new ValueError("When inputs is an array, neither initialState or constants should be provided");null!=this.numConstants&&(r=e.slice(e.length-this.numConstants,e.length),e=e.slice(0,e.length-this.numConstants)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}return t=n(t),r=n(r),{inputs:e,initialState:t,constants:r}},t.prototype.apply=function(t,r){var n=null==r?null:r.initialState,a=null==r?null:r.constants;null==r&&(r={});var o=this.standardizeArgs(t,n,a);t=o.inputs,n=o.initialState,a=o.constants;var i=[],s=[];if(null!=n){r.initialState=n,i=i.concat(n),this.stateSpec=[];for(var u=0,l=n;u<l.length;u++){var c=l[u];this.stateSpec.push(new InputSpec({shape:c.shape}))}s=s.concat(this.stateSpec)}if(null!=a&&(r.constants=a,i=i.concat(a),this.numConstants=a.length),i[0]instanceof SymbolicTensor){var p=[t].concat(i),d=this.inputSpec.concat(s),h=this.inputSpec;this.inputSpec=d;var f=e.prototype.apply.call(this,p,r);return this.inputSpec=h,f}return e.prototype.apply.call(this,t,r)},t.prototype.call=function(e,t){var r=this;return tidy(function(){var n=null==t?null:t.mask,a=null==t?null:t.training,o=null==t?null:t.initialState;if(e=getExactlyOneTensor(e),null==o){if(r.stateful)throw new NotImplementedError("stateful RNN layer is not implemented yet.");o=r.getInitialState(e)}if(null!=n)throw new NotImplementedError("Masking is not implemented for RNN yet");var i=Array.isArray(r.cell.stateSize)?r.cell.stateSize.length:1;if(o.length!==i)throw new ValueError("RNN Layer has "+i+" state(s) but was passed "+o.length+" initial state(s).");e.shape[1];r.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");var s={training:a},u=rnn(function(e,t){var n=r.cell.call([e].concat(t),s);return[n[0],n.slice(1)]},e,o,r.goBackwards,null,null,r.unroll),l=u[0],c=u[1],p=u[2];if(r.stateful)throw new NotImplementedError("stateful RNN layer is not implemented yet");var d=r.returnSequences?c:l;return r.returnState?[d].concat(p):d})},t.prototype.getInitialState=function(e){var t=this;return tidy(function(){var r=zeros(e.shape);return r=sum(r,[1,2]),r=expandDims$1(r),Array.isArray(t.cell.stateSize)?t.cell.stateSize.map(function(e){return e>1?tile$1(r,[1,e]):r}):t.cell.stateSize>1?[tile$1(r,[1,t.cell.stateSize])]:[r]})},Object.defineProperty(t.prototype,"trainableWeights",{get:function(){return this.trainable?this.cell.trainableWeights:[]},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"nonTrainableWeights",{get:function(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights},enumerable:!0,configurable:!0}),t.prototype.getConfig=function(){var t={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};null!=this.numConstants&&(t.numConstants=this.numConstants);var r=this.cell.getConfig();t.cell={className:this.cell.getClassName(),config:r};var n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t.className="RNN",t}(Layer);SerializationMap.register(RNN);var RNNCell=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$26(t,e),t=__decorate$37([doc()],t)}(Layer),SimpleRNNCell=function(e){function t(t){var r=e.call(this,t)||this;return r.DEFAULT_ACTIVATION="tanh",r.DEFAULT_KERNEL_INITIALIZER="glorotNormal",r.DEFAULT_RECURRENT_INITIALIZER="orthogonal",r.DEFAULT_BIAS_INITIALIZER="zeros",r.units=t.units,r.activation=getActivation(null==t.activation?r.DEFAULT_ACTIVATION:t.activation),r.useBias=null==t.useBias||t.useBias,r.kernelInitializer=getInitializer(t.kernelInitializer||r.DEFAULT_KERNEL_INITIALIZER),r.recurrentInitializer=getInitializer(t.recurrentInitializer||r.DEFAULT_RECURRENT_INITIALIZER),r.biasInitializer=getInitializer(t.biasInitializer||r.DEFAULT_BIAS_INITIALIZER),r.kernelRegularizer=getRegularizer(t.kernelRegularizer),r.recurrentRegularizer=getRegularizer(t.recurrentRegularizer),r.biasRegularizer=getRegularizer(t.biasRegularizer),r.kernelConstraint=getConstraint(t.kernelConstraint),r.recurrentConstraint=getConstraint(t.recurrentConstraint),r.biasConstraint=getConstraint(t.biasConstraint),r.dropout=min$1([1,max$1([0,null==t.dropout?0:t.dropout])]),r.recurrentDropout=min$1([1,max$1([0,null==t.recurrentDropout?0:t.recurrentDropout])]),r.stateSize=r.units,r}return __extends$26(t,e),t.prototype.build=function(e){e=getExactlyOneShape(e),this.kernel=this.addWeight("kernel",[e[e.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0},t.prototype.call=function(e,t){var r=this;return tidy(function(){if(2!==(e=e).length)throw new ValueError("SimpleRNNCell expects 2 input Tensors, got "+e.length+".");var t=e[1];if(e=e[0],0!==r.dropout||0!==r.recurrentDropout)throw new NotImplementedError("Dropout is not implemented for SimpleRNNCell yet");var n=dot$1(e,r.kernel.read());null!=r.bias&&(n=biasAdd(n,r.bias.read()));var a=add(n,dot$1(t,r.recurrentKernel.read()));return null!=r.activation&&(a=r.activation.apply(a)),[a,a]})},t.prototype.getConfig=function(){var t={units:this.units,activation:serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:serializeInitializer(this.kernelInitializer),recurrentInitializer:serializeInitializer(this.recurrentInitializer),biasInitializer:serializeInitializer(this.biasInitializer),kernelRegularizer:serializeRegularizer(this.kernelRegularizer),recurrentRegularizer:serializeRegularizer(this.recurrentRegularizer),biasRegularizer:serializeRegularizer(this.biasRegularizer),activityRegularizer:serializeRegularizer(this.activityRegularizer),kernelConstraint:serializeConstraint(this.kernelConstraint),recurrentConstraint:serializeConstraint(this.recurrentConstraint),biasConstraint:serializeConstraint(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="SimpleRNNCell",t}(RNNCell);SerializationMap.register(SimpleRNNCell);var SimpleRNN=function(e){function t(t){return t.cell=new SimpleRNNCell(t),e.call(this,t)||this}return __extends$26(t,e),t.prototype.call=function(t,r){var n=this;return tidy(function(){var a=null==r?null:r.mask,o=null==r?null:r.training,i=null==r?null:r.initialState;return e.prototype.call.call(n,t,{mask:a,training:o,initialState:i})})},Object.defineProperty(t.prototype,"units",{get:function(){return this.cell.units},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"activation",{get:function(){return this.cell.activation},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"useBias",{get:function(){return this.cell.useBias},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelInitializer",{get:function(){return this.cell.kernelInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentInitializer",{get:function(){return this.cell.recurrentInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasInitializer",{get:function(){return this.cell.biasInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelRegularizer",{get:function(){return this.cell.kernelRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentRegularizer",{get:function(){return this.cell.recurrentRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasRegularizer",{get:function(){return this.cell.biasRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelConstraint",{get:function(){return this.cell.kernelConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentConstraint",{get:function(){return this.cell.recurrentConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasConstraint",{get:function(){return this.cell.biasConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"dropout",{get:function(){return this.cell.dropout},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentDropout",{get:function(){return this.cell.recurrentDropout},enumerable:!0,configurable:!0}),t.prototype.getConfig=function(){var t={units:this.units,activation:serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:serializeInitializer(this.kernelInitializer),recurrentInitializer:serializeInitializer(this.recurrentInitializer),biasInitializer:serializeInitializer(this.biasInitializer),kernelRegularizer:serializeRegularizer(this.kernelRegularizer),recurrentRegularizer:serializeRegularizer(this.recurrentRegularizer),biasRegularizer:serializeRegularizer(this.biasRegularizer),activityRegularizer:serializeRegularizer(this.activityRegularizer),kernelConstraint:serializeConstraint(this.kernelConstraint),recurrentConstraint:serializeConstraint(this.recurrentConstraint),biasConstraint:serializeConstraint(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout},r=e.prototype.getConfig.call(this);return delete r.cell,Object.assign(t,r),t},t.className="SimpleRNN",t}(RNN);SerializationMap.register(SimpleRNN);var GRUCell=function(e){function t(t){var r=e.call(this,t)||this;return r.DEFAULT_ACTIVATION="tanh",r.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",r.DEFAULT_KERNEL_INITIALIZER="glorotNormal",r.DEFAULT_RECURRENT_INITIALIZER="orthogonal",r.DEFAULT_BIAS_INITIALIZER="zeros",r.units=t.units,r.activation=getActivation(void 0===t.activation?r.DEFAULT_ACTIVATION:t.activation),r.recurrentActivation=getActivation(void 0===t.activation?r.DEFAULT_RECURRENT_ACTIVATION:t.recurrentActivation),r.useBias=null==t.useBias||t.useBias,r.kernelInitializer=getInitializer(t.kernelInitializer||r.DEFAULT_KERNEL_INITIALIZER),r.recurrentInitializer=getInitializer(t.recurrentInitializer||r.DEFAULT_RECURRENT_INITIALIZER),r.biasInitializer=getInitializer(t.biasInitializer||r.DEFAULT_BIAS_INITIALIZER),r.kernelRegularizer=getRegularizer(t.kernelRegularizer),r.recurrentRegularizer=getRegularizer(t.recurrentRegularizer),r.biasRegularizer=getRegularizer(t.biasRegularizer),r.kernelConstraint=getConstraint(t.kernelConstraint),r.recurrentConstraint=getConstraint(t.recurrentConstraint),r.biasConstraint=getConstraint(t.biasConstraint),r.dropout=min$1([1,max$1([0,null==t.dropout?0:t.dropout])]),r.recurrentDropout=min$1([1,max$1([0,null==t.recurrentDropout?0:t.recurrentDropout])]),r.implementation=t.implementation,r.stateSize=r.units,r}return __extends$26(t,e),t.prototype.build=function(e){var t=(e=getExactlyOneShape(e))[e.length-1];this.kernel=this.addWeight("kernel",[t,3*this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,3*this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[3*this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0},t.prototype.call=function(e,t){var r=this;return tidy(function(){if(0!==r.dropout||0!==r.recurrentDropout)throw new NotImplementedError("Dropout is not implemented for GRUCell yet");if(2!==(e=e).length)throw new ValueError("GRUCell expects 2 input Tensors (inputs, h, c), got "+e.length+".");var t=e[1];e=e[0];var n,a,o;if(1===r.implementation){var i=sliceAlongLastAxis(r.kernel.read(),0,r.units),s=sliceAlongLastAxis(r.kernel.read(),r.units,r.units),u=sliceAlongLastAxis(r.kernel.read(),2*r.units,r.units),l=sliceAlongLastAxis(r.recurrentKernel.read(),0,r.units),c=sliceAlongLastAxis(r.recurrentKernel.read(),r.units,r.units),p=sliceAlongLastAxis(r.recurrentKernel.read(),2*r.units,r.units),d=e,h=e,f=dot$1(e,i),m=dot$1(d,s),g=dot$1(h,u);if(r.useBias){var y=sliceAlongFirstAxis(r.bias.read(),0,r.units),v=sliceAlongFirstAxis(r.bias.read(),r.units,r.units),b=sliceAlongFirstAxis(r.bias.read(),2*r.units,r.units);f=biasAdd(f,y),m=biasAdd(m,v),g=biasAdd(g,b)}var x=t,w=t,_=t;n=r.recurrentActivation.apply(add(f,dot$1(x,l))),a=r.recurrentActivation.apply(add(m,dot$1(w,c))),o=r.activation.apply(add(g,dot$1(mul(a,_),p)))}else{var S=dot$1(e,r.kernel.read());r.useBias&&(S=biasAdd(S,r.bias.read()));var N=dot$1(t,sliceAlongLastAxis(r.recurrentKernel.read(),0,2*r.units)),f=sliceAlongLastAxis(S,0,r.units),m=sliceAlongLastAxis(S,r.units,r.units),A=sliceAlongLastAxis(N,0,r.units),E=sliceAlongLastAxis(N,r.units,r.units);n=r.recurrentActivation.apply(add(f,A)),a=r.recurrentActivation.apply(add(m,E));var g=sliceAlongLastAxis(S,2*r.units,r.units),T=dot$1(mul(a,t),sliceAlongLastAxis(r.recurrentKernel.read(),2*r.units,r.units));o=r.activation.apply(add(g,T))}var I=add(mul(n,t),mul(scalarPlusArray(getScalar(1),neg(n)),o));return[I,I]})},t.prototype.getConfig=function(){var t={units:this.units,activation:serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:serializeInitializer(this.kernelInitializer),recurrentInitializer:serializeInitializer(this.recurrentInitializer),biasInitializer:serializeInitializer(this.biasInitializer),kernelRegularizer:serializeRegularizer(this.kernelRegularizer),recurrentRegularizer:serializeRegularizer(this.recurrentRegularizer),biasRegularizer:serializeRegularizer(this.biasRegularizer),activityRegularizer:serializeRegularizer(this.activityRegularizer),kernelConstraint:serializeConstraint(this.kernelConstraint),recurrentConstraint:serializeConstraint(this.recurrentConstraint),biasConstraint:serializeConstraint(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="GRUCell",t}(RNNCell);SerializationMap.register(GRUCell);var GRU=function(e){function t(t){return 0===t.implementation&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),t.cell=new GRUCell(t),e.call(this,t)||this}return __extends$26(t,e),t.prototype.call=function(t,r){var n=this;return tidy(function(){var a=null==r?null:r.mask,o=null==r?null:r.training,i=null==r?null:r.initialState;return e.prototype.call.call(n,t,{mask:a,training:o,initialState:i})})},Object.defineProperty(t.prototype,"units",{get:function(){return this.cell.units},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"activation",{get:function(){return this.cell.activation},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"useBias",{get:function(){return this.cell.useBias},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelInitializer",{get:function(){return this.cell.kernelInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentInitializer",{get:function(){return this.cell.recurrentInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasInitializer",{get:function(){return this.cell.biasInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelRegularizer",{get:function(){return this.cell.kernelRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentRegularizer",{get:function(){return this.cell.recurrentRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasRegularizer",{get:function(){return this.cell.biasRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelConstraint",{get:function(){return this.cell.kernelConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentConstraint",{get:function(){return this.cell.recurrentConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasConstraint",{get:function(){return this.cell.biasConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"dropout",{get:function(){return this.cell.dropout},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentDropout",{get:function(){return this.cell.recurrentDropout},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"implementation",{get:function(){return this.cell.implementation},enumerable:!0,configurable:!0}),t.prototype.getConfig=function(){var t={units:this.units,activation:serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:serializeInitializer(this.kernelInitializer),recurrentInitializer:serializeInitializer(this.recurrentInitializer),biasInitializer:serializeInitializer(this.biasInitializer),kernelRegularizer:serializeRegularizer(this.kernelRegularizer),recurrentRegularizer:serializeRegularizer(this.recurrentRegularizer),biasRegularizer:serializeRegularizer(this.biasRegularizer),activityRegularizer:serializeRegularizer(this.activityRegularizer),kernelConstraint:serializeConstraint(this.kernelConstraint),recurrentConstraint:serializeConstraint(this.recurrentConstraint),biasConstraint:serializeConstraint(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation},r=e.prototype.getConfig.call(this);return delete r.cell,Object.assign(t,r),t},t.fromConfig=function(e,t){return 0===t.implmentation&&(t.implementation=1),new e(t)},t.className="GRU",t}(RNN);SerializationMap.register(GRU);var LSTMCell=function(e){function t(t){var r=e.call(this,t)||this;return r.DEFAULT_ACTIVATION="tanh",r.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",r.DEFAULT_KERNEL_INITIALIZER="glorotNormal",r.DEFAULT_RECURRENT_INITIALIZER="orthogonal",r.DEFAULT_BIAS_INITIALIZER="zeros",r.units=t.units,r.activation=getActivation(void 0===t.activation?r.DEFAULT_ACTIVATION:t.activation),r.recurrentActivation=getActivation(void 0===t.activation?r.DEFAULT_RECURRENT_ACTIVATION:t.recurrentActivation),r.useBias=null==t.useBias||t.useBias,r.kernelInitializer=getInitializer(t.kernelInitializer||r.DEFAULT_KERNEL_INITIALIZER),r.recurrentInitializer=getInitializer(t.recurrentInitializer||r.DEFAULT_RECURRENT_INITIALIZER),r.biasInitializer=getInitializer(t.biasInitializer||r.DEFAULT_BIAS_INITIALIZER),r.unitForgetBias=t.unitForgetBias,r.kernelRegularizer=getRegularizer(t.kernelRegularizer),r.recurrentRegularizer=getRegularizer(t.recurrentRegularizer),r.biasRegularizer=getRegularizer(t.biasRegularizer),r.kernelConstraint=getConstraint(t.kernelConstraint),r.recurrentConstraint=getConstraint(t.recurrentConstraint),r.biasConstraint=getConstraint(t.biasConstraint),r.dropout=min$1([1,max$1([0,null==t.dropout?0:t.dropout])]),r.recurrentDropout=min$1([1,max$1([0,null==t.recurrentDropout?0:t.recurrentDropout])]),r.implementation=t.implementation,r.stateSize=[r.units,r.units],r}return __extends$26(t,e),t.prototype.build=function(e){var t=(e=getExactlyOneShape(e))[e.length-1];this.kernel=this.addWeight("kernel",[t,4*this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,4*this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);var r;if(this.useBias){if(this.unitForgetBias){var n=this.biasInitializer,a=this.units;r=new(o=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return __extends$26(t,e),t.prototype.apply=function(e,t){var r=n.apply([a]),o=(new Ones).apply([a]),i=n.apply([2*a]);return concatAlongFirstAxis(concatAlongFirstAxis(r,o),i)},t}(Initializer),o.className="CustomInit",o)}else r=this.biasInitializer;this.bias=this.addWeight("bias",[4*this.units],null,r,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0;var o},t.prototype.call=function(e,t){var r=this;return tidy(function(){if(0!==r.dropout||0!==r.recurrentDropout)throw new NotImplementedError("Dropout is not implemented for LSTMCell yet");if(3!==(e=e).length)throw new ValueError("LSTMCell expects 3 input Tensors (inputs, h, c), got "+e.length+".");var t=e[1],n=e[2];e=e[0];var a,o,i,s;if(1===r.implementation){var u=sliceAlongLastAxis(r.kernel.read(),0,r.units),l=sliceAlongLastAxis(r.kernel.read(),r.units,r.units),c=sliceAlongLastAxis(r.kernel.read(),2*r.units,r.units),p=sliceAlongLastAxis(r.kernel.read(),3*r.units,r.units),d=sliceAlongLastAxis(r.recurrentKernel.read(),0,r.units),h=sliceAlongLastAxis(r.recurrentKernel.read(),r.units,r.units),f=sliceAlongLastAxis(r.recurrentKernel.read(),2*r.units,r.units),m=sliceAlongLastAxis(r.recurrentKernel.read(),3*r.units,r.units),g=e,y=e,v=e,b=dot$1(e,u),x=dot$1(g,l),w=dot$1(y,c),_=dot$1(v,p);if(r.useBias){var S=sliceAlongFirstAxis(r.bias.read(),0,r.units),N=sliceAlongFirstAxis(r.bias.read(),r.units,r.units),A=sliceAlongFirstAxis(r.bias.read(),2*r.units,r.units),E=sliceAlongFirstAxis(r.bias.read(),3*r.units,r.units);b=biasAdd(b,S),x=biasAdd(x,N),w=biasAdd(w,A),_=biasAdd(_,E)}var T=t,I=t,O=t,P=t;a=r.recurrentActivation.apply(add(b,dot$1(T,d))),o=r.recurrentActivation.apply(add(x,dot$1(I,h))),i=add(mul(o,n),mul(a,r.activation.apply(add(w,dot$1(O,f))))),s=r.recurrentActivation.apply(add(_,dot$1(P,m)))}else{var R=dot$1(e,r.kernel.read());R=add(R,dot$1(t,r.recurrentKernel.read())),r.useBias&&(R=biasAdd(R,r.bias.read()));var C=sliceAlongLastAxis(R,0,r.units),k=sliceAlongLastAxis(R,r.units,r.units),D=sliceAlongLastAxis(R,2*r.units,r.units),M=sliceAlongLastAxis(R,3*r.units,r.units);a=r.recurrentActivation.apply(C),o=r.recurrentActivation.apply(k),i=add(mul(o,n),mul(a,r.activation.apply(D))),s=r.recurrentActivation.apply(M)}var L=mul(s,r.activation.apply(i));return[L,L,i]})},t.prototype.getConfig=function(){var t={units:this.units,activation:serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:serializeInitializer(this.kernelInitializer),recurrentInitializer:serializeInitializer(this.recurrentInitializer),biasInitializer:serializeInitializer(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:serializeRegularizer(this.kernelRegularizer),recurrentRegularizer:serializeRegularizer(this.recurrentRegularizer),biasRegularizer:serializeRegularizer(this.biasRegularizer),activityRegularizer:serializeRegularizer(this.activityRegularizer),kernelConstraint:serializeConstraint(this.kernelConstraint),recurrentConstraint:serializeConstraint(this.recurrentConstraint),biasConstraint:serializeConstraint(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.className="LSTMCell",t}(RNNCell);SerializationMap.register(LSTMCell);var LSTM=function(e){function t(t){return 0===t.implementation&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),t.cell=new LSTMCell(t),e.call(this,t)||this}return __extends$26(t,e),t.prototype.call=function(t,r){var n=this;return tidy(function(){var a=null==r?null:r.mask,o=null==r?null:r.training,i=null==r?null:r.initialState;return e.prototype.call.call(n,t,{mask:a,training:o,initialState:i})})},Object.defineProperty(t.prototype,"units",{get:function(){return this.cell.units},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"activation",{get:function(){return this.cell.activation},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"useBias",{get:function(){return this.cell.useBias},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelInitializer",{get:function(){return this.cell.kernelInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentInitializer",{get:function(){return this.cell.recurrentInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasInitializer",{get:function(){return this.cell.biasInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"unitForgetBias",{get:function(){return this.cell.unitForgetBias},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelRegularizer",{get:function(){return this.cell.kernelRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentRegularizer",{get:function(){return this.cell.recurrentRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasRegularizer",{get:function(){return this.cell.biasRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelConstraint",{get:function(){return this.cell.kernelConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentConstraint",{get:function(){return this.cell.recurrentConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasConstraint",{get:function(){return this.cell.biasConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"dropout",{get:function(){return this.cell.dropout},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentDropout",{get:function(){return this.cell.recurrentDropout},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"implementation",{get:function(){return this.cell.implementation},enumerable:!0,configurable:!0}),t.prototype.getConfig=function(){var t={units:this.units,activation:serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:serializeInitializer(this.kernelInitializer),recurrentInitializer:serializeInitializer(this.recurrentInitializer),biasInitializer:serializeInitializer(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:serializeRegularizer(this.kernelRegularizer),recurrentRegularizer:serializeRegularizer(this.recurrentRegularizer),biasRegularizer:serializeRegularizer(this.biasRegularizer),activityRegularizer:serializeRegularizer(this.activityRegularizer),kernelConstraint:serializeConstraint(this.kernelConstraint),recurrentConstraint:serializeConstraint(this.recurrentConstraint),biasConstraint:serializeConstraint(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation},r=e.prototype.getConfig.call(this);return delete r.cell,Object.assign(t,r),t},t.fromConfig=function(e,t){return 0===t.implmentation&&(t.implementation=1),new e(t)},t.className="LSTM",t}(RNN);SerializationMap.register(LSTM);var StackedRNNCells=function(e){function t(t){var r=e.call(this,t)||this;return r.cells=t.cells,r}return __extends$26(t,e),Object.defineProperty(t.prototype,"stateSize",{get:function(){for(var e=[],t=0,r=this.cells.slice().reverse();t<r.length;t++){var n=r[t];Array.isArray(n.stateSize)?e.push.apply(e,n.stateSize):e.push(n.stateSize)}return e},enumerable:!0,configurable:!0}),t.prototype.call=function(e,t){var r=this;return tidy(function(){for(var n=(e=e).slice(1),a=[],o=0,i=r.cells.slice().reverse();o<i.length;o++){c=i[o];Array.isArray(c.stateSize)?a.push(n.splice(0,c.stateSize.length)):a.push(n.splice(0,1))}a.reverse();for(var s,u=[],l=0;l<r.cells.length;++l){var c=r.cells[l];n=a[l],s=0===l?[e[0]].concat(n):[s[0]].concat(n),s=c.call(s,t),u.push(s.slice(1))}n=[];for(var p=0,d=u.slice().reverse();p<d.length;p++){var h=d[p];n.push.apply(n,h)}return[s[0]].concat(n)})},t.prototype.build=function(e){isArrayOfShapes(e)&&(e=e[0]),e=e;for(var t,r=0,n=this.cells;r<n.length;r++){var a=n[r];a.build(e),t=Array.isArray(a.stateSize)?a.stateSize[0]:a.stateSize,e=[e[0],t]}this.built=!0},t.prototype.getConfig=function(){for(var t=[],r=0,n=this.cells;r<n.length;r++){var a=n[r];t.push({className:this.getClassName(),config:a.getConfig()})}var o={cells:t},i=e.prototype.getConfig.call(this);return Object.assign(o,i),o},t.fromConfig=function(e,t,r){void 0===r&&(r={});for(var n=[],a=0,o=t.cells;a<o.length;a++){var i=o[a];n.push(deserialize(i,r))}return new e({cells:n})},Object.defineProperty(t.prototype,"trainableWeights",{get:function(){if(!this.trainable)return[];for(var e=[],t=0,r=this.cells;t<r.length;t++){var n=r[t];e.push.apply(e,n.trainableWeights)}return e},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"nonTrainableWeights",{get:function(){for(var e=[],t=0,r=this.cells;t<r.length;t++){i=r[t];e.push.apply(e,i.nonTrainableWeights)}if(!this.trainable){for(var n=[],a=0,o=this.cells;a<o.length;a++){var i=o[a];n.push.apply(n,i.trainableWeights)}return n.concat(e)}return e},enumerable:!0,configurable:!0}),t.prototype.getWeights=function(){for(var e=[],t=0,r=this.cells;t<r.length;t++){var n=r[t];e.push.apply(e,n.weights)}return batchGetValue(e)},t.prototype.setWeights=function(e){for(var t=[],r=0,n=this.cells;r<n.length;r++)for(var a=n[r],o=a.weights.length,i=e.splice(o),s=0;s<a.weights.length;++s)t.push([a.weights[s],i[s]]);batchSetValue(t)},t.className="StackedRNNCells",t}(RNNCell);SerializationMap.register(StackedRNNCells);var __extends$27=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)t.hasOwnProperty(r)&&(e[r]=t[r])};return function(t,r){function n(){this.constructor=t}e(t,r),t.prototype=null===r?Object.create(r):(n.prototype=r.prototype,new 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this.layer.getWeights()},t.prototype.setWeights=function(e){this.layer.setWeights(e)},t.prototype.getConfig=function(){var t={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.fromConfig=function(e,t,r){void 0===r&&(r={});var n=deserialize(t.layer,r);delete t.layer;var a={layer:n};return Object.assign(a,t),new e(a)},t}(Layer),TimeDistributed=function(e){function t(t){var r=e.call(this,t)||this;return r.supportsMasking=!0,r}return __extends$27(t,e),t.prototype.build=function(t){if((t=getExactlyOneShape(t)).length<3)throw new ValueError("TimeDistributed layer expects an input shape >= 3D, but received input shape "+JSON.stringify(t));this.inputSpec=[{shape:t}];var r=[t[0]].concat(t.slice(2));this.layer.built||(this.layer.build(r),this.layer.built=!0),e.prototype.build.call(this,t)},t.prototype.computeOutputShape=function(e){var t=[(e=getExactlyOneShape(e))[0]].concat(e.slice(2)),r=this.layer.computeOutputShape(t),n=e[1];return[r[0],n].concat(r.slice(1))},t.prototype.call=function(e,t){var r=this;return tidy(function(){return rnn(function(e,n){return[r.layer.call(e,t),[]]},e=getExactlyOneTensor(e),[],!1,null,null,!1,e.shape[1])[1]})},t.className="TimeDistributed",t}(Wrapper);SerializationMap.register(TimeDistributed);var VALID_BIDIRECTIONAL_MERGE_MODES=["sum","mul","concat","ave"],Bidirectional=function(e){function t(t){var r=e.call(this,t)||this,n=t.layer.getConfig();if(r.forwardLayer=deserialize({className:t.layer.getClassName(),config:n}),n.goBackwards=!0!==n.goBackwards,r.backwardLayer=deserialize({className:t.layer.getClassName(),config:n}),r.forwardLayer.name="forward_"+r.forwardLayer.name,r.backwardLayer.name="backward_"+r.backwardLayer.name,checkBidirectionalMergeMode(t.mergeMode),r.mergeMode=t.mergeMode,t.weights)throw new NotImplementedError("weights support is not implemented for Bidirectional layer yet.");return r._stateful=t.layer.stateful,r.returnSequences=t.layer.returnSequences,r.returnState=t.layer.returnState,r.supportsMasking=!0,r._trainable=!0,r.inputSpec=t.layer.inputSpec,r}return __extends$27(t,e),Object.defineProperty(t.prototype,"trainable",{get:function(){return this._trainable},set:function(e){this._trainable=e,null!=this.forwardLayer&&(this.forwardLayer.trainable=e),null!=this.backwardLayer&&(this.backwardLayer.trainable=e)},enumerable:!0,configurable:!0}),t.prototype.getWeights=function(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())},t.prototype.setWeights=function(e){var t=e.length,r=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,r)),this.backwardLayer.setWeights(e.slice(r))},t.prototype.computeOutputShape=function(e){var t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;var r,n,a;return this.returnState?(a=t.slice(1),r=t[0]):r=t[0],r=r,"concat"===this.mergeMode?(r[r.length-1]*=2,n=[r]):n=null==this.mergeMode?[r,r.slice()]:[r],this.returnState?null==this.mergeMode?n.concat(a).concat(a.slice()):[r].concat(a).concat(a.slice()):singletonOrArray(n)},t.prototype.apply=function(t,r){var n=null;if(null!=r&&(n=r.initialState),Array.isArray(t)&&(n=t.slice(1),t=t[0]),null==n||0===n.length)return e.prototype.apply.call(this,t,r);throw new NotImplementedError("The support for initial states is not implemented for Bidirectional layers yet.")},t.prototype.call=function(e,t){var r=this;return tidy(function(){if(null!=t.mask)throw new NotImplementedError("The support for masking is not implemented for Bidirectional layers yet.");if(null!=t.initialState)throw new NotImplementedError("The support for initial states is not implemented for Bidirectional layers yet.");var n,a=r.forwardLayer.call(e,t),o=r.backwardLayer.call(e,t);r.returnState&&(Array.isArray(a)&&(n=a.slice(1).concat(o.slice(1))),a=a[0],o=o[0]),r.returnSequences&&(o=reverse(o,1));var i;return"concat"===r.mergeMode?i=concatenate([a,o]):"sum"===r.mergeMode?i=add(a,o):"ave"===r.mergeMode?i=scalarTimesArray(getScalar(.5),add(a,o)):"mul"===r.mergeMode?i=mul(a,o):null==r.mergeMode&&(i=[a,o]),r.returnState?null==r.mergeMode?i.concat(n):[i].concat(n):i})},t.prototype.resetStates=function(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()},t.prototype.build=function(e){var t=this;nameScope$1(this.forwardLayer.name,function(){t.forwardLayer.build(e)}),nameScope$1(this.backwardLayer.name,function(){t.backwardLayer.build(e)}),this.built=!0},Object.defineProperty(t.prototype,"trainableWeights",{get:function(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"nonTrainableWeights",{get:function(){return this.forwardLayer.nonTrainableWeights.concat(this.backwardLayer.nonTrainableWeights)},enumerable:!0,configurable:!0}),t.prototype.getConfig=function(){var t={mergeMode:this.mergeMode},r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t.fromConfig=function(e,t){var r=deserialize(t.layer);if(delete t.layer,null!=t.numConstants)throw new NotImplementedError("Deserialization of a Bidirectional layer with numConstants present is not supported yet.");var n=t;return n.layer=r,new e(n)},t.className="Bidirectional",t}(Wrapper);SerializationMap.register(Bidirectional);var __extends$28=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)t.hasOwnProperty(r)&&(e[r]=t[r])};return function(t,r){function 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For multi-output layers, use the functional API.");this.outputs=[e.inboundNodes[0].outputTensors[0]],this.inputs=getSourceInputs(this.outputs[0])}new Node({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:pyListRepeat(null,this.inputs.length),outputMasks:[null],inputShapes:this.inputs.map(function(e){return e.shape}),outputShapes:this.outputs[0].shape})}else{var o=e.apply(this.outputs[0]);if(Array.isArray(o))throw new TypeError("All layers in a Sequential model should have a single output tensor. 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t&&":"!==t.substr(-1)&&(t+=":"),this.slashes||(!t||slashedProtocol[t])&&!1!==a?(a="//"+(a||""),r&&"/"!==r.charAt(0)&&(r="/"+r)):a||(a=""),n&&"#"!==n.charAt(0)&&(n="#"+n),i&&"?"!==i.charAt(0)&&(i="?"+i),r=r.replace(/[?#]/g,function(e){return encodeURIComponent(e)}),i=i.replace("#","%23"),t+a+r+i+n},Url.prototype.resolve=function(e){return this.resolveObject(urlParse(e,!1,!0)).format()},Url.prototype.resolveObject=function(e){if(util$1.isString(e)){var t=new Url;t.parse(e,!1,!0),e=t}for(var r=new Url,n=Object.keys(this),a=0;a<n.length;a++){var o=n[a];r[o]=this[o]}if(r.hash=e.hash,""===e.href)return r.href=r.format(),r;if(e.slashes&&!e.protocol){for(var i=Object.keys(e),s=0;s<i.length;s++){var u=i[s];"protocol"!==u&&(r[u]=e[u])}return slashedProtocol[r.protocol]&&r.hostname&&!r.pathname&&(r.path=r.pathname="/"),r.href=r.format(),r}if(e.protocol&&e.protocol!==r.protocol){if(!slashedProtocol[e.protocol]){for(var l=Object.keys(e),c=0;c<l.length;c++){var p=l[c];r[p]=e[p]}return r.href=r.format(),r}if(r.protocol=e.protocol,e.host||hostlessProtocol[e.protocol])r.pathname=e.pathname;else{for(b=(e.pathname||"").split("/");b.length&&!(e.host=b.shift()););e.host||(e.host=""),e.hostname||(e.hostname=""),""!==b[0]&&b.unshift(""),b.length<2&&b.unshift(""),r.pathname=b.join("/")}if(r.search=e.search,r.query=e.query,r.host=e.host||"",r.auth=e.auth,r.hostname=e.hostname||e.host,r.port=e.port,r.pathname||r.search){var d=r.pathname||"",h=r.search||"";r.path=d+h}return r.slashes=r.slashes||e.slashes,r.href=r.format(),r}var f=r.pathname&&"/"===r.pathname.charAt(0),m=e.host||e.pathname&&"/"===e.pathname.charAt(0),g=m||f||r.host&&e.pathname,y=g,v=r.pathname&&r.pathname.split("/")||[],b=e.pathname&&e.pathname.split("/")||[],x=r.protocol&&!slashedProtocol[r.protocol];if(x&&(r.hostname="",r.port=null,r.host&&(""===v[0]?v[0]=r.host:v.unshift(r.host)),r.host="",e.protocol&&(e.hostname=null,e.port=null,e.host&&(""===b[0]?b[0]=e.host:b.unshift(e.host)),e.host=null),g=g&&(""===b[0]||""===v[0])),m)r.host=e.host||""===e.host?e.host:r.host,r.hostname=e.hostname||""===e.hostname?e.hostname:r.hostname,r.search=e.search,r.query=e.query,v=b;else if(b.length)v||(v=[]),v.pop(),v=v.concat(b),r.search=e.search,r.query=e.query;else if(!util$1.isNullOrUndefined(e.search))return x&&(r.hostname=r.host=v.shift(),(E=!!(r.host&&r.host.indexOf("@")>0)&&r.host.split("@"))&&(r.auth=E.shift(),r.host=r.hostname=E.shift())),r.search=e.search,r.query=e.query,util$1.isNull(r.pathname)&&util$1.isNull(r.search)||(r.path=(r.pathname?r.pathname:"")+(r.search?r.search:"")),r.href=r.format(),r;if(!v.length)return r.pathname=null,r.search?r.path="/"+r.search:r.path=null,r.href=r.format(),r;for(var w=v.slice(-1)[0],_=(r.host||e.host||v.length>1)&&("."===w||".."===w)||""===w,S=0,N=v.length;N>=0;N--)"."===(w=v[N])?v.splice(N,1):".."===w?(v.splice(N,1),S++):S&&(v.splice(N,1),S--);if(!g&&!y)for(;S--;S)v.unshift("..");!g||""===v[0]||v[0]&&"/"===v[0].charAt(0)||v.unshift(""),_&&"/"!==v.join("/").substr(-1)&&v.push("");var A=""===v[0]||v[0]&&"/"===v[0].charAt(0);if(x){r.hostname=r.host=A?"":v.length?v.shift():"";var E=!!(r.host&&r.host.indexOf("@")>0)&&r.host.split("@");E&&(r.auth=E.shift(),r.host=r.hostname=E.shift())}return(g=g||r.host&&v.length)&&!A&&v.unshift(""),v.length?r.pathname=v.join("/"):(r.pathname=null,r.path=null),util$1.isNull(r.pathname)&&util$1.isNull(r.search)||(r.path=(r.pathname?r.pathname:"")+(r.search?r.search:"")),r.auth=e.auth||r.auth,r.slashes=r.slashes||e.slashes,r.href=r.format(),r},Url.prototype.parseHost=function(){var e=this.host,t=portPattern.exec(e);t&&(":"!==(t=t[0])&&(this.port=t.substr(1)),e=e.substr(0,e.length-t.length)),e&&(this.hostname=e)};var aspromise=asPromise,base64_1=createCommonjsModule(function(e,t){var r=t;r.length=function(e){var t=e.length;if(!t)return 0;for(var r=0;--t%4>1&&"="===e.charAt(t);)++r;return Math.ceil(3*e.length)/4-r};for(var n=new Array(64),a=new Array(123),o=0;o<64;)a[n[o]=o<26?o+65:o<52?o+71:o<62?o-4:o-59|43]=o++;r.encode=function(e,t,r){for(var a,o=null,i=[],s=0,u=0;t<r;){var l=e[t++];switch(u){case 0:i[s++]=n[l>>2],a=(3&l)<<4,u=1;break;case 1:i[s++]=n[a|l>>4],a=(15&l)<<2,u=2;break;case 2:i[s++]=n[a|l>>6],i[s++]=n[63&l],u=0}s>8191&&((o||(o=[])).push(String.fromCharCode.apply(String,i)),s=0)}return u&&(i[s++]=n[a],i[s++]=61,1===u&&(i[s++]=61)),o?(s&&o.push(String.fromCharCode.apply(String,i.slice(0,s))),o.join("")):String.fromCharCode.apply(String,i.slice(0,s))};r.decode=function(e,t,r){for(var n,o=r,i=0,s=0;s<e.length;){var u=e.charCodeAt(s++);if(61===u&&i>1)break;if(void 0===(u=a[u]))throw Error("invalid encoding");switch(i){case 0:n=u,i=1;break;case 1:t[r++]=n<<2|(48&u)>>4,n=u,i=2;break;case 2:t[r++]=(15&n)<<4|(60&u)>>2,n=u,i=3;break;case 3:t[r++]=(3&n)<<6|u,i=0}}if(1===i)throw Error("invalid encoding");return r-o},r.test=function(e){return/^(?:[A-Za-z0-9+/]{4})*(?:[A-Za-z0-9+/]{2}==|[A-Za-z0-9+/]{3}=)?$/.test(e)}}),eventemitter=EventEmitter;EventEmitter.prototype.on=function(e,t,r){return(this._listeners[e]||(this._listeners[e]=[])).push({fn:t,ctx:r||this}),this},EventEmitter.prototype.off=function(e,t){if(void 0===e)this._listeners={};else if(void 0===t)this._listeners[e]=[];else for(var r=this._listeners[e],n=0;n<r.length;)r[n].fn===t?r.splice(n,1):++n;return this},EventEmitter.prototype.emit=function(e){var t=this._listeners[e];if(t){for(var r=[],n=1;n<arguments.length;)r.push(arguments[n++]);for(n=0;n<t.length;)t[n].fn.apply(t[n++].ctx,r)}return this};var float_1=factory(factory),inquire_1=inquire,utf8_1=createCommonjsModule(function(e,t){var r=t;r.length=function(e){for(var t=0,r=0,n=0;n<e.length;++n)(r=e.charCodeAt(n))<128?t+=1:r<2048?t+=2:55296==(64512&r)&&56320==(64512&e.charCodeAt(n+1))?(++n,t+=4):t+=3;return t},r.read=function(e,t,r){if(r-t<1)return"";for(var n,a=null,o=[],i=0;t<r;)(n=e[t++])<128?o[i++]=n:n>191&&n<224?o[i++]=(31&n)<<6|63&e[t++]:n>239&&n<365?(n=((7&n)<<18|(63&e[t++])<<12|(63&e[t++])<<6|63&e[t++])-65536,o[i++]=55296+(n>>10),o[i++]=56320+(1023&n)):o[i++]=(15&n)<<12|(63&e[t++])<<6|63&e[t++],i>8191&&((a||(a=[])).push(String.fromCharCode.apply(String,o)),i=0);return a?(i&&a.push(String.fromCharCode.apply(String,o.slice(0,i))),a.join("")):String.fromCharCode.apply(String,o.slice(0,i))},r.write=function(e,t,r){for(var n,a,o=r,i=0;i<e.length;++i)(n=e.charCodeAt(i))<128?t[r++]=n:n<2048?(t[r++]=n>>6|192,t[r++]=63&n|128):55296==(64512&n)&&56320==(64512&(a=e.charCodeAt(i+1)))?(n=65536+((1023&n)<<10)+(1023&a),++i,t[r++]=n>>18|240,t[r++]=n>>12&63|128,t[r++]=n>>6&63|128,t[r++]=63&n|128):(t[r++]=n>>12|224,t[r++]=n>>6&63|128,t[r++]=63&n|128);return r-o}}),pool_1=pool,longbits=LongBits,zero=LongBits.zero=new LongBits(0,0);zero.toNumber=function(){return 0},zero.zzEncode=zero.zzDecode=function(){return this},zero.length=function(){return 1};var zeroHash=LongBits.zeroHash="\0\0\0\0\0\0\0\0";LongBits.fromNumber=function(e){if(0===e)return zero;var t=e<0;t&&(e=-e);var r=e>>>0,n=(e-r)/4294967296>>>0;return t&&(n=~n>>>0,r=~r>>>0,++r>4294967295&&(r=0,++n>4294967295&&(n=0))),new LongBits(r,n)},LongBits.from=function(e){if("number"==typeof e)return LongBits.fromNumber(e);if(minimal.isString(e)){if(!minimal.Long)return LongBits.fromNumber(parseInt(e,10));e=minimal.Long.fromString(e)}return e.low||e.high?new LongBits(e.low>>>0,e.high>>>0):zero},LongBits.prototype.toNumber=function(e){if(!e&&this.hi>>>31){var t=1+~this.lo>>>0,r=~this.hi>>>0;return t||(r=r+1>>>0),-(t+4294967296*r)}return this.lo+4294967296*this.hi},LongBits.prototype.toLong=function(e){return minimal.Long?new minimal.Long(0|this.lo,0|this.hi,Boolean(e)):{low:0|this.lo,high:0|this.hi,unsigned:Boolean(e)}};var charCodeAt=String.prototype.charCodeAt;LongBits.fromHash=function(e){return e===zeroHash?zero:new LongBits((charCodeAt.call(e,0)|charCodeAt.call(e,1)<<8|charCodeAt.call(e,2)<<16|charCodeAt.call(e,3)<<24)>>>0,(charCodeAt.call(e,4)|charCodeAt.call(e,5)<<8|charCodeAt.call(e,6)<<16|charCodeAt.call(e,7)<<24)>>>0)},LongBits.prototype.toHash=function(){return String.fromCharCode(255&this.lo,this.lo>>>8&255,this.lo>>>16&255,this.lo>>>24,255&this.hi,this.hi>>>8&255,this.hi>>>16&255,this.hi>>>24)},LongBits.prototype.zzEncode=function(){var e=this.hi>>31;return this.hi=((this.hi<<1|this.lo>>>31)^e)>>>0,this.lo=(this.lo<<1^e)>>>0,this},LongBits.prototype.zzDecode=function(){var e=-(1&this.lo);return this.lo=((this.lo>>>1|this.hi<<31)^e)>>>0,this.hi=(this.hi>>>1^e)>>>0,this},LongBits.prototype.length=function(){var e=this.lo,t=(this.lo>>>28|this.hi<<4)>>>0,r=this.hi>>>24;return 0===r?0===t?e<16384?e<128?1:2:e<2097152?3:4:t<16384?t<128?5:6:t<2097152?7:8:r<128?9:10};var minimal=createCommonjsModule(function(e,t){function r(e,t,r){for(var n=Object.keys(t),a=0;a<n.length;++a)void 0!==e[n[a]]&&r||(e[n[a]]=t[n[a]]);return e}function n(e){function t(e,n){if(!(this instanceof t))return new t(e,n);Object.defineProperty(this,"message",{get:function(){return e}}),Error.captureStackTrace?Error.captureStackTrace(this,t):Object.defineProperty(this,"stack",{value:(new Error).stack||""}),n&&r(this,n)}return(t.prototype=Object.create(Error.prototype)).constructor=t,Object.defineProperty(t.prototype,"name",{get:function(){return e}}),t.prototype.toString=function(){return this.name+": "+this.message},t}var a=t;a.asPromise=aspromise,a.base64=base64_1,a.EventEmitter=eventemitter,a.float=float_1,a.inquire=inquire_1,a.utf8=utf8_1,a.pool=pool_1,a.LongBits=longbits,a.emptyArray=Object.freeze?Object.freeze([]):[],a.emptyObject=Object.freeze?Object.freeze({}):{},a.isNode=Boolean(commonjsGlobal.process&&commonjsGlobal.process.versions&&commonjsGlobal.process.versions.node),a.isInteger=Number.isInteger||function(e){return"number"==typeof e&&isFinite(e)&&Math.floor(e)===e},a.isString=function(e){return"string"==typeof e||e instanceof String},a.isObject=function(e){return e&&"object"==typeof e},a.isset=a.isSet=function(e,t){var r=e[t];return!(null==r||!e.hasOwnProperty(t))&&("object"!=typeof r||(Array.isArray(r)?r.length:Object.keys(r).length)>0)},a.Buffer=function(){try{var e=a.inquire("buffer").Buffer;return e.prototype.utf8Write?e:null}catch(e){return null}}(),a._Buffer_from=null,a._Buffer_allocUnsafe=null,a.newBuffer=function(e){return"number"==typeof e?a.Buffer?a._Buffer_allocUnsafe(e):new a.Array(e):a.Buffer?a._Buffer_from(e):"undefined"==typeof Uint8Array?e:new Uint8Array(e)},a.Array="undefined"!=typeof Uint8Array?Uint8Array:Array,a.Long=commonjsGlobal.dcodeIO&&commonjsGlobal.dcodeIO.Long||a.inquire("long"),a.key2Re=/^true|false|0|1$/,a.key32Re=/^-?(?:0|[1-9][0-9]*)$/,a.key64Re=/^(?:[\\x00-\\xff]{8}|-?(?:0|[1-9][0-9]*))$/,a.longToHash=function(e){return e?a.LongBits.from(e).toHash():a.LongBits.zeroHash},a.longFromHash=function(e,t){var r=a.LongBits.fromHash(e);return a.Long?a.Long.fromBits(r.lo,r.hi,t):r.toNumber(Boolean(t))},a.merge=r,a.lcFirst=function(e){return e.charAt(0).toLowerCase()+e.substring(1)},a.newError=n,a.ProtocolError=n("ProtocolError"),a.oneOfGetter=function(e){for(var t={},r=0;r<e.length;++r)t[e[r]]=1;return function(){for(var e=Object.keys(this),r=e.length-1;r>-1;--r)if(1===t[e[r]]&&void 0!==this[e[r]]&&null!==this[e[r]])return e[r]}},a.oneOfSetter=function(e){return function(t){for(var r=0;r<e.length;++r)e[r]!==t&&delete this[e[r]]}},a.toJSONOptions={longs:String,enums:String,bytes:String,json:!0},a._configure=function(){var e=a.Buffer;e?(a._Buffer_from=e.from!==Uint8Array.from&&e.from||function(t,r){return new e(t,r)},a._Buffer_allocUnsafe=e.allocUnsafe||function(t){return new e(t)}):a._Buffer_from=a._Buffer_allocUnsafe=null}}),writer=Writer,BufferWriter,LongBits$1=minimal.LongBits,base64=minimal.base64,utf8=minimal.utf8;Writer.create=minimal.Buffer?function(){return(Writer.create=function(){return new BufferWriter})()}:function(){return new Writer},Writer.alloc=function(e){return new minimal.Array(e)},minimal.Array!==Array&&(Writer.alloc=minimal.pool(Writer.alloc,minimal.Array.prototype.subarray)),Writer.prototype._push=function(e,t,r){return this.tail=this.tail.next=new Op(e,t,r),this.len+=t,this},VarintOp.prototype=Object.create(Op.prototype),VarintOp.prototype.fn=writeVarint32,Writer.prototype.uint32=function(e){return this.len+=(this.tail=this.tail.next=new VarintOp((e>>>=0)<128?1:e<16384?2:e<2097152?3:e<268435456?4:5,e)).len,this},Writer.prototype.int32=function(e){return e<0?this._push(writeVarint64,10,LongBits$1.fromNumber(e)):this.uint32(e)},Writer.prototype.sint32=function(e){return this.uint32((e<<1^e>>31)>>>0)},Writer.prototype.uint64=function(e){var t=LongBits$1.from(e);return this._push(writeVarint64,t.length(),t)},Writer.prototype.int64=Writer.prototype.uint64,Writer.prototype.sint64=function(e){var t=LongBits$1.from(e).zzEncode();return this._push(writeVarint64,t.length(),t)},Writer.prototype.bool=function(e){return this._push(writeByte,1,e?1:0)},Writer.prototype.fixed32=function(e){return this._push(writeFixed32,4,e>>>0)},Writer.prototype.sfixed32=Writer.prototype.fixed32,Writer.prototype.fixed64=function(e){var t=LongBits$1.from(e);return this._push(writeFixed32,4,t.lo)._push(writeFixed32,4,t.hi)},Writer.prototype.sfixed64=Writer.prototype.fixed64,Writer.prototype.float=function(e){return this._push(minimal.float.writeFloatLE,4,e)},Writer.prototype.double=function(e){return this._push(minimal.float.writeDoubleLE,8,e)};var writeBytes=minimal.Array.prototype.set?function(e,t,r){t.set(e,r)}:function(e,t,r){for(var n=0;n<e.length;++n)t[r+n]=e[n]};Writer.prototype.bytes=function(e){var t=e.length>>>0;if(!t)return this._push(writeByte,1,0);if(minimal.isString(e)){var r=Writer.alloc(t=base64.length(e));base64.decode(e,r,0),e=r}return this.uint32(t)._push(writeBytes,t,e)},Writer.prototype.string=function(e){var t=utf8.length(e);return t?this.uint32(t)._push(utf8.write,t,e):this._push(writeByte,1,0)},Writer.prototype.fork=function(){return this.states=new State(this),this.head=this.tail=new Op(noop,0,0),this.len=0,this},Writer.prototype.reset=function(){return this.states?(this.head=this.states.head,this.tail=this.states.tail,this.len=this.states.len,this.states=this.states.next):(this.head=this.tail=new Op(noop,0,0),this.len=0),this},Writer.prototype.ldelim=function(){var e=this.head,t=this.tail,r=this.len;return this.reset().uint32(r),r&&(this.tail.next=e.next,this.tail=t,this.len+=r),this},Writer.prototype.finish=function(){for(var e=this.head.next,t=this.constructor.alloc(this.len),r=0;e;)e.fn(e.val,t,r),r+=e.len,e=e.next;return t},Writer._configure=function(e){BufferWriter=e};var writer_buffer=BufferWriter$1;(BufferWriter$1.prototype=Object.create(writer.prototype)).constructor=BufferWriter$1;var Buffer=minimal.Buffer;BufferWriter$1.alloc=function(e){return(BufferWriter$1.alloc=minimal._Buffer_allocUnsafe)(e)};var writeBytesBuffer=Buffer&&Buffer.prototype instanceof Uint8Array&&"set"===Buffer.prototype.set.name?function(e,t,r){t.set(e,r)}:function(e,t,r){if(e.copy)e.copy(t,r,0,e.length);else for(var n=0;n<e.length;)t[r++]=e[n++]};BufferWriter$1.prototype.bytes=function(e){minimal.isString(e)&&(e=minimal._Buffer_from(e,"base64"));var t=e.length>>>0;return this.uint32(t),t&&this._push(writeBytesBuffer,t,e),this},BufferWriter$1.prototype.string=function(e){var t=Buffer.byteLength(e);return this.uint32(t),t&&this._push(writeStringBuffer,t,e),this};var reader=Reader,BufferReader,LongBits$2=minimal.LongBits,utf8$1=minimal.utf8,create_array="undefined"!=typeof Uint8Array?function(e){if(e instanceof Uint8Array||Array.isArray(e))return new Reader(e);throw Error("illegal buffer")}:function(e){if(Array.isArray(e))return new Reader(e);throw Error("illegal buffer")};Reader.create=minimal.Buffer?function(e){return(Reader.create=function(e){return minimal.Buffer.isBuffer(e)?new BufferReader(e):create_array(e)})(e)}:create_array,Reader.prototype._slice=minimal.Array.prototype.subarray||minimal.Array.prototype.slice,Reader.prototype.uint32=function(){var e=4294967295;return function(){if(e=(127&this.buf[this.pos])>>>0,this.buf[this.pos++]<128)return e;if(e=(e|(127&this.buf[this.pos])<<7)>>>0,this.buf[this.pos++]<128)return e;if(e=(e|(127&this.buf[this.pos])<<14)>>>0,this.buf[this.pos++]<128)return e;if(e=(e|(127&this.buf[this.pos])<<21)>>>0,this.buf[this.pos++]<128)return e;if(e=(e|(15&this.buf[this.pos])<<28)>>>0,this.buf[this.pos++]<128)return 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readLongVarint.call(this)[t](!0)},sint64:function(){return readLongVarint.call(this).zzDecode()[t](!1)},fixed64:function(){return readFixed64.call(this)[t](!0)},sfixed64:function(){return readFixed64.call(this)[t](!1)}})};var reader_buffer=BufferReader$1;(BufferReader$1.prototype=Object.create(reader.prototype)).constructor=BufferReader$1,minimal.Buffer&&(BufferReader$1.prototype._slice=minimal.Buffer.prototype.slice),BufferReader$1.prototype.string=function(){var e=this.uint32();return this.buf.utf8Slice(this.pos,this.pos=Math.min(this.pos+e,this.len))};var service=Service;(Service.prototype=Object.create(minimal.EventEmitter.prototype)).constructor=Service,Service.prototype.rpcCall=function e(t,r,n,a,o){if(!a)throw TypeError("request must be specified");var i=this;if(!o)return minimal.asPromise(e,i,t,r,n,a);if(i.rpcImpl)try{return i.rpcImpl(t,r[i.requestDelimited?"encodeDelimited":"encode"](a).finish(),function(e,r){if(e)return i.emit("error",e,t),o(e);{if(null!==r){if(!(r instanceof n))try{r=n[i.responseDelimited?"decodeDelimited":"decode"](r)}catch(e){return i.emit("error",e,t),o(e)}return i.emit("data",r,t),o(null,r)}i.end(!0)}})}catch(e){return i.emit("error",e,t),void setTimeout(function(){o(e)},0)}else setTimeout(function(){o(Error("already ended"))},0)},Service.prototype.end=function(e){return this.rpcImpl&&(e||this.rpcImpl(null,null,null),this.rpcImpl=null,this.emit("end").off()),this};var rpc_1=createCommonjsModule(function(e,t){t.Service=service}),roots={},indexMinimal=createCommonjsModule(function(e,t){function r(){n.Reader._configure(n.BufferReader),n.util._configure()}var n=t;n.build="minimal",n.Writer=writer,n.BufferWriter=writer_buffer,n.Reader=reader,n.BufferReader=reader_buffer,n.util=minimal,n.rpc=rpc_1,n.roots=roots,n.configure=r,n.Writer._configure(n.BufferWriter),r()}),minimal$1=indexMinimal,minimal_1=minimal$1.roots,minimal_2=minimal$1.Reader,minimal_3=minimal$1.util,$Reader=minimal_2,$util=minimal_3,$root=minimal_1.default||(minimal_1.default={}),tensorflow=$root.tensorflow=function(){var e={};return e.Any=function(){function e(e){if(e)for(var t=Object.keys(e),r=0;r<t.length;++r)null!=e[t[r]]&&(this[t[r]]=e[t[r]])}return e.prototype.typeUrl="",e.prototype.value=$util.newBuffer([]),e.decode=function(e,t){e instanceof $Reader||(e=$Reader.create(e));for(var r=void 0===t?e.len:e.pos+t,n=new $root.tensorflow.Any;e.pos<r;){var a=e.uint32();switch(a>>>3){case 1:n.typeUrl=e.string();break;case 2:n.value=e.bytes();break;default:e.skipType(7&a)}}return n},e}(),e.DataType=function(){var e={},t=Object.create(e);return t[e[0]="DT_INVALID"]=0,t[e[1]="DT_FLOAT"]=1,t[e[2]="DT_DOUBLE"]=2,t[e[3]="DT_INT32"]=3,t[e[4]="DT_UINT8"]=4,t[e[5]="DT_INT16"]=5,t[e[6]="DT_INT8"]=6,t[e[7]="DT_STRING"]=7,t[e[8]="DT_COMPLEX64"]=8,t[e[9]="DT_INT64"]=9,t[e[10]="DT_BOOL"]=10,t[e[11]="DT_QINT8"]=11,t[e[12]="DT_QUINT8"]=12,t[e[13]="DT_QINT32"]=13,t[e[14]="DT_BFLOAT16"]=14,t[e[101]="DT_FLOAT_REF"]=101,t[e[102]="DT_DOUBLE_REF"]=102,t[e[103]="DT_INT32_REF"]=103,t[e[104]="DT_UINT8_REF"]=104,t[e[105]="DT_INT16_REF"]=105,t[e[106]="DT_INT8_REF"]=106,t[e[107]="DT_STRING_REF"]=107,t[e[108]="DT_COMPLEX64_REF"]=108,t[e[109]="DT_INT64_REF"]=109,t[e[110]="DT_BOOL_REF"]=110,t[e[111]="DT_QINT8_REF"]=111,t[e[112]="DT_QUINT8_REF"]=112,t[e[113]="DT_QINT32_REF"]=113,t[e[114]="DT_BFLOAT16_REF"]=114,t}(),e.TensorShape=function(){function e(e){if(this.dim=[],e)for(var t=Object.keys(e),r=0;r<t.length;++r)null!=e[t[r]]&&(this[t[r]]=e[t[r]])}return e.prototype.dim=$util.emptyArray,e.prototype.unknownRank=!1,e.decode=function(e,t){e instanceof 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2:n.tensorShape=$root.tensorflow.TensorShape.decode(e,e.uint32());break;case 3:n.versionNumber=e.int32();break;case 4:n.tensorContent=e.bytes();break;case 5:if(n.floatVal&&n.floatVal.length||(n.floatVal=[]),2==(7&a))for(o=e.uint32()+e.pos;e.pos<o;)n.floatVal.push(e.float());else n.floatVal.push(e.float());break;case 6:if(n.doubleVal&&n.doubleVal.length||(n.doubleVal=[]),2==(7&a))for(o=e.uint32()+e.pos;e.pos<o;)n.doubleVal.push(e.double());else n.doubleVal.push(e.double());break;case 7:if(n.intVal&&n.intVal.length||(n.intVal=[]),2==(7&a))for(o=e.uint32()+e.pos;e.pos<o;)n.intVal.push(e.int32());else n.intVal.push(e.int32());break;case 8:n.stringVal&&n.stringVal.length||(n.stringVal=[]),n.stringVal.push(e.bytes());break;case 9:if(n.scomplexVal&&n.scomplexVal.length||(n.scomplexVal=[]),2==(7&a))for(o=e.uint32()+e.pos;e.pos<o;)n.scomplexVal.push(e.float());else n.scomplexVal.push(e.float());break;case 10:if(n.int64Val&&n.int64Val.length||(n.int64Val=[]),2==(7&a))for(o=e.uint32()+e.pos;e.pos<o;)n.int64Val.push(e.int64());else n.int64Val.push(e.int64());break;case 11:if(n.boolVal&&n.boolVal.length||(n.boolVal=[]),2==(7&a))for(o=e.uint32()+e.pos;e.pos<o;)n.boolVal.push(e.bool());else n.boolVal.push(e.bool());break;case 16:if(n.uint32Val&&n.uint32Val.length||(n.uint32Val=[]),2==(7&a))for(o=e.uint32()+e.pos;e.pos<o;)n.uint32Val.push(e.uint32());else n.uint32Val.push(e.uint32());break;case 17:if(n.uint64Val&&n.uint64Val.length||(n.uint64Val=[]),2==(7&a))for(var o=e.uint32()+e.pos;e.pos<o;)n.uint64Val.push(e.uint64());else n.uint64Val.push(e.uint64());break;default:e.skipType(7&a)}}return n},e}(),e.AttrValue=function(){function e(e){if(e)for(var t=Object.keys(e),r=0;r<t.length;++r)null!=e[t[r]]&&(this[t[r]]=e[t[r]])}e.prototype.list=null,e.prototype.s=$util.newBuffer([]),e.prototype.i=$util.Long?$util.Long.fromBits(0,0,!1):0,e.prototype.f=0,e.prototype.b=!1,e.prototype.type=0,e.prototype.shape=null,e.prototype.tensor=null,e.prototype.placeholder="",e.prototype.func=null;var t=void 0;return Object.defineProperty(e.prototype,"value",{get:$util.oneOfGetter(t=["list","s","i","f","b","type","shape","tensor","placeholder","func"]),set:$util.oneOfSetter(t)}),e.decode=function(e,t){e instanceof $Reader||(e=$Reader.create(e));for(var r=void 0===t?e.len:e.pos+t,n=new $root.tensorflow.AttrValue;e.pos<r;){var a=e.uint32();switch(a>>>3){case 1:n.list=$root.tensorflow.AttrValue.ListValue.decode(e,e.uint32());break;case 2:n.s=e.bytes();break;case 3:n.i=e.int64();break;case 4:n.f=e.float();break;case 5:n.b=e.bool();break;case 6:n.type=e.int32();break;case 7:n.shape=$root.tensorflow.TensorShape.decode(e,e.uint32());break;case 8:n.tensor=$root.tensorflow.Tensor.decode(e,e.uint32());break;case 9:n.placeholder=e.string();break;case 10:n.func=$root.tensorflow.NameAttrList.decode(e,e.uint32());break;default:e.skipType(7&a)}}return n},e.ListValue=function(){function e(e){if(this.s=[],this.i=[],this.f=[],this.b=[],this.type=[],this.shape=[],this.tensor=[],this.func=[],e)for(var t=Object.keys(e),r=0;r<t.length;++r)null!=e[t[r]]&&(this[t[r]]=e[t[r]])}return e.prototype.s=$util.emptyArray,e.prototype.i=$util.emptyArray,e.prototype.f=$util.emptyArray,e.prototype.b=$util.emptyArray,e.prototype.type=$util.emptyArray,e.prototype.shape=$util.emptyArray,e.prototype.tensor=$util.emptyArray,e.prototype.func=$util.emptyArray,e.decode=function(e,t){e instanceof $Reader||(e=$Reader.create(e));for(var r=void 0===t?e.len:e.pos+t,n=new $root.tensorflow.AttrValue.ListValue;e.pos<r;){var a=e.uint32();switch(a>>>3){case 2:n.s&&n.s.length||(n.s=[]),n.s.push(e.bytes());break;case 3:if(n.i&&n.i.length||(n.i=[]),2==(7&a))for(o=e.uint32()+e.pos;e.pos<o;)n.i.push(e.int64());else n.i.push(e.int64());break;case 4:if(n.f&&n.f.length||(n.f=[]),2==(7&a))for(o=e.uint32()+e.pos;e.pos<o;)n.f.push(e.float());else n.f.push(e.float());break;case 5:if(n.b&&n.b.length||(n.b=[]),2==(7&a))for(o=e.uint32()+e.pos;e.pos<o;)n.b.push(e.bool());else n.b.push(e.bool());break;case 6:if(n.type&&n.type.length||(n.type=[]),2==(7&a))for(var o=e.uint32()+e.pos;e.pos<o;)n.type.push(e.int32());else n.type.push(e.int32());break;case 7:n.shape&&n.shape.length||(n.shape=[]),n.shape.push($root.tensorflow.TensorShape.decode(e,e.uint32()));break;case 8:n.tensor&&n.tensor.length||(n.tensor=[]),n.tensor.push($root.tensorflow.Tensor.decode(e,e.uint32()));break;case 9:n.func&&n.func.length||(n.func=[]),n.func.push($root.tensorflow.NameAttrList.decode(e,e.uint32()));break;default:e.skipType(7&a)}}return n},e}(),e}(),e.NameAttrList=function(){function e(e){if(this.attr={},e)for(var t=Object.keys(e),r=0;r<t.length;++r)null!=e[t[r]]&&(this[t[r]]=e[t[r]])}return e.prototype.name="",e.prototype.attr=$util.emptyObject,e.decode=function(e,t){e instanceof $Reader||(e=$Reader.create(e));for(var r,n=void 0===t?e.len:e.pos+t,a=new $root.tensorflow.NameAttrList;e.pos<n;){var o=e.uint32();switch(o>>>3){case 1:a.name=e.string();break;case 2:e.skip().pos++,a.attr===$util.emptyObject&&(a.attr={}),r=e.string(),e.pos++,a.attr[r]=$root.tensorflow.AttrValue.decode(e,e.uint32());break;default:e.skipType(7&o)}}return a},e}(),e.NodeDef=function(){function e(e){if(this.input=[],this.attr={},e)for(var t=Object.keys(e),r=0;r<t.length;++r)null!=e[t[r]]&&(this[t[r]]=e[t[r]])}return e.prototype.name="",e.prototype.op="",e.prototype.input=$util.emptyArray,e.prototype.device="",e.prototype.attr=$util.emptyObject,e.decode=function(e,t){e instanceof $Reader||(e=$Reader.create(e));for(var r,n=void 0===t?e.len:e.pos+t,a=new $root.tensorflow.NodeDef;e.pos<n;){var o=e.uint32();switch(o>>>3){case 1:a.name=e.string();break;case 2:a.op=e.string();break;case 3:a.input&&a.input.length||(a.input=[]),a.input.push(e.string());break;case 4:a.device=e.string();break;case 5:e.skip().pos++,a.attr===$util.emptyObject&&(a.attr={}),r=e.string(),e.pos++,a.attr[r]=$root.tensorflow.AttrValue.decode(e,e.uint32());break;default:e.skipType(7&o)}}return a},e}(),e.VersionDef=function(){function e(e){if(this.badConsumers=[],e)for(var t=Object.keys(e),r=0;r<t.length;++r)null!=e[t[r]]&&(this[t[r]]=e[t[r]])}return e.prototype.producer=0,e.prototype.minConsumer=0,e.prototype.badConsumers=$util.emptyArray,e.decode=function(e,t){e instanceof $Reader||(e=$Reader.create(e));for(var r=void 0===t?e.len:e.pos+t,n=new $root.tensorflow.VersionDef;e.pos<r;){var a=e.uint32();switch(a>>>3){case 1:n.producer=e.int32();break;case 2:n.minConsumer=e.int32();break;case 3:if(n.badConsumers&&n.badConsumers.length||(n.badConsumers=[]),2==(7&a))for(var o=e.uint32()+e.pos;e.pos<o;)n.badConsumers.push(e.int32());else n.badConsumers.push(e.int32());break;default:e.skipType(7&a)}}return n},e}(),e.GraphDef=function(){function e(e){if(this.node=[],e)for(var t=Object.keys(e),r=0;r<t.length;++r)null!=e[t[r]]&&(this[t[r]]=e[t[r]])}return e.prototype.node=$util.emptyArray,e.prototype.versions=null,e.prototype.library=null,e.decode=function(e,t){e instanceof $Reader||(e=$Reader.create(e));for(var r=void 0===t?e.len:e.pos+t,n=new $root.tensorflow.GraphDef;e.pos<r;){var a=e.uint32();switch(a>>>3){case 1:n.node&&n.node.length||(n.node=[]),n.node.push($root.tensorflow.NodeDef.decode(e,e.uint32()));break;case 4:n.versions=$root.tensorflow.VersionDef.decode(e,e.uint32());break;case 2:n.library=$root.tensorflow.FunctionDefLibrary.decode(e,e.uint32());break;default:e.skipType(7&a)}}return n},e}(),e.CollectionDef=function(){function e(e){if(e)for(var t=Object.keys(e),r=0;r<t.length;++r)null!=e[t[r]]&&(this[t[r]]=e[t[r]])}e.prototype.nodeList=null,e.prototype.bytesList=null,e.prototype.int64List=null,e.prototype.floatList=null,e.prototype.anyList=null;var t=void 0;return Object.defineProperty(e.prototype,"kind",{get:$util.oneOfGetter(t=["nodeList","bytesList","int64List","floatList","anyList"]),set:$util.oneOfSetter(t)}),e.decode=function(e,t){e instanceof $Reader||(e=$Reader.create(e));for(var r=void 0===t?e.len:e.pos+t,n=new $root.tensorflow.CollectionDef;e.pos<r;){var a=e.uint32();switch(a>>>3){case 1:n.nodeList=$root.tensorflow.CollectionDef.NodeList.decode(e,e.uint32());break;case 2:n.bytesList=$root.tensorflow.CollectionDef.BytesList.decode(e,e.uint32());break;case 3:n.int64List=$root.tensorflow.CollectionDef.Int64List.decode(e,e.uint32());break;case 4:n.floatList=$root.tensorflow.CollectionDef.FloatList.decode(e,e.uint32());break;case 5:n.anyList=$root.tensorflow.CollectionDef.AnyList.decode(e,e.uint32());break;default:e.skipType(7&a)}}return n},e.NodeList=function(){function e(e){if(this.value=[],e)for(var t=Object.keys(e),r=0;r<t.length;++r)null!=e[t[r]]&&(this[t[r]]=e[t[r]])}return e.prototype.value=$util.emptyArray,e.decode=function(e,t){e instanceof $Reader||(e=$Reader.create(e));for(var r=void 0===t?e.len:e.pos+t,n=new $root.tensorflow.CollectionDef.NodeList;e.pos<r;){var a=e.uint32();switch(a>>>3){case 1:n.value&&n.value.length||(n.value=[]),n.value.push(e.string());break;default:e.skipType(7&a)}}return n},e}(),e.BytesList=function(){function e(e){if(this.value=[],e)for(var t=Object.keys(e),r=0;r<t.length;++r)null!=e[t[r]]&&(this[t[r]]=e[t[r]])}return e.prototype.value=$util.emptyArray,e.decode=function(e,t){e instanceof $Reader||(e=$Reader.create(e));for(var r=void 0===t?e.len:e.pos+t,n=new $root.tensorflow.CollectionDef.BytesList;e.pos<r;){var a=e.uint32();switch(a>>>3){case 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n},e}(),e}(),arithmetic=[{tfOpName:"Add",dlOpName:"add",category:"arithmetic",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"BiasAdd",dlOpName:"add",category:"arithmetic",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sub",dlOpName:"sub",category:"arithmetic",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"RealDiv",dlOpName:"div",category:"arithmetic",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Div",dlOpName:"div",category:"arithmetic",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Mul",dlOpName:"mul",category:"arithmetic",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Maximum",dlOpName:"maximum",category:"arithmetic",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"}]},{tfOpName:"Minimum",dlOpName:"minimum",category:"arithmetic",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"}]},{tfOpName:"Pow",dlOpName:"pow",category:"arithmetic",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"SquaredDifference",dlOpName:"squaredDifference",category:"arithmetic",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Mod",dlOpName:"mod",category:"arithmetic",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]}],arithmetic$1=Object.freeze({default:arithmetic}),basic_math=[{tfOpName:"Abs",dlOpName:"abs",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Acos",dlOpName:"acos",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Asin",dlOpName:"asin",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"atan",dlOpName:"atan",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Ceil",dlOpName:"ceil",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ClipByValue",dlOpName:"clipByValue",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"clip_value_min",dlParamName:"clipValueMin",type:"number"},{tfParamName:"clip_value_max",dlParamName:"clipValueMax",type:"number"}]},{tfOpName:"Cos",dlOpName:"cos",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Cosh",dlOpName:"cosh",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Elu",dlOpName:"elu",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Exp",dlOpName:"exp",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Floor",dlOpName:"floor",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Log",dlOpName:"log",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Neg",dlOpName:"neg",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Relu",dlOpName:"relu",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Relu6",dlOpName:"clipByValue",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0},{dlParamName:"clipValueMin",type:"number",defaultValue:0},{dlParamName:"clipValueMax",type:"number",defaultValue:6}]},{tfOpName:"Selu",dlOpName:"selu",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sigmoid",dlOpName:"sigmoid",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sin",dlOpName:"sin",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sinh",dlOpName:"sinh",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sqrt",dlOpName:"sqrt",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Rsqrt",dlOpName:"rsqrt",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Square",dlOpName:"square",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Tan",dlOpName:"tan",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Tanh",dlOpName:"tanh",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sign",dlOpName:"sign",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Round",dlOpName:"round",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Expm1",dlOpName:"expm1",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Log1p",dlOpName:"log1p",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Reciprocal",dlOpName:"reciprocal",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Reciprocal",dlOpName:"reciprocal",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Softplus",dlOpName:"softplus",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Asinh",dlOpName:"asinh",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Acosh",dlOpName:"acosh",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Atanh",dlOpName:"atanh",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Erf",dlOpName:"erf",category:"basic_math",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]}],basicMath=Object.freeze({default:basic_math}),control=[{tfOpName:"LoopCond",dlOpName:"loopCond",category:"control",params:[{tfInputIndex:0,dlParamName:"pred",type:"tensor"}]},{tfOpName:"Switch",dlOpName:"switch",category:"control",params:[{tfInputIndex:0,dlParamName:"data",type:"tensor"},{tfInputIndex:1,dlParamName:"pred",type:"tensor"}]},{tfOpName:"Merge",dlOpName:"merge",category:"control",params:[{tfInputIndex:0,tfInputParamLength:0,dlParamName:"tensors",type:"tensors"}]},{tfOpName:"Enter",dlOpName:"enter",category:"control",params:[{tfInputIndex:0,dlParamName:"tensor",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0},{tfParamName:"frame_name",dlParamName:"frameName",type:"string"},{tfParamName:"is_constant",dlParamName:"isConstant",type:"bool"}]},{tfOpName:"Exit",dlOpName:"exit",category:"control",params:[{tfInputIndex:0,dlParamName:"tensor",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"NextIteration",dlOpName:"nextIteration",category:"control",params:[{tfInputIndex:0,dlParamName:"tensor",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]}],control$1=Object.freeze({default:control}),convolution=[{tfOpName:"AvgPool",dlOpName:"avgPool",category:"convolution",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"strides",dlParamName:"strides",type:"number[]"},{tfParamName:"padding",dlParamName:"pad",type:"string"},{tfParamName:"data_format",dlParamName:"dataFormat",type:"string",notSupported:!0},{tfParamName:"ksize",dlParamName:"kernelSize",type:"number[]"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MaxPool",dlOpName:"maxPool",category:"convolution",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"strides",dlParamName:"strides",type:"number[]"},{tfParamName:"padding",dlParamName:"pad",type:"string"},{tfParamName:"data_format",dlParamName:"dataFormat",type:"string",notSupported:!0},{tfParamName:"ksize",dlParamName:"kernelSize",type:"number[]"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Conv1D",dlOpName:"conv1d",category:"convolution",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"filter",type:"tensor"},{tfParamName:"stride",dlParamName:"stride",type:"number"},{tfParamName:"padding",dlParamName:"pad",type:"string"},{tfParamName:"data_format",dlParamName:"dataFormat",type:"string",defaultValue:"NWC"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0},{tfParamName:"dilation",dlParamName:"dilation",type:"number",defaultValue:1}]},{tfOpName:"Conv2D",dlOpName:"conv2d",category:"convolution",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"filter",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0},{tfParamName:"strides",dlParamName:"strides",type:"number[]"},{tfParamName:"padding",dlParamName:"pad",type:"string"},{tfParamName:"useCudnnOnGpu",dlParamName:"useCudnnOnGpu",type:"bool"},{tfParamName:"data_format",dlParamName:"dataFormat",type:"string",defaultValue:"NHWC"},{tfParamName:"dilations",dlParamName:"dilations",type:"number[]"}]},{tfOpName:"Conv2DBackpropInput",dlOpName:"conv2dTranspose",category:"convolution",params:[{tfInputIndex:2,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"filter",type:"tensor"},{tfInputIndex:0,dlParamName:"outputShape",type:"number[]"},{tfParamName:"strides",dlParamName:"strides",type:"number[]"},{tfParamName:"padding",dlParamName:"pad",type:"string"},{tfParamName:"data_format",dlParamName:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"DepthwiseConv2d",dlOpName:"depthwiseConv2d",category:"convolution",params:[{tfInputIndex:0,dlParamName:"input",type:"tensor"},{tfInputIndex:1,dlParamName:"filter",type:"tensor"},{tfParamName:"strides",dlParamName:"strides",type:"number[]"},{tfParamName:"padding",dlParamName:"pad",type:"string"},{tfParamName:"data_format",dlParamName:"dataFormat",type:"string",defaultValue:"NHWC"},{tfParamName:"dilations",dlParamName:"dilations",type:"number[]"}]},{tfOpName:"DepthwiseConv2dNative",dlOpName:"depthwiseConv2d",category:"convolution",params:[{tfInputIndex:0,dlParamName:"input",type:"tensor"},{tfInputIndex:1,dlParamName:"filter",type:"tensor"},{tfParamName:"strides",dlParamName:"strides",type:"number[]"},{tfParamName:"padding",dlParamName:"pad",type:"string"},{tfParamName:"data_format",dlParamName:"dataFormat",type:"string",defaultValue:"NHWC"},{tfParamName:"dilations",dlParamName:"dilations",type:"number[]"}]}],convolution$1=Object.freeze({default:convolution}),creation=[{tfOpName:"Fill",dlOpName:"fill",category:"creation",params:[{tfInputIndex:0,dlParamName:"shape",type:"number[]"},{tfInputIndex:1,dlParamName:"value",type:"number"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LinSpace",dlOpName:"linspace",category:"creation",params:[{tfInputIndex:0,dlParamName:"start",type:"number"},{tfInputIndex:1,dlParamName:"stop",type:"number"},{tfInputIndex:2,dlParamName:"num",type:"number"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"OneHot",dlOpName:"oneHot",category:"creation",params:[{tfInputIndex:0,dlParamName:"indices",type:"tensor"},{tfInputIndex:1,dlParamName:"depth",type:"number"},{tfInputIndex:2,dlParamName:"onValue",type:"number",defaultValue:1},{tfInputIndex:3,dlParamName:"offValue",type:"number",defaultValue:0},{tfParamName:"axis",dlParamName:"axis",type:"number",notSupported:!0},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Ones",dlOpName:"ones",category:"creation",params:[{tfInputIndex:0,dlParamName:"shape",type:"number[]"},{tfParamName:"T",dlParamName:"dtype",type:"dtype"}]},{tfOpName:"OnesLike",dlOpName:"onesLike",category:"creation",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"dtype",dlParamName:"dtype",type:"dtype"}]},{tfOpName:"RandomUniform",dlOpName:"rand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:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LessEqual",dlOpName:"lessEqual",category:"logical",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalAnd",dlOpName:"logicalAnd",category:"logical",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalNot",dlOpName:"logicalNot",category:"logical",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalOr",dlOpName:"logicalOr",category:"logical",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Select",dlOpName:"where",category:"logical",params:[{tfInputIndex:0,dlParamName:"condition",type:"tensor"},{tfInputIndex:1,dlParamName:"a",type:"tensor"},{tfInputIndex:2,dlParamName:"b",type:"tensor"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]}],logical$1=Object.freeze({default:logical}),matrices=[{tfOpName:"MatMul",dlOpName:"matMul",category:"matrices",params:[{tfInputIndex:0,dlParamName:"a",type:"tensor"},{tfInputIndex:1,dlParamName:"b",type:"tensor"},{tfParamName:"transpose_a",dlParamName:"transposeA",type:"bool",defaultValue:!1},{tfParamName:"transpose_b",dlParamName:"transposeB",type:"bool",defaultValue:!1},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Transpose",dlOpName:"transpose",category:"matrices",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"perm",dlParamName:"perm",type:"number[]"},{tfParamName:"T",dlParamName:"dtype",type:"dtype",notSupported:!0}]}],matrices$1=Object.freeze({default:matrices}),normalization=[{tfOpName:"FusedBatchNorm",dlOpName:"batchNormalization",category:"normalization",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"scale",type:"tensor"},{tfInputIndex:2,dlParamName:"offset",type:"tensor"},{tfInputIndex:3,dlParamName:"mean",type:"tensor"},{tfInputIndex:4,dlParamName:"variance",type:"tensor"},{tfParamName:"epsilon",dlParamName:"epsilon",type:"number",defaultValue:.001},{tfParamName:"data_format",dlParamName:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"FusedBatchNormV2",dlOpName:"batchNormalization",category:"normalization",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"scale",type:"tensor"},{tfInputIndex:2,dlParamName:"offset",type:"tensor"},{tfInputIndex:3,dlParamName:"mean",type:"tensor"},{tfInputIndex:4,dlParamName:"variance",type:"tensor"},{tfParamName:"epsilon",dlParamName:"epsilon",type:"number",defaultValue:.001},{tfParamName:"data_format",dlParamName:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"LRN",dlOpName:"localResponseNormalization",category:"normalization",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"depth_radius",dlParamName:"radius",type:"number",defaultValue:5},{tfParamName:"bias",dlParamName:"bias",type:"number",defaultValue:1},{tfParamName:"alpha",dlParamName:"alpha",type:"number",defaultValue:1},{tfParamName:"beta",dlParamName:"beta",type:"number",defaultValue:.5}]},{tfOpName:"Softmax",dlOpName:"softmax",category:"normalization",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"}]}],normalization$1=Object.freeze({default:normalization}),reduction=[{tfOpName:"Max",dlOpName:"max",category:"reduction",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"axis",type:"number[]"},{tfParamName:"keep_dims",dlParamName:"keepDims",type:"bool"}]},{tfOpName:"Mean",dlOpName:"mean",category:"reduction",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"axis",type:"number[]"},{tfParamName:"keep_dims",dlParamName:"keepDims",type:"bool"}]},{tfOpName:"Min",dlOpName:"min",category:"reduction",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"axis",type:"number[]"},{tfParamName:"keep_dims",dlParamName:"keepDims",type:"bool"}]},{tfOpName:"Sum",dlOpName:"sum",category:"reduction",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"axis",type:"number[]"},{tfParamName:"keep_dims",dlParamName:"keepDims",type:"bool"}]},{tfOpName:"ArgMax",dlOpName:"argMax",category:"reduction",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"axis",type:"number"}]},{tfOpName:"ArgMin",dlOpName:"argMin",category:"reduction",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"axis",type:"number"}]}],reduction$1=Object.freeze({default:reduction}),slice_join=[{tfOpName:"ConcatV2",dlOpName:"concat",category:"slice_join",params:[{tfInputIndex:0,tfInputParamLength:1,dlParamName:"tensors",type:"tensors"},{tfInputIndex:-1,dlParamName:"axis",type:"number"}]},{tfOpName:"Concat",dlOpName:"concat",category:"slice_join",params:[{tfInputIndex:1,tfInputParamLength:1,dlParamName:"tensors",type:"tensors"},{tfInputIndex:0,dlParamName:"axis",type:"number"}]},{tfOpName:"GatherV2",dlOpName:"gather",category:"slice_join",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"indices",type:"tensor"},{tfParamName:"axis",dlParamName:"axis",type:"number",defaultValue:0}]},{tfOpName:"Gather",dlOpName:"gather",category:"slice_join",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"indices",type:"tensor"},{tfParamName:"axis",dlParamName:"axis",type:"number",defaultValue:0},{tfParamName:"validate_indices",dlParamName:"validateIndices",type:"bool",notSupported:!0}]},{tfOpName:"Reverse",dlOpName:"reverse",category:"slice_join",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"axis",type:"number"}]},{tfOpName:"ReverseV2",dlOpName:"reverse",category:"slice_join",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"axis",type:"number"}]},{tfOpName:"Slice",dlOpName:"slice",category:"slice_join",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"begin",type:"number[]"},{tfInputIndex:2,dlParamName:"size",type:"number[]"}]},{tfOpName:"StridedSlice",dlOpName:"stridedSlice",category:"slice_join",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"begin",type:"number[]"},{tfInputIndex:2,dlParamName:"end",type:"number[]"},{tfInputIndex:3,dlParamName:"strides",type:"number[]"},{tfParamName:"begin_mask",dlParamName:"beginMask",type:"number",defaultValue:0},{tfParamName:"end_mask",dlParamName:"endMask",type:"number",defaultValue:0}]},{tfOpName:"Pack",dlOpName:"stack",category:"slice_join",params:[{tfInputIndex:0,tfInputParamLength:0,dlParamName:"tensors",type:"tensors"},{tfParamName:"axis",dlParamName:"axis",type:"number",defaultValue:0}]},{tfOpName:"Tile",dlOpName:"tile",category:"slice_join",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"reps",type:"number[]"}]},{tfOpName:"Split",dlOpName:"split",category:"slice_join",params:[{tfInputIndex:0,dlParamName:"axis",type:"number",defaultValue:0},{tfInputIndex:1,dlParamName:"x",type:"tensor"},{tfParamName:"num_split",dlParamName:"numOrSizeSplits",type:"number",defaultValue:1}]}],sliceJoin=Object.freeze({default:slice_join}),transformation=[{tfOpName:"Cast",dlOpName:"cast",category:"transformation",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"SrcT",dlParamName:"sdtype",type:"dtype",notSupported:!0},{tfParamName:"DstT",dlParamName:"dtype",type:"dtype"}]},{tfOpName:"ExpandDims",dlOpName:"expandDims",category:"transformation",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,tfParamNameDeprecated:"dim",dlParamName:"axis",type:"number"}]},{tfOpName:"Pad",dlOpName:"pad",category:"transformation",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"padding",type:"number[]"},{tfParamName:"constant_value",dlParamName:"constantValue",type:"number",defaultValue:0}]},{tfOpName:"PadV2",dlOpName:"pad",category:"transformation",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"padding",type:"number[]"},{tfInputIndex:2,dlParamName:"constantValue",type:"number",defaultValue:0}]},{tfOpName:"Reshape",dlOpName:"reshape",category:"transformation",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfInputIndex:1,dlParamName:"shape",type:"number[]"}]},{tfOpName:"Squeeze",dlOpName:"squeeze",category:"transformation",params:[{tfInputIndex:0,dlParamName:"x",type:"tensor"},{tfParamName:"axis",tfParamNameDeprecated:"squeeze_dims",dlParamName:"axis",type:"number[]"}]}],transformation$1=Object.freeze({default:transformation}),CONTROL_FLOW_OPS=["Switch","Merge","Enter","Exit","NextIteration"],OperationMapper=function(){function e(){var e=[arithmetic$1,basicMath,control$1,convolution$1,creation$1,logical$1,image$2,graph$1,matrices$1,normalization$1,reduction$1,sliceJoin,transformation$1],t=[].concat.apply([],e.map(function(e){return e.default?e.default:e}));this.opMappers=t.reduce(function(e,t){return e[t.tfOpName]=t,e},{})}return Object.defineProperty(e,"Instance",{get:function(){return this._instance||(this._instance=new this)},enumerable:!0,configurable:!0}),e.prototype.isControlFlow=function(e){return CONTROL_FLOW_OPS.some(function(t){return t===e.op})},e.prototype.transformGraph=function(e){var t=this,r=!1,n=[],a=e.node.reduce(function(e,a){return e[a.name]=t.mapNode(a),t.isControlFlow(a)&&(r=!0),"Placeholder"===a.op&&n.push(e[a.name]),e},{}),o=[],i=[];return Object.keys(a).forEach(function(e){var t=a[e];t.inputNames.forEach(function(e){var r=getNodeNameAndIndex(e)[0];t.inputs.push(a[r]),a[r].children.push(t)}),0===t.inputs.length&&o.push(t)}),Object.keys(a).forEach(function(e){var t=a[e];0===t.children.length&&i.push(t)}),{nodes:a,inputs:o,outputs:i,placeholders:n,withControlFlow:r}},e.prototype.mapNode=function(e){var t=this,r=this.opMappers[e.op];if(void 0===r)throw new Error("Tensorflow Op is not supported: "+e.op);var n={name:e.name,op:r.dlOpName,category:r.category,inputNames:(e.input||[]).map(function(e){return e.startsWith("^")?e.substr(1):e}),inputs:[],children:[],params:{}};return r.params&&(n.params=r.params.reduce(function(r,n){var a=n.tfInputIndex,o=n.tfInputParamLength,i=n.type,s=void 0;if(void 0===a)switch(n.type){case"string":void 0===(s=t.getStringParam(e.attr,n.tfParamName,n.defaultValue))&&n.tfParamNameDeprecated&&(s=t.getStringParam(e.attr,n.tfParamNameDeprecated,n.defaultValue));break;case"number":void 0===(s=t.getNumberParam(e.attr,n.tfParamName,n.defaultValue))&&n.tfParamNameDeprecated&&(s=t.getNumberParam(e.attr,n.tfParamNameDeprecated,n.defaultValue));break;case"number[]":void 0===(s=t.getNumericArrayParam(e.attr,n.tfParamName,n.defaultValue))&&n.tfParamNameDeprecated&&(s=t.getNumericArrayParam(e.attr,n.tfParamNameDeprecated,n.defaultValue));break;case"bool":void 0===(s=t.getBoolParam(e.attr,n.tfParamName,n.defaultValue))&&n.tfParamNameDeprecated&&(s=t.getBoolParam(e.attr,n.tfParamNameDeprecated,n.defaultValue));break;case"shape":void 0===(s=t.getTensorShapeParam(e.attr,n.tfParamName,n.defaultValue))&&n.tfParamNameDeprecated&&(s=t.getTensorShapeParam(e.attr,n.tfParamNameDeprecated,n.defaultValue));break;case"dtype":void 0===(s=t.getDtypeParam(e.attr,n.tfParamName,n.defaultValue))&&n.tfParamNameDeprecated&&(s=t.getDtypeParam(e.attr,n.tfParamNameDeprecated,n.defaultValue));break;case"tensor":case"tensors":break;default:throw new Error("Unsupported param type: "+n.type+" for op: "+e.op)}return r[n.dlParamName]={value:s,inputIndex:a,type:i,inputParamLength:o},r},{})),n},e.prototype.getStringParam=function(e,t,r,n){void 0===n&&(n=!1);var a=e[t];if(void 0!==a){var 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0,void 0,function(){var r,n,a,o,i,s,u,l;return __generator$18(this,function(c){switch(c.label){case 0:r=this.graph.inputs.map(function(e){return{node:e,contexts:t.currentContext}}),n=__assign$1({},this.weightMap,e),a={},c.label=1;case 1:return r.length>0?(o=r.pop(),t.currentContext=o.contexts,i=executeOp$13(o.node,n,t),s=getNodeNameAndIndex(o.node.name,t)[0],u=n,l=s,[4,i]):[3,3];case 2:return u[l]=c.sent(),o.node.children.forEach(function(e){var o=getNodeNameAndIndex(e.name,t)[0];a[o]||("merge"===e.op?e.inputNames.some(function(e){return!!getTensor(e,n,t)})&&(a[o]=!0,r.push({contexts:t.currentContext,node:e})):e.inputNames.every(function(e){return!!getTensor(e,n,t)})&&(a[o]=!0,r.push({contexts:t.currentContext,node:e})))}),[3,1];case 3:return[2,n]}})})},e.prototype.findOutputs=function(e,t,r){return!r||r instanceof Array||(r=[r]),(r||this.graph.outputs.map(function(e){return e.name})).reduce(function(r,n){return r[n]=getTensor(n,e,t),r},{})},e.prototype.dispose=function(){var e=this;Object.keys(this.weightMap).forEach(function(t){return e.weightMap[t].forEach(function(e){return e.dispose()})})},e.prototype.checkInput=function(e){var t=this,r=Object.keys(e),n=[],a=[];if(this.placeholders.forEach(function(e){-1===r.indexOf(e)&&n.push(e)}),r.forEach(function(e){-1===t.placeholders.indexOf(e)&&a.push(e)}),n.length>0)throw new Error("The dict provided in model.execute(dict) has the keys ["+r+"], but is missing the required keys: ["+n+"].");if(a.length>0)throw new Error("The dict provided in model.execute(dict) has unused keys: ["+a+"]. Please provide only the following keys: ["+this.placeholders+"].")},e}(),__awaiter$19=function(e,t,r,n){return new(r||(r=Promise))(function(a,o){function i(e){try{u(n.next(e))}catch(e){o(e)}}function s(e){try{u(n.throw(e))}catch(e){o(e)}}function u(e){e.done?a(e.value):new r(function(t){t(e.value)}).then(i,s)}u((n=n.apply(e,t||[])).next())})},__generator$19=function(e,t){function r(e){return function(t){return n([e,t])}}function n(r){if(a)throw new TypeError("Generator is already executing.");for(;u;)try{if(a=1,o&&(i=o[2&r[0]?"return":r[0]?"throw":"next"])&&!(i=i.call(o,r[1])).done)return i;switch(o=0,i&&(r=[0,i.value]),r[0]){case 0:case 1:i=r;break;case 4:return u.label++,{value:r[1],done:!1};case 5:u.label++,o=r[1],r=[0];continue;case 7:r=u.ops.pop(),u.trys.pop();continue;default:if(i=u.trys,!(i=i.length>0&&i[i.length-1])&&(6===r[0]||2===r[0])){u=0;continue}if(3===r[0]&&(!i||r[1]>i[0]&&r[1]<i[3])){u.label=r[1];break}if(6===r[0]&&u.label<i[1]){u.label=i[1],i=r;break}if(i&&u.label<i[2]){u.label=i[2],u.ops.push(r);break}i[2]&&u.ops.pop(),u.trys.pop();continue}r=t.call(e,u)}catch(e){r=[6,e],o=0}finally{a=i=0}if(5&r[0])throw r[1];return{value:r[0]?r[1]:void 0,done:!0}}var a,o,i,s,u={label:0,sent:function(){if(1&i[0])throw i[1];return i[1]},trys:[],ops:[]};return s={next:r(0),throw:r(1),return:r(2)},"function"==typeof Symbol&&(s[Symbol.iterator]=function(){return this}),s},FrozenModel=function(){function e(e,t,r){this.modelUrl=e,this.weightManifestUrl=t,this.requestOption=r,this.version="n/a",this.pathPrefix=this.getPathPrefix()}return Object.defineProperty(e.prototype,"modelVersion",{get:function(){return this.version},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"inputNodes",{get:function(){return this.executor.inputNodes},enumerable:!0,configurable:!0}),Object.defineProperty(e.prototype,"outputNodes",{get:function(){return this.executor.outputNodes},enumerable:!0,configurable:!0}),e.prototype.getPathPrefix=function(){var e=parse(this.weightManifestUrl),t=e.pathname.split("/");return t.splice(-1),e.pathname=t.join("/"),format(e)+"/"},e.prototype.loadRemoteProtoFile=function(){return __awaiter$19(this,void 0,void 0,function(){var e,t,r,n,a;return __generator$19(this,function(o){switch(o.label){case 0:return o.trys.push([0,3,,4]),[4,fetch(this.modelUrl,this.requestOption)];case 1:return e=o.sent(),r=(t=tensorflow.GraphDef).decode,n=Uint8Array.bind,[4,e.arrayBuffer()];case 2:return[2,r.apply(t,[new(n.apply(Uint8Array,[void 0,o.sent()]))])];case 3:throw a=o.sent(),new Error(this.modelUrl+" not found. "+a);case 4:return[2]}})})},e.prototype.loadWeightManifest=function(){return __awaiter$19(this,void 0,void 0,function(){var e,t,r;return __generator$19(this,function(n){switch(n.label){case 0:return n.trys.push([0,3,,4]),[4,fetch(this.weightManifestUrl,this.requestOption)];case 1:return e=n.sent(),t=this,[4,e.clone().json()];case 2:return t.weightManifest=n.sent(),[3,4];case 3:throw r=n.sent(),new Error(this.weightManifestUrl+" not found. "+r);case 4:return[2]}})})},e.prototype.load=function(){return __awaiter$19(this,void 0,void 0,function(){var e,t,r,n;return __generator$19(this,function(a){switch(a.label){case 0:return e=this.loadRemoteProtoFile(),t=this.loadWeightManifest(),[4,Promise.all([e,t])];case 1:return r=a.sent()[0],this.version=r.versions.producer+"."+r.versions.minConsumer,[4,loadWeights(this.weightManifest,this.pathPrefix,void 0,this.requestOption)];case 2:return n=a.sent(),this.executor=new GraphExecutor(OperationMapper.Instance.transformGraph(r)),this.executor.weightMap=this.convertTensorMapToTensorsMap(n),[2,!0]}})})},e.prototype.predict=function(e,t){return this.execute(e,this.outputNodes)},e.prototype.constructTensorMap=function(e){var t=e instanceof Tensor?[e]:e;if(t.length!==this.inputNodes.length)throw new Error("Input tensor count mismatch,the frozen model has "+this.inputNodes.length+" placeholders, while there are "+t.length+" input tensors.");return this.inputNodes.reduce(function(e,r,n){return e[r]=t[n],e},{})},e.prototype.execute=function(e,t){if(t=t||this.outputNodes,(e instanceof Tensor||Array.isArray(e))&&(e=this.constructTensorMap(e)),this.executor.isControlFlowModel)throw new Error("The model contains control flow ops, please use executeAsync method");var r=this.executor.execute(this.convertTensorMapToTensorsMap(e),t),n=Object.keys(r);return Array.isArray(t)&&t.length>1?t.map(function(e){return r[e]}):r[n[0]]},e.prototype.executeAsync=function(e,t){return __awaiter$19(this,void 0,void 0,function(){var r,n;return __generator$19(this,function(a){switch(a.label){case 0:if(!this.executor.isControlFlowModel)throw new Error("The model does not contain control flow ops, please use execute method for better performance.");return t=t||this.outputNodes,(e instanceof Tensor||Array.isArray(e))&&(e=this.constructTensorMap(e)),[4,this.executor.executeAsync(this.convertTensorMapToTensorsMap(e),t)];case 1:return r=a.sent(),n=Object.keys(r),[2,Array.isArray(t)&&t.length>1?t.map(function(e){return r[e]}):r[n[0]]]}})})},e.prototype.convertTensorMapToTensorsMap=function(e){return Object.keys(e).reduce(function(t,r){return t[r]=[e[r]],t},{})},e.prototype.dispose=function(){this.executor.dispose()},e}(),version$2="0.4.1",version$3="0.11.6",version$4={"tfjs-core":version,"tfjs-layers":version$1,"tfjs-converter":version$2,tfjs:version$3};exports.version=version$4,exports.setBackend=setBackend,exports.getBackend=getBackend,exports.disposeVariables=disposeVariables,exports.memory=memory,exports.version_core=version,exports.nextFrame=nextFrame,exports.environment=environment,exports.io=io,exports.serialization=serialization,exports.test_util=test_util,exports.util=util,exports.webgl=webgl,exports.AdadeltaOptimizer=AdadeltaOptimizer,exports.AdagradOptimizer=AdagradOptimizer,exports.AdamOptimizer=AdamOptimizer,exports.AdamaxOptimizer=AdamaxOptimizer,exports.MomentumOptimizer=MomentumOptimizer,exports.Optimizer=Optimizer,exports.RMSPropOptimizer=RMSPropOptimizer,exports.SGDOptimizer=SGDOptimizer,exports.Tensor=Tensor,exports.TensorBuffer=TensorBuffer,exports.variable=variable,exports.Variable=Variable,exports.ENV=ENV,exports.Environment=Environment,exports.doc=doc,exports.batchNormalization=batchNormalization,exports.batchNormalization2d=batchNormalization2d,exports.batchNormalization3d=batchNormalization3d,exports.batchNormalization4d=batchNormalization4d,exports.concat=concat,exports.concat1d=concat1d,exports.concat2d=concat2d,exports.concat3d=concat3d,exports.concat4d=concat4d,exports.conv1d=conv1d,exports.conv2d=conv2d,exports.conv2dTranspose=conv2dTranspose,exports.depthwiseConv2d=depthwiseConv2d,exports.separableConv2d=separableConv2d,exports.matMul=matMul,exports.matrixTimesVector=matrixTimesVector,exports.outerProduct=outerProduct,exports.vectorTimesMatrix=vectorTimesMatrix,exports.dot=dot,exports.avgPool=avgPool,exports.maxPool=maxPool,exports.transpose=transpose,exports.reverse=reverse,exports.reverse1d=reverse1d,exports.reverse2d=reverse2d,exports.reverse3d=reverse3d,exports.reverse4d=reverse4d,exports.slice=slice,exports.slice1d=slice1d,exports.slice2d=slice2d,exports.slice3d=slice3d,exports.slice4d=slice4d,exports.stridedSlice=stridedSlice,exports.argMax=argMax,exports.argMin=argMin,exports.logSumExp=logSumExp,exports.max=max,exports.mean=mean,exports.min=min,exports.moments=moments,exports.sum=sum,exports.unsortedSegmentSum=unsortedSegmentSum,exports.equal=equal,exports.equalStrict=equalStrict,exports.greater=greater,exports.greaterStrict=greaterStrict,exports.greaterEqual=greaterEqual,exports.greaterEqualStrict=greaterEqualStrict,exports.less=less,exports.lessStrict=lessStrict,exports.lessEqual=lessEqual,exports.lessEqualStrict=lessEqualStrict,exports.notEqual=notEqual,exports.notEqualStrict=notEqualStrict,exports.logicalNot=logicalNot,exports.logicalAnd=logicalAnd,exports.logicalOr=logicalOr,exports.logicalXor=logicalXor,exports.where=where,exports.abs=abs,exports.acos=acos,exports.acosh=acosh,exports.asin=asin,exports.asinh=asinh,exports.atan=atan,exports.atanh=atanh,exports.ceil=ceil,exports.clipByValue=clipByValue,exports.cos=cos,exports.cosh=cosh,exports.elu=elu,exports.exp=exp,exports.expm1=expm1,exports.floor=floor,exports.sign=sign,exports.leakyRelu=leakyRelu,exports.log=log,exports.log1p=log1p,exports.logSigmoid=logSigmoid,exports.neg=neg,exports.prelu=prelu,exports.relu=relu,exports.reciprocal=reciprocal,exports.round=round,exports.selu=selu,exports.sigmoid=sigmoid,exports.sin=sin,exports.sinh=sinh,exports.softplus=softplus,exports.sqrt=sqrt,exports.rsqrt=rsqrt,exports.square=square,exports.step=step,exports.tan=tan,exports.tanh=tanh$1,exports.erf=erf,exports.add=add,exports.addStrict=addStrict,exports.atan2=atan2,exports.div=div,exports.floorDiv=floorDiv,exports.divStrict=divStrict,exports.maximum=maximum,exports.maximumStrict=maximumStrict,exports.minimum=minimum,exports.minimumStrict=minimumStrict,exports.mod=mod,exports.modStrict=modStrict,exports.mul=mul,exports.mulStrict=mulStrict,exports.pow=pow,exports.powStrict=powStrict,exports.sub=sub,exports.subStrict=subStrict,exports.squaredDifference=squaredDifference,exports.squaredDifferenceStrict=squaredDifferenceStrict,exports.norm=norm,exports.cast=cast,exports.clone=clone,exports.fromPixels=fromPixels,exports.toPixels=toPixels,exports.ones=ones,exports.onesLike=onesLike,exports.zeros=zeros,exports.zerosLike=zerosLike,exports.eye=eye,exports.rand=rand,exports.randomNormal=randomNormal,exports.truncatedNormal=truncatedNormal,exports.randomUniform=randomUniform,exports.multinomial=multinomial,exports.reshape=reshape,exports.squeeze=squeeze,exports.tile=tile,exports.gather=gather,exports.oneHot=oneHot,exports.linspace=linspace,exports.range=range,exports.buffer=buffer,exports.fill=fill,exports.tensor=tensor,exports.scalar=scalar,exports.tensor1d=tensor1d,exports.tensor2d=tensor2d,exports.tensor3d=tensor3d,exports.tensor4d=tensor4d,exports.tensor5d=tensor5d,exports.print=print,exports.expandDims=expandDims,exports.stack=stack,exports.unstack=unstack,exports.split=split,exports.cumsum=cumsum,exports.pad=pad,exports.pad1d=pad1d,exports.pad2d=pad2d,exports.pad3d=pad3d,exports.pad4d=pad4d,exports.movingAverage=movingAverage,exports.basicLSTMCell=basicLSTMCell,exports.multiRNNCell=multiRNNCell,exports.softmax=softmax,exports.localResponseNormalization=localResponseNormalization,exports.linalg=linalg,exports.losses=losses,exports.image=image,exports.operation=operation,exports.train=train,exports.tidy=tidy,exports.keep=keep,exports.dispose=dispose,exports.time=time,exports.grad=grad,exports.valueAndGrad=valueAndGrad,exports.grads=grads,exports.valueAndGrads=valueAndGrads,exports.variableGrads=variableGrads,exports.customGrad=customGrad,exports.model=model,exports.sequential=sequential,exports.loadModel=loadModel,exports.input=input,exports.layers=layers,exports.constraints=constraints,exports.initializers=initializers,exports.metrics=metrics,exports.regularizers=regularizers,exports.Callback=Callback,exports.CallbackList=CallbackList,exports.CustomCallback=CustomCallback,exports.Model=Model,exports.RNN=RNN,exports.Sequential=Sequential,exports.SymbolicTensor=SymbolicTensor,exports.version_layers=version$1,exports.FrozenModel=FrozenModel,exports.loadFrozenModel=loadFrozenModel,exports.version_converter=version$2,Object.defineProperty(exports,"__esModule",{value:!0})});