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N?(lu(),N=v.fallback,K=p.mode,se=h.child,be=se.sibling,v=ml(se,{mode:"hidden",children:v.children}),v.subtreeFlags=se.subtreeFlags&65011712,be!==null?N=ml(be,N):(N=$c(N,K,g,null),N.flags|=2),N.return=p,v.return=p,v.sibling=N,p.child=v,v=N,N=p.child,K=h.child.memoizedState,K===null?K=HS(g):(se=K.cachePool,se!==null?(be=Nr._currentValue,se=se.parent!==be?{parent:be,pool:be}:se):se=L3(),K={baseLanes:K.baseLanes|g,cachePool:se}),N.memoizedState=K,N.childLanes=GS(h,L,g),p.memoizedState=VS,v):(ou(p),g=h.child,h=g.sibling,g=ml(g,{mode:"visible",children:v.children}),g.return=p,g.sibling=null,h!==null&&(L=p.deletions,L===null?(p.deletions=[h],p.flags|=16):L.push(h)),p.child=g,p.memoizedState=null,g)}function qS(h,p){return p=H0({mode:"visible",children:p},h.mode),p.return=h,h.child=p}function H0(h,p){return h=yi(22,h,null,p),h.lanes=0,h.stateNode={_visibility:1,_pendingMarkers:null,_retryCache:null,_transitions:null},h}function KS(h,p,g){return Pp(p,h.child,null,g),h=qS(p,p.pendingProps.children),h.flags|=2,p.memoizedState=null,h}function eD(h,p,g){h.lanes|=p;var v=h.alternate;v!==null&&(v.lanes|=p),hS(h.return,p,g)}function XS(h,p,g,v,N){var I=h.memoizedState;I===null?h.memoizedState={isBackwards:p,rendering:null,renderingStartTime:0,last:v,tail:g,tailMode:N}:(I.isBackwards=p,I.rendering=null,I.renderingStartTime=0,I.last=v,I.tail=g,I.tailMode=N)}function tD(h,p,g){var v=p.pendingProps,N=v.revealOrder,I=v.tail;if(Yr(h,p,v.children,g),v=Cr.current,(v&2)!==0)v=v&1|2,p.flags|=128;else{if(h!==null&&(h.flags&128)!==0)e:for(h=p.child;h!==null;){if(h.tag===13)h.memoizedState!==null&&eD(h,g,p);else if(h.tag===19)eD(h,g,p);else if(h.child!==null){h.child.return=h,h=h.child;continue}if(h===p)break e;for(;h.sibling===null;){if(h.return===null||h.return===p)break e;h=h.return}h.sibling.return=h.return,h=h.sibling}v&=1}switch(ee(Cr,v),N){case"forwards":for(g=p.child,N=null;g!==null;)h=g.alternate,h!==null&&z0(h)===null&&(N=g),g=g.sibling;g=N,g===null?(N=p.child,p.child=null):(N=g.sibling,g.sibling=null),XS(p,!1,N,g,I);break;case"backwards":for(g=null,N=p.child,p.child=null;N!==null;){if(h=N.alternate,h!==null&&z0(h)===null){p.child=N;break}h=N.sibling,N.sibling=g,g=N,N=h}XS(p,!0,g,null,I);break;case"together":XS(p,!1,null,null,void 0);break;default:p.memoizedState=null}return p.child}function Sl(h,p,g){if(h!==null&&(p.dependencies=h.dependencies),pu|=p.lanes,(g&p.childLanes)===0)if(h!==null){if(Xg(h,p,g,!1),(g&p.childLanes)===0)return null}else return null;if(h!==null&&p.child!==h.child)throw Error(a(153));if(p.child!==null){for(h=p.child,g=ml(h,h.pendingProps),p.child=g,g.return=p;h.sibling!==null;)h=h.sibling,g=g.sibling=ml(h,h.pendingProps),g.return=p;g.sibling=null}return p.child}

8function YS(h,p){return(h.lanes&p)!==0?!0:(h=h.dependencies,!!(h!==null&&C0(h)))}function vG(h,p,g){switch(p.tag){case 3:xe(p,p.stateNode.containerInfo),nu(p,Nr,h.memoizedState.cache),qg();break;case 27:case 5:_e(p);break;case 4:xe(p,p.stateNode.containerInfo);break;case 10:nu(p,p.type,p.memoizedProps.value);break;case 13:var v=p.memoizedState;if(v!==null)return v.dehydrated!==null?(ou(p),p.flags|=128,null):(g&p.child.childLanes)!==0?Zj(h,p,g):(ou(p),h=Sl(h,p,g),h!==null?h.sibling:null);ou(p);break;case 19:var N=(h.flags&128)!==0;if(v=(g&p.childLanes)!==0,v||(Xg(h,p,g,!1),v=(g&p.childLanes)!==0),N){if(v)return tD(h,p,g);p.flags|=128}if(N=p.memoizedState,N!==null&&(N.rendering=null,N.tail=null,N.lastEffect=null),ee(Cr,Cr.current),v)break;return null;case 22:case 23:return p.lanes=0,Kj(h,p,g);case 24:nu(p,Nr,h.memoizedState.cache)}return Sl(h,p,g)}function nD(h,p,g){if(h!==null)if(h.memoizedProps!==p.pendingProps)Lr=!0;else{if(!YS(h,g)&&(p.flags&128)===0)return Lr=!1,vG(h,p,g);Lr=(h.flags&131072)!==0}else Lr=!1,On&&(p.flags&1048576)!==0&&D3(p,N0,p.index);switch(p.lanes=0,p.tag){case 16:e:{h=p.pendingProps;var v=p.elementType,N=v._init;if(v=N(v._payload),p.type=v,typeof v=="function")sS(v)?(h=Vc(v,h),p.tag=1,p=Jj(null,p,v,h,g)):(p.tag=0,p=WS(null,p,v,h,g));else{if(v!=null){if(N=v.$$typeof,N===E){p.tag=11,p=Hj(null,p,v,h,g);break e}else if(N===A){p.tag=14,p=Gj(null,p,v,h,g);break e}}throw p=X(v)||v,Error(a(306,p,""))}}return p;case 0:return WS(h,p,p.type,p.pendingProps,g);case 1:return v=p.type,N=Vc(v,p.pendingProps),Jj(h,p,v,N,g);case 3:e:{if(xe(p,p.stateNode.containerInfo),h===null)throw Error(a(387));v=p.pendingProps;var I=p.memoizedState;N=I.element,bS(h,p),nx(p,v,null,g);var L=p.memoizedState;if(v=L.cache,nu(p,Nr,v),v!==I.cache&&pS(p,[Nr],g,!0),tx(),v=L.element,I.isDehydrated)if(I={element:v,isDehydrated:!1,cache:L.cache},p.updateQueue.baseState=I,p.memoizedState=I,p.flags&256){p=Qj(h,p,v,g);break e}else if(v!==N){N=Pi(Error(a(424)),p),Kg(N),p=Qj(h,p,v,g);break e}else for(h=p.stateNode.containerInfo,h.nodeType===9?h=h.body:h=h.nodeName==="HTML"?h.ownerDocument.body:h,La=mo(h.firstChild),js=p,On=!0,Oc=null,Fo=!0,g=Mj(p,null,v,g),p.child=g;g;)g.flags=g.flags&-3|4096,g=g.sibling;else{if(qg(),v===N){p=Sl(h,p,g);break e}Yr(h,p,v,g)}p=p.child}return p;case 26:return V0(h,p),h===null?(g=iR(p.type,null,p.pendingProps,null))?p.memoizedState=g:On||(g=p.type,h=p.pendingProps,v=s1(pe.current).createElement(g),v[$t]=p,v[It]=h,Qr(v,g,h),Rn(v),p.stateNode=v):p.memoizedState=iR(p.type,h.memoizedProps,p.pendingProps,h.memoizedState),null;case 27:return _e(p),h===null&&On&&(v=p.stateNode=aR(p.type,p.pendingProps,pe.current),js=p,Fo=!0,N=La,xu(p.type)?(_k=N,La=mo(v.firstChild)):La=N),Yr(h,p,p.pendingProps.children,g),V0(h,p),h===null&&(p.flags|=4194304),p.child;case 5:return h===null&&On&&((N=v=La)&&(v=KG(v,p.type,p.pendingProps,Fo),v!==null?(p.stateNode=v,js=p,La=mo(v.firstChild),Fo=!1,N=!0):N=!1),N||Lc(p)),_e(p),N=p.type,I=p.pendingProps,L=h!==null?h.memoizedProps:null,v=I.children,Ek(N,I)?v=null:L!==null&&Ek(N,L)&&(p.flags|=32),p.memoizedState!==null&&(N=CS(h,p,hG,null,null,g),Nx._currentValue=N),V0(h,p),Yr(h,p,v,g),p.child;case 6:return h===null&&On&&((h=g=La)&&(g=XG(g,p.pendingProps,Fo),g!==null?(p.stateNode=g,js=p,La=null,h=!0):h=!1),h||Lc(p)),null;case 13:return Zj(h,p,g);case 4:return xe(p,p.stateNode.containerInfo),v=p.pendingProps,h===null?p.child=Pp(p,null,v,g):Yr(h,p,v,g),p.child;case 11:return Hj(h,p,p.type,p.pendingProps,g);case 7:return Yr(h,p,p.pendingProps,g),p.child;

8case 8:return Yr(h,p,p.pendingProps.children,g),p.child;case 12:return Yr(h,p,p.pendingProps.children,g),p.child;case 10:return v=p.pendingProps,nu(p,p.type,v.value),Yr(h,p,v.children,g),p.child;case 9:return N=p.type._context,v=p.pendingProps.children,zc(p),N=hs(N),v=v(N),p.flags|=1,Yr(h,p,v,g),p.child;case 14:return Gj(h,p,p.type,p.pendingProps,g);case 15:return qj(h,p,p.type,p.pendingProps,g);case 19:return tD(h,p,g);case 31:return v=p.pendingProps,g=p.mode,v={mode:v.mode,children:v.children},h===null?(g=H0(v,g),g.ref=p.ref,p.child=g,g.return=p,p=g):(g=ml(h.child,v),g.ref=p.ref,p.child=g,g.return=p,p=g),p;case 22:return Kj(h,p,g);case 24:return zc(p),v=hs(Nr),h===null?(N=gS(),N===null&&(N=da,I=fS(),N.pooledCache=I,I.refCount++,I!==null&&(N.pooledCacheLanes|=g),N=I),p.memoizedState={parent:v,cache:N},yS(p),nu(p,Nr,N)):((h.lanes&g)!==0&&(bS(h,p),nx(p,null,null,g),tx()),N=h.memoizedState,I=p.memoizedState,N.parent!==v?(N={parent:v,cache:v},p.memoizedState=N,p.lanes===0&&(p.memoizedState=p.updateQueue.baseState=N),nu(p,Nr,v)):(v=I.cache,nu(p,Nr,v),v!==N.cache&&pS(p,[Nr],g,!0))),Yr(h,p,p.pendingProps.children,g),p.

8child;case 29:throw p.pendingProps}throw Error(a(156,p.tag))}function kl(h){h.flags|=4}function aD(h,p){if(p.type!=="stylesheet"||(p.state.loading&4)!==0)h.flags&=-16777217;else if(h.flags|=16777216,!dR(p)){if(p=Vi.current,p!==null&&((Cn&4194048)===Cn?Oo!==null:(Cn&62914560)!==Cn&&(Cn&536870912)===0||p!==Oo))throw Zg=xS,P3;h.flags|=8192}}function G0(h,p){p!==null&&(h.flags|=4),h.flags&16384&&(p=h.tag!==22?qa():536870912,h.lanes|=p,Vp|=p)}function ux(h,p){if(!On)switch(h.tailMode){case"hidden":p=h.tail;for(var g=null;p!==null;)p.alternate!==null&&(g=p),p=p.sibling;g===null?h.tail=null:g.sibling=null;break;case"collapsed":g=h.tail;for(var v=null;g!==null;)g.alternate!==null&&(v=g),g=g.sibling;v===null?p||h.tail===null?h.tail=null:h.tail.sibling=null:v.sibling=null}}function Da(h){var p=h.alternate!==null&&h.alternate.child===h.child,g=0,v=0;if(p)for(var N=h.child;N!==null;)g|=N.lanes|N.childLanes,v|=N.subtreeFlags&65011712,v|=N.flags&65011712,N.return=h,N=N.sibling;else for(N=h.child;N!==null;)g|=N.lanes|N.childLanes,v|=N.subtreeFlags,v|=N.flags,N.return=h,N=N.sibling;return h.subtreeFlags|=v,h.childLanes=g,p}function wG(h,p,g){var v=p.pendingProps;switch(uS(p),p.tag){case 31:case 16:case 15:case 0:case 11:case 7:case 8:case 12:case 9:case 14:return Da(p),null;case 1:return Da(p),null;case 3:return g=p.stateNode,v=null,h!==null&&(v=h.memoizedState.cache),p.memoizedState.cache!==v&&(p.flags|=2048),bl(Nr),Ie(),g.pendingContext&&(g.context=g.pendingContext,g.pendingContext=null),(h===null||h.child===null)&&(Gg(p)?kl(p):h===null||h.memoizedState.isDehydrated&&(p.flags&256)===0||(p.flags|=1024,$3())),Da(p),null;case 26:return g=p.memoizedState,h===null?(kl(p),g!==null?(Da(p),aD(p,g)):(Da(p),p.flags&=-16777217)):g?g!==h.memoizedState?(kl(p),Da(p),aD(p,g)):(Da(p),p.flags&=-16777217):(h.memoizedProps!==v&&kl(p),Da(p),p.flags&=-16777217),null;case 27:Oe(p),g=pe.current;var N=p.type;if(h!==null&&p.stateNode!=null)h.memoizedProps!==v&&kl(p);else{if(!v){if(p.stateNode===null)throw Error(a(166));return Da(p),null}h=U.current,Gg(p)?R3(p):(h=aR(N,v,g),p.stateNode=h,kl(p))}return Da(p),null;case 5:if(Oe(p),g=p.type,h!==null&&p.stateNode!=null)h.memoizedProps!==v&&kl(p);else{if(!v){if(p.stateNode===null)throw Error(a(166));return Da(p),null}if(h=U.current,Gg(p))R3(p);else{switch(N=s1(pe.current),h){case 1:h=N.createElementNS("http://www.w3.org/2000/svg",g);break;case 2:h=N.createElementNS("http://www.w3.org/1998/Math/MathML",g);break;default:switch(g){case"svg":h=N.createElementNS("http://www.w3.org/2000/svg",g);break;case"math":h=N.createElementNS("http://www.w3.org/1998/Math/MathML",g);break;case"script":h=N.createElement("div"),h.innerHTML="<script><\/script>",h=h.removeChild(h.firstChild);break;case"select":h=typeof v.is=="string"?N.createElement("select",{is:v.is}):N.createElement("select"),v.multiple?h.multiple=!0:v.size&&(h.size=v.size);break;default:h=typeof v.is=="string"?N.createElement(g,{is:v.is}):N.createElement(g)}}h[$t]=p,h[It]=v;e:for(N=p.child;N!==null;){if(N.tag===5||N.tag===6)h.appendChild(N.stateNode);else if(N.tag!==4&&N.tag!==27&&N.child!==null){N.child.return=N,N=N.child;continue}if(N===p)break e;for(;N.sibling===null;){if(N.return===null||N.return===p)break e;N=N.return}N.sibling.return=N.return,N=N.sibling}p.stateNode=h;e:switch(Qr(h,g,v),g){case"button":case"input":case"select":case"textarea":h=!!v.autoFocus;break e;case"img":h=!0;break e;default:h=!1}h&&kl(p)}}return Da(p),p.flags&=-16777217,null;case 6:if(h&&p.stateNode!=null)h.memoizedProps!==v&&kl(p);else{if(typeof v!="string"&&p.stateNode===null)throw Error(a(166));if(h=pe.current,Gg(p)){if(h=p.stateNode,g=p.memoizedProps,v=null,N=js,N!==null)switch(N.tag){case 27:case 5:v=N.memoizedProps}h[$t]=p,h=!!(h.nodeValue===g||v!==null&&v.suppressHydrationWarning===!0||YD(h.nodeValue,g)),h||Lc(p)}else h=s1(h).createTextNode(v),h[$t]=p,p.stateNode=h}return Da(p),null;case 13:if(v=p.memoizedState,h===null||h.memoizedState!==null&&h.memoizedState.dehydrated!==null){if(N=Gg(p),v!==null&&v.dehydrated!==null){if(h===null){if(!N)throw Error(a(318));if(N=p.memoizedState,N=N!==null?N.dehydrated:null,!N)throw Error(a(317));N[$t]=p}else qg(),(p.flags&128)===0&&(p.memoizedState=null),p.flags|=4;Da(p),N=!1}else N=$3(),h!==null&&h.memoizedState!==null&&(h.memoizedState.hydrationErrors=N),N=!0;if(!N)return p.flags&256?(wl(p),p):(wl(p),null)}if(wl(p),(p.flags&128)!==0)return p.lanes=g,p;if(g=v!==null,h=h!==null&&h.memoizedState!==null,g){v=p.child,N=null,v.alternate!==null&&v.alternate.memoizedState!==null&&v.alternate.memoizedState.cachePool!==null&&(N=v.alternate.memoizedState.cachePool.pool);var I=null;v.memoizedState!==null&&v.memoizedState.cachePool!==null&&(I=v.memoizedState.cachePool.pool),I!==N&&(v.flags|=2048)}return g!==h&&g&&(p.child.flags|=8192),G0(p,p.updateQueue),Da(p),null;case 4:return Ie(),h===null&&wk(p.stateNode.containerInfo),Da(p),null;case 10:return bl(p.type),Da(p),null;case 19:if(ne(Cr),N=p.memoizedState,N===null)return Da(p),null;if(v=(p.flags&128)!==0,I=N.rendering,I===null)if(v)ux(N,!1);else{if(Pa!==0||h!==null&&(h.flags&128)!==0)for(h=p.child;h!==null;){if(I=z0(h),I!==null){for(p.flags|=128,ux(N,!1),h=I.updateQueue,p.updateQueue=h,G0(p,h),p.subtreeFlags=0,h=g,g=p.child;g!==null;)j3(g,h),g=g.sibling;return ee(Cr,Cr.current&1|2),p.child}h=h.sibling}N.tail!==null&&tt()>X0&&(p.flags|=128,v=!0,ux(N,!1),p.lanes=4194304)}else{if(!v)if(h=z0(I),h!==null){if(p.flags|=128,v=!0,h=h.updateQueue,p.updateQueue=h,G0(p,h),ux(N,!0),N.tail===null&&N.tailMode==="hidden"&&!I.alternate&&!On)return Da(p),null}else 2*tt()-N.renderingStartTime>X0&&g!==536870912&&(p.flags|=128,v=!0,ux(N,!1),p.lanes=4194304);N.isBackwards?(I.sibling=p.child,p.child=I):(h=N.last,h!==null?h.sibling=I:p.child=I,N.last=I)}return N.tail!==null?(p=N.tail,N.rendering=p,N.tail=p.sibling,N.renderingStartTime=tt(),p.sibling=null,h=Cr.current,ee(Cr,v?h&1|2:h&1),p):(Da(p),null);case 22:case 23:return wl(p),kS(),v=p.memoizedState!==null,h!==null?h.memoizedState!==null!==v&&(p.flags|=8192):v&&(p.flags|=8192),v?(g&536870912)!==0&&(p.flags&128)===0&&(Da(p),p.subtreeFlags&6&&(p.flags|=8192)):Da(p),g=p.updateQueue,g!==null&&G0(p,g.retryQueue),g=null,h!==null&&h.memoizedState!==null&&h.memoizedState.cachePool!==null&&(g=h.memoizedState.cachePool.pool),v=null,p.memoizedState!==null&&p.memoizedState.cachePool!==null&&(v=p.memoizedState.cachePool.pool),v!==g&&(p.flags|=2048),h!==null&&ne(Uc),null;case 24:return g=null,h!==null&&(g=h.memoizedState.cache),p.memoizedState.cache!==g&&(p.flags|=2048),bl(Nr),Da(p),null;case 25:return null;case 30:return null}throw Error(a(156,p.tag))}function SG(h,p){switch(uS(p),p.tag){case 1:return h=p.flags,h&65536?(p.flags=h&-65537|128,p):null;case 3:return bl(Nr),Ie(),h=p.flags,(h&65536)!==0&&(h&128)===0?(p.flags=h&-65537|128,p):null;case 26:case 27:case 5:return Oe(p),null;case 13:if(wl(p),h=p.memoizedState,h!==null&&h.dehydrated!==null){if(p.alternate===null)throw Error(a(340));qg()}return h=p.flags,h&65536?(p.flags=h&-65537|128,p):null;case 19:return ne(Cr),null;case 4:return Ie(),null;case 10:return bl(p.type),null;case 22:case 23:return wl(p),kS(),h!==null&&ne(Uc),h=p.flags,h&65536?(p.flags=h&-65537|128,p):null;case 24:return bl(Nr),null;case 25:return null;default:return null}}function rD(h,p){switch(uS(p),p.tag){case 3:bl(Nr),Ie();break;case 26:case 27:case 5:Oe(p);break;case 4:Ie();break;case 13:wl(p);break;case 19:ne(Cr);break;case 10:bl(p.type);break;case 22:case 23:wl(p),kS(),h!==null&&ne(Uc);break;case 24:bl(Nr)}}function cx(h,p){try{var g=p.updateQueue,v=g!==null?g.lastEffect:null;if(v!==null){var N=v.next;g=N;do{if((g.tag&h)===h){v=void 0;var I=g.create,L=g.inst;v=I(),L.destroy=v}g=g.next}while(g!==N)}}catch(K){ia(p,p.return,K)}}function uu(h,p,g){try{var v=p.updateQueue,N=v!==null?v.lastEffect:null;if(N!==null){var I=N.next;v=I;do{if((v.tag&h)===h){var L=v.inst,K=L.destroy;if(K!==void 0){L.destroy=void 0,N=p;var se=g,be=K;try{be()}catch(Te){ia(N,se,Te)}}}v=v.next}while(v!==I)}}catch(Te){ia(p,p.return,Te)}}function sD(h){var p=h.updateQueue;if(p!==null){var g=h.stateNode;try{G3(p,g)}catch(v){ia(h,h.return,v)}}}function iD(h,p,g){g.props=Vc(h.type,h.memoizedProps),g.state=h.memoizedState;try{g.componentWillUnmount()}catch(v){ia(h,p,v)}}function dx(h,p){try{var g=h.ref;if(g!==null){switch(h.tag){case 26:case 27:case 5:var v=h.stateNode;break;case 30:v=h.stateNode;break;default:v=h.stateNode}typeof g=="function"?h.refCleanup=g(v):g.current=v}}catch(N){ia(h,p,N)}}function Lo(h,p){var 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e=window.matchMedia("(prefers-reduced-motion)"),t=()=>gC.current=e.matches;e.addEventListener("change",t),t()}else gC.current=!1}const vJ=new WeakMap;function wJ(e,t,n){for(const a in t){const r=t[a],s=n[a];if(ys(r))e.addValue(a,r);else if(ys(s))e.addValue(a,Of(r,{owner:e}));else if(s!==r)if(e.hasValue(a)){const i=e.getValue(a);i.liveStyle===!0?i.jump(r):i.hasAnimated||i.set(r)}else{const i=e.getStaticValue(a);e.addValue(a,Of(i!==void 0?i:r,{owner:e}))}}for(const a in n)t[a]===void 0&&e.removeValue(a);return t}const yM=["AnimationStart","AnimationComplete","Update","BeforeLayoutMeasure","LayoutMeasure","LayoutAnimationStart","LayoutAnimationComplete"];class SJ{scrapeMotionValuesFromProps(t,n,a){return{}}constructor({parent:t,props:n,presenceContext:a,reducedMotionConfig:r,blockInitialAnimation:s,visualState:i},o={}){this.current=null,this.children=new Set,this.isVariantNode=!1,this.isControllingVariants=!1,this.shouldReduceMotion=null,this.values=new Map,this.KeyframeResolver=bI,this.features={},this.valueSubscriptions=new Map,this.prevMotionValues={},this.events={},this.propEventSubscriptions={},this.notifyUpdate=()=>this.notify("Update",this.latestValues),this.render=()=>{this.current&&(this.triggerBuild(),this.renderInstance(this.current,this.renderState,this.props.style,this.projection))},this.renderScheduledAt=0,this.scheduleRender=()=>{const m=ni.now();this.renderScheduledAt<m&&(this.renderScheduledAt=m,wa.render(this.render,!1,!0))};const{latestValues:l,renderState:d}=i;this.latestValues=l,this.baseTarget={...l},this.initialValues=n.initial?{...l}:{},this.renderState=d,this.parent=t,this.props=n,this.presenceContext=a,this.depth=t?t.depth+1:0,this.reducedMotionConfig=r,this.options=o,this.blockInitialAnimation=!!s,this.isControllingVariants=lw(n),this.isVariantNode=gO(n),this.isVariantNode&&(this.variantChildren=new Set),this.manuallyAnimateOnMount=!!(t&&t.current);const{willChange:c,...f}=this.scrapeMotionValuesFromProps(n,{},this);for(const m in f){const x=f[m];l[m]!==void 0&&ys(x)&&x.set(l[m])}}mount(t){this.current=t,vJ.set(t,this),this.projection&&!this.projection.instance&&this.projection.mount(t),this.parent&&this.isVariantNode&&!this.isControllingVariants&&(this.removeFromVariantTree=this.parent.addVariantChild(this)),this.values.forEac

17h((n,a)=>this.bindToMotionValue(a,n)),jO.current||bJ(),this.shouldReduceMotion=this.reducedMotionConfig==="never"?!1:this.reducedMotionConfig==="always"?!0:gC.current,this.parent?.addChild(this),this.update(this.props,this.presenceContext)}unmount(){this.projection&&this.projection.unmount(),Gu(this.notifyUpdate),Gu(this.render),this.valueSubscriptions.forEach(t=>t()),this.valueSubscriptions.clear(),this.removeFromVariantTree&&this.removeFromVariantTree(),this.parent?.removeChild(this);for(const t in this.events)this.events[t].clear();for(const t in this.features){const n=this.features[t];n&&(n.unmount(),n.isMounted=!1)}this.current=null}addChild(t){this.children.add(t),this.enteringChildren??(this.enteringChildren=new Set),this.enteringChildren.add(t)}removeChild(t){this.children.delete(t),this.enteringChildren&&this.enteringChildren.delete(t)}bindToMotionValue(t,n){this.valueSubscriptions.has(t)&&this.valueSubscriptions.get(t)();const a=lm.has(t);a&&this.onBindTransform&&this.onBindTransform();const r=n.on("change",i=>{this.latestValues[t]=i,this.props.onUpdate&&wa.preRender(this.notifyUpdate),a&&this.projection&&(this.projection.isTransformDirty=!0),this.scheduleRender()});let s;window.MotionCheckAppearSync&&(s=window.MotionCheckAppearSync(this,t,n)),this.valueSubscriptions.set(t,()=>{r(),s&&s(),n.owner&&n.stop()})}sortNodePosition(t){return!this.current||!this.sortInstanceNodePosition||this.type!==t.type?0:this.sortInstanceNodePosition(this.current,t.current)}updateFeatures(){let t="animation";for(t in Lf){const n=Lf[t];if(!n)continue;const{isEnabled:a,Feature:r}=n;if(!this.features[t]&&r&&a(this.props)&&(this.features[t]=new r(this)),this.features[t]){const s=this.features[t];s.isMounted?s.update():(s.mount(),s.isMounted=!0)}}}triggerBuild(){this.build(this.renderState,this.latestValues,this.props)}measureViewportBox(){return this.current?this.measureInstanceViewportBox(this.current,this.props):er()}getStaticValue(t){return this.latestValues[t]}setStaticValue(t,n){this.latestValues[t]=n}update(t,n){(t.transformTemplate||this.props.transformTemplate)&&this.scheduleRender(),this.prevProps=this.props,this.props=t,this.prevPresenceContext=this.presenceContext,this.presenceContext=n;for(let a=0;a<yM.length;a++){const r=yM[a];this.propEventSubscriptions[r]&&(this.propEventSubscriptions[r](),delete this.propEventSubscriptions[r]);const s="on"+r,i=t[s];i&&(this.propEventSubscriptions[r]=this.on(r,i))}this.prevMotionValues=wJ(this,this.scrapeMotionValuesFromProps(t,this.prevProps,this),this.prevMotionValues),this.handleChildMotionValue&&this.handleChildMotionValue()}getProps(){return this.props}getVariant(t){return this.props.variants?this.props.variants[t]:void 0}getDefaultTransition(){return this.props.transition}getTransformPagePoint(){return this.props.transformPagePoint}getClosestVariantNode(){return this.isVariantNode?this:this.parent?this.parent.getClosestVariantNode():void 0}addVariantChild(t){const n=this.getClosestVariantNode();if(n)return n.variantChildren&&n.variantChildren.add(t),()=>n.variantChildren.delete(t)}addValue(t,n){const a=this.values.get(t);n!==a&&(a&&this.removeValue(t),this.bindToMotionValue(t,n),this.values.set(t,n),this.latestValues[t]=n.get())}removeValue(t){this.values.delete(t);const n=this.valueSubscriptions.get(t);n&&(n(),this.valueSubscriptions.delete(t)),delete this.latestValues[t],this.removeValueFromRenderState(t,this.renderState)}hasValue(t){return this.values.has(t)}getValue(t,n){if(this.props.values&&this.props.values[t])return this.props.values[t];let a=this.values.get(t);return a===void 0&&n!==void 0&&(a=Of(n===null?void 0:n,{owner:this}),this.addValue(t,a)),a}readValue(t,n){let a=this.latestValues[t]!==void 0||!this.current?this.latestValues[t]:this.getBaseTargetFromProps(this.props,t)??this.readValueFromInstance(this.current,t,this.options);return a!=null&&(typeof a=="string"&&(kF(a)||CF(a))?a=parseFloat(a):!DY(a)&&qu.test(n)&&(a=iO(t,n)),this.setBaseTarget(t,ys(a)?a.get():a)),ys(a)?a.get():a}setBaseTarget(t,n){this.baseTarget[t]=n}getBaseTarget(t){const{initial:n}=this.props;let a;if(typeof n=="string"||typeof n=="object"){const s=jI(this.props,n,this.presenceContext?.custom);s&&(a=s[t])}if(n&&a!==void 0)return a;const r=this.getBaseTargetFromProps(this.props,t);return r!==void 0&&!ys(r)?r:this.initialValues[t]!==void 0&&a===void 0?void 0:this.baseTarget[t]}on(t,n){return this.events[t]||(this.events[t]=new oI),this.events[t].add(n)}notify(t,...n){this.events[t]&&this.events[t].notify(...n)}scheduleRenderMicrotask(){SI.render(this.render)}}class DO extends SJ{constructor(){super(...arguments),this.KeyframeResolver=vY}sortInstanceNodePosition(t,n){return t.compareDocumentPosition(n)&2?1:-1}getBaseTargetFromProps(t,n){return t.style?t.style[n]:void 0}removeValueFromRenderState(t,{vars:n,style:a}){delete n[t],delete a[t]}handleChildMotionValue(){this.childSubscription&&(this.childSubscription(),delete this.childSubscription);const{children:t}=this.props;ys(t)&&(this.childSubscription=t.on("change",n=>{this.current&&(this.current.textContent=`${n}`)}))}}function RO(e,{style:t,vars:n},a,r){const s=e.style;let i;for(i in t)s[i]=t[i];r?.applyProjectionStyles(s,a);for(i in n)s.setProperty(i,n[i])}function kJ(e){return window.getComputedStyle(e)}class NJ extends DO{constructor(){super(...arguments),this.type="html",this.renderInstance=RO}readValueFromInstance(t,n){if(lm.has(n))return this.projection?.isProjecting?oC(n):LX(t,n);{const a=kJ(t),r=(cI(n)?a.getPropertyValue(n):a[n])||0;return typeof r=="string"?r.trim():r}}measureInstanceViewportBox(t,{transformPagePoint:n}){return _O(t,n)}build(t,n,a){TI(t,n,a.transformTemplate)}scrapeMotionValuesFromProps(t,n,a){return DI(t,n,a)}}const MO=new Set(["baseFrequency","diffuseConstant","kernelMatrix","kernelUnitLength","keySplines","keyTimes","limitingConeAngle","markerHeight","markerWidth","numOctaves","targetX","targetY","surfaceScale","specularConstant","specularExponent","stdDeviation","tableValues","viewBox","gradientTransform","pathLength","startOffset","textLength","lengthAdjust"]);function CJ(e,t,n,a){RO(e,t,void 0,a);for(const r in t.attrs)e.setAttribute(MO.has(r)?r:RI(r),t.attrs[r])}class EJ extends DO{constructor(){super(...arguments),this.type="svg",this.isSVGTag=!1,this.measureInstanceViewportBox=er}getBaseTargetFromProps(t,n){return t[n]}readValueFromInstance(t,n){if(lm.has(n)){const a=sO(n);return a&&a.default||0}return n=MO.has(n)?n:RI(n),t.getAttribute(n)}scrapeMotionValuesFromProps(t,n,a){return kO(t,n,a)}build(t,n,a){bO(t,n,this.isSVGTag,a.transformTemplate,a.style)}renderInstance(t,n,a,r){CJ(t,n,a,r)}mount(t){this.isSVGTag=wO(t.tagName),super.mount(t)}}const IJ=(e,t)=>_I(e)?new EJ(t):new NJ(t,{allowProjection:e!==D.Fragment});function jf(e,t,n){const a=e.getProps();return jI(a,t,n!==void 0?n:a.custom,e)}const xC=e=>Array.isArray(e);function TJ(e,t,n){e.hasValue(t)?e.getValue(t).set(n):e.addValue(t,Of(n))}function AJ(e){return xC(e)?e[e.length-1]||0:e}function _J(e,t){const n=jf(e,t);let{transitionEnd:a={},transition:r={},...s}=n||{};s={...s,...a};for(const i in s){const o=AJ(s[i]);TJ(e,i,o)}}function jJ(e){return!!(ys(e)&&e.add)}function yC(e,t){const n=e.getValue("willChange");if(jJ(n))return n.add(t);if(!n&&zl.WillChange){const a=new zl.WillChange("auto");e.addValue("willChange",a),a.add(t)}}function $O(e){return e.props[NO]}

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t=this.visualElement.getProps(),{drag:n=!1,dragDirectionLock:a=!1,dragPropagation:r=!1,dragConstraints:s=!1,dragElastic:i=vC,dragMomentum:o=!0}=t;return{...t,drag:n,dragDirectionLock:a,dragPropagation:r,dragConstraints:s,dragElastic:i,dragMomentum:o}}}function w1(e,t,n){return(t===!0||t===e)&&(n===null||n===e)}function xQ(e,t=10){let n=null;return Math.abs(e.y)>t?n="y":Math.abs(e.x)>t&&(n="x"),n}class yQ extends cc{constructor(t){super(t),this.removeGroupControls=Zi,this.removeListeners=Zi,this.controls=new gQ(t)}mount(){const{dragControls:t}=this.node.getProps();t&&(this.removeGroupControls=t.subscribe(this.controls)),this.removeListeners=this.controls.addListeners()||Zi}unmount(){this.removeGroupControls(),this.removeListeners()}}const AM=e=>(t,n)=>{e&&wa.postRender(()=>e(t,n))};class bQ extends cc{constructor(){super(...arguments),this.removePointerDownListener=Zi}onPointerDown(t){this.session=new 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TQ(e,t,n,a,r,s){r?(e.opacity=Ma(0,n.opacity??1,AQ(a)),e.opacityExit=Ma(t.opacity??1,0,_Q(a))):s&&(e.opacity=Ma(t.opacity??1,n.opacity??1,a));for(let i=0;i<IQ;i++){const o=`border${GO[i]}Radius`;let l=RM(t,o),d=RM(n,o);if(l===void 0&&d===void 0)continue;l||(l=0),d||(d=0),l===0||d===0||DM(l)===DM(d)?(e[o]=Math.max(Ma(jM(l),jM(d),a),0),(Zo.test(d)||Zo.test(l))&&(e[o]+="%")):e[o]=d}(t.rotate||n.rotate)&&(e.rotate=Ma(t.rotate||0,n.rotate||0,a))}function RM(e,t){return e[t]!==void 0?e[t]:e.borderRadius}const AQ=qO(0,.5,RF),_Q=qO(.5,.95,Zi);function qO(e,t,n){return a=>a<e?0:a>t?1:n(gy(e,t,a))}function MM(e,t){e.min=t.min,e.max=t.max}function qi(e,t){MM(e.x,t.x),MM(e.y,t.y)}function $M(e,t){e.translate=t.translate,e.scale=t.scale,e.originPoint=t.originPoint,e.origin=t.origin}function BM(e,t,n,a,r){return e-=t,e=bv(e,1/n,a),r!==void 0&&(e=bv(e,1/r,a)),e}function jQ(e,t=0,n=1,a=.5,r,s=e,i=e){if(Zo.test(t)&&(t=parseFloat(t),t=Ma(i.min,i.max,t/100)-i.min),typeof t!="number")return;let o=Ma(s.min,s.max,a);e===s&&(o-=t),e.min=BM(e.min,t,n,o,r),e.max=BM(e.max,t,n,o,r)}function FM(e,t,[n,a,r],s,i){jQ(e,t[n],t[a],t[r],t.scale,s,i)}const DQ=["x","scaleX","originX"],RQ=["y","scaleY","originY"];function OM(e,t,n,a){FM(e.x,t,DQ,n?n.x:void 0,a?a.x:void 0),FM(e.y,t,RQ,n?n.y:void 0,a?a.y:void 0)}function LM(e){return e.translate===0&&e.scale===1}function KO(e){return LM(e.x)&&LM(e.y)}function PM(e,t){return e.min===t.min&&e.max===t.max}function MQ(e,t){return PM(e.x,t.x)&&PM(e.y,t.y)}function zM(e,t){return Math.round(e.min)===Math.round(t.min)&&Math.round(e.max)===Math.round(t.max)}function XO(e,t){return zM(e.x,t.x)&&zM(e.y,t.y)}function UM(e){return Ms(e.x)/Ms(e.y)}function WM(e,t){return e.translate===t.translate&&e.scale===t.scale&&e.originPoint===t.originPoint}class $Q{constructor(){this.members=[]}add(t){aI(this.members,t),t.scheduleRender()}remove(t){if(rI(this.members,t),t===this.prevLead&&(this.prevLead=void 0),t===this.lead){const n=this.members[this.members.length-1];n&&this.promote(n)}}relegate(t){const n=this.members.findIndex(r=>t===r);if(n===0)return!1;let a;for(let r=n;r>=0;r--){const s=this.members[r];if(s.isPresent!==!1){a=s;break}}return a?(this.promote(a),!0):!1}promote(t,n){const a=this.lead;if(t!==a&&(this.prevLead=a,this.lead=t,t.show(),a)){a.instance&&a.scheduleRender(),t.scheduleRender(),t.resumeFrom=a,n&&(t.resumeFrom.preserveOpacity=!0),a.snapshot&&(t.snapshot=a.snapshot,t.snapshot.latestValues=a.animationValues||a.latestValues),t.root&&t.root.isUpdating&&(t.isLayoutDirty=!0);const{crossfade:r}=t.options;r===!1&&a.hide()}}

17exitAnimationComplete(){this.members.forEach(t=>{const{options:n,resumingFrom:a}=t;n.onExitComplete&&n.onExitComplete(),a&&a.options.onExitComplete&&a.options.onExitComplete()})}scheduleRender(){this.members.forEach(t=>{t.instance&&t.scheduleRender(!1)})}removeLeadSnapshot(){this.lead&&this.lead.snapshot&&(this.lead.snapshot=void 0)}}function BQ(e,t,n){let a="";const r=e.x.translate/t.x,s=e.y.translate/t.y,i=n?.z||0;if((r||s||i)&&(a=`translate3d(${r}px, ${s}px, ${i}px) `),(t.x!==1||t.y!==1)&&(a+=`scale(${1/t.x}, ${1/t.y}) `),n){const{transformPerspective:d,rotate:c,rotateX:f,rotateY:m,skewX:x,skewY:y}=n;d&&(a=`perspective(${d}px) ${a}`),c&&(a+=`rotate(${c}deg) `),f&&(a+=`rotateX(${f}deg) `),m&&(a+=`rotateY(${m}deg) `),x&&(a+=`skewX(${x}deg) `),y&&(a+=`skewY(${y}deg) `)}const o=e.x.scale*t.x,l=e.y.scale*t.y;return(o!==1||l!==1)&&(a+=`scale(${o}, ${l})`),a||"none"}const rN=["","X","Y","Z"],FQ=1e3;let OQ=0;function sN(e,t,n,a){const{latestValues:r}=t;r[e]&&(n[e]=r[e],t.setStaticValue(e,0),a&&(a[e]=0))}function YO(e){if(e.hasCheckedOptimisedAppear=!0,e.root===e)return;const{visualElement:t}=e.options;if(!t)return;const n=$O(t);if(window.MotionHasOptimisedAnimation(n,"transform")){const{layout:r,layoutId:s}=e.options;window.MotionCancelOptimisedAnimation(n,"transform",wa,!(r||s))}const{parent:a}=e;a&&!a.hasCheckedOptimisedAppear&&YO(a)}function JO({attachResizeListener:e,defaultParent:t,measureScroll:n,checkIsScrollRoot:a,resetTransform:r}){return class{constructor(i={},o=t?.()){this.id=OQ++,this.animationId=0,this.animationCommitId=0,this.children=new Set,this.options={},this.isTreeAnimating=!1,this.isAnimationBlocked=!1,this.isLayoutDirty=!1,this.isProjectionDirty=!1,this.isSharedProjectionDirty=!1,this.isTransformDirty=!1,this.updateManuallyBlocked=!1,this.updateBlockedByResize=!1,this.isUpdating=!1,this.isSVG=!1,this.needsReset=!1,this.shouldResetTransform=!1,this.hasCheckedOptimisedAppear=!1,this.treeScale={x:1,y:1},this.eventHandlers=new Map,this.hasTreeAnimated=!1,this.updateScheduled=!1,this.scheduleUpdate=()=>this.update(),this.projectionUpdateScheduled=!1,this.checkUpdateFailed=()=>{this.isUpdating&&(this.isUpdating=!1,this.clearAllSnapshots())},this.updateProjection=()=>{this.projectionUpdateScheduled=!1,this.nodes.forEach(zQ),this.nodes.forEach(HQ),this.nodes.forEach(GQ),this.nodes.forEach(UQ)},this.resolvedRelativeTargetAt=0,this.hasProjected=!1,this.isVisible=!0,this.animationProgress=0,this.sharedNodes=new Map,this.latestValues=i,this.root=o?o.root||o:this,this.path=o?[...o.path,o]:[],this.parent=o,this.depth=o?o.depth+1:0;for(let l=0;l<this.path.length;l++)this.path[l].shouldResetTransform=!0;this.root===this&&(this.nodes=new CQ)}addEventListener(i,o){return this.eventHandlers.has(i)||this.eventHandlers.set(i,new oI),this.eventHandlers.get(i).add(o)}notifyListeners(i,...o){const l=this.eventHandlers.get(i);l&&l.notify(...o)}hasListeners(i){return this.eventHandlers.has(i)}mount(i){if(this.instance)return;this.isSVG=hO(i)&&!_Y(i),this.instance=i;const{layoutId:o,layout:l,visualElement:d}=this.options;if(d&&!d.current&&d.mount(i),this.root.nodes.add(this),this.parent&&this.parent.children.add(this),this.root.hasTreeAnimated&&(l||o)&&(this.isLayoutDirty=!0),e){let c,f=0;const m=()=>this.root.updateBlockedByResize=!1;wa.read(()=>{f=window.innerWidth}),e(i,()=>{const x=window.innerWidth;x!==f&&(f=x,this.root.updateBlockedByResize=!0,c&&c(),c=EQ(m,250),nv.hasAnimatedSinceResize&&(nv.hasAnimatedSinceResize=!1,this.nodes.forEach(GM)))})}o&&this.root.registerSharedNode(o,this),this.options.animate!==!1&&d&&(o||l)&&this.addEventListener("didUpdate",({delta:c,hasLayoutChanged:f,hasRelativeLayoutChanged:m,layout:x})=>{if(this.isTreeAnimationBlocked()){this.target=void 0,this.relativeTarget=void 0;return}const y=this.options.transition||d.getDefaultTransition()||JQ,{onLayoutAnimationStart:b,onLayoutAnimationComplete:w}=d.getProps(),S=!this.targetLayout||!XO(this.targetLayout,x),k=!f&&m;if(this.options.layoutRoot||this.resumeFrom||k||f&&(S||!this.currentAnimation)){this.resumeFrom&&(this.resumingFrom=this.resumeFrom,this.resumingFrom.resumingFrom=void 0);const C={...vI(y,"layout"),onPlay:b,onComplete:w};(d.shouldReduceMotion||this.options.layoutRoot)&&(C.delay=0,C.type=!1),this.startAnimation(C),this.setAnimationOrigin(c,k)}else f||GM(this),this.isLead()&&this.options.onExitComplete&&this.options.onExitComplete();this.targetLayout=x})}unmount(){this.options.layoutId&&this.willUpdate(),this.root.nodes.remove(this);const i=this.getStack();i&&i.remove(this),this.parent&&this.parent.children.delete(this),this.instance=void 0,this.eventHandlers.clear(),Gu(this.updateProjection)}blockUpdate(){this.updateManuallyBlocked=!0}unblockUpdate(){this.updateManuallyBlocked=!1}isUpdateBlocked(){return this.updateManuallyBlocked||this.updateBlockedByResize}isTreeAnimationBlocked(){return this.isAnimationBlocked||this.parent&&this.parent.isTreeAnimationBlocked()||!1}startUpdate(){this.isUpdateBlocked()||(this.isUpdating=!0,this.nodes&&this.nodes.forEac

17h(qQ),this.animationId++)}getTransformTemplate(){const{visualElement:i}=this.options;return i&&i.getProps().transformTemplate}willUpdate(i=!0){if(this.root.hasTreeAnimated=!0,this.root.isUpdateBlocked()){this.options.onExitComplete&&this.options.onExitComplete();return}if(window.MotionCancelOptimisedAnimation&&!this.hasCheckedOptimisedAppear&&YO(this),!this.root.isUpdating&&this.root.startUpdate(),this.isLayoutDirty)return;this.isLayoutDirty=!0;for(let c=0;c<this.path.length;c++){const f=this.path[c];f.shouldResetTransform=!0,f.updateScroll("snapshot"),f.options.layoutRoot&&f.willUpdate(!1)}const{layoutId:o,layout:l}=this.options;if(o===void 0&&!l)return;const d=this.getTransformTemplate();this.prevTransformTemplateValue=d?d(this.latestValues,""):void 0,this.updateSnapshot(),i&&this.notifyListeners("willUpdate")}update(){if(this.updateScheduled=!1,this.isUpdateBlocked()){this.unblockUpdate(),this.clearAllSnapshots(),this.nodes.forEach(VM);return}if(this.animationId<=this.animationCommitId){this.nodes.forEach(HM);return}this.animationCommitId=this.animationId,this.isUpdating?(this.isUpdating=!1,this.nodes.forEach(VQ),this.nodes.forEach(LQ),this.nodes.forEach(PQ)):this.nodes.forEach(HM),this.clearAllSnapshots();const o=ni.now();ts.delta=Pl(0,1e3/60,o-ts.timestamp),ts.timestamp=o,ts.isProcessing=!0,qk.update.process(ts),qk.preRender.process(ts),qk.render.process(ts),ts.isProcessing=!1}didUpdate(){this.updateScheduled||(this.updateScheduled=!0,SI.read(this.scheduleUpdate))}clearAllSnapshots(){this.nodes.forEach(WQ),this.sharedNodes.forEach(KQ)}scheduleUpdateProjection(){this.projectionUpdateScheduled||(this.projectionUpdateScheduled=!0,wa.preRender(this.updateProjection,!1,!0))}scheduleCheckAfterUnmount(){wa.postRender(()=>{this.isLayoutDirty?this.root.didUpdate():this.root.checkUpdateFailed()})}updateSnapshot(){this.snapshot||!this.instance||(this.snapshot=this.measure(),this.snapshot&&!Ms(this.snapshot.measuredBox.x)&&!Ms(this.snapshot.measuredBox.y)&&(this.snapshot=void 0))}updateLayout(){if(!this.instance||(this.updateScroll(),!(this.options.alwaysMeasureLayout&&this.isLead())&&!this.isLayoutDirty))return;if(this.resumeFrom&&!this.resumeFrom.instance)for(let l=0;l<this.path.length;l++)this.path[l].updateScroll();const i=this.layout;this.layout=this.measure(!1),this.layoutCorrected=er(),this.isLayoutDirty=!1,this.projectionDelta=void 0,this.notifyListeners("measure",this.layout.layoutBox);const{visualElement:o}=this.options;o&&o.notify("LayoutMeasure",this.layout.layoutBox,i?i.layoutBox:void 0)}updateScroll(i="measure"){let o=!!(this.options.layoutScroll&&this.instance);if(this.scroll&&this.scroll.animationId===this.root.animationId&&this.scroll.phase===i&&(o=!1),o&&this.instance){const l=a(this.instance);this.scroll={animationId:this.root.animationId,phase:i,isRoot:l,offset:n(this.instance),wasRoot:this.scroll?this.scroll.isRoot:l}}}resetTransform(){if(!r)return;const i=this.isLayoutDirty||this.shouldResetTransform||this.options.alwaysMeasureLayout,o=this.projectionDelta&&!KO(this.projectionDelta),l=this.getTransformTemplate(),d=l?l(this.latestValues,""):void 0,c=d!==this.prevTransformTemplateValue;i&&this.instance&&(o||td(this.latestValues)||c)&&(r(this.instance,d),this.shouldResetTransform=!1,this.scheduleRender())}measure(i=!0){const o=this.measurePageBox();let l=this.removeElementScroll(o);return i&&(l=this.removeTransform(l)),QQ(l),{animationId:this.root.animationId,measuredBox:o,layoutBox:l,latestValues:{},source:this.id}}measurePageBox(){const{visualElement:i}=this.options;if(!i)return er();const o=i.measureViewportBox();if(!(this.scroll?.wasRoot||this.path.some(ZQ))){const{scroll:d}=this.root;d&&(Ef(o.x,d.offset.x),Ef(o.y,d.offset.y))}return o}removeElementScroll(i){const o=er();if(qi(o,i),this.scroll?.wasRoot)return o;for(let l=0;l<this.path.length;l++){const d=this.path[l],{scroll:c,options:f}=d;d!==this.root&&c&&f.layoutScroll&&(c.wasRoot&&qi(o,i),Ef(o.x,c.offset.x),Ef(o.y,c.offset.y))}return o}applyTransform(i,o=!1){const l=er();qi(l,i);for(let d=0;d<this.path.length;d++){const c=this.path[d];!o&&c.options.layoutScroll&&c.scroll&&c!==c.root&&If(l,{x:-c.scroll.offset.x,y:-c.scroll.offset.y}),td(c.latestValues)&&If(l,c.latestValues)}return td(this.latestValues)&&If(l,this.latestValues),l}removeTransform(i){const o=er();qi(o,i);for(let l=0;l<this.path.length;l++){const d=this.path[l];if(!d.instance||!td(d.latestValues))continue;fC(d.latestValues)&&d.updateSnapshot();const c=er(),f=d.measurePageBox();qi(c,f),OM(o,d.latestValues,d.snapshot?d.snapshot.layoutBox:void 0,c)}return td(this.latestValues)&&OM(o,this.latestValues),o}setTargetDelta(i){this.targetDelta=i,this.root.scheduleUpdateProjection(),this.isProjectionDirty=!0}setOptions(i){this.options={...this.options,...i,crossfade:i.crossfade!==void 0?i.crossfade:!0}}clearMeasurements(){this.scroll=void 0,this.layout=void 0,this.snapshot=void 0,this.prevTransformTemplateValue=void 0,this.targetDelta=void 0,this.target=void 0,this.isLayoutDirty=!1}forceRelativeParentToResolveTarget(){this.relativeParent&&this.relativeParent.resolvedRelativeTargetAt!==ts.timestamp&&this.relativeParent.resolveTargetDelta(!0)}resolveTargetDelta(i=!1){const o=this.getLead();this.isProjectionDirty||(this.isProjectionDirty=o.isProjectionDirty),this.isTransformDirty||(this.isTransformDirty=o.isTransformDirty),this.isSharedProjectionDirty||(this.isSharedProjectionDirty=o.isSharedProjectionDirty);const l=!!this.resumingFrom||this!==o;if(!(i||l&&this.isSharedProjectionDirty||this.isProjectionDirty||this.parent?.isProjectionDirty||this.attemptToResolveRelativeTarget||this.root.updateBlockedByResize))return;const{layout:c,layoutId:f}=this.options;if(!(!this.layout||!(c||f))){if(this.resolvedRelativeTargetAt=ts.timestamp,!this.targetDelta&&!this.relativeTarget){const m=this.getClosestProjectingParent();m&&m.layout&&this.animationProgress!==1?(this.relativeParent=m,this.forceRelativeParentToResolveTarget(),this.relativeTarget=er(),this.relativeTargetOrigin=er(),ry(this.relativeTargetOrigin,this.layout.layoutBox,m.layout.layoutBox),qi(this.relativeTarget,this.relativeTargetOrigin)):this.relativeParent=this.relativeTarget=void 0}if(!(!this.relativeTarget&&!this.targetDelta)&&(this.target||(this.target=er(),this.targetWithTransforms=er()),this.relativeTarget&&this.relativeTargetOrigin&&this.relativeParent&&this.relativeParent.target?(this.forceRelativeParentToResolveTarget(),sQ(this.target,this.relativeTarget,this.relativeParent.target)):this.targetDelta?(this.resumingFrom?this.target=this.applyTransform(this.layout.layoutBox):qi(this.target,this.layout.layoutBox),AO(this.target,this.targetDelta)):qi(this.target,this.layout.layoutBox),this.attemptToResolveRelativeTarget)){this.attemptToResolveRelativeTarget=!1;const m=this.getClosestProjectingParent();m&&!!m.resumingFrom==!!this.resumingFrom&&!m.options.layoutScroll&&m.target&&this.animationProgress!==1?(this.relativeParent=m,this.forceRelativeParentToResolveTarget(),this.relativeTarget=er(),this.relativeTargetOrigin=er(),ry(this.relativeTargetOrigin,this.target,m.target),qi(this.relativeTarget,this.relativeTargetOrigin)):this.relativeParent=this.relativeTarget=void 0}}}getClosestProjectingParent(){if(!(!this.parent||fC(this.parent.latestValues)||TO(this.parent.latestValues)))return this.parent.isProjecting()?this.parent:this.parent.getClosestProjectingParent()}isProjecting(){return!!((this.relativeTarget||this.targetDelta||this.options.layoutRoot)&&this.layout)}calcProjection(){const i=this.getLead(),o=!!this.resumingFrom||this!==i;let l=!0;

17if((this.isProjectionDirty||this.parent?.isProjectionDirty)&&(l=!1),o&&(this.isSharedProjectionDirty||this.isTransformDirty)&&(l=!1),this.resolvedRelativeTargetAt===ts.timestamp&&(l=!1),l)return;const{layout:d,layoutId:c}=this.options;if(this.isTreeAnimating=!!(this.parent&&this.parent.isTreeAnimating||this.currentAnimation||this.pendingAnimation),this.isTreeAnimating||(this.targetDelta=this.relativeTarget=void 0),!this.layout||!(d||c))return;qi(this.layoutCorrected,this.layout.layoutBox);const f=this.treeScale.x,m=this.treeScale.y;xJ(this.layoutCorrected,this.treeScale,this.path,o),i.layout&&!i.target&&(this.treeScale.x!==1||this.treeScale.y!==1)&&(i.target=i.layout.layoutBox,i.targetWithTransforms=er());const{target:x}=i;if(!x){this.prevProjectionDelta&&(this.createProjectionDeltas(),this.scheduleRender());return}!this.projectionDelta||!this.prevProjectionDelta?this.createProjectionDeltas():($M(this.prevProjectionDelta.x,this.projectionDelta.x),$M(this.prevProjectionDelta.y,this.projectionDelta.y)),ay(this.projectionDelta,this.layoutCorrected,x,this.latestValues),(this.treeScale.x!==f||this.treeScale.y!==m||!WM(this.projectionDelta.x,this.prevProjectionDelta.x)||!WM(this.projectionDelta.y,this.prevProjectionDelta.y))&&(this.hasProjected=!0,this.scheduleRender(),this.notifyListeners("projectionUpdate",x))}hide(){this.isVisible=!1}show(){this.isVisible=!0}scheduleRender(i=!0){if(this.options.visualElement?.scheduleRender(),i){const o=this.getStack();o&&o.scheduleRender()}this.resumingFrom&&!this.resumingFrom.instance&&(this.resumingFrom=void 0)}createProjectionDeltas(){this.prevProjectionDelta=Tf(),this.projectionDelta=Tf(),this.projectionDeltaWithTransform=Tf()}setAnimationOrigin(i,o=!1){const l=this.snapshot,d=l?l.latestValues:{},c={...this.latestValues},f=Tf();(!this.relativeParent||!this.relativeParent.options.layoutRoot)&&(this.relativeTarget=this.relativeTargetOrigin=void 0),this.attemptToResolveRelativeTarget=!o;const m=er(),x=l?l.source:void 0,y=this.layout?this.layout.source:void 0,b=x!==y,w=this.getStack(),S=!w||w.members.length<=1,k=!!(b&&!S&&this.options.crossfade===!0&&!this.path.some(YQ));this.animationProgress=0;let C;this.mixTargetDelta=E=>{const T=E/1e3;qM(f.x,i.x,T),qM(f.y,i.y,T),this.setTargetDelta(f),this.relativeTarget&&this.relativeTargetOrigin&&this.layout&&this.relativeParent&&this.relativeParent.layout&&(ry(m,this.layout.layoutBox,this.relativeParent.layout.layoutBox),XQ(this.relativeTarget,this.relativeTargetOrigin,m,T),C&&MQ(this.relativeTarget,C)&&(this.isProjectionDirty=!1),C||(C=er()),qi(C,this.relativeTarget)),b&&(this.animationValues=c,TQ(c,d,this.latestValues,T,k,S)),this.root.scheduleUpdateProjection(),this.scheduleRender(),this.animationProgress=T},this.mixTargetDelta(this.options.layoutRoot?1e3:0)}startAnimation(i){this.notifyListeners("animationStart"),this.currentAnimation?.stop(),this.resumingFrom?.currentAnimation?.stop(),this.pendingAnimation&&(Gu(this.pendingAnimation),this.pendingAnimation=void 0),this.pendingAnimation=wa.update(()=>{nv.hasAnimatedSinceResize=!0,this.motionValue||(this.motionValue=Of(0)),this.currentAnimation=kQ(this.motionValue,[0,1e3],{...i,velocity:0,isSync:!0,onUpdate:o=>{this.mixTargetDelta(o),i.onUpdate&&i.onUpdate(o)},onStop:()=>{},onComplete:()=>{i.onComplete&&i.onComplete(),this.completeAnimation()}}),this.resumingFrom&&(this.resumingFrom.currentAnimation=this.currentAnimation),this.pendingAnimation=void 0})}completeAnimation(){this.resumingFrom&&(this.resumingFrom.currentAnimation=void 0,this.resumingFrom.preserveOpacity=void 0);const i=this.getStack();i&&i.exitAnimationComplete(),this.resumingFrom=this.currentAnimation=this.animationValues=void 0,this.notifyListeners("animationComplete")}finishAnimation(){this.currentAnimation&&(this.mixTargetDelta&&this.mixTargetDelta(FQ),this.currentAnimation.stop()),this.completeAnimation()}applyTransformsToTarget(){const 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n,a=[],r=this.isTapeOn(),s=this.state.numBytes,i=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let o;this.backendName==null&&this.backend;let l,d=NN(t)?t.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(NN(t)){let{kernelName:y,inputs:b,attrs:w}=t;this.backendName==null&&this.backend;let S=Dy(y,this.backendName);Z(S!=null,()=>`Cannot find registered kernel '${y}' for backend '${this.backendName}'`),o=()=>{let k=this.backend.numDataIds();l=S.kernelFunc({inputs:b,attrs:w,backend:this.backend});let C=Array.isArray(l)?l:[l];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(y,k,C);let E=C.map(T=>T.rank!=null?T:this.makeTensorFromTensorInfo(T));if(r){let T=this.getTensorsForGradient(y,b,E);a=this.saveTensorsForBackwardMode(T)}return E}}else{let{forwardFunc:y}=t,b=w=>{r&&(a=w.map(S=>this.keep(this.clone(S))))};o=()=>{let w=this.backend.numDataIds();l=this.tidy(()=>y(this.backend,b));let S=Array.isArray(l)?l:[l];return 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s=r.inputsToSave||[],i=r.outputsToSave||[],o;r.saveAllInputs?(Z(Array.isArray(n),()=>"saveAllInputs is true, expected inputs to be an array."),o=Object.keys(n).map(d=>n[d])):o=s.map(d=>n[d]);let l=a.filter((d,c)=>i[c]);return o.concat(l)}return[]}makeTensor(t,n,a,r){if(t==null)throw new Error("Values passed to engine.makeTensor() are null");a=a||"float32",r=r||this.backend;let s=t;a==="string"&&Ou(t[0])&&(s=t.map(l=>Eb(l)));let i=r.write(s,n,a),o=new en(n,a,i,this.nextTensorId());if(this.trackTensor(o,r),a==="string"){let l=this.state.tensorInfo.get(i),d=P8(s);this.state.numBytes+=d-l.bytes,l.bytes=d}return o}makeTensorFromDataId(t,n,a,r){a=a||"float32";let s={dataId:t,shape:n,dtype:a};return this.makeTensorFromTensorInfo(s,r)}makeTensorFromTensorInfo(t,n){let{dataId:a,shape:r,dtype:s}=t,i=new en(r,s,a,this.nextTensorId());return this.trackTensor(i,n),i}makeVariable(t,n=!0,a,r){a=a||this.nextVariableId().toString(),r!=null&&r!==t.dtype&&(t=t.cast(r));let s=new Id(t,n,a,this.nextTensorId());if(this.state.registeredVariables[s.name]!=null)throw new Error(`Variable with name ${s.name} was already registered`);return this.state.registeredVariables[s.name]=s,this.incRef(s,this.backend),s}trackTensor(t,n){this.state.numTensors++,t.dtype==="string"&&this.state.numStringTensors++;let a=0;t.dtype!=="complex64"&&t.dtype!=="string"&&(a=t.size*Nv(t.dtype)),this.state.numBytes+=a,this.state.tensorInfo.has(t.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(t.dataId,{backend:n||this.backend,dtype:t.dtype,shape:t.shape,bytes:a})),t instanceof Id||this.track(t)}incRef(t,n){this.trackTensor(t,n),this.backend.incRef(t.dataId)}removeDataId(t,n){this.state.tensorInfo.has(t)&&this.state.tensorInfo.get(t).backend===n&&(this.state.tensorInfo.delete(t),this.state.numDataBuffers--)}disposeTensor(t){if(!this.state.tensorInfo.has(t.dataId))return;let n=this.state.tensorInfo.get(t.dataId);if(this.state.numTensors--,t.dtype==="string"&&(this.state.numStringTensors--,this.state.numBytes-=n.bytes),t.dtype!=="complex64"&&t.dtype!=="string"){let a=t.size*Nv(t.dtype);this.state.numBytes-=a}n.backend.disposeData(t.dataId)&&this.removeDataId(t.dataId,n.backend)}disposeVariables(){for(let t in this.state.registeredVariables){let n=this.state.registeredVariables[t];this.disposeVariable(n)}}disposeVariable(t){this.disposeTensor(t),this.state.registeredVariables[t.name]!=null&&delete this.state.registeredVariables[t.name]}memory(){let t=this.backend.memory();return t.numTensors=this.state.numTensors,t.numDataBuffers=this.state.numDataBuffers,t.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(t.unreliable=!0,t.reasons==null&&(t.reasons=[]),t.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),t}async profile(t){this.state.profiling=!0;let 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Map,BP=class{getClassName(){return this.constructor.className}static fromConfig(e,t){return new e(t)}},FP=class Sf{constructor(){this.classNameMap={}}static getMap(){return Sf.instance==null&&(Sf.instance=new Sf),Sf.instance}static register(t){Sf.getMap().classNameMap[t.className]=[t,t.fromConfig]}};function OP(e,t,n){Z(e.className!=null,()=>"Class being registered does not have the static className property defined."),Z(typeof e.className=="string",()=>"className is required to be a string, but got type "+typeof e.className),Z(e.className.length>0,()=>"Class being registered has an empty-string as its className, which is disallowed."),typeof t>"u"&&(t="Custom"),typeof n>"u"&&(n=e.className);let a=n,r=t+">"+a;return FP.register(e),Qce.set(r,e),QC.set(e,r),e}function Zce(e){return QC.has(e)?QC.get(e):e.className}var Jl=class extends BP{minimize(e,t=!1,n){let{value:a,grads:r}=this.computeGradients(e,n);if(n!=null){let s=n.map(i=>({name:i.name,tensor:r[i.name]}));this.applyGradients(s)}else this.applyGradients(r);return Kt(r),t?a:(a.dispose(),null)}get iterations(){return this.iterations_==null&&(this.iterations_=0),this.iterations_}incrementIterations(){this.iterations_=this.iterations+1}computeGradients(e,t){return OL(e,t)}dispose(){this.iterations_!=null&&Kt(this.iterations_)}async saveIterations(){return this.iterations_==null&&(this.iterations_=0),{name:"iter",tensor:Et(this.iterations_,"int32")}}async getWeights(){throw new Error("getWeights() is not implemented for this optimizer yet.")}async setWeights(e){throw new Error(`setWeights() is not implemented for this optimizer class ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}};Object.defineProperty(Jl,Symbol.hasInstance,{value:e=>e.minimize!=null&&e.computeGradients!=null&&e.applyGradients!=null});var oA=class extends Jl{static get className(){return"Adadelta"}constructor(e,t,n=null){super(),this.learningRate=e,this.rho=t,this.epsilon=n,this.accumulatedGrads=[],this.accumulatedUpdates=[],n==null&&(this.epsilon=ae.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let a=ae.registeredVariables[t],r=!1;this.accumulatedGrads[n]==null&&(this.accumulatedGrads[n]={originalName:`${t}/accum_grad`,variable:ue(()=>pn(a).variable(r))}),this.accumulatedUpdates[n]==null&&(this.accumulatedUpdates[n]={originalName:`${t}/accum_var`,variable:ue(()=>pn(a).variable(r))});let s=Array.isArray(e)?e[n].tensor:e[t];if(s==null)return;let i=this.accumulatedGrads[n].variable,o=this.accumulatedUpdates[n].variable;ue(()=>{let l=ke(ie(i,this.rho),ie(Jn(s),1-this.rho)),d=ie(ht($r(ke(o,this.epsilon)),$r(ke(i,this.epsilon))),s),c=ke(ie(o,this.rho),ie(Jn(d),1-this.rho));i.assign(l),o.assign(c);let f=ke(ie(d,-this.learningRate),a);a.assign(f)})}),this.incrementIterations()}dispose(){this.accumulatedUpdates!=null&&(Kt(this.accumulatedGrads.map(e=>e.variable)),Kt(this.accumulatedUpdates.map(e=>e.variable)))}async getWeights(){let e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=e.length/2,n=!1;this.accumulatedGrads=e.slice(0,t).map(a=>({originalName:a.name,variable:a.tensor.variable(n)})),this.accumulatedUpdates=e.slice(t,t*2).map(a=>({originalName:a.name,variable:a.tensor.variable(n)}))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}},lA=class extends Jl{static get className(){return"Adagrad"}constructor(e,t=.1){super(),this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let a=ae.registeredVariables[t];this.accumulatedGrads[n]==null&&(this.accumulatedGrads[n]={originalName:`${t}/accumulator`,variable:ue(()=>ri(a.shape,this.initialAccumulatorValue).variable(!1))});let r=Array.isArray(e)?e[n].tensor:e[t];if(r==null)return;let s=this.accumulatedGrads[n].variable;ue(()=>{let i=ke(s,Jn(r));s.assign(i);let o=ke(ie(ht(r,$r(ke(i,ae.backend.epsilon()))),-this.learningRate),a);a.assign(o)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&Kt(this.accumulatedGrads.map(e=>e.variable))}async getWeights(){return[await this.saveIterations()].concat(this.accumulatedGrads.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulatedGrads=e.map(n=>({originalName:n.name,variable:n.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}},uA=class extends Jl{static get className(){return"Adam"}constructor(e,t,n,a=null){super(),this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=a,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],ue(()=>{this.accBeta1=Et(t).variable(),this.accBeta2=Et(n).variable()}),a==null&&(this.epsilon=ae.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);ue(()=>{let n=st(1,this.accBeta1),a=st(1,this.accBeta2);t.forEach((r,s)=>{let i=ae.registeredVariables[r],o=!1;this.accumulatedFirstMoment[s]==null&&(this.accumulatedFirstMoment[s]={originalName:`${r}/m`,variable:ue(()=>pn(i).variable(o))}),this.accumulatedSecondMoment[s]==null&&(this.accumulatedSecondMoment[s]={originalName:`${r}/v`,variable:ue(()=>pn(i).variable(o))});let l=Array.isArray(e)?e[s].tensor:e[r];if(l==null)return;let d=this.accumulatedFirstMoment[s].variable,c=this.accumulatedSecondMoment[s].variable,f=ke(ie(d,this.beta1),ie(l,1-this.beta1)),m=ke(ie(c,this.beta2),ie(Jn(l),1-this.beta2)),x=ht(f,n),y=ht(m,a);d.assign(f),c.assign(m);let b=ke(ie(ht(x,ke($r(y),this.epsilon)),-this.learningRate),i);i.assign(b)}),this.accBeta1.assign(ie(this.accBeta1,this.beta1)),this.accBeta2.assign(ie(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&Kt(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&Kt(this.accumulatedSecondMoment.map(e=>e.variable))}async getWeights(){let e=[...this.accumulatedFirstMoment,...this.accumulatedSecondMoment];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e),ue(()=>{this.accBeta1.assign(sl(this.beta1,this.iterations_+1)),this.accBeta2.assign(sl(this.beta2,this.iterations_+1))});let t=e.length/2,n=!1;this.accumulatedFirstMoment=e.slice(0,t).map(a=>({originalName:a.name,variable:a.tensor.variable(n)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(a=>({originalName:a.name,variable:a.tensor.variable(n)}))}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon)}},cA=class extends Jl{static get className(){return"Adamax"}constructor(e,t,n,a=null,r=0){super(),this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=a,this.decay=r,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],ue(()=>{this.iteration=Et(0).variable(),this.accBeta1=Et(t).variable()}),a==null&&(this.epsilon=ae.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);ue(()=>{let n=st(1,this.accBeta1),a=ht(-this.learningRate,ke(ie(this.iteration,this.decay),1));t.forEach((r,s)=>{let i=ae.registeredVariables[r],o=!1;this.accumulatedFirstMoment[s]==null&&(this.accumulatedFirstMoment[s]={originalName:`${r}/m`,variable:pn(i).variable(o)}),this.accumulatedWeightedInfNorm[s]==null&&(this.accumulatedWeightedInfNorm[s]={originalName:`${r}/v`,variable:pn(i).variable(o)});let l=Array.isArray(e)?e[s].tensor:e[r];if(l==null)return;let d=this.accumulatedFirstMoment[s].variable,c=this.accumulatedWeightedInfNorm[s].variable,f=ke(ie(d,this.beta1),ie(l,1-this.beta1)),m=ie(c,this.beta2),x=tr(l),y=ul(m,x);d.assign(f),c.assign(y);let b=ke(ie(ht(a,n),ht(f,ke(y,this.epsilon))),i);i.assign(b)}),this.iteration.assign(ke(this.iteration,1)),this.accBeta1.assign(ie(this.accBeta1,this.beta1))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),this.accumulatedFirstMoment!=null&&Kt(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedWeightedInfNorm!=null&&Kt(this.accumulatedWeightedInfNorm.map(e=>e.variable))}async getWeights(){throw new Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}},h2=class extends Jl{static get className(){return"SGD"}constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let a=Array.isArray(e)?e[n].tensor:e[t];if(a==null)return;let r=ae.registeredVariables[t];ue(()=>{let s=ke(ie(this.c,a),r);r.assign(s)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=xr(Et(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(e=await this.extractIterations(e),e.length!==0)throw new Error("SGD optimizer does not have settable weights.")}getConfig(){return{learningRate:this.learningRate}}static fromConfig(e,t){return new e(t.learningRate)}},dA=class extends h2{static get className(){return"Momentum"}constructor(e,t,n=!1){super(e),this.learningRate=e,this.momentum=t,this.useNesterov=n,this.accumulations=[],this.m=Et(this.momentum)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let a=ae.registeredVariables[t];this.accumulations[n]==null&&(this.accumulations[n]={originalName:`${t}/momentum`,variable:ue(()=>pn(a).variable(!1))});let r=this.accumulations[n].variable,s=Array.isArray(e)?e[n].tensor:e[t];s!=null&&ue(()=>{let i,o=ke(ie(this.m,r),s);this.useNesterov?i=ke(ie(this.c,ke(s,ie(o,this.m))),a):i=ke(ie(this.c,o),a),r.assign(o),a.assign(i)})}),this.incrementIterations()}dispose(){this.m.dispose(),this.accumulations!=null&&Kt(this.accumulations.map(e=>e.variable))}setMomentum(e){this.momentum=e}async getWeights(){return[await this.saveIterations()].concat(this.accumulations.map(e=>({name:e.originalName,tensor:e.variable}

83)))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulations=e.map(n=>({originalName:n.name,variable:n.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}}static fromConfig(e,t){return new e(t.learningRate,t.momentum,t.useNesterov)}},hA=class extends Jl{static get className(){return"RMSProp"}constructor(e,t=.9,n=0,a=null,r=!1){if(super(),this.learningRate=e,this.decay=t,this.momentum=n,this.epsilon=a,this.accumulatedMeanSquares=[],this.accumulatedMoments=[],this.accumulatedMeanGrads=[],this.centered=r,a==null&&(this.epsilon=ae.backend.epsilon()),e==null)throw new Error("learningRate for RMSPropOptimizer must be defined.")}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let a=ae.registeredVariables[t],r=!1;this.accumulatedMeanSquares[n]==null&&(this.accumulatedMeanSquares[n]={originalName:`${t}/rms`,variable:ue(()=>pn(a).variable(r))}),this.accumulatedMoments[n]==null&&(this.accumulatedMoments[n]={originalName:`${t}/momentum`,variable:ue(()=>pn(a).variable(r))}),this.accumulatedMeanGrads[n]==null&&this.centered&&(this.accumulatedMeanGrads[n]={originalName:`${t}/mg`,variable:ue(()=>pn(a).variable(r))});let s=Array.isArray(e)?e[n].tensor:e[t];if(s==null)return;let i=this.accumulatedMeanSquares[n].variable,o=this.accumulatedMoments[n].variable;ue(()=>{let l=ke(ie(i,this.decay),ie(Jn(s),1-this.decay));if(this.centered){let d=this.accumulatedMeanGrads[n].variable,c=ke(ie(d,this.decay),ie(s,1-this.decay)),f=ht(ie(s,this.learningRate),$r(st(l,ke(Jn(c),this.epsilon)))),m=ke(ie(o,this.momentum),f);i.assign(l),d.assign(c),o.assign(m);let x=st(a,m);a.assign(x)}else{let d=ke(ie(i,this.decay),ie(Jn(s),1-this.decay)),c=ke(ie(o,this.momentum),ht(ie(s,this.learningRate),$r(ke(d,this.epsilon))));i.assign(d),o.assign(c);let f=st(a,c);a.assign(f)}})}),this.incrementIterations()}dispose(){this.accumulatedMeanSquares!=null&&Kt(this.accumulatedMeanSquares.map(e=>e.variable)),this.accumulatedMeanGrads!=null&&this.centered&&Kt(this.accumulatedMeanGrads.map(e=>e.variable)),this.accumulatedMoments!=null&&Kt(this.accumulatedMoments.map(e=>e.variable))}async getWeights(){let e=[...this.accumulatedMeanSquares,...this.accumulatedMoments];return this.centered&&e.push(...this.accumulatedMeanGrads),[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=this.centered?e.length/3:e.length/2,n=!1;this.accumulatedMeanSquares=e.slice(0,t).map(a=>({originalName:a.name,variable:a.tensor.variable(n)})),this.accumulatedMoments=e.slice(t,t*2).map(a=>({originalName:a.name,variable:a.tensor.variable(n)})),this.centered&&(this.accumulatedMeanGrads=e.slice(t*2,t*3).map(a=>({originalName:a.name,variable:a.tensor.variable(n)})))}getConfig(){return{learningRate:this.learningRate,decay:this.decay,momentum:this.momentum,epsilon:this.epsilon,centered:this.centered}}static fromConfig(e,t){return new e(t.learningRate,t.decay,t.momentum,t.epsilon,t.centered)}},ede=[oA,lA,uA,cA,dA,hA,h2];function tde(){for(let e of ede)OP(e)}var Hr={};Xt(Hr,{CompositeArrayBuffer:()=>ql,browserFiles:()=>lde,browserHTTPRequest:()=>fde,concatenateArrayBuffers:()=>Ure,copyModel:()=>cse,decodeWeights:()=>cL,decodeWeightsStream:()=>hL,encodeWeights:()=>Bre,fromMemory:()=>gde,fromMemorySync:()=>WP,getLoadHandlers:()=>Yre,getModelArtifactsForJSON:()=>eT,getModelArtifactsForJSONSync:()=>fL,getModelArtifactsInfoForJSON:()=>Tb,getSaveHandlers:()=>Xre,getWeightSpecs:()=>GC,http:()=>fA,isHTTPScheme:()=>eE,listModels:()=>lse,loadWeights:()=>cde,moveModel:()=>dse,registerLoadRouter:()=>Kre,registerSaveRouter:()=>qre,removeModel:()=>use,weightsLoaderFactory:()=>PP,withSaveHandler:()=>xde,withSaveHandlerSync:()=>yde});var nde="model",ade=".json",rde=".weights.bin";function H5(e){return new Promise(t=>setTimeout(t)).then(e)}var _v=class ZC{constructor(t){if(!fe().getBool("IS_BROWSER"))throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");t.startsWith(ZC.URL_SCHEME)&&(t=t.slice(ZC.URL_SCHEME.length)),(t==null||t.length===0)&&(t=nde),this.modelJsonFileName=t+ade,this.weightDataFileName=t+rde}async save(t){if(typeof document>"u")throw new Error("Browser downloads are not supported in this environment since `document` is not present");let n=ql.join(t.weightData),a=window.URL.createObjectURL(new Blob([n],{type:"application/octet-stream"}));if(t.modelTopology instanceof ArrayBuffer)throw new Error("BrowserDownloads.save() does not support saving model topology in binary formats yet.");{let r=[{paths:["./"+this.weightDataFileName],weights:t.weightSpecs}],s=pL(t,r),i=window.URL.createObjectURL(new Blob([JSON.stringify(s)],{type:"application/json"})),o=this.modelJsonAnchor==null?document.createElement("a"):this.modelJsonAnchor;if(o.download=this.modelJsonFileName,o.href=i,await H5(()=>o.dispatchEvent(new MouseEvent("click"))),t.weightData!=null){let 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InputLayer name: ${this.name}`)}dispose(){return{refCountAfterDispose:this._refCount,numDisposedVariables:0}}getConfig(){return{batchInputShape:this.batchInputShape,dtype:this.dtype,sparse:this.sparse,name:this.name}}};Sg.className="InputLayer";De.registerClass(Sg);function E6(e){if(e.batchShape==null&&e.shape==null)throw new Error("Please provide to Input either a `shape` or a `batchShape` argument. 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o=0;o<n.length;o++){let l=this.inputLayers[o],d=n[o],c=l.name+"_0_0";a[c]=d}let r=Object.keys(this.nodesByDepth).map(o=>parseInt(o,10)).sort(j1);if(r.length>1)for(let o of r){let l=this.nodesByDepth[o];for(let d of l){let c=d.outboundLayer;if(this.inputLayers.map(b=>b.id).indexOf(c.id)!==-1)continue;let f=[];for(let b=0;b<d.inboundLayers.length;b++){let w=d.inboundLayers[b],S=d.nodeIndices[b],k=d.tensorIndices[b],C=`${w.name}_${S}_${k}`,E=a[C];f.push(E)}let m=c.computeOutputShape(Ds(f)),x=jv(m),y=c.inboundNodes.indexOf(d);for(let b=0;b<x.length;b++){let w=`${c.name}_${y}_${b}`;a[w]=x[b]}}}let s=[],i=[];for(let o=0;o<this.outputLayers.length;o++){let l=this.outputLayers[o],d=this.outputLayersNodeIndices[o],c=this.outputLayersTensorIndices[o],f=`${l.name}_${d}_${c}`;i.push(f)}for(let o=0;o<i.length;o++){let l=i[o];qo(l in a),s.push(a[l])}return Ds(s)}runInternalGraph(t,n){n==null&&(n=Bd(null,t.length));let a={};for(let l=0;l<this.inputs.length;++l){let d=this.inputs[l],c=t[l],f=n[l];a[d.id]=[c,f]}let r=Object.keys(this.nodesByDepth).map(l=>parseInt(l,10)).sort(j1);for(let l of r){let d=this.nodesByDepth[l];for(let c of d){let f=c.outboundLayer,m=c.inputTensors,x=c.outputTensors,y=new Array;for(let b of m)b.id in a&&y.push(a[b.id]);if(y.length===m.length){let b={},w,S,k,C;if(c.callArgs!=null&&(b=c.callArgs),y.length===1){let[E,T]=y[0];b.mask==null&&(b.mask=T),k=Wn(f.call(E,b)),C=Wn(f.computeMask(E,T)),w=[E],S=[T]}else w=y.map(E=>E[0]),S=y.map(E=>E[1]),b.mask==null&&(b.mask=S),k=Wn(f.call(w,b)),C=Wn(f.computeMask(w,S));if(f.activityRegularizer)throw new an("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let E=0;E<x.length;++E){let T=x[E],_=k[E],A=C[E];a[T.id]=[_,A]}}}}let s=[],i=[],o=[];for(let l of this.outputs){qo(l.id in a,`Could not compute output ${l.name} : 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Got array shapes: ${JSON.stringify(e.map(s=>s.shape))}`);if(r.length>1)throw new ce(`All target Tensors (y) should have the same number of samples. Got array shapes: ${JSON.stringify(t.map(s=>s.shape))}`);if(a.length>0&&r.length>0&&!R.arraysEqual(a,r))throw new ce(`Input Tensors should have the same number of samples as target Tensors. Found ${a[0]} input sample(s) and ${r[0]} target sample(s).`)}function Dge(e,t,n){let a=[mp,N2,Ly];for(let r=0;r<e.length;++r){let s=e[r],i=t[r],o=n[r];if(i!=null){if(i===Ly&&s.shape[s.shape.length-1]===1)throw new ce(`You are passing a target array of shape ${s.shape} while using a loss 'categorical_crossentropy'. 'categorical_crossentropy'expects targets to be binary matrices (1s and 0s) of shape [samples, classes].`);if(a.indexOf(i)!==-1){let l=s.shape.slice(1),d=o.slice(1);for(let c=0;c<l.length;++c){let f=l[c],m=d[c];if(m!=null&&f!==m)throw new ce(`A target Tensor with shape ${s.shape} was passed for an output of shape ${o}, while using a loss function that expects targets to have the same shape as the output.`)}}}}}function y$(e,t,n,a=!0,r=""){let s;if(Array.isArray(e)){if(e.length!==t.length)throw new ce(`Error when checking model ${r}: 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).`);s=e}else{if(t.length>1)throw new ce(`The model expects ${t.length} ${r} Tensors, but only received one Tensor. Found: array with shape ${JSON.stringify(e.shape)}.`);s=[e]}if(n!=null)for(let i=0;i<t.length;++i){if(n[i]==null)continue;let o=s[i];if(o.shape.length!==n[i].length)throw new ce(`Error when checking ${r}: expected ${t[i]} to have ${n[i].length} dimension(s), but got array with shape ${JSON.stringify(o.shape)}`);for(let l=0;l<n[i].length;++l){if(l===0&&!a)continue;let d=o.shape[l],c=n[i][l];if(c!=null&&c!==d)throw new ce(`Error when checking ${r}: expected ${t[i]} to have shape ${JSON.stringify(n[i])} but got array with shape ${JSON.stringify(o.shape)}.`)}}}function Rge(e,t){if(e==null||Array.isArray(e)&&e.length===0)return t.map(a=>[]);let n;if(typeof e=="string"||typeof e=="function")n=[e];else if(Array.isArray(e)||typeof e=="object")n=e;else throw new TypeError(`Type of metrics argument not understood. Expected an string,function, Array, or Object, found: ${e}`);if(Array.isArray(n))return t.map(a=>n);{let a=[];for(let r of t){let s=n.hasOwnProperty(r)?n[r]:[];Array.isArray(s)||(s=[s]),a.push(s)}return a}}var Mge="layers-model",Ol=class extends wge{constructor(e){super(e),this.isTraining=!1}summary(e,t,n=console.log){if(!this.built)throw new ce("This model has never been called, thus its weights have not been created yet. So no summary can be displayed. Build the model first (e.g., by calling it on some test data).");mge(this,e,t,n)}compile(e){if(e.loss==null&&(e.loss=[]),this.loss=e.loss,typeof e.optimizer=="string")this.optimizer_=fge(e.optimizer),this.isOptimizerOwned=!0;else{if(!(e.optimizer instanceof Jl))throw new ce("User-defined optimizer must be an instance of tf.Optimizer.");this.optimizer_=e.optimizer,this.isOptimizerOwned=!1}let t=[];if(!Array.isArray(e.loss)&&typeof e.loss!="string"&&typeof e.loss!="function"){e.loss=e.loss;for(let s in e.loss)if(this.outputNames.indexOf(s)===-1)throw new ce(`Unknown entry in loss dictionary: "${s}". Only expected the following keys: ${this.outputNames}`);for(let s of this.outputNames)e.loss[s]==null&&console.warn(`Output "${s}" is missing from loss dictionary. We assume this was done on purpose, and we will not be expecting data to be passed to ${s} during training`),t.push(_N(e.loss[s]))}else if(Array.isArray(e.loss)){if(e.loss.length!==this.outputs.length)throw new ce(`When passing an Array as loss, it should have one entry per model output. The model has ${this.outputs.length} output(s), but you passed loss=${e.loss}.`);t=e.loss.map(s=>_N(s))}else{let s=_N(e.loss);this.outputs.forEach(i=>{t.push(s)})}this.lossFunctions=t,this.feedOutputNames=[],this.feedOutputShapes=[],this.feedLossFns=[];for(let s=0;s<this.outputs.length;++s){let i=this.internalOutputShapes[s],o=this.outputNames[s];this.feedOutputNames.push(o),this.feedOutputShapes.push(i),this.feedLossFns.push(this.lossFunctions[s])}let n=[];this.metrics=e.metrics,this.metricsNames=["loss"],this.metricsTensors=[],wd("loss",()=>{for(let s=0;s<this.outputs.length;++s){if(n.indexOf(s)!==-1)continue;let i=this.lossFunctions[s];this.outputs.length>1&&(this.metricsTensors.push([i,s]),this.metricsNames.push(this.outputNames[s]+"_loss"))}});let a=Rge(e.metrics,this.outputNames),r=(s,i,o)=>{this.outputNames.length>1&&(i=this.outputNames[s]+"_"+i),this.metricsNames.push(i),this.metricsTensors.push([o,s])};wd("metric",()=>{for(let s=0;s<this.outputs.length;++s){if(n.indexOf(s)!==-1)continue;let i=a[s];(o=>{let l="",d,c,f;for(let m of o){if(typeof m=="string"&&["accuracy","acc","crossentropy","ce"].indexOf(m)!==-1){let y=this.internalOutputShapes[s];y[y.length-1]===1||this.lossFunctions[s]===N2?["accuracy","acc"].indexOf(m)!==-1?c=BA:["crossentropy","ce"].indexOf(m)!==-1&&(c=L6):this.lossFunctions[s]===Bv?["accuracy","acc"].indexOf(m)!==-1?c=P6:["crossentropy","ce"].indexOf(m)!==-1&&(c=z6):["accuracy","acc"].indexOf(m)!==-1?c=FA:["crossentropy","ce"].indexOf(m)!==-1&&(c=OA);let b;["accuracy","acc"].indexOf(m)!==-1?b="acc":["crossentropy","ce"].indexOf(m)!==-1&&(b="ce"),f=c,d=l+b}else f=pge(m),d=l+M1(m);let x;wd(d,()=>{x=f}),r(s,d,x)}})(i)}}),this.collectedTrainableWeights=this.trainableWeights}checkTrainableWeightsConsistency(){this.collectedTrainableWeights!=null&&this.trainableWeights.length!==this.collectedTrainableWeights.length&&console.warn("Discrepancy between trainableweights and collected trainable weights. Did you set `model.trainable` without calling `model.compile()` afterwards?")}evaluate(e,t,n={}){let a=n.batchSize==null?32:n.batchSize;jN(a);let r=this.standardizeUserDataXY(e,t,!0,a);try{let s=r[0].concat(r[1]);this.makeTestFunction();let i=this.testFunction,o=this.testLoop(i,s,a,n.verbose,n.steps);return Ds(o)}finally{go(r[0],e),go(r[1],t)}}async evaluateDataset(e,t){return this.makeTestFunction(),Age(this,e,t)}checkNumSamples(e,t,n,a="steps"){let r;if(n!=null){if(r=null,t!=null)throw new ce(`If ${a} is set, batchSize must be null or undefined.Got batchSize = ${t}`)}else if(e!=null)Array.isArray(e)?r=e[0].shape[0]:r=e.shape[0];else throw new ce(`Either the input data should have a defined shape, or ${a} shoud be specified.`);return r}execute(e,t){if(Array.isArray(t)&&t.length===0)throw new ce("`outputs` is an empty Array, which is not allowed.");let n=Array.isArray(t),a=n?t:[t],r=this.retrieveSymbolicTensors(a),s=new _f;if(e instanceof en&&(e=[e]),Array.isArray(e)){if(e.length!==this.inputs.length)throw new ce(`The number of inputs provided (${e.length}) does not match the number of inputs of this model (${this.inputs.length}).`);for(let o=0;o<this.inputs.length;++o)s.add(this.inputs[o],e[o])}else for(let o of this.inputs){let l=e[o.name];if(l==null)throw new ce(`No value is provided for the model's input ${o.name}`);s.add(o,l)}let i=Vx(r,s);return n?i:i[0]}retrieveSymbolicTensors(e){let t=Bd(null,e.length),n=e.length;for(let a of this.layers){let r=Array.isArray(a.output)?a.output:[a.output],s=r.map(i=>i.name);for(let i=0;i<e.length;++i){let o=s.indexOf(e[i]);if(o!==-1&&(t[i]=r[o],n--),n===0)break}if(n===0)break}if(n>0){let a=[];throw t.forEach((r,s)=>{r==null&&a.push(e[s])}),new ce(`Cannot find SymbolicTensors for output name(s): ${JSON.stringify(a)}`)}return t}predictLoop(e,t=32,n=!1){return ue(()=>{let a=this.checkNumSamples(e);if(n)throw new an("Verbose predictLoop() is not implemented yet.");let r=DN(a,t),s=this.outputs.map(i=>[]);for(let i=0;i<r.length;++i)ue(()=>{let o=r[i][0],l=r[i][1],d=Mx(e,o,l),c=[];if(Array.isArray(d))for(let m=0;m<d.length;++m)c.push({key:this.inputs[m],value:d[m]});else c.push({key:this.inputs[0],value:d});let f=new _f(c);return Vx(this.outputs,f)}).forEach((o,l)=>s[l].push(o));return Ds(s.map(i=>Qn(i,0)))})}predict(e,t={}){let n=G6(e);y$(n,this.inputNames,this.feedInputShapes,!1);try{let a=t.batchSize==null?32:t.batchSize;return jN(a),this.predictLoop(n,a)}finally{go(n,e)}}predictOnBatch(e){y$(e,this.inputNames,this.feedInputShapes,!0);let t=(Array.isArray(e)?e[0]:e).shape[0];return this.predictLoop(e,t)}standardizeUserDataXY(e,t,n=!0,a){if(this.optimizer_==null)throw new Xo("You must compile a model before training/testing. Use LayersModel.compile(modelCompileArgs).");let r=[];for(let s=0;s<this.feedOutputShapes.length;++s){let i=this.feedOutputShapes[s];this.feedLossFns[s]===Bv?r.push(i.slice(0,i.length-1).concat([1])):r.push(i)}if(e=x$(e,this.feedInputNames,this.feedInputShapes,!1,"input"),t=x$(t,this.feedOutputNames,r,!1,"target"),jge(e,t),Dge(t,this.feedLossFns,this.feedOutputShapes),this.stateful&&a!=null&&a>0&&e[0].shape[0]%a!==0)throw new ce(`In a stateful network, you should only pass inputs with a number of samples that is divisible by the batch size ${a}. Found: ${e[0].shape[0]} sample(s).`);return[e,t]}async standardizeUserData(e,t,n,a,r=!0,s){let[i,o]=this.standardizeUserDataXY(e,t,r,s);if(n!=null)throw new Error("sample weight is not supported yet.");let l=null;if(a!=null){let d=W6(a,this.outputNames);l=[];for(let c=0;c<d.length;++c)l.push(await V6(o[c],null,d[c]))}return[i,o,l]}testLoop(e,t,n,a=0,r){return ue(()=>{let s=this.checkNumSamples(t,n,r,"steps"),i=[];if(a>0)throw new an("Verbose mode is not implemented yet.");if(r!=null)throw new an("steps mode in testLoop() is not implemented yet");{let o=DN(s,n),l=Ln(To(0,s));for(let d=0;d<o.length;++d){let c=o[d][0],f=o[d][1],m=Sd(l,c,f-c),x=uE(t,m),y=e(x);if(d===0)for(let b=0;b<y.length;++b)i.push(Et(0));for(let b=0;b<y.length;++b){let w=y[b];i[b]=ke(i[b],ie(f-c,w))}}for(let d=0;d<i.length;++d)i[d]=ht(i[d],s)}return i})}getDedupedMetricsNames(){let e=this.metricsNames,t=[];for(let n=0;n<e.length;++n){let a=e[n],r=a;if(a$(e,a)>1){let s=a$(e.slice(0,n),a);r+=`_${s}`}t.push(r)}return t}makeTrainFunction(){return e=>{let t=[],n=e.slice(0,this.inputs.length),a=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),r=e.slice(this.inputs.length+this.outputs.length,this.inputs.length+this.outputs.length*2),s=[],i=()=>{let l=[];for(let m=0;m<this.inputs.length;++m)l.push({key:this.inputs[m],value:n[m]});let d=new _f(l),c=Vx(this.outputs,d,{training:!0}),f;for(let m=0;m<this.lossFunctions.length;++m){let x=this.lossFunctions[m],y=x(a[m],c[m]);r[m]!=null&&(y=kge(y,r[m]));let b=ba(y);t.push(b),m===0?f=y:f=ke(f,y)}for(let m=0;m<this.metricsTensors.length;++m){let x;if(this.outputs.length>1&&m<this.outputs.length)x=t[m];else{let y=this.metricsTensors[m][0],b=this.metricsTensors[m][1];x=ba(y(a[b],c[b]))}xr(x),s.push(x)}return f=ba(f),this.calculateLosses().forEach(m=>{f=ke(f,m)}),f},o=this.collectedTrainableWeights.map(l=>l.read());return[this.optimizer_.minimize(i,!0,o)].concat(s)}}makeTestFunction(){this.testFunction=e=>ue(()=>{let t=[],n,a=e.slice(0,this.inputs.length),r=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),s=[];for(let l=0;l<this.inputs.length;++l)s.push({key:this.inputs[l],value:a[l]});let i=new _f(s),o=Vx(this.outputs,i);for(let l=0;l<this.lossFunctions.length;++l){let d=this.lossFunctions[l],c=ba(d(r[l],o[l]));l===0?n=c:n=ke(n,c),t.push(n)}for(let l=0;l<this.metricsTensors.length;++l){let d=this.metricsTensors[l][0],c=this.metricsTensors[l][1],f=ba(d(r[c],o[c]));t.push(f)}return t})}async fit(e,t,n={}){if(this.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");this.isTraining=!0;let a,r,s,i,o,l,d,c,f;try{let m=n.batchSize==null?32:n.batchSize;jN(m);let x=await this.standardizeUserData(e,t,n.sampleWeight,n.classWeight,!1,m);a=x[0],r=x[1],f=x[2];let y=!1,b;if(n.validationData!=null&&n.validationData.length>0){if(y=!0,n.validationData.length===2)o=n.validationData[0],l=n.validationData[1];else throw n.validationData.length===3?new an("validationData including sample weights is not supported yet."):new ce(`When passing validation data, it must contain 2 (valX, valY) or 3 (valX, valY, valSampleWeight) items;

92if(e.weightsManifest!=null){let s=await Hr.loadWeights(e.weightsManifest,e.pathPrefix,r.weights.map(o=>o.originalName)),i={};for(let o of r.weights)i[o.originalName]=s[o.originalName];r.loadWeights(i),Kt(s)}return r}async function Bge(e,t){if(t==null&&(t={}),typeof e=="string"){let n=Hr.getLoadHandlers(e,t);if(n.length===0)n.push(Hr.browserHTTPRequest(e,t));else if(n.length>1)throw new ce(`Found more than one (${n.length}) load handlers for URL '${e}'`);e=n[0]}return Fge(e,void 0,t)}async function Fge(e,t,n){if(n==null&&(n={}),e.load==null)throw new ce("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let a=await e.load(),r=a.modelTopology;r.model_config!=null&&(r=r.model_config);let s=n.strict==null?!0:n.strict,i=a.weightData!=null&&a.weightSpecs!=null&&s,o=Eo(Py(r),t,i),l=a.trainingConfig;if(l!=null&&o.loadTrainingConfig(l),a.userDefinedMetadata!=null&&o.setUserDefinedMetadata(a.userDefinedMetadata),a.weightData!=null){if(a.weightSpecs==null)throw new ce("LayersModel artifacts contains weight data, but not weight specs. Therefore loading of weights cannot proceed.");let{modelWeights:d,optimizerWeights:c}=Oge(a.weightData,a.weightSpecs);o.loadWeights(d,s),o.optimizer!=null&&c.length>0&&await o.optimizer.setWeights(c),Kt(d),Kt(c.map(f=>f.tensor))}return o}function Oge(e,t){let n=Hr.decodeWeights(e,t),a={},r=[];return t.forEach(s=>{s.group==="optimizer"?r.push({name:s.name,tensor:n[s.name]}):a[s.name]=n[s.name]}),{modelWeights:a,optimizerWeights:r}}var C2=class dE extends Ol{constructor(t){if(super({inputs:[],outputs:[]}),t=t||{},this.trainable=!0,this.built=!1,this.name=t.name!=null?t.name:p2("sequential_"),t.layers!=null)for(let n of t.layers)this.add(n)}checkShape(t){if(t.inboundNodes[0].outputTensors[0].shape.some(n=>n<0))throw new ce(`Negative dimension size caused by adding layer ${t.name} with input shape [${t.inboundNodes[0].inputTensors[0].shape}]`)}add(t){let n=t instanceof dE||t instanceof Ol,a;if(n){if(a=t,a.outputs.length!==1)throw new ce("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");if(a.inputs.length!==1)throw new ce("All layers in a Sequential model should have a single input tensor. For multi-input layers, use the functional API.")}if(this.outputs.length===0){if(t.inboundNodes.length===0){if(t.batchInputShape==null)throw new ce("The first layer in a Sequential model must get an `inputShape` or `batchInputShape` argument.");let r=E6({batchShape:t.batchInputShape,dtype:t.dtype,name:t.name+"_input"});t.apply(r)}if(n)this.outputs=a.outputs,this.inputs=a.inputs;else{if(t.inboundNodes.length!==1)throw new ce(`A layer added to a Sequential model must not already be connected somewhere else. LayersModel received layer ${t.name} which has ${t.inboundNodes.length} pre-existing inbound connections.`);if(t.inboundNodes[0].outputTensors.length!==1)throw new ce("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");this.checkShape(t),this.outputs=[t.inboundNodes[0].outputTensors[0]],this.inputs=C6(this.outputs[0])}this.inboundNodes=[],new S2({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:Bd(null,this.inputs.length),outputMasks:[null],inputShapes:this.inputs.map(r=>r.shape),outputShapes:this.outputs[0].shape})}else{let r=t.apply(this.outputs[0]);if(Array.isArray(r))throw new TypeError("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");this.checkShape(t),this.outputs=[r],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}this.layers.push(t),this.built=!1}pop(){if(this.layers.length===0)throw new TypeError("There are no layers in the model.");if(this.layers.pop(),this.layers.length===0)this.outputs=[],this.inboundNodes=[],this.outboundNodes=[];else{let t=this.layers.length-1;this.layers[t].outboundNodes=[],this.outputs=[this.layers[t].output],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}}call(t,n){return this.model==null&&this.build(),this.model.call(t,n)}build(t){if(En(t),this.inputs.length===0||this.outputs.length===0)throw new TypeError("Sequential model cannot be built: model is empty. Add some layers first.");this.model=new Ol({inputs:this.inputs,outputs:this.outputs[0],name:this.name+"_model"}),this.model.trainable=this.trainable,this.supportsMasking=this.model.supportsMasking,this.inputLayers=this.model.inputLayers,this.inputLayersNodeIndices=this.model.inputLayersNodeIndices,this.inputLayersTensorIndices=this.model.inputLayersTensorIndices,this.outputLayers=this.model.outputLayers,this.outputLayersNodeIndices=this.model.outputLayersNodeIndices,this.outputLayersTensorIndices=this.model.outputLayersTensorIndices,this.nodesByDepth=this.model.nodesByDepth,this.containerNodes=this.model.containerNodes,this.outputNames=this.model.outputNames,this.inputNames=this.model.inputNames,this.built=!0}countParams(){return this.built||this.build(),super.countParams()}summary(t,n,a=console.log){this.built||this.build(),super.summary(t,n,a)}setWeights(t){this.model==null&&this.build(),this.model.setWeights(t)}evaluate(t,n,a={}){if(!this.built)throw new Xo("The model needs to be compiled before being used.");return this.model.evaluate(t,n,a)}async evaluateDataset(t,n){if(!this.built)throw new Xo("The model needs to be compiled before being used.");return this.model.evaluateDataset(t,n)}predict(t,n={}){return this.model==null&&this.build(),this.model.predict(t,n)}predictOnBatch(t){return this.model==null&&this.build(),this.model.predictOnBatch(t)}compile(t){this.build(),this.model.compile(t),this.optimizer_=this.model.optimizer,this.isOptimizerOwned=this.model.isOptimizerOwned,this.loss=this.model.loss,this.metrics=this.model.metrics,this.metricsTensors=this.model.metricsTensors,this.metricsNames=this.model.metricsNames}get optimizer(){return this.model==null?void 0:this.model.optimizer}set optimizer(t){this.model.optimizer=t}async fit(t,n,a={}){if(!this.built)throw new Xo("The model needs to be compiled before being used.");return this.model.fit(t,n,a)}async fitDataset(t,n){if(!this.built)throw new Xo("The model needs to be compiled before being used.");return this.model.fitDataset(t,n)}async trainOnBatch(t,n){return this.model.trainOnBatch(t,n)}static fromConfig(t,n,a={},r=!1){let s,i={};if(n instanceof Array){if(n[0].className==null||n[0].className==="Merge")throw new ce("Legacy serialization format not supported yet.");s=n}else R.assert(n.layers!=null,()=>"When the config data for a Sequential model is not an Array, it must be an Object that contains the 'layers' field."),s=n.layers,delete n.layers,i=n;let o=new t(i);if(!(o instanceof dE))throw new an(`Sequential.fromConfig called on non-Sequential input: ${o}`);for(let l of s){let d=Eo(l,void 0,r);r&&d.setFastWeightInitDuringBuild(!0),o.add(d)}return o}set stopTraining(t){if(this.model==null)throw new ce("Cannot set the stopTraining property of a sequential model before it is compiled.");this.model.stopTraining=t}get stopTraining(){if(this.model==null)throw new ce("Cannot get the stopTraining property of a sequential model before it is compiled.");return this.model.stopTraining}getConfig(){let t=[];for(let n of this.layers){let a={};a.className=n.getClassName(),a.config=n.getConfig(),t.push(a)}return{name:this.name,layers:t}}};C2.className="Sequential";De.registerClass(C2);function Lge(e){return new Ol(e)}function Pge(e){return new C2(e)}function K6(e){return E6(e)}function zge(e,t){MA.registerCallbackConstructor(e,t)}var rs=class extends De.Serializable{getConfig(){return{}}},X6=class extends rs{apply(e,t=1){return ime(e,t)}};X6.className="elu";De.registerClass(X6);var Y6=class extends rs{apply(e){return Yw(e)}};Y6.className="selu";De.registerClass(Y6);var J6=class extends rs{apply(e){return Vn(e)}};J6.className="relu";De.registerClass(J6);var Q6=class extends rs{apply(e){return ue(()=>ec(6,Vn(e)))}};Q6.className="relu6";De.registerClass(Q6);var Z6=class extends rs{apply(e){return e}};Z6.className="linear";De.registerClass(Z6);var ez=class extends rs{apply(e){return eo(e)}};ez.className="sigmoid";De.registerClass(ez);var tz=class extends rs{apply(e){return lme(e)}};tz.className="hardSigmoid";De.registerClass(tz);var nz=class extends rs{apply(e){return hp(e)}};nz.className="softplus";De.registerClass(nz);var az=class extends rs{apply(e){return ome(e)}};az.className="softsign";De.registerClass(az);var rz=class extends rs{apply(e){return Zu(e)}};rz.className="tanh";De.registerClass(rz);var PA=class extends rs{apply(e,t=-1){return bc(e,t)}};PA.className="softmax";De.registerClass(PA);var sz=class extends rs{apply(e,t=-1){return Ww(e,t)}};sz.className="logSoftmax";De.registerClass(sz);var iz=class extends rs{apply(e){return ue(()=>ue(()=>{let t=Math.sqrt(2),n=ie(.5,ke(1,Pw(ht(e,t))));return ie(e,n)}))}};iz.className="gelu";De.registerClass(iz);var oz=class extends rs{apply(e){return ue(()=>ie(.5,ie(e,ke(1,Zu(ie($r(ht(2,Math.PI)),ke(e,ie(.044715,sl(e,3)))))))))}};oz.className="gelu_new";De.registerClass(oz);var lz=class extends rs{apply(e){return ue(()=>ie(e,Zu(hp(e))))}};lz.className="mish";De.registerClass(lz);var uz=class extends rs{apply(e,t=1){return ue(()=>ie(eo(ie(e,t)),e))}};uz.className="swish";De.registerClass(uz);function ac(e){return e.getClassName()}function RN(e,t={}){return Vb(e,De.SerializationMap.getMap().classNameMap,t,"activation")}function rc(e){if(e==null){let t={};return t.className="linear",t.config={},RN(t)}if(typeof e=="string"){let t={};return t.className=e,t.config={},RN(t)}else return e instanceof rs?e:RN(e)}function zA(e){if(e!=null&&typeof e!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}var cz=class extends De.Serializable{},Xb=class extends cz{constructor(e){super(),zA(e),this.l1=e==null||e.l1==null?.01:e.l1,this.l2=e==null||e.l2==null?.01:e.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(e){return ue(()=>{let t=va([1]);return this.hasL1&&(t=ke(t,yt(ie(this.l1,tr(e))))),this.hasL2&&(t=ke(t,yt(ie(this.l2,Gb(e))))),le(t,[])})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};Xb.className="L1L2";De.registerClass(Xb);function Uge(e){return zA(e),new Xb({l1:e!=null?e.l1:null,l2:0})}function Wge(e){return zA(e),new Xb({l2:e!=null?e.l2:null,l1:0})}var b$={l1l2:"L1L2"};function ra(e){return yA(e)}function v$(e,t={}){return Vb(e,De.SerializationMap.getMap().classNameMap,t,"regularizer")}function xa(e){if(e==null)return null;if(typeof e=="string"){let t={className:e in b$?b$[e]:e,config:{}};return v$(t)}else return e instanceof cz?e:v$(e)}var UA=class extends rn{constructor(e){super(e??{}),this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=zt(e);let n=Vn(e);return this.maxValue!=null&&(n=ns(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};UA.className="ReLU";De.registerClass(UA);var WA=class extends rn{constructor(e){super(e??{}),this.DEFAULT_ALPHA=.3,e==null&&(e={}),this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=zt(e);return Rb(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};WA.className="LeakyReLU";De.registerClass(WA);var VA=class extends rn{constructor(e){if(super(e??{}),this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=ga(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=xa(e.alphaRegularizer),this.alphaConstraint=Sr(e.alphaConstraint),e.sharedAxes==null)this.sharedAxes=null;else if(Array.isArray(e.sharedAxes))this.sharedAxes=e.sharedAxes;else if(typeof e.sharedAxes=="number")this.sharedAxes=[e.sharedAxes];else throw new ce(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=En(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let a of this.sharedAxes)t[a-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let a=1;a<e.length;++a)n[a]=e[a];this.inputSpec=[new nr({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=zt(e),Lb(e,this.alpha.read())}getConfig(){let e={alphaInitializer:Sa(this.alphaInitializer),alphaRegularizer:ra(this.alphaRegularizer),alphaConstraint:wr(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};VA.className="PReLU";De.registerClass(VA);var HA=class extends rn{constructor(e){if(super(e??{}),this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new an(`Non-default alpha value (${e.alpha}) is not supported by the ELU layer yet.`);this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=zt(e);return mg(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};HA.className="ELU";De.registerClass(HA);var GA=class extends rn{constructor(e){super(e??{}),this.DEFAULT_THETA=1,e==null&&(e={}),this.theta=e.theta==null?this.DEFAULT_THETA:e.theta}call(e,t){let n=zt(e);return ie(n,He(Es(n,this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};GA.className="ThresholdedReLU";De.registerClass(GA);var qA=class extends rn{constructor(e){super(e??{}),this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new PA().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){return ue(()=>{let n=zt(e),a=t.mask;if(a!=null){let r=ie(st($s(n.shape),He(a,n.dtype)),Et(-1e9));n=ke(n,r)}return this.axis instanceof Array?this.axis.length>1?as(st(n,$b(n,this.axis,!0))):this.softmax(n,this.axis[0]):this.softmax(n,this.axis)})}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};qA.className="Softmax";De.registerClass(qA);function Bf(e,t,n){if(typeof e=="number")return Bd(e,t);if(e.length!==t)throw new ce(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${e.length} elements.`);for(let a=0;a<t;++a){let r=e[a];if(!nme(r))throw new ce(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${JSON.stringify(e)} including a non-integer number ${r}`)}return e}function Io(e,t,n,a,r=1){if(e==null)return e;let s=t+(t-1)*(r-1),i;return n==="same"?i=e:i=e-s+1,Math.floor((i+a-1)/a)}function Ko(e,t,n,a){if(e==null)return null;if(a==="valid")e=e*t+nc([n-t,0]);else if(a==="same")e=e*t;else throw new ce(`Unsupport padding mode: ${a}.`);return e}function KA(e,t){return ue(()=>(Va(t),t==="channelsFirst"?Qt(e,[0,2,3,1]):e))}function dz(e,t){return ue(()=>(Va(t),t==="channelsFirst"?Qt(e,[0,2,3,4,1]):e))}function Vge(e,t,n,a=1,r="valid",s,i=1){return ue(()=>{if(s==null&&(s=Ao()),Va(s),e.shape.length!==3)throw new ce(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new ce(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new ce(`The bias for a conv1dWithBias operation should be 1, but is ${n.shape.length} instead`);if(s==="channelsFirst"&&(e=Qt(e,[0,2,1])),r==="causal")throw new an("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=Bw(e,t,a,r==="same"?"same":"valid","NWC",i);return n!=null&&(o=Mo(o,n)),o})}function w$(e,t,n,a=[1,1],r="valid",s,i,o=null){return ue(()=>{if(s==null&&(s=Ao()),Va(s),e.rank!==3&&e.rank!==4)throw new ce(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new ce(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=KA(e,s);if(r==="causal")throw new an("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Yf.conv2d({x:l,filter:t,strides:a,pad:r==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=Qt(l,[0,3,1,2])),l})}function Hge(e,t,n,a=[1,1,1],r="valid",s,i){return ue(()=>{if(s==null&&(s=Ao()),Va(s),e.rank!==4&&e.rank!==5)throw new ce(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new ce(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=dz(e,s);if(r==="causal")throw new an("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=ST(o,t,a,r==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Mo(o,n)),s==="channelsFirst"&&(o=Qt(o,[0,4,1,2,3])),o})}var hz=class pz extends rn{constructor(t,n){if(super(n),this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",pz.verifyArgs(n),this.rank=t,Rr(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new an(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Bf(n.kernelSize,t,"kernelSize"),this.strides=Bf(n.strides==null?1:n.strides,t,"strides"),this.padding=n.padding==null?"valid":n.padding,$i(this.padding),this.dataFormat=n.dataFormat==null?"channelsLast":n.dataFormat,Va(this.dataFormat),this.activation=rc(n.activation),this.useBias=n.useBias==null?!0:n.useBias,this.biasInitializer=ga(n.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Sr(n.biasConstraint),this.biasRegularizer=xa(n.biasRegularizer),this.activityRegularizer=xa(n.activityRegularizer),this.dilationRate=Bf(n.dilationRate==null?1:n.dilationRate,t,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new ce(`dilationRate must be a number or an array of a single number for 1D convolution, but received ${JSON.stringify(this.dilationRate)}`);if(this.rank===2){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==2)throw new ce(`dilationRate must be a number or array of two numbers for 2D convolution, but received ${JSON.stringify(this.dilationRate)}`)}else if(this.rank===3){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==3)throw new ce(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(t){if(qo("kernelSize"in t,"required key 'kernelSize' not in config"),typeof t.kernelSize!="number"&&!bA(t.kernelSize,"number",1,3))throw new ce(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(t.kernelSize)}.`)}getConfig(){let t={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:ac(this.activation),useBias:this.useBias,biasInitializer:Sa(this.biasInitializer),biasRegularizer:ra(this.biasRegularizer),activityRegularizer:ra(this.activityRegularizer),biasConstraint:wr(this.biasConstraint)},n=super.getConfig();return Object.assign(t,n),t}},E2=class fz extends hz{constructor(t,n){super(t,n),this.kernel=null,fz.verifyArgs(n),this.filters=n.filters,Rr(this.filters,"filters"),this.kernelInitializer=ga(n.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Sr(n.kernelConstraint),this.kernelRegularizer=xa(n.kernelRegularizer)}build(t){t=En(t);let n=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[n]==null)throw new ce(`The channel dimension of the input should be defined. Found ${t[n]}`);let a=t[n],r=this.kernelSize.concat([a,this.filters]);this.kernel=this.addWeight("kernel",r,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:{[n]:a}}],this.built=!0}call(t,n){return ue(()=>{t=zt(t);let a,r=this.bias==null?null:this.bias.read(),s=g6(this.activation.getClassName());if(s!=null&&this.rank===2)a=w$(t,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate,s);else{if(this.rank===1)a=Vge(t,this.kernel.read(),r,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)a=w$(t,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)a=Hge(t,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new an("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(a=this.activation.apply(a))}return a})}computeOutputShape(t){t=En(t);let n=[],a=this.dataFormat==="channelsLast"?t.slice(1,t.length-1):t.slice(2);for(let s=0;s<a.length;++s){let i=Io(a[s],this.kernelSize[s],this.padding,this.strides[s],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[s]);n.push(i)}let r=[t[0]];return this.dataFormat==="channelsLast"?(r=r.concat(n),r.push(this.filters)):(r.push(this.filters),r=r.concat(n)),r}getConfig(){let t={filters:this.filters,kernelInitializer:Sa(this.kernelInitializer),kernelRegularizer:ra(this.kernelRegularizer),kernelConstraint:wr(this.kernelConstraint)},n=super.getConfig();return Object.assign(t,n),t}static verifyArgs(t){if(!("filters"in t)||typeof t.filters!="number"||t.filters<1)throw new ce(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(t.filters)}`)}},I2=class mz extends E2{constructor(t){super(2,t),mz.verifyArgs(t)}getConfig(){let t=super.getConfig();return delete t.rank,t}static verifyArgs(t){if(typeof t.kernelSize!="number"&&!bA(t.kernelSize,"number",1,2))throw new ce(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(t.kernelSize)}.`)}};I2.className="Conv2D";De.registerClass(I2);var T2=class gz extends E2{constructor(t){super(3,t),gz.verifyArgs(t)}getConfig(){let t=super.getConfig();return delete t.rank,t}static verifyArgs(t){if(typeof t.kernelSize!="number"&&!(Array.isArray(t.kernelSize)&&(t.kernelSize.length===1||t.kernelSize.length===3)))throw new ce(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(t.kernelSize)}.`)}};T2.className="Conv3D";De.registerClass(T2);var XA=class extends I2{constructor(e){if(super(e),this.inputSpec=[new nr({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new ce(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=En(e),e.length!==4)throw new ce("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new ce("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],a=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",a,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new nr({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return ue(()=>{let n=zt(e);if(n.shape.length!==4)throw new ce(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let a=n.shape,r=a[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=a[s],l=a[i],d=this.kernelSize[0],c=this.kernelSize[1],f=this.strides[0],m=this.strides[1],x=Ko(o,f,d,this.padding),y=Ko(l,m,c,this.padding),b=[r,x,y,this.filters];this.dataFormat!=="channelsLast"&&(n=Qt(n,[0,2,3,1]));let w=Fw(n,this.kernel.read(),b,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(w=Qt(w,[0,3,1,2])),this.bias!=null&&(w=Mo(w,this.bias.read(),this.dataFormat)),this.activation!=null&&(w=this.activation.apply(w)),w})}computeOutputShape(e){e=En(e);let t=e.slice(),n,a,r;this.dataFormat==="channelsFirst"?(n=1,a=2,r=3):(n=3,a=1,r=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[a]=Ko(t[a],o,s,this.padding),t[r]=Ko(t[r],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};XA.className="Conv2DTranspose";De.registerClass(XA);var YA=class extends T2{constructor(e){if(super(e),this.inputSpec=[new nr({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new ce(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=En(e),e.length!==5)throw new ce("Input should have rank 5; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new ce("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],a=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",a,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new nr({ndim:5,axes:{[t]:n}})],this.built=!0}call(e,t){return ue(()=>{let n=zt(e);if(n.shape.length!==5)throw new ce(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let a=n.shape,r=a[0],s,i,o;this.dataFormat==="channelsFirst"?(o=2,s=3,i=4):(o=1,s=2,i=3);let l=a[o],d=a[s],c=a[i],f=this.kernelSize[0],m=this.kernelSize[1],x=this.kernelSize[2],y=this.strides[0],b=this.strides[1],w=this.strides[2],S=Ko(l,y,f,this.padding),k=Ko(d,b,m,this.padding),C=Ko(c,w,x,this.padding),E=[r,S,k,C,this.filters];this.dataFormat!=="channelsLast"&&(n=Qt(n,[0,2,3,4,1]));let T=kT(n,this.kernel.read(),E,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(T=Qt(T,[0,4,1,2,3])),this.bias!==null&&(T=Mo(T,this.bias.read(),this.dataFormat)),this.activation!==null&&(T=this.activation.apply(T)),T})}computeOutputShape(e){e=En(e);let t=e.slice(),n,a,r,s;this.dataFormat==="channelsFirst"?(n=1,a=2,r=3,s=4):(n=4,a=1,r=2,s=3);let i=this.kernelSize[0],o=this.kernelSize[1],l=this.kernelSize[2],d=this.strides[0],c=this.strides[1],f=this.strides[2];return t[n]=this.filters,t[a]=Ko(t[a],d,i,this.padding),t[r]=Ko(t[r],c,o,this.padding),t[s]=Ko(t[s],f,l,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};YA.className="Conv3DTranspose";De.registerClass(YA);var xz=class extends E2{constructor(e,t){if(super(e,t),this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new ce("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new ce("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(t.padding!=null&&t.padding!=="same"&&t.padding!=="valid")throw new ce(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=ga(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=xa(t.depthwiseRegularizer),this.depthwiseConstraint=Sr(t.depthwiseConstraint),this.pointwiseInitializer=ga(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=xa(t.pointwiseRegularizer),this.pointwiseConstraint=Sr(t.pointwiseConstraint)}build(e){if(e=En(e),e.length<this.rank+2)throw new ce(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank+2}, but received input shape: ${JSON.stringify(e)}`);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null||e[t]<0)throw new ce(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],a=this.kernelSize.concat([n,this.depthMultiplier]),r=[];for(let i=0;i<this.rank;++i)r.push(1);r.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",a,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",r,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new nr({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return ue(()=>{e=zt(e);let n;if(this.rank===1)throw new an("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=Qt(e,[0,2,3,1])),n=bg(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Mo(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=Qt(n,[0,3,1,2])),n})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=Sa(this.depthwiseInitializer),e.pointwiseInitializer=Sa(this.pointwiseInitializer),e.depthwiseRegularizer=ra(this.depthwiseRegularizer),e.pointwiseRegularizer=ra(this.pointwiseRegularizer),e.depthwiseConstraint=wr(this.depthwiseConstraint),e.pointwiseConstraint=wr(this.pointwiseConstraint),e}};xz.className="SeparableConv";var JA=class extends xz{constructor(e){super(2,e)}};JA.className="SeparableConv2D";De.registerClass(JA);var QA=class yz extends E2{constructor(t){super(1,t),yz.verifyArgs(t),this.inputSpec=[{ndim:3}]}getConfig(){let t=super.getConfig();return delete t.rank,delete t.dataFormat,t}static verifyArgs(t){if(typeof t.kernelSize!="number"&&!bA(t.kernelSize,"number",1,1))throw new ce(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(t.kernelSize)}.`)}};QA.className="Conv1D";De.registerClass(QA);var ZA=class extends rn{constructor(e){super(e),typeof e.cropping=="number"?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:typeof e.cropping[0]=="number"?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=e.dataFormat===void 0?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(e){return this.dataFormat==="channelsFirst"?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-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]]}call(e,t){return ue(()=>{if(e=zt(e),this.dataFormat==="channelsLast"){let n=R1(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return R1(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=R1(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return R1(n,this.cropping[1][0],e.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let e={cropping:this.cropping,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};ZA.className="Cropping2D";De.registerClass(ZA);var e_=class extends rn{constructor(e){super(e),this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=e.size==null?this.DEFAULT_SIZE:e.size,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Va(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,Zfe(this.interpolation)}computeOutputShape(e){if(this.dataFormat==="channelsFirst"){let t=e[2]==null?null:this.size[0]*e[2],n=e[3]==null?null:this.size[1]*e[3];return[e[0],e[1],t,n]}else{let t=e[1]==null?null:this.size[0]*e[1],n=e[2]==null?null:this.size[1]*e[2];return[e[0],t,n,e[3]]}}call(e,t){return ue(()=>{let n=zt(e),a=n.shape;if(this.dataFormat==="channelsFirst"){n=Qt(n,[0,2,3,1]);let r=this.size[0]*a[2],s=this.size[1]*a[3],i=this.interpolation==="nearest"?Ii.resizeNearestNeighbor(n,[r,s]):Ii.resizeBilinear(n,[r,s]);return Qt(i,[0,3,1,2])}else{let r=this.size[0]*a[1],s=this.size[1]*a[2];return this.interpolation==="nearest"?Ii.resizeNearestNeighbor(n,[r,s]):Ii.resizeBilinear(n,[r,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat,interpolation:this.interpolation},t=super.getConfig();return Object.assign(e,t),e}};e_.className="UpSampling2D";De.registerClass(e_);function Gge(e,t,n=[1,1],a="valid",r,s){return ue(()=>{r==null&&(r=Ao()),Va(r);let i=KA(e,r);if(e.rank!==4)throw new ce(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new ce(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=dp(i,t,n,a==="same"?"same":"valid","NHWC",s),r==="channelsFirst"&&(i=Qt(i,[0,3,1,2])),i})}var t_=class extends hz{constructor(e){super(2,e),this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=ga(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Sr(e.depthwiseConstraint),this.depthwiseRegularizer=xa(e.depthwiseRegularizer)}build(e){if(e=En(e),e.length<4)throw new ce(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new ce(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],a=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",a,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return ue(()=>{e=zt(e);let n=Gge(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Mo(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=En(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],a=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,r=Io(t,this.kernelSize[0],this.padding,this.strides[0]),s=Io(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],a,r,s]:[e[0],r,s,a]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Sa(this.depthwiseInitializer),e.depthwiseRegularizer=ra(this.depthwiseRegularizer),e.depthwiseConstraint=wr(this.depthwiseRegularizer),e}};t_.className="DepthwiseConv2D";De.registerClass(t_);function bz(e,t,n,a){if(Array.isArray(e)){if(t!=null||n!=null)throw new ce("When input

92if(a!=null){n.initialState=a,i=i.concat(a),this.stateSpec=[];for(let l of a)this.stateSpec.push(new nr({shape:l.shape}));o=o.concat(this.stateSpec)}if(r!=null&&(n.constants=r,i=i.concat(r),this.numConstants=r.length),i[0]instanceof _o){let l=[t].concat(i),d=this.inputSpec.concat(o),c=this.inputSpec;this.inputSpec=d;let f=super.apply(l,n);return this.inputSpec=c,f}else return super.apply(t,n)}call(t,n){return ue(()=>{let a=n==null?null:n.mask,r=n==null?null:n.training,s=n==null?null:n.initialState;t=zt(t),s==null&&(this.stateful?s=this.states_:s=this.getInitialState(t));let i=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(s.length!==i)throw new ce(`RNN Layer has ${i} state(s) but was passed ${s.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let o={training:r},l=vz((x,y)=>{let b=this.cell.call([x].concat(y),o);return[b[0],b.slice(1)]},t,s,this.goBackwards,a,null,this.unroll,this.returnSequences),d=l[0],c=l[1],f=l[2];this.stateful&&this.resetStates(f,r);let m=this.returnSequences?c:d;return this.returnState?[m].concat(f):m})}getInitialState(t){return ue(()=>{let n=va(t.shape);return n=yt(n,[1,2]),n=Hb(n),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(a=>a>1?aE(n,[1,a]):n):this.cell.stateSize>1?[aE(n,[1,this.cell.stateSize])]:[n]})}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(t){super.setFastWeightInitDuringBuild(t),this.cell!=null&&this.cell.setFastWeightInitDuringBuild(t)}getConfig(){let t=super.getConfig(),n={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(n.numConstants=this.numConstants);let a=this.cell.getConfig();return this.getClassName()===wz.className&&(n.cell={className:this.cell.getClassName(),config:a}),Object.assign(Object.assign(Object.assign({},a),t),n)}static fromConfig(t,n,a={}){let r=n.cell,s=Eo(r,a);return new t(Object.assign(n,{cell:s}))}};Ql.className="RNN";De.registerClass(Ql);var Yb=class extends rn{},A2=class extends Yb{constructor(e){super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Rr(this.units,"units"),this.activation=rc(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=ga(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=ga(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=ga(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=xa(e.kernelRegularizer),this.recurrentRegularizer=xa(e.recurrentRegularizer),this.biasRegularizer=xa(e.biasRegularizer),this.kernelConstraint=Sr(e.kernelConstraint),this.recurrentConstraint=Sr(e.recurrentConstraint),this.biasConstraint=Sr(e.biasConstraint),this.dropout=Jf([1,nc([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Jf([1,nc([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=En(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}call(e,t){return ue(()=>{if(e=e,e.length!==2)throw new ce(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let a=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=sc({ones:()=>oi(e),rate:this.dropout,training:a,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=sc({ones:()=>oi(n),rate:this.recurrentDropout,training:a,dropoutFunc:this.dropoutFunc}));let r,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?r=al(ie(e,s),this.kernel.read()):r=al(e,this.kernel.read()),this.bias!=null&&(r=Mo(r,this.bias.read())),i!=null&&(n=ie(n,i));let o=ke(r,al(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:ac(this.activation),useBias:this.useBias,kernelInitializer:Sa(this.kernelInitializer),recurrentInitializer:Sa(this.recurrentInitializer),biasInitializer:Sa(this.biasInitializer),kernelRegularizer:ra(this.kernelRegularizer),recurrentRegularizer:ra(this.recurrentRegularizer),biasRegularizer:ra(this.biasRegularizer),activityRegularizer:ra(this.activityRegularizer),kernelConstraint:wr(this.kernelConstraint),recurrentConstraint:wr(this.recurrentConstraint),biasConstraint:wr(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign(Object.assign({},e),t)}};A2.className="SimpleRNNCell";De.registerClass(A2);var n_=class extends Ql{constructor(e){e.cell=new A2(e),super(e)}call(e,t){return ue(()=>{this.cell.dropoutMask!=null&&(Kt(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Kt(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}static fromConfig(e,t){return new e(t)}};n_.className="SimpleRNN";De.registerClass(n_);var _2=class extends Yb{constructor(e){if(super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new ce("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Rr(this.units,"units"),this.activation=rc(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=rc(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=ga(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=ga(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=ga(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=xa(e.kernelRegularizer),this.recurrentRegularizer=xa(e.recurrentRegularizer),this.biasRegularizer=xa(e.biasRegularizer),this.kernelConstraint=Sr(e.kernelConstraint),this.recurrentConstraint=Sr(e.recurrentConstraint),this.biasConstraint=Sr(e.biasConstraint),this.dropout=Jf([1,nc([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Jf([1,nc([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=En(e);let t=e[e.length-1];this.kernel=this.addWeight("kernel",[t,this.units*3],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*3],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units*3],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return ue(()=>{if(e=e,e.length!==2)throw new ce(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,a=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=sc({ones:()=>oi(e),rate:this.dropout,training:n,count:3,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=sc({ones:()=>oi(a),rate:this.recurrentDropout,training:n,count:3,dropoutFunc:this.dropoutFunc}));let r=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=ie(e,r[0]));let d=al(e,this.kernel.read());this.useBias&&(d=Mo(d,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(a=ie(a,s[0]));let c=this.recurrentKernel.read(),[f,m]=Bs(c,[2*this.units,this.units],c.rank-1),x=al(a,f),[y,b,w]=Bs(d,3,d.rank-1),[S,k]=Bs(x,2,x.rank-1);i=this.recurrentActivation.apply(ke(y,S)),o=this.recurrentActivation.apply(ke(b,k));let C=al(ie(o,a),m);l=this.activation.apply(ke(w,C));let E=ke(ie(i,a),ie(ke(1,ua(i)),l));return[E,E]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:ac(this.activation),recurrentActivation:ac(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Sa(this.kernelInitializer),recurrentInitializer:Sa(this.recurrentInitializer),biasInitializer:Sa(this.biasInitializer),kernelRegularizer:ra(this.kernelRegularizer),recurrentRegularizer:ra(this.recurrentRegularizer),biasRegularizer:ra(this.biasRegularizer),activityRegularizer:ra(this.activityRegularizer),kernelConstraint:wr(this.kernelConstraint),recurrentConstraint:wr(this.recurrentConstraint),biasConstraint:wr(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign(Object.assign({},e),t)}};_2.className="GRUCell";De.registerClass(_2);var a_=class extends Ql{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new _2(e),super(e)}call(e,t){return ue(()=>{this.cell.dropoutMask!=null&&(Kt(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Kt(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};a_.className="GRU";De.registerClass(a_);var Jb=class extends Yb{constructor(e){super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Rr(this.units,"units"),this.activation=rc(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=rc(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=ga(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=ga(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=ga(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=xa(e.kernelRegularizer),this.recurrentRegularizer=xa(e.recurrentRegularizer),this.biasRegularizer=xa(e.biasRegularizer),this.kernelConstraint=Sr(e.kernelConstraint),this.recurrentConstraint=Sr(e.recurrentConstraint),this.biasConstraint=Sr(e.biasConstraint),this.dropout=Jf([1,nc([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Jf([1,nc([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=En(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let a;if(this.useBias){if(this.unitForgetBias){let r=this.biasInitializer,s=this.units;a=new(t=class extends ao{apply(i,o){let l=r.apply([s]),d=new m2().apply([s]),c=r.apply([s*2]);return s$(s$(l,d),c)}},t.className="CustomInit",t)}else a=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,a,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return ue(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new ce(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let a=e[1],r=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=sc({ones:()=>oi(e),rate:this.dropout,training:n,count:4,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=sc({ones:()=>oi(a),rate:this.recurrentDropout,training:n,count:4,dropoutFunc:this.dropoutFunc}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,d,c;0<this.dropout&&this.dropout<1&&(e=ie(e,s[0]));let f=al(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(a=ie(a,i[0])),f=ke(f,al(a,this.recurrentKernel.read())),this.useBias&&(f=Mo(f,this.bias.read()));let[m,x,y,b]=Bs(f,4,f.rank-1);o=this.recurrentActivation.apply(m),l=this.recurrentActivation.apply(x),d=ke(ie(l,r),ie(o,this.activation.apply(y))),c=this.recurrentActivation.apply(b);let w=ie(c,this.activation.apply(d));return[w,w,d]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:ac(this.activation),recurrentActivation:ac(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Sa(this.kernelInitializer),recurrentInitializer:Sa(this.recurrentInitializer),biasInitializer:Sa(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:ra(this.kernelRegularizer),recurrentRegularizer:ra(this.recurrentRegularizer),biasRegularizer:ra(this.biasRegularizer),activityRegularizer:ra(this.activityRegularizer),kernelConstraint:wr(this.kernelConstraint),recurrentConstraint:wr(this.recurrentConstraint),biasConstraint:wr(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign(Object.assign({},e),t)}};Jb.className="LSTMCell";De.registerClass(Jb);var r_=class extends Ql{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Jb(e),super(e)}call(e,t){return ue(()=>{this.cell.dropoutMask!=null&&(Kt(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Kt(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};r_.className="LSTM";De.registerClass(r_);var j2=class extends Yb{constructor(e){super(e),this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return ue(()=>{e=e;let n=e.slice(1),a=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?a.push(n.splice(0,i.stateSize.length)):a.push(n.splice(0,1));a.reverse();let r=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=a[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),r.push(s.slice(1))}n=[];for(let i of r.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){sE(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,a)=>{wd(`RNNCell_${a}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=a=>({className:a.getClassName(),config:a.getConfig()}),n={cells:this.cells.map(t)};return Object.assign(Object.assign({},e),n)}static fromConfig(e,t,n={}){let a=[];for(let r of t.cells)a.push(Eo(r,n));return new e({cells:a})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return iE(e)}setWeights(e){let t=[];for(let n of this.cells){let a=n.weights.length,r=e.splice(a);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],r[s]])}TA(t)}};j2.className="StackedRNNCells";De.registerClass(j2);function sc(e){let{ones:t,rate:n,training:a=!1,count:r=1,dropoutFunc:s}=e,i=()=>s!=null?s(t(),n):k6(t(),n),o=()=>qb(i,t,a);return!r||r<=1?xr(o().clone()):Array(r).fill(void 0).map(o).map(l=>xr(l.clone()))}var qge=function(e,t){var n={};for(var a in e)Object.prototype.hasOwnProperty.call(e,a)&&t.indexOf(a)<0&&(n[a]=e[a]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var r=0,a=Object.getOwnPropertySymbols(e);r<a.length;r++)t.indexOf(a[r])<0&&Object.prototype.propertyIsEnumerable.call(e,a[r])&&(n[a[r]]=e[a[r]]);return n},Sz=class extends Ql{constructor(e){if(e.unroll)throw new an("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new an("It is not possible at the moment to stack convolutional cells.");super(e),this.inputSpec=[new nr({ndim:5})]}call(e,t){return ue(()=>{if(this.cell.dropoutMask!=null&&(Kt(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Kt(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new ce("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return ue(()=>{let{stateSize:t}=this.cell,n=e.shape,a=this.computeSingleOutputShape(n),r=[a[0],...a.slice(2)],s=va(r);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){ue(()=>{if(!this.stateful)throw new Ru("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,a=this.computeSingleOutputShape(n),r=[a[0],...a.slice(2)];if(n[0]==null)throw new ce("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(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>va(r)):this.states_=[va(r)];else if(e==null)Kt(this.states_),this.keptStates!=null&&(Kt(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>va(r)):this.states_[0]=va(r);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new ce(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t?this.keptStates.push(this.states_.slice()):Kt(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=r;if(!R.arraysEqual(i.shape,o))throw new ce(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>xr(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:a,padding:r,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],d=e[o?4:3],c=Io(l,a[0],r,s[0],i[0]),f=Io(d,a[1],r,s[1],i[1]);return[...e.slice(0,2),...o?[n,c,f]:[c,f,n]]}};Sz.className="ConvRNN2D";var D2=class extends Jb{constructor(e){let{filters:t,kernelSize:n,strides:a,padding:r,dataFormat:s,dilationRate:i}=e;super(Object.assign(Object.assign({},e),{units:t})),this.filters=t,Rr(this.filters,"filters"),this.kernelSize=Bf(n,2,"kernelSize"),this.kernelSize.forEach(o=>Rr(o,"kernelSize")),this.strides=Bf(a||1,2,"strides"),this.strides.forEach(o=>Rr(o,"strides")),this.padding=r||"valid",$i(this.padding),this.dataFormat=s||"channelsLast",Va(this.dataFormat),this.dilationRate=Bf(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>Rr(o,"dilationRate"))}build(e){var t;e=En(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new ce(`The channel dimension of the input should be defined. Found ${e[n]}`);let a=e[n],r=4,s=this.kernelSize.concat([a,this.filters*r]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*r]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,d=this.filters;o=new(t=class extends ao{apply(c,f){let m=l.apply([d]),x=$s([d]),y=l.apply([d*2]);return vA([m,x,y])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*r],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return ue(()=>{if(e.length!==3)throw new ce(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,a=e[0],r=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=sc({ones:()=>oi(a),rate:this.dropout,training:n,count:i,dropoutFunc:this.dropoutFunc}));let o=this.dropoutMask,l=(H,B,Y)=>!B||!B[Y]?H:ie(B[Y],H),d=l(a,o,0),c=l(a,o,1),f=l(a,o,2),m=l(a,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=sc({ones:()=>oi(r),rate:this.recurrentDropout,training:n,count:i,dropoutFunc:this.dropoutFunc}));let x=this.recurrentDropoutMask,y=l(r,x,0),b=l(r,x,1),w=l(r,x,2),S=l(r,x,3),k=3,[C,E,T,_]=Bs(this.kernel.read(),i,k),[A,$,O,z]=this.useBias?Bs(this.bias.read(),i):[null,null,null,null];d=this.inputConv(d,C,A,this.padding),c=this.inputConv(c,E,$,this.padding),f=this.inputConv(f,T,O,this.padding),m=this.inputConv(m,_,z,this.padding);let[P,j,G,X]=Bs(this.recurrentKernel.read(),i,k);y=this.recurrentConv(y,P),b=this.recurrentConv(b,j),w=this.recurrentConv(w,G),S=this.recurrentConv(S,X);let J=this.recurrentActivation.apply(ke(d,y)),V=this.recurrentActivation.apply(ke(c,b)),Q=ke(ie(V,s),ie(J,this.activation.apply(ke(f,w)))),F=ie(this.recurrentActivation.apply(ke(m,S)),this.activation.apply(Q));return[F,F,Q]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=qge(e,["units"]),a={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign(Object.assign({},n),a)}inputConv(e,t,n,a){let r=ws(e,t,this.strides,a||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Mo(r,n,this.dataFormat):r}recurrentConv(e,t){return ws(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};D2.className="ConvLSTM2DCell";De.registerClass(D2);var s_=class extends Sz{constructor(e){let t=new D2(e);super(Object.assign(Object.assign({},e),{cell:t}))}static fromConfig(e,t){return new e(t)}};s_.className="ConvLSTM2D";De.registerClass(s_);var R2=class extends rn{constructor(e){super(e),this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(this.noiseShape==null)return this.noiseShape;let t=e.shape,n=[];for(let a=0;a<this.noiseShape.length;++a)n.push(this.noiseShape[a]==null?t[a]:this.noiseShape[a]);return n}call(e,t){return ue(()=>{this.invokeCallHook(e,t);let n=zt(e);if(0<this.rate&&this.rate<1){let a=t.training==null?!1:t.training,r=this.getNoiseShape(n);return qb(()=>k6(n,this.rate,r,this.seed),()=>n,a)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};R2.className="Dropout";De.registerClass(R2);var i_=class extends R2{constructor(e){super(e),this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};i_.className="SpatialDropout1D";De.registerClass(i_);var o_=class extends rn{constructor(e){if(super(e),this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.batchInputShape==null&&e.inputShape==null&&e.inputDim!=null){let t=null;e.batchSize!=null&&(t=e.batchSize),this.batchInputShape=[t,e.inputDim]}this.units=e.units,Rr(this.units,"units"),this.activation=rc(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=ga(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=ga(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Sr(e.kernelConstraint),this.biasConstraint=Sr(e.biasConstraint),this.kernelRegularizer=xa(e.kernelRegularizer),this.biasRegularizer=xa(e.biasRegularizer),this.activityRegularizer=xa(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=En(e);let t=e[e.length-1];this.kernel==null&&(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:{[-1]:t}}],this.built=!0}computeOutputShape(e){e=En(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return ue(()=>{this.invokeCallHook(e,t);let n=zt(e),a=g6(this.activation.getClassName()),r;return a!=null?r=al(n,this.kernel.read(),a,this.bias?this.bias.read():null):(r=al(n,this.kernel.read()),this.bias!=null&&(r=Mo(r,this.bias.read())),this.activation!=null&&(r=this.activation.apply(r))),r})}getConfig(){let e={units:this.units,activation:ac(this.activation),useBias:this.useBias,kernelInitializer:Sa(this.kernelInitializer),biasInitializer:Sa(this.biasInitializer),kernelRegularizer:ra(this.kernelRegularizer),biasRegularizer:ra(this.biasRegularizer),activityRegularizer:ra(this.activityRegularizer),kernelConstraint:wr(this.kernelConstraint),biasConstraint:wr(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};o_.className="Dense";De.registerClass(o_);var l_=class extends rn{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=En(e);for(let t of e.slice(1))if(t==null)throw new ce(`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],Hu(e,1)]}call(e,t){return ue(()=>{this.invokeCallHook(e,t);let n=zt(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let a=[0];for(let r=2;r<n.rank;++r)a.push(r);a.push(1),n=Qt(n,a)}return sme(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};l_.className="Flatten";De.registerClass(l_);var u_=class extends rn{constructor(e){super(e),this.supportsMasking=!0,this.activation=rc(e.activation)}call(e,t){return ue(()=>{this.invokeCallHook(e,t);let n=zt(e);return this.activation.apply(n)})}getConfig(){let e={activation:ac(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};u_.className="Activation";De.registerClass(u_);var c_=class extends rn{constructor(e){super(e),this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return ue(()=>(e=zt(e),ame(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};c_.className="RepeatVector";De.registerClass(c_);var d_=class extends rn{constructor(e){super(e),this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let n="Total size of new array must be unchanged.",a=t.slice(),r=1,s=null;for(let o=0;o<a.length;++o){let l=a[o];if(this.isUnknown(l))if(s===null)s=o;else throw new ce("Can only specifiy one unknown dimension.");else r*=l}let i=Hu(e);if(s!==null){if(r===0||i%r!==0)throw new ce(n);a[s]=i/r}else if(i!==r)throw new ce(n);return a}computeOutputShape(e){let t=!1;for(let n=0;n<e.length;++n)if(this.isUnknown(e[n])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))}call(e,t){return ue(()=>{this.invokeCallHook(e,t);let n=zt(e),a=n.shape,r=a.slice(0,1).concat(this.fixUnknownDimension(a.slice(1),this.targetShape));return le(n,r)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};d_.className="Reshape";De.registerClass(d_);var h_=class extends rn{constructor(e){if(super(e),e.dims==null)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(e.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${e.dims} instead.`);let t=To(1,e.dims.length+1);if(!R.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new nr({ndim:this.dims.length+1})]}computeOutputShape(e){e=En(e);let t=e.slice();return this.dims.forEach((n,a)=>{t[a+1]=e[n]}),t}call(e,t){return Qt(zt(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};h_.className="Permute";De.registerClass(h_);var p_=class extends rn{constructor(e){super(e??{}),this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=zt(e);return $y(Md(n,this.maskValue),-1)}call(e,t){return ue(()=>{this.invokeCallHook(e,t);let n=zt(e),a=$y(Md(n,this.maskValue),-1,!0);return ie(n,He(a,n.dtype))})}};p_.className="Masking";De.registerClass(p_);var f_=class extends rn{constructor(e){if(super(e),this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(Wn(e.inputLength))}this.inputDim=e.inputDim,Rr(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Rr(this.outputDim,"outputDim"),this.embeddingsInitializer=ga(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=xa(e.embeddingsRegularizer),this.activityRegularizer=xa(e.activityRegularizer),this.embeddingsConstraint=Sr(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return ue(()=>this.maskZero?(e=zt(e),Md(e,pn(e))):null)}computeOutputShape(e){if(e=En(e),this.inputLength==null)return[...e,this.outputDim];let t=Wn(this.inputLength);if(t.length!==e.length-1)throw new ce(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let a=0;a<t.length;++a){let r=t[a],s=e[a+1];if(r!=null&&s!=null&&r!==s)throw new ce(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);r==null&&(t[n]=s),n++}}return[e[0],...t,this.outputDim]}call(e,t){return ue(()=>{this.invokeCallHook(e,t);let n=zt(e);n.dtype!=="int32"&&(n=Wl(n,"int32"));let a=S6(this.embeddings.read(),le(n,[n.size]));return le(a,En(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Sa(this.embeddingsInitializer),embeddingsRegularizer:ra(this.embeddingsRegularizer),activityRegularizer:ra(this.activityRegularizer),embeddingsConstraint:wr(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};f_.className="Embedding";De.registerClass(f_);var gp=class extends rn{constructor(e){super(e||{}),this.supportsMasking=!0}mergeFunction(e){throw new an}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let a=0;a<t.length;++a){let r=e[e.length-t.length+a],s=t[a];if(r==null||s==null||r<0||s<0)n.push(null);else if(r===1)n.push(s);else if(s===1)n.push(r);else{if(r!==s)throw new ce("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(r)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[En(e)]),e=e,e.length<2)throw new ce(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let r of e)r!=null&&r[0]!==null&&t.push(r[0]);if(t=Vu(t),t.length>1)throw new ce(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=e[0]==null?null:e[0].slice(1);for(let r=1;r<e.length;++r){let s=e[r]==null?null:e[r].slice(1);n=this.computeElementwiseOpOutputShape(n,s)}let a=e.map(r=>r.length);e.indexOf(null)===-1&&Vu(a).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return ue(()=>{if(e=e,this.reshapeRequired){let n=[],a=e.map(r=>r.rank);if(a.indexOf(null)===-1){let r=nc(a);for(let s of e){let i=s.rank;for(let o=0;o<r-i;++o)s=Hb(s,1);n.push(s)}return this.mergeFunction(n)}else{let r=!1;for(let o of e){let l=o.rank;if(l==null){let d=o.shape,c=d[0],f=d.slice(1).concat([c]),m=le(o,[c].concat(Hu(d.slice(1))));m=Qt(m,[1,0]),m=le(m,f),n.push(m),r=!0}else if(l>1){let d=To(1,l).concat([0]);n.push(Qt(o,d)),r=!0}else n.push(o)}let s=this.mergeFunction(n),i=s.rank;if(r){if(i==null){let o=s.shape,l=o.length,d=o[l-1],c=[d].concat(o.slice(0,o.length-1));s=le(Qt(le(s,[-1,d]),[1,0]),c)}else if(i>1){let o=[i-1].concat(To(0,i-1));s=Qt(s,o)}}return s}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let a=1;a<e.length;++a){let r=e[a]==null?null:e[a].slice(1);t=this.computeElementwiseOpOutputShape(t,r)}let n=[];for(let a of e)a!=null&&a[0]!==null&&n.push(a[0]);return n=Vu(n),n.length===1?t=n.concat(t):t=[null].concat(t),t}computeMask(e,t){return ue(()=>{if(t==null)return null;if(!Array.isArray(t))throw new ce("`mask` should be an Array");if(!Array.isArray(e))throw new ce("`inputs` should be an Array");if(t.length!==e.length)throw new ce(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(a=>a==null))return null;t=t.map(a=>a==null?a:Dr(a,0));let n=t[0];for(let a=1;a<t.length-1;++a)n=to(n,t[a]);return n})}},m_=class extends gp{constructor(e){super(e)}mergeFunction(e){return ue(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ke(t,e[n]);return t})}};m_.className="Add";De.registerClass(m_);var g_=class extends gp{constructor(e){super(e)}mergeFunction(e){return ue(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ie(t,e[n]);return t})}};g_.className="Multiply";De.registerClass(g_);var x_=class extends gp{constructor(e){super(e)}mergeFunction(e){return ue(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ke(t,e[n]);return ie(1/e.length,t)})}};x_.className="Average";De.registerClass(x_);var y_=class extends gp{constructor(e){super(e)}mergeFunction(e){return ue(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=ul(t,e[n]);return t})}};y_.className="Maximum";De.registerClass(y_);var b_=class extends gp{constructor(e){super(e)}mergeFunction(e){return ue(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=ec(t,e[n]);return t})}};b_.className="Minimum";De.registerClass(b_);var v_=class extends gp{constructor(e){super(e),this.DEFAULT_AXIS=-1,e==null&&(e={}),this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){if(!(Array.isArray(e)&&Array.isArray(e[0]))||e.length===1)throw new ce("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;let t=!0;for(let a of e)if(a!=null){t=!1;break}if(t)return;let n=[];for(let a=0;a<e.length;++a){let r=e[a].slice();r.splice(this.axis,1);let s=!1;for(let i of n)if(R.arraysEqual(i,r)){s=!0;break}s||n.push(r)}if(n.length>1)throw new ce("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return ue(()=>vA(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new ce("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),a=this.axis<0?n.length+this.axis:this.axis;for(let r of t.slice(1)){if(n[a]==null||r[a]==null){n[a]=null;break}n[a]+=r[a]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new ce("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new ce("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new ce(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return ue(()=>{let n=!0;if(t.forEach(s=>{if(s!=null){n=!1;return}}),n)return null;let a=[];for(let s=0;s<e.length;++s)t[s]==null?a.push(He(oi(e[s]),"bool")):t[s].rank<e[s].rank?a.push(Dr(t[s],-1)):a.push(t[s]);let r=Qn(a,this.axis);return $w(r,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};v_.className="Concatenate";De.registerClass(v_);function $x(e,t){for(;e<0;)e+=t;return e}function Kge(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new an("batchDot is not implemented for tensors of 4D or higher rank yet");if(R.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),R.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof n=="number"&&(n=[n,n]),e.dtype==="complex64"||t.dtype==="complex64")throw new an("batchDot is not implemented for complex64-type Tensors yet.");let a=e.shape.length,r=t.shape.length;n==null&&(n=[a-1,r-2]);let s=n;return ue(()=>{let i;if(a>r){i=a-r;let l=[];for(let d=0;d<i;++d)l.push(1);t=le(t,t.shape.concat(l))}else if(r>a){i=r-a;let l=[];for(let d=0;d<i;++d)l.push(1);e=le(e,e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=yt(ie(e,t),s[0]):o=yt(ie(Qt(e,[1,0]),t),s[1]);else{let l=s[0]!==e.shape.length-1,d=s[1]===t.shape.length-1;o=Jt(e,t,l,d)}if(i>0){let l;a>r?l=a+r-3:l=a-1;let d=[];for(let c=l;c<l+i;++c)d.push(c);o=vc(o,d)}return o.shape.length===1&&(o=Dr(o,1)),o})}var w_=class extends gp{constructor(e){super(e),this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){R.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new an("Dot layer does not support tensors of 4D or higher rank yet.");let a=this.interpretAxes(t,n);if(t[a[0]]!==n[a[1]])throw new ce(`Dimension incompatibility: ${t[a[0]]} !== ${n[a[1]]}`)}mergeFunction(e){if(e.length!==2)throw new ce(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],n=e[1],a;return Array.isArray(this.axes)?a=this.axes.map((r,s)=>$x(r,e[s].shape.length)):a=[$x(this.axes,t.shape.length),$x(this.axes,n.shape.length)],this.normalize&&(t=$v(t,a[0]),n=$v(n,a[1])),Kge(t,n,a)}interpretAxes(e,t){let n;return Array.isArray(this.axes)?n=this.axes:n=[$x(this.axes,e.length),$x(this.axes,t.length)],n}computeOutputShape(e){R.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new an("Dot layer does not support tensors of 4D or higher rank yet.");let a=this.interpretAxes(t,n);t.splice(a[0],1),n.splice(a[1],1),n.splice(0,1);let r=t.concat(n);return r.length===1&&r.push(1),r}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};w_.className="Dot";De.registerClass(w_);var S_=class extends rn{constructor(e){super(e),this.supportsMasking=!0,this.stddev=e.stddev}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={stddev:this.stddev};return Object.assign(t,e),t}call(e,t){return ue(()=>{this.invokeCallHook(e,t);let n=zt(e);return qb(()=>ke(f2(n.shape,0,this.stddev),n),()=>n,t.training||!1)})}};S_.className="GaussianNoise";De.registerClass(S_);var k_=class extends rn{constructor(e){super(e),this.supportsMasking=!0,this.rate=e.rate}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return ue(()=>{this.invokeCallHook(e,t);let n=zt(e);return this.rate>0&&this.rate<1?qb(()=>{let a=Math.sqrt(this.rate/(1-this.rate));return ie(n,f2(n.shape,1,a))},()=>n,t.training||!1):n})}};k_.className="GaussianDropout";De.registerClass(k_);var N_=class extends rn{constructor(e){super(e),this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||zt(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return ue(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return qb(()=>{let a=zt(e),r=-1.6732632423543772*1.0507009873554805,s=Xl(yc(n),this.rate);s=Wl(s,"float32");let i=((1-this.rate)*(1+this.rate*r**2))**-.5,o=-i*r*this.rate,l=ke(ie(a,s),ie(ke(s,-1),r));return ke(ie(l,i),o)},()=>zt(e),t.training||!1)}return e})}};N_.className="AlphaDropout";De.registerClass(N_);function zy(e,t,n,a,r,s=.001){let i;if(e.rank===2)i=hT(e,t,n,a,r,s);else if(e.rank===3)i=pT(e,t,n,a,r,s);else if(e.rank===4)i=fT(e,t,n,a,r,s);else throw new an(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return i}function Xge(e,t,n,a,r=.001){return ue(()=>{let s=Fb(e,a),i=s.mean,o=s.variance;return[zy(e,i,o,n,t,r),i,o]})}function Yge(e,t,n,a,r=.001){return ue(()=>{let s=Fb(e,a),i=s.mean,o=s.variance,l=[];for(let x of To(0,e.rank))a.indexOf(x)!==-1?l.push(1):l.push(e.shape[x]);let d=le(i,l),c=le(o,l),f=t==null?null:le(t,l),m=n==null?null:le(n,l);return[zy(e,d,c,m,f,r),i,o]})}function Jge(e,t,n,a,r=.001){return R.arraysEqual(a.slice().sort(),To(0,e.rank-1))?Xge(e,t,n,a,r):Yge(e,t,n,a,r)}var C_=class extends rn{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=ga(e.betaInitializer||"zeros"),this.gammaInitializer=ga(e.gammaInitializer||"ones"),this.movingMeanInitializer=ga(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=ga(e.movingVarianceInitializer||"ones"),this.betaConstraint=Sr(e.betaConstraint),this.gammaConstraint=Sr(e.gammaConstraint),this.betaRegularizer=xa(e.betaRegularizer),this.gammaRegularizer=xa(e.gammaRegularizer)}build(e){e=En(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new ce(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new nr({ndim:e.length,axes:{[t]:n}})];let a=[n];this.scale&&(this.gamma=this.addWeight("gamma",a,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",a,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",a,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",a,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return ue(()=>{let n=t.training==null?!1:t.training,a=zt(e),r=a.shape,s=r.length,i=To(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=Bd(1,s);l[o]=r[o];let d=i.slice();d.sort();let c=!R.arraysEqual(d,To(0,s).slice(0,s-1)),f=()=>{if(c){let w=le(this.movingMean.read(),l),S=le(this.movingVariance.read(),l),k=this.center?le(this.beta.read(),l):null,C=this.scale?le(this.gamma.read(),l):null;return zy(a,w,S,k,C,this.epsilon)}else return zy(a,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return f();let[m,x,y]=Jge(a,this.gamma.read(),this.beta.read(),i,this.epsilon),b=(w,S,k)=>{ue(()=>{let C=1-k,E=w.read(),T=ie(st(E,S),C);w.write(st(E,T))})};return b(this.movingMean,x,this.momentum),b(this.movingVariance,y,this.momentum),m})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Sa(this.betaInitializer),gammaInitializer:Sa(this.gammaInitializer),movingMeanInitializer:Sa(this.movingMeanInitializer),movingVarianceInitializer:Sa(this.movingVarianceInitializer),betaRegularizer:ra(this.betaRegularizer),gammaRegularizer:ra(this.gammaRegularizer),betaConstraint:wr(this.betaConstraint),gammaConstraint:wr(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};C_.className="BatchNormalization";De.registerClass(C_);var E_=class extends rn{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=ga(e.betaInitializer||"zeros"),this.gammaInitializer=ga(e.gammaInitializer||"ones"),this.betaRegularizer=xa(e.betaRegularizer),this.gammaRegularizer=xa(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=En(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let r=0;r<this.axis.length;++r)this.axis[r]<0&&(this.axis[r]+=t);for(let r of this.axis)if(r<0||r>=t)throw new Error(`Invalid axis: ${r}`);if(this.axis.length!==Vu(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(r=>e[r]),a=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,a):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,a):this.beta=null,this.built=!0}call(e,t){let n=zt(e),a=n.shape,r=a.length;return ue(()=>{let{mean:s,variance:i}=Fb(n,this.axis,!0),o=Bd(1,r);for(let x of this.axis)o[x]=a[x];let l=x=>x!=null&&x.shape.length!==r?le(x,o):x,d=this.scale?l(this.gamma.read()):null,c=this.center?l(this.beta.read()):null,f=[],m=[];for(let x=0;x<r;++x)this.axis.indexOf(x)!==-1?(f.push(a[x]),m.push(1)):(f.push(1),m.push(a[x]));return s=ai(s,f),i=ai(i,f),d!=null&&(d=ai(d,m)),c!=null&&(c=ai(c,m)),zy(n,s,i,c,d,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Sa(this.betaInitializer),gammaInitializer:Sa(this.gammaInitializer),betaRegularizer:ra(this.betaRegularizer),gammaRegularizer:ra(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};E_.className="LayerNormalization";De.registerClass(E_);function Qge(e,t,n){return ue(()=>{if(e.rank!==4)throw new ce(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new ce("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=Ao()),n!=="channelsLast"&&n!=="channelsFirst")throw new ce(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let a;return n==="channelsFirst"?a=[[0,0],[0,0],t[0],t[1]]:a=[[0,0],t[0],t[1],[0,0]],Ro(e,a)})}var I_=class extends rn{constructor(e){if(e==null&&(e={}),super(e),this.dataFormat=e.dataFormat==null?Ao():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new ce(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${e.padding.length} array.`);let t,n;if(typeof e.padding[0]=="number")t=[e.padding[0],e.padding[0]],n=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,e.padding[0].length!==2)throw new ce(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new ce(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new nr({ndim:4})]}computeOutputShape(e){e=En(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return ue(()=>Qge(zt(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};I_.className="ZeroPadding2D";De.registerClass(I_);function M2(e,t,n,a,r,s){return ue(()=>{Va(r),y6(s),$i(a),n==null&&(n=[1,1]),a==null&&(a="valid"),r==null&&(r=Ao()),s==null&&(s="max"),e=KA(e,r);let i,o=a==="same"?"same":"valid";return s==="max"?i=Ar(e,t,n,o):i=Kl(e,t,n,o),r==="channelsFirst"&&(i=Qt(i,[0,3,1,2])),i})}function kz(e,t,n,a,r,s){return ue(()=>{Va(r),y6(s),$i(a),n==null&&(n=[1,1,1]),a==null&&(a="valid"),r==null&&(r=Ao()),s==null&&(s="max"),e=dz(e,r);let i,o=a==="same"?"same":"valid";return s==="max"?i=OT(e,t,n,o):i=dT(e,t,n,o),r==="channelsFirst"&&(i=Qt(i,[0,4,1,2,3])),i})}var Nz=class extends rn{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new ce(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Rr(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new ce(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Rr(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,$i(this.padding),this.inputSpec=[new nr({ndim:3})]}computeOutputShape(e){e=En(e);let t=Io(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return ue(()=>{this.invokeCallHook(e,t),e=Hb(zt(e),2);let n=this.poolingFunction(zt(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return vc(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},T_=class extends Nz{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Va(r),$i(a),M2(e,t,n,a,r,"max")}};T_.className="MaxPooling1D";De.registerClass(T_);var A_=class extends Nz{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Va(r),$i(a),M2(e,t,n,a,r,"avg")}};A_.className="AveragePooling1D";De.registerClass(A_);var Cz=class extends rn{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new ce(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];Rr(this.poolSize,"poolSize"),Rr(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Va(this.dataFormat),$i(this.padding),this.inputSpec=[new nr({ndim:4})]}computeOutputShape(e){e=En(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Io(t,this.poolSize[0],this.padding,this.strides[0]),n=Io(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return ue(()=>(this.invokeCallHook(e,t),this.poolingFunction(zt(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},__=class extends Cz{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Va(r),$i(a),M2(e,t,n,a,r,"max")}};__.className="MaxPooling2D";De.registerClass(__);var j_=class extends Cz{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Va(r),$i(a),M2(e,t,n,a,r,"avg")}};j_.className="AveragePooling2D";De.registerClass(j_);var Ez=class extends rn{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new ce(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Rr(this.poolSize,"poolSize"),Rr(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Va(this.dataFormat),$i(this.padding),this.inputSpec=[new nr({ndim:5})]}computeOutputShape(e){e=En(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],a=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Io(t,this.poolSize[0],this.padding,this.strides[0]),n=Io(n,this.poolSize[1],this.padding,this.strides[1]),a=Io(a,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,a]:[e[0],t,n,a,e[4]]}call(e,t){return ue(()=>(this.invokeCallHook(e,t),this.poolingFunction(zt(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},D_=class extends Ez{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Va(r),$i(a),kz(e,t,n,a,r,"max")}};D_.className="MaxPooling3D";De.registerClass(D_);var R_=class extends Ez{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Va(r),$i(a),kz(e,t,n,a,r,"avg")}};R_.className="AveragePooling3D";De.registerClass(R_);var Iz=class extends rn{constructor(e){super(e),this.inputSpec=[new nr({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new an}},M_=class extends Iz{constructor(e){super(e||{})}call(e,t){return ue(()=>{let n=zt(e);return ba(n,1)})}};M_.className="GlobalAveragePooling1D";De.registerClass(M_);var $_=class extends Iz{constructor(e){super(e||{})}call(e,t){return ue(()=>{let n=zt(e);return ji(n,1)})}};$_.className="GlobalMaxPooling1D";De.registerClass($_);var Tz=class extends rn{constructor(e){super(e),this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Va(this.dataFormat),this.inputSpec=[new nr({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new an}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},B_=class extends Tz{call(e,t){return ue(()=>{let n=zt(e);return this.dataFormat==="channelsLast"?ba(n,[1,2]):ba(n,[2,3])})}};B_.className="GlobalAveragePooling2D";De.registerClass(B_);var F_=class extends Tz{call(e,t){return ue(()=>{let n=zt(e);return this.dataFormat==="channelsLast"?ji(n,[1,2]):ji(n,[2,3])})}};F_.className="GlobalMaxPooling2D";De.registerClass(F_);var Az=class extends rn{constructor(e){super(e),this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let a=t.layer,r=Eo(a,n);delete t.layer;let s={layer:r};return Object.assign(s,t),new e(s)}},O_=class extends Az{constructor(e){super(e),this.supportsMasking=!0}build(e){if(e=En(e),e.length<3)throw new ce(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=En(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),a=e[1];return[n[0],a].concat(n.slice(1))}call(e,t){return ue(()=>(e=zt(e),vz((n,a)=>[zt(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};O_.className="TimeDistributed";De.registerClass(O_);function Zge(e){fp(Qfe,"BidirectionalMergeMode",e)}var exe="concat",L_=class extends Az{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Eo(n),t.goBackwards=t.goBackwards!==!0;let a={};if(a.className=e.layer.getClassName(),a.config=t,this.backwardLayer=Eo(a),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?exe:e.mergeMode,Zge(this.mergeMode),e.weights)throw new an("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,a,r;return this.returnState&&(r=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,a=[n]):this.mergeMode==null?a=[n,n.slice()]:a=[n],this.returnState?this.mergeMode==null?a.concat(r).concat(r.slice()):[n].concat(r).concat(r.slice()):Ds(a)}apply(e,t){let n=t==null?null:t.initialState,a=t==null?null:t.constants;t==null&&(t={});let r=bz(e,n,a,this.numConstants);if(e=r.inputs,n=r.initialState,a=r.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&a==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new ce("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let d=n.map(c=>new nr({shape:c.shape}));this.forwardLayer.stateSpec=d.slice(0,l/2),this.backwardLayer.stateSpec=d.slice(l/2),i.push(...d)}if(a!=null)throw new an("Support for constants in Bidirectional layers is not implemented yet.");let o=s[0]instanceof _o;for(let l of s)if(l instanceof _o!==o)throw new ce("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(o){let l=[e].concat(s),d=this.inputSpec.concat(i),c=this.inputSpec;this.inputSpec=d;let f=super.apply(l,t);return this.inputSpec=c,f}else return super.apply(e,t)}call(e,t){return ue(()=>{let n=t.initialState,a,r;if(n==null)a=this.forwardLayer.call(e,t),r=this.backwardLayer.call(e,t);else{let o=n.slice(0,n.length/2),l=n.slice(n.length/2);a=this.forwardLayer.call(e,Object.assign(t,{initialState:o})),r=this.backwardLayer.call(e,Object.assign(t,{initialState:l}))}let s;this.returnState&&(Array.isArray(a)&&(s=a.slice(1).concat(r.slice(1))),a=a[0],r=r[0]),this.returnSequences&&(r=Mi(r,1));let i;return this.mergeMode==="concat"?i=vA([a,r]):this.mergeMode==="sum"?i=ke(a,r):this.mergeMode==="ave"?i=ie(.5,ke(a,r)):this.mergeMode==="mul"?i=ie(a,r):this.mergeMode==null&&(i=[a,r]),this.returnState?this.mergeMode==null?i.concat(s):[i].concat(s):i})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){wd(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),wd(this.backwardLayer.name,()=>{this.backwardLayer.build(e)}),this.built=!0}computeMask(e,t){Array.isArray(t)&&(t=t[0]);let n;if(this.returnSequences?this.mergeMode==null?n=[t,t]:n=t:this.mergeMode==null?n=[null,null]:n=null,this.returnState){let a=this.forwardLayer.states.map(r=>null);return Array.isArray(n)?n.concat(a).concat(a):[n].concat(a).concat(a)}else return n}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return this.forwardLayer.nonTrainableWeights.concat(this.backwardLayer.nonTrainableWeights)}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.forwardLayer!=null&&this.forwardLayer.setFastWeightInitDuringBuild(e),this.backwardLayer!=null&&this.backwardLayer.setFastWeightInitDuringBuild(e)}getConfig(){let e={mergeMode:this.mergeMode},t=super.getConfig();return Object.assign(e,t),e}static fromConfig(e,t){let n=Eo(t.layer);if(delete t.layer,t.numConstants!=null)throw new an("Deserialization of a Bidirectional layer with numConstants present is not supported yet.");let a=t;return a.layer=n,new e(a)}};L_.className="Bidirectional";De.registerClass(L_);var P_=class extends rn{constructor(e){super(e),this.scale=e.scale,e.offset?this.offset=e.offset:this.offset=0}getConfig(){let e={scale:this.scale,offset:this.offset},t=super.getConfig();return Object.assign(e,t),e}call(e,t){return ue(()=>(e=zt(e),e.dtype!=="float32"&&(e=Wl(e,"float32")),ke(ie(e,this.scale),this.offset)))}};P_.className="Rescaling";De.registerClass(P_);var{resizeBilinear:txe,cropAndResize:nxe}=Ii,z_=class extends rn{constructor(e){super(e),this.height=e.height,this.width=e.width}centerCrop(e,t,n,a,r,s,i,o){return ue(()=>{let l,d=!1,c=t/s,f=n/i,m=(a+t)/s,x=(r+n)/i,y=[c,f,m,x],b=[];e.rank===3?(d=!0,l=rr([e])):l=e;for(let C=0;C<l.shape[0];C++)b.push(y);let w=bs(b,[b.length,4]),S=$d(0,b.length,1,"int32"),k=nxe(l,w,S,[a,r],"nearest");return Wl(d?zt($a(k)):k,o)})}upsize(e,t,n,a){return ue(()=>{let r=txe(e,[t,n]);return Wl(r,a)})}call(e,t){return ue(()=>{let n=zt(e),a=n.dtype,r=n.shape,s=r[r.length-3],i=r[r.length-2],o=0;s!==this.height&&(o=Math.floor((s-this.height)/2));let l=0;return i!==this.width&&(l=Math.floor((i-this.width)/2),l===0&&(l=1)),o>=0&&l>=0?this.centerCrop(n,o,l,this.height,this.width,s,i,a):this.upsize(e,this.height,this.width,a)})}getConfig(){let e={height:this.height,width:this.width},t=super.getConfig();return Object.assign(e,t),e}computeOutputShape(e){e=En(e);let t=e.length-3,n=e.length-2;return e[t]=this.height,e[n]=this.width,e}};z_.className="CenterCrop";De.registerClass(z_);function axe(e,t,n,a){let r=zt(e);if(r.dtype!=="int32"&&(r=Wl(r,"int32")),t==="int")return r;let s=r.shape;if(r.rank===0&&(r=Dr(r,-1)),t==="oneHot"&&r.shape[r.shape.length-1]!==1&&(r=Dr(r,-1)),r.rank>2)throw new ce(`When outputMode is not int, maximum output rank is 2 Received outputMode ${t} and input shape ${s} which would result in output rank ${r.rank}.`);let i=["multiHot","oneHot"].includes(t),o=r,l;if(typeof a<"u"&&t==="count"?l=Av(o,a,n,i):l=Av(o,[],n,i),t!=="tfIdf")return l;if(a)return ie(l,a);throw new ce("When outputMode is 'tfIdf', weights must be provided.")}var U_=class extends rn{constructor(e){super(e),this.numTokens=e.numTokens,e.outputMode?this.outputMode=e.outputMode:this.outputMode="multiHot"}getConfig(){let e={numTokens:this.numTokens,outputMode:this.outputMode},t=super.getConfig();return Object.assign(e,t),e}computeOutputShape(e){return e=En(e),e==null?[this.numTokens]:this.outputMode==="oneHot"&&e[e.length-1]!==1?(e.push(this.numTokens),e):(e[e.length-1]=this.numTokens,e)}call(e,t){return ue(()=>{e=zt(e),e.dtype!=="int32"&&(e=Wl(e,"int32"));let n;if(typeof t.countWeights<"u"){if(this.outputMode!=="count")throw new ce(`countWeights is not used when outputMode !== count.
93              Received countWeights=${t.countWeights}`);n=zt(t.countWeights)}let a=ji(e),r=Vf(e),s=Es(this.numTokens,a).bufferSync().get(0),i=Xl(r,0).bufferSync().get(0);if(!(s&&i))throw new ce(`Input values must be between 0 < values <= numTokens with numTokens=${this.numTokens}`);return axe(e,this.outputMode,this.numTokens,n)})}};U_.className="CategoryEncoding";De.registerClass(U_);var rxe=["bilinear","nearest"],S$=new Set(rxe),W_=class extends rn{constructor(e){if(super(e),this.height=e.height,this.width=e.width,e.interpolation)if(S$.has(e.interpolation))this.interpolation=e.interpolation;else throw new ce(`Invalid interpolation parameter: ${e.interpolation} is not implemented`);else this.interpolation="bilinear";this.cropToAspectRatio=!!e.cropToAspectRatio}computeOutputShape(e){e=En(e);let t=e[2];return[this.height,this.width,t]}getConfig(){let e={height:this.height,width:this.width,interpolation:this.interpolation,cropToAspectRatio:this.cropToAspectRatio},t=super.getConfig();return Object.assign(e,t),e}call(e,t){return ue(()=>{let n=[this.height,this.width];if(this.interpolation==="bilinear")return Ii.resizeBilinear(e,n,!this.cropToAspectRatio);if(this.interpolation==="nearest")return Ii.resizeNearestNeighbor(e,n,!this.cropToAspectRatio);throw new Error(`Interpolation is ${this.interpolation} but only ${[...S$]} are supported`)})}};W_.className="Resizing";De.registerClass(W_);var _z=class{constructor(e){this.seed=e}next(){if(this.seed!==void 0)return this.seed++}};_z.className="RandomSeed";var jz=class extends rn{constructor(e){super(e),this.randomGenerator=new _z(e.seed)}getConfig(){let e={seed:this.randomGenerator.seed},t=super.getConfig();return Object.assign(e,t),e}};jz.className="BaseRandomLayer";var sxe=["bilinear","nearest"],k$=new Set(sxe),V_=class extends jz{constructor(e){super(e);let{factor:t,interpolation:n="bilinear"}=e;if(this.factor=t,Array.isArray(this.factor)&&this.factor.length===2)this.widthLower=this.factor[0],this.widthUpper=this.factor[1];else if(!Array.isArray(this.factor)&&this.factor>0)this.widthLower=-this.factor,this.widthUpper=this.factor;else throw new ce(`Invalid factor: ${this.factor}. Must be positive number or tuple of 2 numbers`);if(this.widthLower<-1||this.widthUpper<-1)throw new ce(`factor must have values larger than -1. Got: ${this.factor}`);if(this.widthUpper<this.widthLower)throw new ce(`factor cannot have upper bound less than lower bound.
94        Got upper bound: ${this.widthUpper}.
95        Got lower bound: ${this.widthLower}
96      `);if(n)if(k$.has(n))this.interpolation=n;else throw new ce(`Invalid interpolation parameter: ${n} is not implemented`)}getConfig(){let e={factor:this.factor,interpolation:this.interpolation},t=super.getConfig();return Object.assign(e,t),e}computeOutputShape(e){e=En(e);let t=e[2];return[this.imgHeight,-1,t]}call(e,t){return ue(()=>{let n=zt(e);this.imgHeight=n.shape[n.shape.length-3];let a=n.shape[n.shape.length-2];this.widthFactor=yc([1],1+this.widthLower,1+this.widthUpper,"float32",this.randomGenerator.next());let r=this.widthFactor.dataSync()[0]*a;r=Math.round(r);let s=[this.imgHeight,r];switch(this.interpolation){case"bilinear":return Ii.resizeBilinear(e,s);case"nearest":return Ii.resizeNearestNeighbor(e,s);default:throw new Error(`Interpolation is ${this.interpolation}
97          but only ${[...k$]} are supported`)}})}};V_.className="RandomWidth";De.registerClass(V_);function ixe(e){return new Sg(e)}function oxe(e){return new HA(e)}function lxe(e){return new UA(e)}function uxe(e){return new WA(e)}function cxe(e){return new VA(e)}function dxe(e){return new qA(e)}function hxe(e){return new GA(e)}function pxe(e){return new QA(e)}function fxe(e){return new I2(e)}function mxe(e){return new XA(e)}function gxe(e){return new T2(e)}function xxe(e){return new YA(e)}function yxe(e){return new JA(e)}function bxe(e){return new ZA(e)}function vxe(e){return new e_(e)}function wxe(e){return new t_(e)}function Sxe(e){return new u_(e)}function kxe(e){return new o_(e)}function Nxe(e){return new R2(e)}function Cxe(e){return new i_(e)}function Exe(e){return new l_(e)}function Ixe(e){return new c_(e)}function Txe(e){return new d_(e)}function Axe(e){return new h_(e)}function _xe(e){return new f_(e)}function jxe(e){return new m_(e)}function Dxe(e){return new x_(e)}function Rxe(e){return new v_(e)}function Mxe(e){return new y_(e)}function $xe(e){return new b_(e)}function Bxe(e){return new g_(e)}function Fxe(e){return new w_(e)}function Oxe(e){return new C_(e)}function Lxe(e){return new E_(e)}function Pxe(e){return new I_(e)}function H_(e){return new A_(e)}function zxe(e){return H_(e)}function Uxe(e){return H_(e)}function G_(e){return new j_(e)}function Wxe(e){return G_(e)}function Vxe(e){return G_(e)}function q_(e){return new R_(e)}function Hxe(e){return q_(e)}function Gxe(e){return q_(e)}function qxe(e){return new M_(e)}function Kxe(e){return new B_(e)}function Dz(e){return new $_(e)}function Rz(e){return new F_(e)}function Mz(e){return new T_(e)}function $z(e){return new __(e)}function Xxe(e){return new D_(e)}function Yxe(e){return new a_(e)}function Jxe(e){return new _2(e)}function Qxe(e){return new r_(e)}function Zxe(e){return new Jb(e)}function eye(e){return new n_(e)}function tye(e){return new A2(e)}function nye(e){return new s_(e)}function aye(e){return new D2(e)}function rye(e){return new Ql(e)}function sye(e){return new j2(e)}function iye(e){return new L_(e)}function oye(e){return new O_(e)}var lye=Dz,uye=Rz,cye=Mz,dye=$z;function hye(e){return new S_(e)}function pye(e){return new k_(e)}function fye(e){return new N_(e)}function mye(e){return new p_(e)}function gye(e){return new P_(e)}function xye(e){return new z_(e)}function yye(e){return new W_(e)}function bye(e){return new U_(e)}function vye(e){return new V_(e)}var Bz={};Xt(Bz,{MAPE:()=>jye,MSE:()=>Mye,binaryAccuracy:()=>wye,binaryCrossentropy:()=>Sye,categoricalAccuracy:()=>Nye,categoricalCrossentropy:()=>Cye,cosineProximity:()=>Tye,mape:()=>Dye,meanAbsoluteError:()=>Aye,meanAbsolutePercentageError:()=>_ye,meanSquaredError:()=>Rye,mse:()=>$ye,precision:()=>Eye,r2Score:()=>Bye,recall:()=>Iye,sparseCategoricalAccuracy:()=>kye});function wye(e,t){return BA(e,t)}function Sye(e,t){return L6(e,t)}function kye(e,t){return P6(e,t)}function Nye(e,t){return FA(e,t)}function Cye(e,t){return OA(e,t)}function Eye(e,t){return O6(e,t)}function Iye(e,t){return rge(e,t)}function Tye(e,t){return $A(e,t)}function Aye(e,t){return k2(e,t)}function _ye(e,t){return kg(e,t)}function jye(e,t){return kg(e,t)}function Dye(e,t){return kg(e,t)}function Rye(e,t){return mp(e,t)}function Mye(e,t){return mp(e,t)}function $ye(e,t){return mp(e,t)}function Bye(e,t){return sge(e,t)}var Fz={};Xt(Fz,{modelFromJSON:()=>$ge});var Oz={};Xt(Oz,{l1:()=>Oye,l1l2:()=>Fye,l2:()=>Lye});function Fye(e){return new Xb(e)}function Oye(e){return Uge(e)}function Lye(e){return Wge(e)}var Lz=class extends Qf{constructor(){super(...arguments),this.model=null}setModel(e){if(!(e instanceof Ol))throw new Error("model must be a LayersModel, not some other Container");this.model=e}};function $1(e,t){return e<t}function N$(e,t){return e>t}var Pz=class extends Lz{constructor(e){if(super(),e==null&&(e={}),e.restoreBestWeights)throw new an("restoreBestWeights = True is not implemented in EarlyStopping yet.");this.monitor=e.monitor||"val_loss",this.minDelta=Math.abs(e.minDelta||0),this.patience=e.patience||0,this.verbose=e.verbose||0,this.mode=e.mode||"auto",this.baseline=e.baseline,["auto","min","max"].indexOf(this.mode)===-1&&(console.warn(`EarlyStopping mode '${this.mode}

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Br{constructor(e,t=Pu.FAIL){super(),this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,n=0;function a(s){return s instanceof Br?{value:s.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let r=await p7(this.iterators,a);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case Pu.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case Pu.SHORTEST:return{value:null,done:!0};case Pu.LONGEST:}return this.count++,{value:r,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},b7=class extends Br{constructor(e,t){super(),this.upstream=e,this.bufferSize=t,this.buffer=new f7(t)}summary(){return`${this.upstream.summary()} -> Prefetch`}refill(){for(;!this.buffer.isFull();){let e=this.upstream.next();this.buffer.push(e)}}next(){return this.refill(),this.buffer.shift()}},w0e=class extends b7{constructor(e,t,n){super(e,t),this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=t0e.alea(n||R.now().toString()),this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}randomInt(e){return Math.floor(this.random()*e)}chooseIndex(){return this.randomInt(this.buffer.length())}async serialNext(){for(this.upstreamExhausted||this.refill();!this.buffer.isEmpty();){let e=this.chooseIndex(),t=await this.buffer.shuffleExcise(e);if(t.done)this.upstreamExhausted=!0;else return this.refill(),t}return{value:null,done:!0}}},Ng=class{constructor(){this.size=null}batch(e,t=!0){let n=this;R.assert(e>0,()=>`batchSize needs to be positive, but it is
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At least one type of data should be returned.")}summary(){return"microphone"}static async create(t={}){if(!fe().get("IS_BROWSER"))throw new Error("microphone API is only supported in browser environment.");let n=new S7(t);return await n.start(),n}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(a){throw new Error(`Error thrown while initializing video stream: ${a.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let t=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new t,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let n=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,n.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let t,n,a=await this.getAudioData();if(this.includeSpectrogram){let r=this.flattenQueue(a.freqDataQueue);t=this.getTensorFromAudioDataArray(r,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let r=this.flattenQueue(a.timeDataQueue);n=this.getTensorFromAudioDataArray(r,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:t,waveform:n},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let t=[],n=[],a=0;return new Promise(r=>{let s=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-1/0&&r({freqDataQueue:t,timeDataQueue:n}),t.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),n.push(this.timeData.slice())),++a===this.numFrames&&(clearInterval(s),r({freqDataQueue:t,timeDataQueue:n}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(t){let n=t[0].length,a=new Float32Array(t.length*n);return t.forEach((r,s)=>a.set(r,s*n)),a}getTensorFromAudioDataArray(t,n){let a=new Float32Array(R.sizeFromShape(n));return a.set(t,a.length-t.length),bs(a,n)}},I0e=class k7 extends Br{constructor(t,n){if(super(),this.webcamVideoElement=t,this.webcamConfig=n,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=Ln([0],"int32"),this.webcamConfig.centerCrop){let a=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,r=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,s=(1-a)/2,i=(1-r)/2,o=s+a,l=r+i;this.cropBox=nl([i,s,l,o],[1,4])}else this.cropBox=nl([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(t,n={}){if(!fe().get("IS_BROWSER"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!t){if(t=document.createElement("video"),!n.resizeWidth||!n.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");t.width=n.resizeWidth,t.height=n.resizeHeight}let a=new k7(t,n);return await a.start(),a}async start(){this.webcamConfig.facingMode&&R.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(t){throw t.message=`Error thrown while initializing video stream

104function F0e(e){return Qs(async()=>{let t=await e();return J_(()=>t.next())})}async function O0e(e,t){return I0e.create(e,t)}async function L0e(e){return E0e.create(e)}var P0e="4.22.0";function bt(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&R.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the CPU backend.`)})}var z0e=cl.whereImpl,Z_=class _7 extends tb{nextDataId(){return _7.nextDataId++}constructor(){super(),this.blockSize=48,this.firstUse=!0,this.data=new mw(this,Ji())}write(t,n,a){this.firstUse&&(this.firstUse=!1,fe().get("IS_NODE")&&W.warn(`
105============================
106Hi, looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, visit https://github.com/tensorflow/tfjs-node for more details. 
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w=1;w<c.length;++w)if(c[w]!==c[w-1])throw new Error("starts, limits, and deltas must have the same shape");let f=c.length===0?1:c[0],m=R.getArrayFromDType("int32",f+1);m[0]=0;for(let w=0;w<f;++w){let S=o?e[0]:e[w],k=l?a[0]:a[w],C=d?s[0]:s[w];if(C===0)throw new Error("Requires delta != 0");let E;if(C>0&&k<S||C<0&&k>S)E=0;else if(E=Math.ceil(Math.abs((k-S)/C)),E>L$)throw new Error(`Requires ((limit - start) / delta) <= ${L$}`);m[w+1]=m[w]+E}let x=m[f],y=R.getArrayFromDType(n,x),b=0;for(let w=0;w<f;++w){let S=m[w+1]-m[w],k=o?e[0]:e[w],C=d?s[0]:s[w];for(let E=0;E<S;++E)y[b++]=k,k+=C}return[m,y]}var Xi=W.RowPartitionType,F1e=class NE{constructor(t,n,a,r,s,i,o,l,d,c){this.shape=t,this.shapeShape=n,this.values=a,this.valuesShape=r,this.valuesDType=s,this.defaultValue=i,this.defaultValueShape=o,this.rowPartitionValues=l,this.rowPartitionValuesShapes=d,this.rowPartitionTypes=W.getRowPartitionTypesHelper(c),this.raggedRank=W.getRaggedRank(this.rowPartitionTypes)}getRowPartitionTypeByDimension(t){return this.rowPartitionTypes[0]===Xi.FIRST_DIM_SIZE?this.rowPartitionTypes[t+1]:this.rowPartitionTypes[t]}getRowPartitionTensor(t){return this.rowPartitionTypes[0]===Xi.FIRST_DIM_SIZE?this.rowPartitionValues[t+1]:this.rowPartitionValues[t]}getMaxWidth(t){let n=this.getRowPartitionTensor(t-1);switch(this.getRowPartitionTypeByDimension(t-1)){case Xi.VALUE_ROWIDS:return NE.getMaxWidthValueRowID(n);case Xi.ROW_SPLITS:return NE.getMaxWidthRowSplit(n);default:throw new Error(`Cannot handle partition type ${Xi[this.getRowPartitionTypeByDimension(t-1)]}`)}}static getMaxWidthRowSplit(t){let n=t.length;if(n===0||n===1)return 0;let a=0;for(let r=0;r<n-1;++r){let s=t[r+1]-t[r];s>a&&(a=s)}return a}static getMaxWidthValueRowID(t){let n=t.length;if(n===0)return 0;let a=0,r=t[0],s=0;for(let i=1;i<n;++i){let o=t[i];o!==r&&(r=o,s=Math.max(i-a,s),a=i)}return Math.max(n-a,s)}tensorShapeFromTensor(t,n,a=!0){if(n.length===0){if(t[0]===-1)return[];throw new Error("The only valid scalar shape tensor is the fully unknown shape specified as -1.")}return z$(t,a)}calculateOutputSize(t){let n=this.valuesShape,a=this.defaultValueShape;W.validateDefaultValueShape(a,n);let r=this.tensorShapeFromTensor(this.shape,this.shapeShape),s=W.combineRaggedTensorToTensorShapes(this.raggedRank,r,n);s[0]<0&&(s[0]=t);for(let i=1;i<=this.raggedRank;++i)s[i]<0&&(s[i]=this.getMaxWidth(i));return s}calculateFirstParentOutputIndex(t,n,a){let r=Math.min(t,a),s=[],i=0;for(let o=0;o<r;++o,i+=n)s.push(i);for(let o=r;o<t;++o)s.push(-1);return R.assert(s.length===t,()=>"Final length of result must be equal to firstDimension."),s}calculateOutputIndexRowSplit(t,n,a,r){let s=t.length,i=[];for(let o=0;o<s-1;++o){let l=t[o+1]-t[o],d=Math.min(r,l),c=n[o];c===-1&&(d=0);for(let f=0;f<d;++f)i.push(c),c+=a;for(let f=0;f<l-d;++f)i.push(-1)}if(s>0&&i.length!==t[s-1])throw new Error("Invalid row split size.");return i}calculateOutputIndexValueRowID(t,n,a,r){let s=t.length,i=[];if(s===0)return[];let o=0,l=t[0];if(l>=n.length)throw new Error(`Got currentValueRowId=${l}, which is not less than ${n.length}`);let d=n[l];i.push(d);for(let c=1;c<s;++c){let f=t[c];if(f===l)d>=0&&(++o,o<r?d+=a:d=-1);else{if(o=0,l=f,f>=n.length)throw new Error(`Got nextValueRowId=${f} which is not less than ${n.length}`);d=n[f]}i.push(d)}if(i.length!==t.length)throw new Error("Invalid row ids.");return i}calculateOutputIndex(t,n,a,r){let s=this.getRowPartitionTensor(t),i=this.getRowPartitionTypeByDimension(t);switch(i){case Xi.VALUE_ROWIDS:return this.calculateOutputIndexValueRowID(s,n,a,r);case Xi.ROW_SPLITS:if(s.length-1>n.length)throw new Error(`Row partition size is greater than output size: ${s.length-1} > ${n.length}`);return this.calculateOutputIndexRowSplit(s,n,a,r);default:throw new Error(`Unsupported partition type: ${Xi[i]}`)}}getFirstDimensionSize(){let t=this.rowPartitionValues[0];if(this.rowPartitionTypes.length===0)throw new Error("No row_partition_types given.");let n=this.rowPartitionTypes[0];switch(n){case Xi.FIRST_DIM_SIZE:return t[0];case Xi.VALUE_ROWIDS:throw new Error("Cannot handle VALUE_ROWIDS in first dimension.");case Xi.ROW_SPLITS:return this.rowPartitionValuesShapes[0][0]-1;default:throw new Error(`Cannot handle type ${Xi[n]}`)}}compute(){if(this.rowPartitionValues[0].length<=0)throw new Error("Invalid first partition input. Tensor requires at least one element.");let t=this.getFirstDimensionSize(),n=this.calculateOutputSize(t),a=new Array(this.raggedRank+1);a[a.length-1]=1;for(let i=a.length-2;i>=0;--i)a[i]=a[i+1]*n[i+1];let r=z$(n,!1),s=R.getArrayFromDType(this.valuesDType,R.sizeFromShape(r));if(a[0]*n[0]>0){let i=this.calculateFirstParentOutputIndex(t,a[0],n[0]);for(let o=1;o<=this.raggedRank;++o)i=this.calculateOutputIndex(o-1,i,a[o],n[o]);this.setOutput(this.raggedRank,i,s,r)}return[r,s]}setOutput(t,n,a,r){if(a.length===0)return;let s=this.values,i=a,o=r.slice();o=o.slice(t+1);let l=R.sizeFromShape(o),d=n.length,c=this.defaultValue;if(c.length!==l&&c.length!==1){let y=this.defaultValueShape;ue(()=>{let b=le(c,y);c=vd(b,o).dataSync()})}let f=0,m=0,x=0;for(let y=0;y<=d;++y){let b=y<d?n[y]:-1;if(b===x){++x;continue}if(m<x){let w=s.subarray(f*l),S=i.subarray(m*l),k=(x-m)*l;P$(S,w,k)}if(y>=d){let 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Od(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{begin:s,size:i}=a;bt(r,"slice");let[o,l]=vr.parseSliceParams(r,s,i);vr.assertParamsValid(r,o,l);let d=n.data.get(r.dataId).values,c=Wv(d,o,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,c)}var U1e={kernelName:ag,backendName:"cpu",kernelFunc:Od};function uU(e,t,n,a,r,s,i){let o=t[0],l=s[0],d=new Array(l),c=new Array(o),f=t[1];if(l===0){if(o!==0)throw new Error(W.getSparseFillEmptyRowsIndicesDenseShapeMismatch(o));let w=R.getArrayFromDType(n,0),S=R.getArrayFromDType(r,0);return[w,[0,f],S,d,c]}let m=!0,x=0,y=new Array(l).fill(0);for(let w=0;w<o;++w){let S=e[w*f];if(S<0)throw new Error(W.getSparseFillEmptyRowsNegativeIndexErrorMessage(w,S));if(S>=l)throw new Error(W.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(w,S,l));++y[S],m=m&&S>=x,x=S}let b=!0;for(let w=0;w<l;++w){let S=y[w]===0;d[w]=S,b=b&&!S,y[w]=Math.max(y[w],1),w>0&&(y[w]+=y[w-1])}if(b&&m){let w=e,S=a;for(let k=0;k<o;++k)c[k]=k;return[w,[o,f],S,d,c]}else{let w=y[l-1],S=R.getArrayFromDType(n,w*f),k=R.getArrayFromDType(r,w),C=new Array(l).fill(0);for(let E=0;E<o;++E){let T=e[E*f],_=C[T],A=(T===0?0:y[T-1])+_;C[T]++;for(let $=0;$<f;++$)S[A*f+$]=e[E*f+$];k[A]=a[E],c[E]=A}for(let E=0;E<l;++E)if(C[E]===0){let T=E===0?0:y[E-1];S[T*f+0]=E;for(let _=1;_<f;++_)S[T*f+_]=0;k[T]=i}return[S,[w,f],k,d,c]}}function cU(e,t,n,a,r){let s=R.sizeFromShape(a),i=t[0],o=r.length,l=[],d=1,c=-1;for(let b=0;b<o;++b){let w=r[b];if(w===-1){if(c!==-1)throw new Error(W.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(c,b));c=b,l.push(1)}else{if(w<0)throw new Error(W.getSparseReshapeNegativeOutputDimErrorMessage(b,w));d*=w,l.push(w)}}if(c!==-1){if(d<=0)throw new Error(W.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage());let b=Math.trunc(s/d);if(d*b!==s)throw new Error(W.getSparseReshapeInputOutputMultipleErrorMessage(a,l));l[c]=b}if(R.sizeFromShape(l)!==s)throw new Error(W.getSparseReshapeInputOutputMismatchErrorMessage(a,l));let f=a.length,m=[];if(f>0){m[f-1]=1;for(let b=f-2;b>=0;--b)m[b]=m[b+1]*a[b+1]}let x=[];if(o>0){x[o-1]=1;for(let b=o-2;b>=0;--b)x[b]=x[b+1]*l[b+1]}let y=R.getArrayFromDType(n,i*o);for(let b=0;b<i;++b){let w=0;for(let S=0;S<f;++S)w+=e[b*f+S]*m[S];for(let S=0;S<o;++S)y[b*o+S]=Math.trunc(w/x[S]),w%=x[S]}return[y,[i,o],l]}function o4(e,t,n,a,r,s=!1,i=0){let o=a.length,l=[t[0],e.length/t[0]],d=l[1],c=o>0?r[o-1]+1:0;if(c<0)throw new Error(W.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let f=t.slice();f[0]=c;let m=f.reduce((k,C)=>k*C,1),x=R.getArrayFromDType(n,m);if(o===0)return c>0&&x.fill(i),[x,f];if(c<=0)throw new Error(W.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let y=0,b=1,w=0,S=r[y];for(;;){let k=0;if(b<o){if(k=r[b],S===k){++b;continue}if(S>=k)throw new Error(W.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage())}if(S<0||S>=c)throw new Error(W.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(S,c));S>w&&x.fill(i,w*d,S*d);for(let C=y;C<b;++C){let E=a[C];if(E<0||E>=l[0])throw new Error(W.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(C,a[C],l[0]));for(let T=0;T<d;T++)x[S*d+T]+=e[E*d+T]}if(s)for(let C=0;C<d;C++)x[S*d+C]/=b-y;if(y=b,++b,w=S+1,S=k,b>o)break}return w<c&&x.fill(i,w*d,c*d),[x,f]}var W1e=dl(e=>Math.sqrt(e)),V1e=Gn(ap,e=>Math.sqrt(e)),H1e={kernelName:ap,backendName:"cpu",kernelFunc:V1e},dU=Ha((e,t)=>{let n=e-t;return n*n}),G1e=kr(ip,dU),q1e={kernelName:ip,backendName:"cpu",kernelFunc:G1e},hU=dl((e,t)=>{let{pattern:n,replaceGlobal:a,rewrite:r}=t;return e.replace(new RegExp(n,a?"g":""),r)}),K1e=wc(yb,hU),X1e={kernelName:yb,backendName:"cpu",kernelFunc:K1e};function pU(e,t,n,a){let r=Zt(e,t.dtype);for(let s=0;s<r.size;s++){let i=r.indexToLoc(s),o=new Array(i.length);for(let l=0;l<o.length;l++)o[l]=i[l]*n[l]+a[l];r.set(t.get(...o),...i)}return r}var Y1e=class{constructor(e,t,n,a,r,s){this.separator=R.encodeString(e),this.nGramWidths=t,this.leftPad=R.encodeString(n),this.rightPad=R.encodeString(a),this.padWidth=r,this.preserveShort=s}getPadWidth(e){return Math.min(this.padWidth<0?e-1:this.padWidth,e-1)}getNumNGrams(e,t){let n=this.getPadWidth(t);return Math.max(0,e+2*n-t+1)}createNGrams(e,t,n,a,r,s){for(let i=0;i<r;++i){let o=this.getPadWidth(s),l=Math.max(0,o-i),d=Math.max(0,o-(r-(i+1))),c=s-(l+d),f=t+(l>0?0:i-o),m=0;m+=l*this.leftPad.length;for(let S=0;S<c;++S)m+=e[f+S].length;m+=d*this.rightPad.length;let x=l+d+c-1;m+=x*this.separator.length,n[a+i]=new Uint8Array(m);let y=n[a+i],b=0,w=S=>S.forEach(k=>y[b++]=k);for(let S=0;S<l;++S)w(this.leftPad),w(this.separator);for(let S=0;S<c-1;++S)w(e[f+S]),w(this.separator);if(c>0){w(e[f+c-1]);for(let S=0;S<d;++S)w(this.separator),w(this.rightPad)}else{for(let S=0;S<d-1;++S)w(this.rightPad),w(this.separator);w(this.rightPad)}}}compute(e,t){let n=e.length,a=t.length;if(a>0){let o=t[0];if(o!==0)throw new Error(`First split value must be 0, got ${o}`);for(let l=1;l<a;++l){let d=t[l]>=o;if(d=d&&t[l]<=n,!d)throw new Error(`Invalid split value ${t[l]}, must be in [${o}, ${n}]`);o=t[l]}if(o!==n)throw new Error(`Last split value must be data size. 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i=R.sizeFromShape(r.shape),o=n.data.get(r.dataId).values,l=R.getTypedArrayFromDType("float32",i);for(let d=0;d<o.length;d++)l[d]=o[d]<0?s*o[d]:o[d];return n.makeTensorInfo(r.shape,"float32",l)}var nve={kernelName:Ch,backendName:"cpu",kernelFunc:bU},ave=Ha((e,t)=>e<0?t*e:e);function vU(e){let{inputs:t,backend:n}=e,{x:a,alpha:r}=t;bt([a,r],"prelu");let s=n.data.get(a.dataId).values,i=n.data.get(r.dataId).values,[o,l]=ave(a.shape,r.shape,s,i,"float32");return n.makeTensorInfo(l,"float32",o)}var rve={kernelName:zh,backendName:"cpu",kernelFunc:vU},wU=Gn(Vh,e=>Math.max(0,e)),sve={kernelName:Vh,backendName:"cpu",kernelFunc:wU},SU=Gn(qh,e=>Math.min(Math.max(0,e),6)),ive={kernelName:qh,backendName:"cpu",kernelFunc:SU};function Vv(e,t,n,a,r){if(n==="linear")return ol({inputs:{x:t},backend:e});if(n==="relu")return wU({inputs:{x:t},backend:e});if(n==="elu")return yU({inputs:{x:t},backend:e});if(n==="relu6")return SU({inputs:{x:t},backend:e});if(n==="prelu")return 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lve={kernelName:th,backendName:"cpu",kernelFunc:kU};function uve(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:d,activation:c,leakyreluAlpha:f}=a,m,x,y,b=[];m=kU({inputs:{a:r,b:s},attrs:{transposeA:l,transposeB:d},backend:n}),i&&(x=em({inputs:{a:m,b:i},backend:n}),b.push(m),m=x),c&&(y=Vv(n,m,c,o,f),b.push(m),m=y);for(let w of b)n.disposeIntermediateTensorInfo(w);return m}var cve={kernelName:Nd,backendName:"cpu",kernelFunc:uve},dve=Gn(Gd,e=>Math.acos(e)),hve={kernelName:Gd,backendName:"cpu",kernelFunc:dve},pve=Gn(qd,e=>Math.acosh(e)),fve={kernelName:qd,backendName:"cpu",kernelFunc:pve};function mve(e){let{inputs:t,backend:n}=e,a=t;bt(t,"addN");let r=a.map(o=>n.data.get(o.dataId).values),s=Zt(a[0].shape,a[0].dtype),i=s.values;for(let o=0;o<a.length;o++){let l=r[o];for(let d=0;d<i.length;d++)i[d]+=l[d]}return n.makeTensorInfo(s.shape,s.dtype,s.values)}var gve={kernelName:Kd,backendName:"cpu",kernelFunc:mve};function 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c=W.computePool3DInfo(s.shape,i,o,1,l,d),f=c.strideDepth,m=c.strideHeight,x=c.strideWidth,y=c.filterDepth,b=c.filterHeight,w=c.filterWidth,S=c.dilationDepth,k=c.dilationHeight,C=c.dilationWidth,E=c.effectiveFilterDepth,T=c.effectiveFilterHeight,_=c.effectiveFilterWidth,A=E-1-c.padInfo.front,$=_-1-c.padInfo.left,O=T-1-c.padInfo.top,z=Zt(s.shape,"float32"),P=1/(y*b*w),j=n.bufferSync(r);for(let G=0;G<c.batchSize;++G)for(let X=0;X<c.inChannels;++X)for(let J=0;J<c.inDepth;++J)for(let V=0;V<c.inHeight;++V)for(let Q=0;Q<c.inWidth;++Q){let F=J-A,H=V-O,B=Q-$,Y=0;for(let ne=0;ne<E;ne+=S){let ee=(F+ne)/f;if(!(ee<0||ee>=c.outDepth||Math.floor(ee)!==ee))for(let U=0;U<T;U+=k){let oe=(H+U)/m;if(!(oe<0||oe>=c.outHeight||Math.floor(oe)!==oe))for(let pe=0;pe<_;pe+=C){let he=(B+pe)/x;if(he<0||he>=c.outWidth||Math.floor(he)!==he)continue;let xe=j.get(G,ee,oe,he,X);Y+=xe}}}z.set(Y*P,G,J,V,Q,X)}return n.makeTensorInfo(z.shape,z.dtype,z.values)}var Uve={kernelName:rb,backendName:"cpu",kernelFunc:zve};function Wve(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,i=s;bt([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:d}=a,c=W.computePool2DInfo(i.shape,o,l,1,d),f=c.strideHeight,m=c.strideWidth,x=c.filterHeight,y=c.filterWidth,b=c.dilationHeight,w=c.dilationWidth,S=c.effectiveFilterHeight,k=c.effectiveFilterWidth,C=k-1-c.padInfo.left,E=S-1-c.padInfo.top,T=Zt(i.shape,"float32"),_=1/(x*y),A=n.data.get(r.dataId).values,$=Zt(r.shape,"float32",A);for(let O=0;O<c.batchSize;++O)for(let z=0;z<c.inChannels;++z)for(let P=0;P<c.inHeight;++P)for(let j=0;j<c.inWidth;++j){let G=P-E,X=j-C,J=0;for(let V=0;V<S;V+=b){let Q=(G+V)/f;if(!(Q<0||Q>=c.outHeight||Math.floor(Q)!==Q))for(let F=0;F<k;F+=w){let H=(X+F)/m;if(H<0||H>=c.outWidth||Math.floor(H)!==H)continue;let B=$.get(O,Q,H,z);J+=B}}T.set(J*_,O,P,j,z)}return n.makeTensorInfo(T.shape,T.dtype,T.values)}var Vve={kernelName:ab,backendName:"cpu",kernelFunc:Wve};function 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n.makeTensorInfo(r.shape,r.dtype,b)}var Gve={kernelName:bh,backendName:"cpu",kernelFunc:Hve};function qve(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,crops:i}=a;bt([r],"batchToSpaceND");let o=s.reduce((S,k)=>S*k),l=W.getReshaped(r.shape,s,o),d=W.getPermuted(l.length,s.length),c=W.getReshapedPermuted(r.shape,s,o),f=W.getSliceBeginCoords(i,s.length),m=W.getSliceSize(c,i,s.length),x=ca({inputs:{x:r},backend:n,attrs:{shape:l}}),y=Ps({inputs:{x},backend:n,attrs:{perm:d}}),b=ca({inputs:{x:y},backend:n,attrs:{shape:c}}),w=Od({inputs:{x:b},backend:n,attrs:{begin:f,size:m}});return n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(b),w}var Kve={kernelName:ym,backendName:"cpu",kernelFunc:qve};function Xve(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i}=a,o=n.data.get(r.dataId).values,l=n.data.get(s.dataId).values,d=n4(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,d)}var Yve={kernelName:bm,backendName:"cpu",kernelFunc:Xve};function Jve(e){let{inputs:t,backend:n}=e,{s0:a,s1:r}=t,s=n.data.get(a.dataId).values,i=n.data.get(r.dataId).values,o=W.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return n.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var Qve={kernelName:sb,backendName:"cpu",kernelFunc:Jve},Zve=Gn(pc,(e,t)=>{let n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e}),ewe={kernelName:pc,backendName:"cpu",kernelFunc:Zve},twe=e=>{let{x:t}=e.inputs,n=e.backend,a=new Float32Array(R.sizeFromShape(t.shape)),r=n.data.get(t.dataId),s=r.complexTensorInfos.real,i=r.complexTensorInfos.imag,o=n.data.get(s.dataId).values,l=n.data.get(i.dataId).values;for(let d=0;d<o.length;d++){let c=o[d],f=l[d];a[d]=Math.hypot(c,f)}return n.makeOutput(a,t.shape,"float32")},nwe={kernelName:ib,backendName:"cpu",kernelFunc:twe};function 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Swe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a;bt(r,"cumprod");let l=W.getAxesPermutation([s],r.shape.length),d=r;l!=null&&(d=Ps({inputs:{x:r},backend:n,attrs:{perm:l}}));let c=W.getInnerMostAxes(1,r.shape.length)[0];if(c!==d.shape.length-1)throw new Error(`backend.cumprod in CPU expects an inner-most axis=${d.shape.length-1} but got axis=${c}`);let f=Di(d.dtype,"int32"),m=R.makeOnesTypedArray(R.sizeFromShape(d.shape),f),x=n.data.get(d.dataId).values,y=d.shape[d.shape.length-1],b=o?(S,k)=>S+y-k-1:(S,k)=>S+k;for(let S=0;S<x.length;S+=y)for(let k=0;k<y;k++){let C=b(S,k);if(k===0)m[C]=i?1:x[C];else{let E=b(S,k-1);m[C]=i?x[E]*m[E]:x[C]*m[E]}}let w=n.makeTensorInfo(d.shape,f,m);if(l!=null){let S=W.getUndoAxesPermutation(l),k=Ps({inputs:{x:w},backend:n,attrs:{perm:S}});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(d),k}return w}var kwe={kernelName:Nm,backendName:"cpu",kernelFunc:Swe};function Nwe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a;bt(r,"cumsum");let l=W.getAxesPermutation([s],r.shape.length),d=r;l!=null&&(d=Ps({inputs:{x:r},backend:n,attrs:{perm:l}}));let c=W.getInnerMostAxes(1,r.shape.length)[0];if(c!==d.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${d.shape.length-1} but got axis=${c}`);let f=Di(d.dtype,"int32"),m=R.makeZerosTypedArray(R.sizeFromShape(d.shape),f),x=n.data.get(d.dataId).values,y=d.shape[d.shape.length-1],b=o?(S,k)=>S+y-k-1:(S,k)=>S+k;for(let S=0;S<x.length;S+=y)for(let k=0;k<y;k++){let C=b(S,k);if(k===0)m[C]=i?0:x[C];else{let E=b(S,k-1);m[C]=i?x[E]+m[E]:x[C]+m[E]}}let w=n.makeTensorInfo(d.shape,f,m);if(l!=null){let S=W.getUndoAxesPermutation(l),k=Ps({inputs:{x:w},backend:n,attrs:{perm:S}});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(d),k}return w}var Cwe={kernelName:uh,backendName:"cpu",kernelFunc:Nwe};function Ewe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=a;if(r.shape.length===1){let l=n.data.get(r.dataId).values,d=n.data.get(s.dataId).values,c=n4(l,d,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}else if(r.shape.length===2){let l=n.bufferSync(r),d=n.bufferSync(s),c=M7(l,d,i,o);return n.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var Iwe={kernelName:ob,backendName:"cpu",kernelFunc:Ewe};function Twe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockSize:s,dataFormat:i}=a;R.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. Got ${i}`);let o=r.shape[0],l=r.shape[1],d=r.shape[2],c=r.shape[3],f=l*s,m=d*s,x=c/(s*s),y=n.data.get(r.dataId).values,b=new Float32Array(o*f*m*x),w=0;for(let S=0;S<o;++S)for(let k=0;k<f;++k){let C=Math.floor(k/s),E=k%s;for(let T=0;T<m;++T){let _=Math.floor(T/s),A=T%s,$=(E*s+A)*x;for(let O=0;O<x;++O){let z=O+$+c*(_+d*(C+l*S));b[w++]=y[z]}}}return n.makeTensorInfo([o,f,m,x],r.dtype,b)}var Awe={kernelName:Em,backendName:"cpu",kernelFunc:Twe};function IU(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:d}=a;bt([r,s],"depthwiseConv2DNative");let c=R.computeStrides(r.shape),f=R.computeStrides(s.shape),m=l;m==null&&(m=[1,1]),R.assert(W.eitherStridesOrDilationsAreOne(i,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. 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Wwe(e){let{inputs:t,backend:n,attrs:a}=e,{equation:r}=a,s=t,{allDims:i,summedDims:o,idDims:l}=W.decodeEinsumEquation(r,s.length);W.checkEinsumDimSizes(i.length,l,s);let{path:d,steps:c}=W.getEinsumComputePath(o,l),f=c.length,m=null,x=i.length,y=[];for(let b=0;b<f;++b){for(let w of c[b]){let{permutationIndices:S,expandDims:k}=W.getEinsumPermutation(x,l[w]),C;W.isIdentityPermutation(S)?C=s[w]:(C=Ps({inputs:{x:s[w]},backend:n,attrs:{perm:S}}),y.push(C));let E=C.shape.slice();for(let T=0;T<k.length;++T)E.splice(k[T],0,1);R.arraysEqual(C.shape,E)||(C=ca({inputs:{x:C},backend:n,attrs:{shape:E}}),y.push(C)),m===null?m=C:(m=B2({inputs:{a:C,b:m},backend:n}),y.push(m))}b<f-1&&(d[b]>=0&&(m=Qb({inputs:{x:m},backend:n,attrs:{axis:d[b]-(i.length-x),keepDims:!1}}),y.push(m)),x--)}for(let b of y)b!==m&&n.disposeIntermediateTensorInfo(b);return m}var Vwe={kernelName:kw,backendName:"cpu",kernelFunc:Wwe};function Hwe(e){let{inputs:t,backend:n}=e,{dy:a,y:r}=t;bt([a,r],"eluGrad");let s=new Float32Array(R.sizeFromShape(r.shape)),i=n.data.get(r.dataId).values,o=n.data.get(a.dataId).values;for(let l=0;l<i.length;++l){let d=i[l];d>=0?s[l]=o[l]:s[l]=o[l]*(d+1)}return n.makeTensorInfo(r.shape,"float32",s)}var Gwe={kernelName:Im,backendName:"cpu",kernelFunc:Hwe},qwe=W.ERF_P,Kwe=W.ERF_A1,Xwe=W.ERF_A2,Ywe=W.ERF_A3,Jwe=W.ERF_A4,Qwe=W.ERF_A5,Zwe=Gn(fh,e=>{let t=Math.sign(e),n=Math.abs(e),a=1/(1+qwe*n);return t*(1-((((Qwe*a+Jwe)*a+Ywe)*a+Xwe)*a+Kwe)*a*Math.exp(-n*n))}),e2e={kernelName:fh,backendName:"cpu",kernelFunc:Zwe};function Hv(e){let{inputs:t,backend:n,attrs:a}=e,{input:r}=t,{dim:s}=a,i=r.shape.length,o=r.shape.slice(),l=s;return s<0&&(R.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),ca({inputs:{x:r},backend:n,attrs:{shape:o}})}var t2e={kernelName:Am,backendName:"cpu",kernelFunc:Hv},n2e=Ha((e,t)=>e/t),f4=kr(hh,n2e),CE={kernelName:hh,backendName:"cpu",kernelFunc:f4};function TU(e,t,n){let 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YSe={kernelName:Kh,backendName:"cpu",kernelFunc:XSe},JSe={kernelName:pg,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:a}=e,{radians:r,fillValue:s,center:i}=t,o=n,l=R.getTypedArrayFromDType(a.dtype,R.sizeFromShape(a.shape)),[d,c,f,m]=a.shape,[x,y]=W.getImageCenter(i,c,f),b=255,w=Math.sin(r),S=Math.cos(r),k=o.data.get(a.dataId).values;for(let C=0;C<d;C++){let E=C*f*c*m;for(let T=0;T<c;T++){let _=T*(f*m);for(let A=0;A<f;A++){let $=A*m;for(let O=0;O<m;O++){let z=[d,T,A,O],P=z[2],j=z[1],G=(P-x)*S-(j-y)*w,X=(P-x)*w+(j-y)*S;G=Math.round(G+x),X=Math.round(X+y);let J=s;if(typeof s!="number"&&(O===3?J=b:J=s[O]),G>=0&&G<f&&X>=0&&X<c){let Q=X*(f*m),F=G*m,H=E+Q+F+O;J=k[H]}let V=E+_+$+O;l[V]=J}}}}return{dataId:o.write(l,a.shape,a.dtype),shape:a.shape,dtype:a.dtype}}},QSe=Gn(Xh,e=>{let t=Math.floor(e);return e-t<.5?Math.floor(e):e-t>.5?Math.ceil(e):t%2===0?t:t+1}),ZSe={kernelName:Xh,backendName:"cpu",kernelFunc:QSe};function eke(e){let{inputs:t,backend:n,attrs:a}=e,{indices:r,updates:s}=t,{shape:i}=a,{sliceRank:o,numUpdates:l,sliceSize:d,strides:c,outputSize:f}=W.calculateShapes(s,r,i),m=!0,x=n.bufferSync(r),y=n.bufferSync(s),b=xd(x,y,i,f,d,l,o,c,0,m);return n.makeTensorInfo(i,b.dtype,b.values)}var tke={kernelName:Zm,backendName:"cpu",kernelFunc:eke};function nke(e,t){let n=0,a=e.length,r=0;for(;n<a;)r=Math.floor((n+a)/2),e[r]<t?n=r+1:a=r;return a}function ake(e,t){let n=0,a=e.length,r=0;for(;n<a;)r=Math.floor((n+a)/2),e[r]<=t?n=r+1:a=r;return a}function rke(e,t,n,a,r,s){let i=R.getArrayFromDType("int32",n*r);for(let o=0;o<n;++o){let l=e.slice(o*a,(o+1)*a),d=o*r;for(let c=0;c<r;++c)i[d+c]=s==="left"?nke(l,t[c+d]):ake(l,t[c+d])}return i}function ske(e){let{inputs:t,backend:n,attrs:a}=e,{sortedSequence:r,values:s}=t,{side:i}=a,o=n.data.get(r.dataId).values,l=n.data.get(s.dataId).values,d=rke(o,l,r.shape[0],r.shape[1],s.shape[1],i);return n.makeTensorInfo(s.shape,"int32",d)}var ike={kernelName:tg,backendName:"cpu",kernelFunc:ske};function oke(e){let{inputs:t,backend:n}=e,{condition:a,t:r,e:s}=t;bt([a,r,s],"select");let i=a.shape.length,o=n.data.get(a.dataId).values,l=n.data.get(r.dataId).values,d=n.data.get(s.dataId).values,c=Di(r.dtype,s.dtype),f=R.makeZerosTypedArray(R.sizeFromShape(r.shape),c),m=0,x=i===0||i>1||r.shape.length===1?1:R.sizeFromShape(r.shape.slice(1));for(let y=0;y<o.length;y++)for(let b=0;b<x;b++)o[y]===1?f[m++]=l[y]:f[m++]=d[y];return n.makeTensorInfo(r.shape,c,f)}var lke={kernelName:ng,backendName:"cpu",kernelFunc:oke},uke=W.SELU_SCALEALPHA,cke=W.SELU_SCALE,dke=Gn(Jh,e=>e>=0?cke*e:uke*(Math.exp(e)-1)),hke={kernelName:Jh,backendName:"cpu",kernelFunc:dke},pke=Gn(ep,e=>e<0?-1:e>0?1:0),fke={kernelName:ep,backendName:"cpu",kernelFunc:pke},mke=Gn(Qh,e=>Math.sin(e)),gke={kernelName:Qh,backendName:"cpu",kernelFunc:mke},xke=Gn(Zh,e=>Math.sinh(e)),yke={kernelName:Zh,backendName:"cpu",kernelFunc:xke},bke=11920928955078125e-23,U$=Math.log(bke)+2,vke=Gn(np,e=>{let t=e>-U$,n=e<U$,a=Math.exp(e),r;return n?r=a:t?r=e:r=Math.log(1+a),r}),wke={kernelName:np,backendName:"cpu",kernelFunc:vke};function Ske(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,paddings:i}=a;bt([r],"spaceToBatchND");let o=R.sizeFromShape(s),l=[[0,0]];l.push(...i);for(let w=1+s.length;w<r.shape.length;++w)l.push([0,0]);let d=RU.kernelFunc({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),c=W.getReshaped(d.shape,s,o,!1),f=W.getPermuted(c.length,s.length,!1),m=W.getReshapedPermuted(d.shape,s,o,!1),x=ca({inputs:{x:d},backend:n,attrs:{shape:c}}),y=Ps({inputs:{x},backend:n,attrs:{perm:f}}),b=ca({inputs:{x:y},backend:n,attrs:{shape:m}});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(y),b}var kke={kernelName:rg,backendName:"cpu",kernelFunc:Ske};function Nke(e){let{inputs:t,backend:n}=e,{indices:a,values:r,denseShape:s,defaultValue:i}=t;if(s.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
108        ${s.shape}`);if(a.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
109        ${a.shape}`);if(r.shape.length!==1)throw new Error(`Values must be a vector, saw:
110        ${r.shape}`);if(i.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
111        ${i.shape}`);let o=n.data.get(a.dataId).values,l=n.data.get(r.dataId).values,d=n.data.get(s.dataId).values,c=n.data.get(i.dataId).values[0],[f,m,x,y,b]=uU(o,a.shape,a.dtype,l,r.dtype,d,c);return[n.makeTensorInfo(m,a.dtype,f),n.makeTensorInfo([m[0]],r.dtype,x),n.makeTensorInfo([y.length],"bool",new Uint8Array(y.map(w=>Number(w)))),n.makeTensorInfo([b.length],a.dtype,new Int32Array(b))]}var Cke={kernelName:fb,backendName:"cpu",kernelFunc:Nke};function Eke(e){let{inputs:t,backend:n}=e,{inputIndices:a,inputShape:r,newShape:s}=t;if(a.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape
112        ${a.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape
113        ${r.shape}`);if(s.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${s.shape}`);let i=Array.from(n.data.get(r.dataId).values),o=n.data.get(a.dataId).values,l=Array.from(n.data.get(s.dataId).values),[d,c,f]=cU(o,a.shape,a.dtype,i,l);return[n.makeTensorInfo(c,a.dtype,d),n.makeTensorInfo([f.length],s.dtype,new Int32Array(f))]}var Ike={kernelName:ig,backendName:"cpu",kernelFunc:Eke};function Tke(e){let{inputs:t,backend:n}=e,{data:a,indices:r,segmentIds:s}=t;if(a.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
114          ${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
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r=R.sizeFromShape(e),s=null;e.length<=1&&r<=n?s=[1,r]:e.length===2&&e[0]<=n&&e[1]<=n?s=e:e.length===3&&e[0]*e[1]<=n&&e[2]<=n?s=[e[0]*e[1],e[2]]:e.length===3&&e[0]<=n&&e[1]*e[2]<=n?s=[e[0],e[1]*e[2]]:e.length===4&&e[0]*e[1]*e[2]<=n&&e[3]<=n?s=[e[0]*e[1]*e[2],e[3]]:e.length===4&&e[0]<=n&&e[1]*e[2]*e[3]<=n&&(s=[e[0],e[1]*e[2]*e[3]]);let i=s!=null&&Math.max(...s)>a&&Math.min(...s)<=(t?2:1)&&Math.min(...s)>0;if(s==null||i)if(t){let o=Ld(e),l=2,d=2;e.length&&([l,d]=Pd(e)),r=o*(l/2)*(d/2),s=R.sizeToSquarishShape(r).map(c=>c*2)}else s=R.sizeToSquarishShape(r);return s}function z1(e){return e%2===0}function Wy(e,t){if(e=e.slice(-2),t=t.slice(-2),R.arraysEqual(e,t)||!e.length||!t.length||e[0]===0||e[1]===0||t[0]===0||t[1]===0)return!0;if(e.length!==t.length){let n=e[e.length-1],a=t[t.length-1];if(n===a||z1(n)&&z1(a)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&z1(e[0])&&z1(t[0])}var lv,uv;function e9(e){if(lv==null){let t=jo(e);lv=t.getParameter(t.MAX_TEXTURE_SIZE)}return lv}function 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e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(a),e.deleteFramebuffer(r),s}function s9(e){return e!==2?!1:jo(e).fenceSync!=null}function Eg(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&R.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var Nt=fe();Nt.registerFlag("HAS_WEBGL",()=>Nt.getNumber("WEBGL_VERSION")>0);Nt.registerFlag("WEBGL_VERSION",()=>AE(2)?2:AE(1)?1:0);Nt.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Nt.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Nt.get("WEBGL_VERSION")===2);Nt.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Nt.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Nt.registerFlag("WEBGL_PACK",()=>Nt.getBool("HAS_WEBGL"));Nt.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_CLIP",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_REDUCE",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_LAZILY_UNPACK",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_CONV_IM2COL",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_PACK_CONV2DTRANSPOSE",()=>Nt.getBool("WEBGL_PACK"));Nt.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>e9(Nt.getNumber("WEBGL_VERSION")));Nt.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>t9(Nt.getNumber("WEBGL_VERSION")));Nt.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=Nt.getNumber("WEBGL_VERSION");return e===0?0:n9(e)});Nt.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Nt.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!Ib.isMobile());Nt.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>a9(Nt.getNumber("WEBGL_VERSION")));Nt.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Nt.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Nt.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Nt.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>r9(Nt.getNumber("WEBGL_VERSION")));Nt.registerFlag("WEBGL_FENCE_API_ENABLED",()=>s9(Nt.getNumber("WEBGL_VERSION")));Nt.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Nt.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Nt.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",()=>-1,e=>{if(typeof e!="number")throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be a number but got ${e}.`);if(e<0&&e!==-1)throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${e}.`)});Nt.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>Ib.isMobile()?1:-1,e=>{if(typeof e!="number")throw new Error(`WEBGL_FLUSH_THRESHOLD must be a number but got ${e}.`);if(e<0&&e!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${e}.`)});Nt.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);Nt.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);Nt.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);Nt.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);Nt.registerFlag("WEBGL_EXP_CONV",()=>!1);Nt.registerFlag("SOFTWARE_WEBGL_ENABLED",()=>Nt.getBool("IS_TEST"));Nt.registerFlag("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE",()=>1/0);Nt.registerFlag("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE",()=>!1);Nt.registerFlag("WEBGL2_ISNAN_CUSTOM",()=>!1);Nt.registerFlag("ENGINE_COMPILE_ONLY",()=>!1);function Is(){let e,t,n,a,r,s,i,o,l,d;return fe().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",a="in",r="texture",s="outputColor",i="out vec4 outputColor;",o=fe().getBool("WEBGL2_ISNAN_CUSTOM")?`
122      bool isnan_custom(float val) {
123        uint floatToUint = floatBitsToUint(val);
124        return (floatToUint & 0x7fffffffu) > 0x7f800000u;
125      }
126
127      bvec4 isnan_custom(vec4 val) {
128        return bvec4(isnan_custom(val.x),
129          isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));
130      }
131
132      #define isnan(value) isnan_custom(value)
133    `:"",l="",d=`
134      #define round(value) newRound(value)
135      int newRound(float value) {
136        return int(floor(value + 0.5));
137      }
138
139      ivec4 newRound(vec4 value) {
140        return ivec4(floor(value + vec4(0.5)));
141      }
142    `):(e="",t="attribute",n="varying",a="varying",r="texture2D",s="gl_FragColor",i="",o=`
143      #define isnan(value) isnan_custom(value)
144      bool isnan_custom(float val) {
145        return (val > 0. || val < 1. || val == 0.) ? false : true;
146      }
147      bvec4 isnan_custom(vec4 val) {
148        return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));
149      }
150    `,l=`
151      uniform float INFINITY;
152
153      bool isinf(float val) {
154        return abs(val) == INFINITY;
155      }
156      bvec4 isinf(vec4 val) {
157        return equal(abs(val), vec4(INFINITY));
158      }
159    `,d=`
160      int round(float value) {
161        return int(floor(value + 0.5));
162      }
163
164      ivec4 round(vec4 value) {
165        return ivec4(floor(value + vec4(0.5)));
166      }
167    `),{version:e,attribute:t,varyingVs:n,varyingFs:a,texture2D:r,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:d}}function xp(e,t,n="index"){let a=R.computeStrides(t);return a.map((r,s)=>{let i=`int ${e[s]} = ${n} / ${r}`,o=s===a.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * ${r}`:`index -= ${e[s]} * ${r}`;return`${i}; ${o};`}).join("")}function F2(e,t,n="index"){let a=R.computeStrides(t);return a.map((r,s)=>{let i=`int ${e[s]} = ${n} / outShapeStrides[${s}]`,o=s===a.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * outShapeStrides[${s}]`:`index -= ${e[s]} * outShapeStrides[${s}]`;return`${i}; ${o};`}).join("")}function DNe(e,t){let n=e.length,a=e.map(s=>`${t}[${s}]`),r=new Array(n-1);r[n-2]=a[n-1];for(let s=n-3;s>=0;--s)r[s]=`(${r[s+1]} * ${a[s+1]})`;return r}function RNe(e,t,n="index"){let a=e.map((s,i)=>i),r=DNe(a,t);return r.map((s,i)=>{let o=`int ${e[i]} = ${n} / ${r[i]}`,l=i===r.length-1?`int ${e[i+1]} = ${n} - ${e[i]} * ${r[i]}`:`index -= ${e[i]} * ${r[i]}`;return`${o}; ${l};`}).join("")}function y4(e){let t=R.computeStrides(e).map(n=>n.toString());return`
168  int getFlatIndex(ivec3 coords) {
169    return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
170  }
171`}function b4(){return`
172  int getFlatIndex(ivec3 coords) {
173    return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
174  }
175`}var i9=`
176  const float FLOAT_MAX = 1.70141184e38;
177  const float FLOAT_MIN = 1.17549435e-38;
178
179  lowp vec4 encode_float(highp float v) {
180    if (isnan(v)) {
181      return vec4(255, 255, 255, 255);
182    }
183
184    highp float av = abs(v);
185
186    if(av < FLOAT_MIN) {
187      return vec4(0.0, 0.0, 0.0, 0.0);
188    } else if(v > FLOAT_MAX) {
189      return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;
190    } else if(v < -FLOAT_MAX) {
191      return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;
192    }
193
194    highp vec4 c = vec4(0,0,0,0);
195
196    highp float e = floor(log2(av));
197    highp float m = exp2(fract(log2(av))) - 1.0;
198
199    c[2] = floor(128.0 * m);
200    m -= c[2] / 128.0;
201    c[1] = floor(32768.0 * m);
202    m -= c[1] / 32768.0;
203    c[0] = floor(8388608.0 * m);
204
205    highp float ebias = e + 127.0;
206    c[3] = floor(ebias / 2.0);
207    ebias -= c[3] * 2.0;
208    c[2] += floor(ebias) * 128.0;
209
210    c[3] += 128.0 * step(0.0, -v);
211
212    return c / 255.0;
213  }
214`,{getBroadcastDims:o9}=W;function MNe(e,t,n){let a=[];if(e.forEach(m=>{let x=R.sizeFromShape(m.shapeInfo.logicalShape);if(m.shapeInfo.isUniform?a.push(`uniform float ${m.name}${x>1?`[${x}]`:""};`):(a.push(`uniform sampler2D ${m.name};`),a.push(`uniform int offset${m.name};`)),n.enableShapeUniforms){let{uniformShape:y}=v4(n.packedInputs,m.shapeInfo.logicalShape,m.shapeInfo.texShape);switch(y.length){case 1:a.push(`uniform int ${m.name}Shape;`);break;case 2:a.push(`uniform ivec2 ${m.name}Shape;`);break;case 3:a.push(`uniform ivec3 ${m.name}Shape;`);break;case 4:a.push(`uniform ivec4 ${m.name}Shape;`);break}a.push(`uniform ivec2 ${m.name}TexShape;`)}}),n.enableShapeUniforms){switch(t.logicalShape.length){case 1:a.push("uniform int outShape;");break;case 2:a.push("uniform ivec2 outShape;"),a.push("uniform int outShapeStrides;");break;case 3:a.push("uniform ivec3 outShape;"),a.push("uniform ivec2 outShapeStrides;");break;case 4:a.push("uniform ivec4 outShape;"),a.push("uniform ivec3 outShapeStrides;");break}a.push("uniform ivec2 outTexShape;")}n.customUniforms&&n.customUniforms.forEach(m=>{a.push(`uniform ${m.type} ${m.name}${m.arrayIndex?`[${m.arrayIndex}]`:""};`)});let r=a.join(`
215`),s=e.map(m=>$Ne(m,t,n.packedInputs,n.enableShapeUniforms)).join(`
216`),i=t.texShape,o=Is(),l=ONe(o),d,c,f=zNe(o);return t.isPacked?(d=BNe(t.logicalShape,i,n.enableShapeUniforms),c=PNe(o)):(d=FNe(t.logicalShape,i,n.enableShapeUniforms),c=LNe(o)),n.packedInputs&&(f+=HNe),[f,l,c,r,d,s,n.userCode].join(`
217`)}function Ig(e,t=!1){let n=e.shapeInfo.logicalShape;switch(n.length){case 0:return aCe(e,t);case 1:return sCe(e,t);case 2:return oCe(e,t);case 3:return uCe(e,t);case 4:return dCe(e,t);case 5:return hCe(e);case 6:return pCe(e);default:throw new Error(`${n.length}-D input sampling is not yet supported`)}}function l9(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return nCe(e);case 1:return rCe(e,t);case 2:return iCe(e,t);case 3:return lCe(e,t);default:return cCe(e,t)}}function $Ne(e,t,n=!1,a){let r="";n?r+=l9(e,a):r+=Ig(e,a);let s=e.shapeInfo.logicalShape,i=t.logicalShape;return s.length<=i.length&&(n?r+=fCe(e,t):r+=mCe(e,t)),r}function BNe(e,t,n){switch(e.length){case 0:return u9();case 1:return GNe(e,t,n);case 2:return eCe(e,t,n);case 3:return KNe(e,t,n);default:return YNe(e,t,n)}}function FNe(e,t,n){switch(e.length){case 0:return u9();case 1:return qNe(e,t,n);case 2:return tCe(e,t,n);case 3:return XNe(e,t,n);case 4:return JNe(e,t,n);case 5:return QNe(e,t);case 6:return ZNe(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function ONe(e){return`
218    float sampleTexture(sampler2D textureSampler, vec2 uv) {
219      return ${e.texture2D}(textureSampler, uv).r;
220    }
221  `}function LNe(e){return`
222    void setOutput(float val) {
223      ${e.output} = vec4(val, 0, 0, 0);
224    }
225  `}function PNe(e){return`
226    void setOutput(vec4 val) {
227      ${e.output} = val;
228    }
229  `}function zNe(e){return`${e.version}
230    precision highp float;
231    precision highp int;
232    precision highp sampler2D;
233    ${e.varyingFs} vec2 resultUV;
234    ${e.defineOutput}
235    const vec2 halfCR = vec2(0.5, 0.5);
236
237    struct ivec5
238    {
239      int x;
240      int y;
241      int z;
242      int w;
243      int u;
244    };
245
246    struct ivec6
247    {
248      int x;
249      int y;
250      int z;
251      int w;
252      int u;
253      int v;
254    };
255
256    uniform float NAN;
257    ${e.defineSpecialNaN}
258    ${e.defineSpecialInf}
259    ${e.defineRound}
260
261    int imod(int x, int y) {
262      return x - y * (x / y);
263    }
264
265    int idiv(int a, int b, float sign) {
266      int res = a / b;
267      int mod = imod(a, b);
268      if (sign < 0. && mod != 0) {
269        res -= 1;
270      }
271      return res;
272    }
273
274    //Based on the work of Dave Hoskins
275    //https://www.shadertoy.com/view/4djSRW
276    #define HASHSCALE1 443.8975
277    float random(float seed){
278      vec2 p = resultUV * seed;
279      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);
280      p3 += dot(p3, p3.yzx + 19.19);
281      return fract((p3.x + p3.y) * p3.z);
282    }
283
284    ${UNe}
285    ${WNe}
286    ${VNe}
287  `}var UNe=`
288vec2 uvFromFlat(int texNumR, int texNumC, int index) {
289  int texR = index / texNumC;
290  int texC = index - texR * texNumC;
291  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
292}
293vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
294  int texelIndex = index / 2;
295  int texR = texelIndex / texNumC;
296  int texC = texelIndex - texR * texNumC;
297  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
298}
299`,WNe=`
300vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
301  int texNumC, int row, int col) {
302  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
303  int texR = texelIndex / texNumC;
304  int texC = texelIndex - texR * texNumC;
305  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
306}
307`,VNe=`
308vec2 packedUVfrom3D(int texNumR, int texNumC,
309    int texelsInBatch, int texelsInLogicalRow, int b,
310    int row, int col) {
311  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);
312  int texR = index / texNumC;
313  int texC = index - texR * texNumC;
314  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
315}
316`,HNe=`
317  float getChannel(vec4 frag, vec2 innerDims) {
318    vec2 modCoord = mod(innerDims, 2.);
319    return modCoord.x == 0. ?
320      (modCoord.y == 0. ? frag.r : frag.g) :
321      (modCoord.y == 0. ? frag.b : frag.a);
322  }
323  float getChannel(vec4 frag, int dim) {
324    float modCoord = mod(float(dim), 2.);
325    return modCoord == 0. ? frag.r : frag.g;
326  }
327`;function u9(){return`
328    int getOutputCoords() {
329      return 0;
330    }
331  `}function GNe(e,t,n){let a=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return a[0]===1?n?`
332      int getOutputCoords() {
333        return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));
334      }
335    `:`
336      int getOutputCoords() {
337        return 2 * int(resultUV.x * ${a[1]}.0);
338      }

1043:(e.buildVao(d),Object.assign({program:t,fragmentShader:l,source:o,webGLProgram:d,inShapeInfos:s,outShapeInfo:i},c9(e,t,d)))}function c9(e,t,n){let a=[],r=[],s,i,o,l=null,d=null;d=e.getUniformLocation(n,"NAN",!1),fe().getNumber("WEBGL_VERSION")===1&&(l=e.getUniformLocation(n,"INFINITY",!1));let c=!1;for(let f of t.variableNames){let m={name:f,uniform:e.getUniformLocation(n,f,c),offset:e.getUniformLocation(n,`offset${f}`,c)};t.enableShapeUniforms&&(m.shape=e.getUniformLocation(n,`${f}Shape`,c),m.texShape=e.getUniformLocation(n,`${f}TexShape`,c)),a.push(m)}if(t.enableShapeUniforms&&(s=e.getUniformLocation(n,"outShape",c),o=e.getUniformLocation(n,"outShapeStrides",c),i=e.getUniformLocation(n,"outTexShape",c)),t.customUniforms)for(let f of t.customUniforms)r.push(e.getUniformLocation(n,f.name,c));return{variablesLocations:a,customUniformLocations:r,infLoc:l,nanLoc:d,outShapeLocation:s,outShapeStridesLocation:o,outTexShapeLocation:i}}function V$(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((n,a)=>{let r=n.logicalShape,s=t[a],i=s.shape;if(!R.arraysEqual(r,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${r} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!R.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function xCe(e,t,n,a,r){t.program.enableShapeUniforms||(V$(t.inShapeInfos,n),V$([t.outShapeInfo],[a]));let s=a.texData.texture,i=a.texData.texShape;a.texData.isPacked?e.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):e.setOutputMatrixTexture(s.texture,i[0],i[1]),e.setProgram(t.webGLProgram),e.bindVertexArray(t.webGLProgram.vao),fe().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN);for(let l=0;l<n.length;++l){let d=n[l],{uniform:c,offset:f,shape:m,texShape:x}=t.variablesLocations[l];if(m){let{uniformShape:y}=v4(t.program.packedInputs,d.shape,d.texData.texShape);switch(y.length){case 1:e.gl.uniform1iv(m,new Int32Array(y));break;case 2:e.gl.uniform2iv(m,new Int32Array(y));break;case 3:e.gl.uniform3iv(m,new Int32Array(y));break;case 4:e.gl.uniform4iv(m,new Int32Array(y));break}}if(x&&e.gl.uniform2i(x,d.texData.texShape[0],d.texData.texShape[1]),c!=null){if(d.isUniform){if(R.sizeFromShape(d.shape)<2)e.gl.uniform1f(c,d.uniformValues[0]);else{let y=d.uniformValues;y instanceof Float32Array||(y=new Float32Array(y)),e.gl.uniform1fv(c,y)}continue}d.texData.slice!=null&&f!=null&&e.gl.uniform1i(f,d.texData.slice.flatOffset),e.setInputMatrixTexture(d.texData.texture.texture,c,l)}}let o=t.outShapeLocation;if(o)switch(a.shape.length){case 1:e.gl.uniform1iv(o,new Int32Array(a.shape));break;case 2:e.gl.uniform2iv(o,new Int32Array(a.shape));break;case 3:e.gl.uniform3iv(o,new Int32Array(a.shape));break;case 4:e.gl.uniform4iv(o,new Int32Array(a.shape));break}if(t.outShapeStridesLocation){let l=R.computeStrides(a.shape);switch(a.shape.length){case 2:e.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(l));break;case 3:e.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(l));break;case 4:e.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(l));break}}if(t.outTexShapeLocation&&e.gl.uniform2i(t.outTexShapeLocation,a.texData.texShape[0],a.texData.texShape[1]),t.program.customUniforms&&r)for(let l=0;l<t.program.customUniforms.length;++l){let d=t.program.customUniforms[l],c=t.customUniformLocations[l],f=r[l];if(d.type==="float")e.gl.uniform1fv(c,f);else if(d.type==="vec2")e.gl.uniform2fv(c,f);else if(d.type==="vec3")e.gl.uniform3fv(c,f);else if(d.type==="vec4")e.gl.uniform4fv(c,f);else if(d.type==="int")e.gl.uniform1iv(c,f);else if(d.type==="ivec2")e.gl.uniform2iv(c,f);else if(d.type==="ivec3")e.gl.uniform3iv(c,f);else if(d.type==="ivec4")e.gl.uniform4iv(c,f);else throw Error(`uniform type ${d.type} is not supported yet.`)}e.executeProgram()}function yCe(e,t,n){let a="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!i.isUniform){let l=i.texData.texShape,{useSqueezeShape:d,uniformShape:c,keptDims:f}=v4(e.packedInputs,i.shape,l),m="",x="",y="";if(c.length===1&&e.packedInputs){let T=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];m=`${T[0]>1}_${T[1]>1}`}else if(c.length===2&&!e.packedInputs)x=`${c[0]>1}_${c[1]>1}`;else if(c.length>2&&!e.packedInputs){let T=R.computeStrides(c);y=`${T[0]===l[1]}_${T[T.length-1]===l[1]}`}let b=i.shape.length,w=c.length===2&&R.arraysEqual(i.shape,l),S=R.sizeFromShape(i.shape)===1,k=W.getBroadcastDims(i.shape,n.shape),C=!e.packedInputs&&b===n.shape.length&&R.arraysEqual(l,n.texData.texShape),E=e.packedInputs||c.length>2?"":`${l[0]>1}_${l[1]>1}`;a+=`${b}_${C}_${d?f:""}_${c.length}_${S}_${k}_${w}_${m}_${x}_${y}_${E}_${o}`}else{let l=i.isUniform?"uniform":i.texData.texShape;a+=`${i.shape}_${l}_${o}`}});let r=e.userCode,s=e.constructor.name;return s+="_"+a+"_"+r+`${fe().getNumber("WEBGL_VERSION")}`,s}function ss(e){return fe().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var bCe=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=Uy.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=Is();this.outputShape=e,this.enableShapeUniforms=ss(this.outputShape.length),this.userCode=`
1044      ivec3 outCoordsFromFlatIndex(int index) {
1045        ${this.enableShapeUniforms?F2(["r","c","d"],e):xp(["r","c","d"],e)}
1046        return ivec3(r, c, d);
1047      }
1048
1049      void main() {
1050        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
1051        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);
1052
1053        vec4 result = vec4(0.);
1054
1055        for (int i=0; i<4; i++) {
1056          int flatIndex = index + i;
1057          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
1058          result[i] = getA(rc.x, rc.y, rc.z);
1059        }
1060
1061        ${t.output} = result;
1062      }
1063    `}},vCe=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Uy.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=Is();this.outputShape=e,this.enableShapeUniforms=ss(this.outputShape.length),this.userCode=`
1064      ivec3 outCoordsFromFlatIndex(int index) {
1065        ${this.enableShapeUniforms?F2(["r","c","d"],e):xp(["r","c","d"],e)}
1066        return ivec3(r, c, d);
1067      }
1068
1069      void main() {
1070        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
1071        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);
1072
1073        vec4 result = vec4(0.);
1074
1075        for (int i=0; i<4; i++) {
1076          int flatIndex = index + i;
1077          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
1078          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));
1079        }
1080
1081        ${t.output} = result;
1082      }
1083    `}},wCe=class{constructor(e){this.variableNames=["A"],this.outTexUsage=Ti.DOWNLOAD;let t=Is();this.outputShape=e,this.userCode=`
1084      ${i9}
1085
1086      void main() {
1087        float x = getAAtOutCoords();
1088        ${t.output} = encode_float(x);
1089      }
1090    `}},SCe=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Ti.DOWNLOAD;let t=Is();this.outputShape=e,this.userCode=`
1091      ${i9}
1092
1093      void main() {
1094        ivec3 coords = getOutputCoords();
1095        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
1096        ${t.output} = encode_float(x);
1097      }
1098    `}},kCe={R:0,G:1,B:2,A:3},H$=class{constructor(e,t=!1,n="RGBA"){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let a=Is();this.outputShape=e,this.enableShapeUniforms=ss(this.outputShape.length);let r="result";t&&(r="floor(result * 255. + 0.5)");let s="";for(let i=0;i<n.length;i++){let o=n[i];s+=`
1099          if(offset == ${i}) {
1100            result = values[${kCe[o]}];
1101          }`}this.userCode=`
1102      ${this.enableShapeUniforms?b4():y4(e)}
1103
1104      void main() {
1105        ivec3 coords = getOutputCoords();
1106        int flatIndex = getFlatIndex(coords);
1107        float result = 0.;
1108        int offset = imod(flatIndex, ${n.length});
1109
1110        flatIndex = idiv(flatIndex, ${n.length}, 1.);
1111
1112        int r = flatIndex / texShape[1];

1174if(r==null)throw new Error("All WebGL1 implementations are expected to offer OES_vertex_array_object.");this.createVertexArray=()=>at(e,()=>r.createVertexArrayOES()),this.bindVertexArray=s=>at(e,()=>r.bindVertexArrayOES(s)),this.deleteVertexArray=s=>at(e,()=>r.deleteVertexArrayOES(s)),this.getVertexArray=()=>at(e,()=>e.getParameter(r.VERTEX_ARRAY_BINDING_OES))}let n="WEBGL_color_buffer_float",a="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),fe().getNumber("WEBGL_VERSION")===1){let r="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=qx(this.gl,r),Ai(this.gl,s))this.textureHalfFloatExtension=qx(this.gl,s);else if(fe().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(n),Ai(this.gl,a))this.colorBufferHalfFloatExtension=qx(this.gl,a);else if(fe().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",Ai(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(Ai(this.gl,a))this.colorBufferHalfFloatExtension=this.gl.getExtension(a);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=p9(this.gl),this.indexBuffer=f9(this.gl),this.framebuffer=GU(this.gl),this.textureConfig=g4(this.gl,this.textureHalfFloatExtension)}get debug(){return fe().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&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."),this.outputTexture!=null&&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.");let e=this.gl;at(e,()=>e.finish()),at(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),at(e,()=>e.deleteFramebuffer(this.framebuffer)),at(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),at(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),at(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),m9(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),g9(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),x9(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),S9(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,a){this.throwIfDisposed(),w9(this.gl,e,t,n,a,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),b9(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),y9(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(TE(this.gl,this.framebuffer),this.outputTexture=null),at(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>C9(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,a,r,s){return E9(this.gl,e,t,n,a,r,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return N9(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let a=k9(this.gl,t,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),a}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,n;if(fe().getBool("WEBGL_FENCE_API_ENABLED")){let a=e,r=a.fenceSync(a.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let s=a.clientWaitSync(r,0,0);return s===a.ALREADY_SIGNALED||s===a.CONDITION_SATISFIED},t=r}else fe().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,fe().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>I9(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl;this.vertexShader==null&&(this.vertexShader=h9(t));let n=PU(t);at(t,()=>t.attachShader(n,this.vertexShader)),at(t,()=>t.attachShader(n,e)),zU(t,n);let a=Object.assign(n,{vao:this.createVertexArray()});return this.debug&&iv(t,a),a}buildVao(e){this.setProgram(e),this.bindVertexArray(e.vao);let t=this.gl;at(t,()=>t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,this.indexBuffer)),v9(t,e,this.vertexBuffer)}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&(at(this.gl,()=>this.gl.deleteProgram(e)),this.deleteVertexArray(e.vao))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&iv(this.gl,this.program),at(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?KU(this.gl,e,t):XU(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),at(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,n){this.throwIfDisposed(),this.throwIfNoProgram(),YU(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[a,r]=Cg(t,n);this.setOutputMatrixTextureDriver(e,a,r)}setOutputMatrixWriteRegion(e,t,n,a){this.setOutputMatrixWriteRegionDriver(n,e,a,t)}setOutputPackedMatrixWriteRegion(e,t,n,a){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&iv(this.gl,this.program),Kx(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;if(this.debug){let t=this.getVertexArray();console.assert(t===this.program.vao,"VAO changed between setProgram and executeProgram!"),this.debugValidate()}at(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),at(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=qx(this.gl,fe().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension}getQueryTimerExtensionWebGL2(){return this.getQueryTimerExtension()}getQueryTimerExtensionWebGL1(){return this.getQueryTimerExtension()}beginQuery(){if(fe().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,a=this.getQueryTimerExtensionWebGL2(),r=n.createQuery();return n.beginQuery(a.TIME_ELAPSED_EXT,r),r}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(fe().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,n=this.getQueryTimerExtensionWebGL2();t.endQuery(n.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await R.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,fe().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,fe().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let n=this.gl;return n.getQueryParameter(e,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(e,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let n=this.gl,a=this.getQueryTimerExtensionWebGL2(),r=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(a.GPU_DISJOINT_EXT)),r&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),a=n.getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),a&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=CCe(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:n}=this.itemsToPoll[t];n()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){if(this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),this.itemsToPoll.length>1)return;let n;"setTimeoutCustom"in fe().platform&&(n=fe().platform.setTimeoutCustom.bind(fe().platform)),R.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0),()=>0,null,n)}bindTextureToFrameBuffer(e){this.throwIfDisposed(),ov(this.gl,e,this.framebuffer),this.debug&&Kx(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(ov(this.gl,this.outputTexture,this.framebuffer),this.debug&&Kx(this.gl)):TE(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let n=t();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(e,t,n){this.throwIfDisposed();let a=this.gl;ov(a,e,this.framebuffer),this.debug&&Kx(a),this.outputTexture=e,at(a,()=>a.viewport(0,0,t,n)),at(a,()=>a.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,a){this.throwIfDisposed(),at(this.gl,()=>this.gl.scissor(e,t,n,a))}throwIfDisposed(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")}throwIfNoProgram(){if(this.program==null)throw new Error("No GPU program is currently set.")}};function CCe(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{addImpl:ECe,bincountImpl:T9,bincountReduceImpl:ICe,bitwiseAndImpl:TCe,castImpl:ACe,ceilImpl:_Ce,concatImpl:jCe,equalImpl:DCe,expImpl:RCe,expm1Impl:MCe,floorImpl:$Ce,gatherNdImpl:BCe,gatherV2Impl:FCe,greaterImpl:OCe,greaterEqualImpl:LCe,lessImpl:PCe,lessEqualImpl:zCe,linSpaceImpl:UCe,logImpl:WCe,maxImpl:VCe,maximumImpl:HCe,minimumImpl:GCe,multiplyImpl:qCe,negImpl:KCe,notEqualImpl:XCe,prodImpl:YCe,raggedGatherImpl:JCe,raggedRangeImpl:QCe,raggedTensorToTensorImpl:ZCe,rangeImpl:eEe,rsqrtImpl:tEe,scatterImpl:nEe,sigmoidImpl:aEe,simpleAbsImpl:A9,sliceImpl:rEe,sparseFillEmptyRowsImpl:sEe,sparseReshapeImpl:iEe,sparseSegmentReductionImpl:_9,sqrtImpl:oEe,staticRegexReplaceImpl:lEe,stridedSliceImpl:uEe,stringNGramsImpl:cEe,stringSplitImpl:dEe,stringToHashBucketFastImpl:hEe,subImpl:pEe,tileImpl:fEe,topKImpl:mEe,transposeImpl:E4,uniqueImpl:gEe}=e4;function j9(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function xs(e,t){return t===1?[e]:j9(e,t)}function xEe(e,t){if(e===1)return"rc";let n="";for(let a=0;a<e;a++)n+=t[a],a<e-1&&(n+=",");return n}var yEe=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=ss(this.outputShape.length),this.rank===0)this.userCode=`
1175        void main() {
1176          setOutput(vec4(getA(), 0., 0., 0.));
1177        }
1178      `;else{let t=xs("rc",this.rank),n=ea(this.rank),a=this.getOutOfBoundsCondition(t),r=this.getSetup(t),s=this.getOutput(t);this.userCode=`
1179        void main() {
1180          ${n} rc = getOutputCoords();
1181
1182          if(${a}) {
1183            setOutput(vec4(0));
1184          } else {
1185            ${r}
1186
1187            setOutput(vec4(${s}));
1188          }
1189        }
1190      `}}getSourceCoordsArr(e){let t=[];for(let n=0;n<=1;n++)for(let a=0;a<=1;a++){let r=`${n===0?"r":"rp1"}, ${a===0?"c":"cp1"}`;for(let s=2;s<this.rank;s++)r=`${e[e.length-1-s]},`+r;t.push(r)}return t}getOutOfBoundsCondition(e){if(this.rank===1)return`rc > ${this.enableShapeUniforms?"outShape":this.outputShape[0]}`;let t="";for(let n=this.rank-2;n<this.rank;n++)t+=`${e[n]} >= ${this.enableShapeUniforms?`outShape[${n}]`:this.outputShape[n]}`,n<this.rank-1&&(t+="||");return t}getSetup(e){if(this.rank===1)return"";let t=e.slice(-2),n=this.enableShapeUniforms?`outShape[${this.rank} - 1]`:this.outputShape[this.rank-1],a=this.enableShapeUniforms?`outShape[${this.rank} - 2]`:this.outputShape[this.rank-2];return`
1191      int r = ${t[0]};
1192      int c = ${t[1]};
1193      int rp1 = r + 1;
1194      int cp1 = c + 1;
1195
1196      bool cEdge = cp1 >= ${n};
1197      bool rEdge = rp1 >= ${a};
1198    `}getOutput(e){let t=this.getSourceCoordsArr(e);return this.rank===1?`getA(rc), (rc + 1 >= ${this.enableShapeUniforms?"outShape":this.outputShape[0]} ? 0. : getA(rc + 1)), 0, 0`:`getA(${t[0]}),
1199            cEdge ? 0. : getA(${t[1]}),
1200            rEdge ? 0. : getA(${t[2]}),
1201            rEdge || cEdge ? 0. : getA(${t[3]})`}},D9=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=ss(this.outputShape.length);let n="";for(let a=0;a<4;a++){let r="thisRC = rc;";a%2===1&&(r+="thisRC.z += 1;"),a>1&&(r+="thisRC.y += 1;"),n+=`
1202        ${r}
1203        ${a>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
1204          int flatIndex = getFlatIndex(thisRC);
1205
1206          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
1207          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));
1208
1209          result[${a}] =
1210            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
1211        ${a>0?"}":""}
1212      `}this.userCode=`
1213      ${bEe(t,this.enableShapeUniforms)}
1214      ${this.enableShapeUniforms?b4():y4(e)}
1215
1216      void main() {
1217        ivec3 rc = getOutputCoords();
1218
1219        vec4 result = vec4(0.);
1220
1221        ivec3 thisRC;
1222        int rows = ${this.enableShapeUniforms?"outShape[1]":e[1]};
1223        int cols = ${this.enableShapeUniforms?"outShape[2]":e[2]};
1224
1225        ${n}
1226
1227        setOutput(result);
1228      }
1229    `}};function bEe(e,t){return`
1230    ivec3 inputCoordsFromReshapedOutCoords(int index) {
1231      ${t?RNe(["r","c","d"],"inputShape"):xp(["r","c","d"],e)}
1232      return ivec3(r, c, d);
1233    }
1234  `}var vEe=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.usedTextures={},this.logEnabled=!1}acquireTexture(e,t,n){let a=q$(t,n),r=K$(e,a,n);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let s=G$(e,a,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[r].pop();return this.usedTextures[r].push(o),o}let i;return a===Vr.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):a===Vr.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):a===Vr.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):a===Vr.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):a===Vr.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,a){if(this.freeTextures==null)return;let r=q$(n,a),s=K$(t,r,a);s in this.freeTextures||(this.freeTextures[s]=[]);let i=G$(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,a),o=fe().getNumber("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],d=l&&l.indexOf(e);if(d==null||d<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l[d]=l[l.length-1],l.pop(),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function wEe(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;if(t===n.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function G$(e,t,n,a,r){let s=SEe(t,a),i;if(r){let[l,d]=Cg(e[0],e[1]);i=l*d}else{let[l,d]=Zb(e[0],e[1]);i=l*d}let o=wEe(n,s);return i*o}function SEe(e,t){switch(e){case Vr.PACKED_2X2_FLOAT32:return N4(t);case Vr.PACKED_2X2_FLOAT16:return C4(t);case Vr.UNPACKED_FLOAT32:return w4(t);case Vr.UNPACKED_FLOAT16:return S4(t);case Vr.PACKED_4X1_UNSIGNED_BYTE:return k4(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function kEe(e){return fe().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?Vr.PACKED_2X2_FLOAT32:Vr.UNPACKED_FLOAT32:e?Vr.PACKED_2X2_FLOAT16:Vr.UNPACKED_FLOAT16}function q$(e,t){if(e===Ti.UPLOAD)return Vr.PACKED_2X2_FLOAT32;if(e===Ti.RENDER||e==null)return kEe(t);if(e===Ti.DOWNLOAD||e===Ti.PIXELS)return Vr.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function K$(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var Yo=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=ss(this.outputShape.length),this.userCode=`
1235      float unaryOperation(float x) {
1236        ${t}
1237      }
1238
1239      void main() {
1240        float x = getAAtOutCoords();
1241        float y = unaryOperation(x);
1242
1243        setOutput(y);
1244      }
1245    `}},ro="if (isnan(x)) return x;",NEe="return x;",X$="return abs(x);",CEe="return (x >= 0.0) ? x : (exp(x) - 1.0);",EEe=ro+`
1246  return (x < 0.0) ? 0.0 : x;
1247`,IEe=ro+`
1248  return (x < 0.0) ? 0.0 : min(6.0, x);
1249`,Mu="return x;",TEe="return 1.0 / (1.0 + exp(-1.0 * x));",AEe="return x;",_Ee=`
1250  vec4 result;
1251
1252  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
1253  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);
1254  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);
1255  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
1256
1257  return result;
1258`,jEe=`
1259  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
1260  bvec4 isNaN = isnan(x);
1261
1262  result.r = isNaN.r ? x.r : result.r;
1263  result.g = isNaN.g ? x.g : result.g;
1264  result.b = isNaN.b ? x.b : result.b;
1265  result.a = isNaN.a ? x.a : result.a;
1266
1267  return result;
1268`,DEe=`
1269  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
1270  bvec4 isNaN = isnan(x);
1271
1272  result.r = isNaN.r ? x.r : result.r;
1273  result.g = isNaN.g ? x.g : result.g;
1274  result.b = isNaN.b ? x.b : result.b;
1275  result.a = isNaN.a ? x.a : result.a;
1276
1277  return result;
1278`,REe="return 1.0 / (1.0 + exp(-1.0 * x));",zu=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=ss(this.outputShape.length),this.userCode=`
1279      vec4 unaryOperation(vec4 x) {
1280        ${t}
1281      }
1282
1283      void main() {
1284        vec4 x = getAAtOutCoords();
1285        vec4 y = unaryOperation(x);
1286
1287        setOutput(y);
1288      }
1289    `}},MEe=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e,this.enableShapeUniforms=ss(this.outputShape.length);let t=e.length,n=xs("rc",t),a=ea(t),r=xEe(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
1290      void main() {
1291        ${a} rc = getOutputCoords();
1292        vec4 packedInput = getA(${r});
1293
1294        setOutput(getChannel(packedInput, ${i}));
1295      }
1296    `}},$Ee=cl.whereImpl,BEe=1e-7,FEe=1e-4,BN={};function OEe(e){return e in BN||(BN[e]={}),BN[e]}var LEe=fe().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),PEe=600;function zEe(){return fe().global.screen==null?1024:fe().global.screen.height*fe().global.screen.width*window.devicePixelRatio*PEe/1024/1024}var I4=class R9 extends tb{nextDataId(){return R9.nextDataId++}constructor(t){if(super(),this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!fe().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let n;if(t!=null){if(t instanceof cv)n=t;else{let a=jo(fe().getNumber("WEBGL_VERSION"),t);n=new cv(a)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let a=jo(fe().getNumber("WEBGL_VERSION"));n=new cv(a),this.binaryCache=OEe(fe().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=n,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new vEe(this.gpgpu),this.numMBBeforeWarning=zEe(),this.texData=new mw(this,Ji())}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}writeTexture(t,n,a,r,s,i){let o=this.makeTensorInfo(n,a),l=this.texData.get(o.dataId);l.isPacked=!1,l.texture={texture:t,texShape:[r,s]},l.texShape=[r,s];let d=Xx(n),c=new H$(d,!1,i),f=this.runWebGLProgram(c,[o],a,[[r,s]]);return f.shape=n,l.texture=null,this.disposeIntermediateTensorInfo(o),f.dataId}write(t,n,a){if((fe().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||fe().getBool("DEBUG"))&&this.checkNumericalProblems(t),a==="complex64"&&t!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let r={id:this.nextDataId()};return this.texData.set(r,{shape:n,dtype:a,values:t,usage:Ti.UPLOAD,refCount:1}),r}refCount(t){return this.texData.has(t)?this.texData.get(t).refCount:0}incRef(t){let n=this.texData.get(t);n.refCount++}decRef(t){if(this.texData.has(t)){let n=this.texData.get(t);n.refCount--}}move(t,n,a,r,s){if(fe().getBool("DEBUG")&&this.checkNumericalProblems(n),r==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(t,{shape:a,dtype:r,values:n,usage:Ti.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(t){this.disposeData(t.dataId)}readSync(t){let n=this.texData.get(t),{values:a,dtype:r,complexTensorInfos:s,slice:i,shape:o,isPacked:l}=n;if(i!=null){let m;l?m=new zu(o,Mu):m=new Yo(o,Mu);let x=this.runWebGLProgram(m,[{dataId:t,shape:o,dtype:r}],r),y=this.readSync(x.dataId);return this.disposeIntermediateTensorInfo(x),y}if(a!=null)return this.convertAndCacheOnCPU(t);if(r==="string")return a;let d=this.activeTimers!=null,c;d&&(c=R.now());let f;if(r==="complex64"){let m=this.readSync(s.real.dataId),x=this.readSync(s.imag.dataId);f=W.mergeRealAndImagArrays(m,x)}else f=this.getValuesFromTexture(t);return d&&(this.downloadWaitMs+=R.now()-c),this.convertAndCacheOnCPU(t,f)}async read(t){if(this.pendingRead.has(t)){let y=this.pendingRead.get(t);return new Promise(b=>y.push(b))}let n=this.texData.get(t),{values:a,shape:r,slice:s,dtype:i,complexTensorInfos:o,isPacked:l}=n;if(s!=null){let y;l?y=new zu(r,Mu):y=new Yo(r,Mu);let b=this.runWebGLProgram(y,[{dataId:t,shape:r,dtype:i}],i),w=this.read(b.dataId);return this.disposeIntermediateTensorInfo(b),w}if(a!=null)return this.convertAndCacheOnCPU(t);if(fe().getBool("DEBUG")&&!fe().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&fe().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let d=null,c;if(i!=="complex64"&&fe().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(t);let y=this.texData.get(c.dataId);d=this.gpgpu.createBufferFromTexture(y.texture.texture,...P1(r))}this.pendingRead.set(t,[]),i!=="complex64"&&await this.gpgpu.createAndWaitForFence();let f;if(i==="complex64"){let y=await Promise.all([this.read(o.real.dataId),this.read(o.imag.dataId)]),b=y[0],w=y[1];f=W.mergeRealAndImagArrays(b,w)}else if(d==null)f=this.getValuesFromTexture(t);else{let y=R.sizeFromShape(r);f=this.gpgpu.downloadFloat32MatrixFromBuffer(d,y)}if(c!=null&&this.disposeIntermediateTensorInfo(c),d!=null){let y=this.gpgpu.gl;at(y,()=>y.deleteBuffer(d))}let m=this.convertAndCacheOnCPU(t,f),x=this.pendingRead.get(t);return this.pendingRead.delete(t),x.forEach(y=>y(m)),this.pendingDisposal.has(t)&&(this.pendingDisposal.delete(t),this.disposeData(t)&&Ji().removeDataId(t,this),this.pendingDeletes--),m}readToGPU(t,n={}){let a=this.texData.get(t),{values:r,shape:s,slice:i,dtype:o,isPacked:l,texture:d}=a;if(o==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(i!=null){let x;l?x=new zu(s,Mu):x=new Yo(s,Mu);let y=this.runWebGLProgram(x,[{dataId:t,shape:s,dtype:o}],o),b=this.readToGPU(y,n);return this.disposeIntermediateTensorInfo(y),b}if(d==null)throw r!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let c=this.decode(t,n.customTexShape),f=Ji().makeTensorFromTensorInfo(c),m=this.texData.get(c.dataId);return Object.assign({tensorRef:f},m.texture)}bufferSync(t){let n=this.readSync(t.dataId);if(t.dtype==="string")try{let a=n.map(r=>R.decodeString(r));return Zt(t.shape,t.dtype,a)}catch{throw new Error("Failed to decode encoded string bytes into utf-8")}return Zt(t.shape,t.dtype,n)}checkNumericalProblems(t){if(t!=null)for(let n=0;n<t.length;n++){let a=t[n];if(!BU(a))throw fe().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${a} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${a} cannot be represented on this device.`)}}getValuesFromTexture(t){let{shape:n,dtype:a,isPacked:r}=this.texData.get(t),s=R.sizeFromShape(n);if(fe().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let m=this.decode(t),x=this.texData.get(m.dataId),y=this.gpgpu.downloadMatrixFromPackedTexture(x.texture.texture,...P1(n)).subarray(0,s);return this.disposeIntermediateTensorInfo(m),y}let i=fe().getBool("WEBGL_PACK")&&r===!0,o=i?Xx(n):n,l=i?new SCe(o):new wCe(o),d=this.runWebGLProgram(l,[{shape:o,dtype:a,dataId:t}],"float32"),c=this.texData.get(d.dataId),f=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture.texture,c.texShape[0],c.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(d),f}timerAvailable(){return fe().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(t){let n=this.activeTimers,a=[],r=!1;this.programTimersStack==null?(this.programTimersStack=a,r=!0):this.activeTimers.push(a),this.activeTimers=a,t();let s=R.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),i=R.flatten(this.activeTimers.map(l=>

1296l.name)).filter(l=>l!=null);this.activeTimers=n,r&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(fe().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let l=await Promise.all(s);o.kernelMs=R.sum(l),o.getExtraProfileInfo=()=>l.map((d,c)=>({name:i[c],ms:d})).map(d=>`${d.name}: ${d.ms}`).join(", ")}else o.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,o})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return fe().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:R.now(),endMs:null}}endTimer(t){return fe().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),t):(t.endMs=R.now(),t)}async getQueryTime(t){if(fe().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(t);let n=t;return n.endMs-n.startMs}disposeData(t,n=!1){if(this.pendingDisposal.has(t))return!1;if(!this.texData.has(t))return!0;if(n?this.texData.get(t).refCount=0:this.texData.get(t).refCount--,!n&&this.texData.get(t).refCount>0)return!1;if(this.pendingRead.has(t))return this.pendingDisposal.add(t),this.pendingDeletes++,!1;this.releaseGPUData(t);let{complexTensorInfos:a}=this.texData.get(t);return a!=null&&(this.disposeData(a.real.dataId,n),this.disposeData(a.imag.dataId,n)),this.texData.delete(t),!0}releaseGPUData(t){let{texture:n,dtype:a,texShape:r,usage:s,isPacked:i,slice:o}=this.texData.get(t),l=o&&o.origDataId||t,d=this.dataRefCount.get(l);d>1?this.dataRefCount.set(l,d-1):(this.dataRefCount.delete(l),n!=null&&(this.numBytesInGPU-=this.computeBytes(r,a),this.textureManager.releaseTexture(n,r,s,i)));let c=this.texData.get(t);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(t){return this.uploadToGPU(t),this.texData.get(t).texture.texture}getDataInfo(t){return this.texData.get(t)}shouldExecuteOnCPU(t,n=LEe){return fe().getBool("WEBGL_CPU_FORWARD")&&t.every(a=>this.texData.get(a.dataId).texture==null&&R.sizeFromShape(a.shape)<n)}getGPGPUContext(){return this.gpgpu}where(t){W.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let n=t.dataSync();return $Ee(t.shape,n)}packedUnaryOp(t,n,a){let r=new zu(t.shape,n),s=this.compileAndRun(r,[t],a);return Ji().makeTensorFromTensorInfo(s)}abs(t){if(this.shouldExecuteOnCPU([t])&&t.dtype!=="complex64"){let r=A9(this.texData.get(t.dataId).values);return this.makeOutput(t.shape,t.dtype,r)}if(fe().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,X$,t.dtype);let n=new Yo(t.shape,X$),a=this.compileAndRun(n,[t]);return Ji().makeTensorFromTensorInfo(a)}makeTensorInfo(t,n,a){let r;if(n==="string"&&a!=null&&a.length>0&&R.isString(a[0])){let s=a.map(i=>R.encodeString(i));r=this.write(s,t,n)}else r=this.write(a,t,n);return this.texData.get(r).usage=null,{dataId:r,shape:t,dtype:n}}makeOutput(t,n,a){return Ji().makeTensorFromTensorInfo(this.makeTensorInfo(t,n,a),this)}unpackTensor(t){let n=new MEe(t.shape);return this.runWebGLProgram(n,[t],t.dtype)}packTensor(t){let n=new yEe(t.shape);return this.runWebGLProgram(n,[t],t.dtype,null,!0)}packedReshape(t,n){let a=[Ld(t.shape),...Pd(t.shape)],r={dtype:t.dtype,shape:a,dataId:t.dataId},s=[Ld(n),...Pd(n)],i=new D9(s,a),o=!0,l=[a],d=this.runWebGLProgram(i,[r],t.dtype,l,o);return{dataId:d.dataId,shape:n,dtype:d.dtype}}decode(t,n){let a=this.texData.get(t),{isPacked:r,shape:s,dtype:i}=a;if(n!=null){let m=R.sizeFromShape(s),x=n[0]*n[1]*4;R.assert(m<=x,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let o=Xx(s),l;r?l=new vCe(o):l=new bCe(o);let d=!0,c=[n??P1(o)],f=this.runWebGLProgram(l,[{shape:o,dtype:i,dataId:t}],i,c,d,n);return{dtype:i,shape:s,dataId:f.dataId}}runWebGLProgram(t,n,a,r,s=!1,i){let o=this.makeTensorInfo(t.outputShape,a),l=this.texData.get(o.dataId);if(t.packedOutput&&(l.isPacked=!0),t.outPackingScheme===Uy.DENSE){let S=i??P1(t.outputShape);l.texShape=S.map(k=>k*2)}if(t.outTexUsage!=null&&(l.usage=t.outTexUsage),R.sizeFromShape(o.shape)===0)return l.values=R.getTypedArrayFromDType(o.dtype,0),o;let d=[],c=n.map(S=>{if(S.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let k=this.texData.get(S.dataId);if(k.texture==null){if(!t.packedInputs&&R.sizeFromShape(S.shape)<=fe().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:S.shape,texData:null,isUniform:!0,uniformValues:k.values};t.packedInputs&&(k.isPacked=!0,k.shape=S.shape)}if(this.uploadToGPU(S.dataId),!!k.isPacked!=!!t.packedInputs)S=k.isPacked?this.unpackTensor(S):this.packTensor(S),d.push(S),k=this.texData.get(S.dataId);else if(k.isPacked&&!Wy(k.shape,S.shape)){let C=S,E=S.shape;S.shape=k.shape,S=this.packedReshape(S,E),d.push(S),k=this.texData.get(S.dataId),C.shape=E}return{shape:S.shape,texData:k,isUniform:!1}});this.uploadToGPU(o.dataId);let f={shape:o.shape,texData:l,isUniform:!1},m=yCe(t,c,f),x=this.getAndSaveBinary(m,()=>gCe(this.gpgpu,t,c,f)),y=this.activeTimers!=null,b;y&&(b=this.startTimer()),fe().get("ENGINE_COMPILE_ONLY")||xCe(this.gpgpu,x,c,f,r),d.forEach(S=>this.disposeIntermediateTensorInfo(S)),y&&(b=this.endTimer(b),this.activeTimers.push({name:t.constructor.name,query:this.getQueryTime(b)}));let w=fe().getNumber("WEBGL_FLUSH_THRESHOLD");if(w>0){let S=R.now();S-this.lastGlFlushTime>w&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=S)}if(!fe().getBool("WEBGL_LAZILY_UNPACK")&&l.isPacked&&s===!1){let S=this.unpackTensor(o);return this.disposeIntermediateTensorInfo(o),S}return o}compileAndRun(t,n,a,r,s=!1){return a=a||n[0].dtype,this.runWebGLProgram(t,n,a,r,s)}getAndSaveBinary(t,n){return t in this.binaryCache||(this.binaryCache[t]=n()),this.binaryCache[t]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(fe().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(t=>{this.gpgpu.deleteProgram(this.binaryCache[t].webGLProgram),delete this.binaryCache[t]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement<"u"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=ue(()=>{if(!fe().get("WEBGL_RENDER_FLOAT32_ENABLED")){let t=fe().getBool("DEBUG");fe().set("DEBUG",!1);let n=this.abs(Et(1e-8)).dataSync()[0];if(fe().set("DEBUG",t),n>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?BEe:FEe}uploadToGPU(t){let n=this.texData.get(t),{shape:a,dtype:r,values:s,texture:i,usage:o,isPacked:l}=n;if(i!=null)return;let d=this.activeTimers!=null,c;d&&(c=R.now());let f=n.texShape;if(f==null&&(f=ZU(a,l),n.texShape=f),s!=null){let m=Xx(a),x,y=f[1],b=f[0],w=s instanceof Uint8Array||s instanceof Uint8ClampedArray;(l||!w)&&([y,b]=Cg(f[0],f[1])),l?x=new NCe(m,w):x=new H$(m,w);let S=w?[b,y]:f,k=this.makeTensorInfo(S,r),C=this.texData.get(k.dataId);w?C.usage=Ti.PIXELS:C.usage=Ti.UPLOAD,C.texShape=S,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(k.dataId),y,b,s);let E=[[b,y]],T=this.runWebGLProgram(x,[k],r,E,!0),_=this.texData.get(T.dataId);n.texShape=_.texShape,n.isPacked=_.isPacked,n.usage=_.usage,fe().get("ENGINE_COMPILE_ONLY")?this.disposeData(T.dataId):(n.texture=_.texture,n.values=null,this.texData.delete(T.dataId)),this.disposeIntermediateTensorInfo(k),d&&(this.uploadWaitMs+=R.now()-c)}else{let m=this.acquireTexture(f,o,r,l);n.texture=m}}convertAndCacheOnCPU(t,n){let a=this.texData.get(t),{dtype:r}=a;return n!=null&&(a.values=UEe(n,r)),a.values}acquireTexture(t,n,a,r){if(this.numBytesInGPU+=this.computeBytes(t,a),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let s=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${s} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(t,n,r)}computeBytes(t,n){return t[0]*t[1]*R.bytesPerElement(n)}checkCompileCompletion(){for(let[,t]of Object.entries(this.binaryCache))this.checkCompletion_(t)}async checkCompileCompletionAsync(){let t=[];if(this.gpgpu.parallelCompilationExtension){for(let[,n]of Object.entries(this.binaryCache))t.push(this.checkCompletionAsync_(n));return Promise.all(t)}else{for(let[,n]of Object.entries(this.binaryCache)){let a=new Promise(r=>{try{this.checkCompletion_(n),r(!0)}catch(s){throw s}});t.push(a)}return Promise.all(t)}}async checkCompletionAsync_(t){return this.gpgpu.gl.getProgramParameter(t.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(t):(await gA(),this.checkCompletionAsync_(t))}checkCompletion_(t){if(this.gpgpu.gl.getProgramParameter(t.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(t.webGLProgram)),this.gpgpu.gl.getShaderParameter(t.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?(x4(t.source,this.gpgpu.gl.getShaderInfoLog(t.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let t of Object.values(this.binaryCache)){this.gpgpu.buildVao(t.webGLProgram);let{variablesLocations:n,customUniformLocations:a,infLoc:r,nanLoc:s,outShapeLocation:i,outShapeStridesLocation:o,outTexShapeLocation:l}=c9(this.gpgpu,t.program,t.webGLProgram);t.variablesLocations=n,t.customUniformLocations=a,t.infLoc=r,t.nanLoc=s,t.outShapeLocation=i,t.outShapeStridesLocation=o,t.outTexShapeLocation=l}}createTensorFromGPUData(t,n,a){t.channels=t.channels||"RGBA";let{texture:r,height:s,width:i,channels:o}=t,l=Ji().backend;if(!l.gpgpu.gl.isTexture(r))throw new Error("The texture is invali

1364let m=fe().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,x;return m?x=new jg(t,l.shape,d.shape,n):x=new zd(e,l.shape,d.shape),c.runWebGLProgram(x,[l,d],f)}}function Vy(e,t=!1){if(e==="linear")return t?AEe:NEe;if(e==="relu")return t?jEe:EEe;if(e==="elu")return t?_Ee:CEe;if(e==="relu6")return t?DEe:IEe;if(e==="prelu")return t?O9:F9;if(e==="leakyrelu")return t?B9:$9;if(e==="sigmoid")return t?REe:TEe;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var L9=class{constructor(e,t,n,a=!1,r=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n,this.enableShapeUniforms=ss(this.outputShape.length);let d=a?e[1]:e[2],c=Math.ceil(d/2),f=a?"i * 2, rc.y":"rc.y, i * 2",m=r?"rc.z, i * 2":"i * 2, rc.z",x=a?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],y=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],b="",w="";i&&(o?b=`vec4 activation(vec4 a) {
1365          vec4 b = getPreluActivationWeightsAtOutCoords();
1366          ${i}
1367        }`:l?b=`vec4 activation(vec4 a) {
1368          vec4 b = getLeakyreluAlphaAtOutCoords();
1369          ${i}
1370        }`:b=`vec4 activation(vec4 x) {
1371          ${i}
1372        }`,w="result = activation(result);");let S=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let k="rc.x",C="rc.x";e[0]<t[0]?k=`imod(rc.x, ${e[0]})`:t[0]<e[0]&&(C=`imod(rc.x, ${t[0]})`),this.userCode=`
1373      ${b}
1374      // Don't use uniform for sharedDimensionPacked for performance.
1375      const float sharedDimension = ${c}.0;
1376
1377      vec4 dot2x2ARowBCol(ivec3 rc) {
1378        vec4 result = vec4(0);
1379        int batchA = ${k};
1380        int batchB = ${C};
1381        for (int i = 0; i < ${c}; i++) {
1382          vec4 a = getMatrixA(batchA, ${f});
1383          vec4 b = getMatrixB(batchB, ${m});
1384
1385          // These swizzled products need to be separately added.

1583,attrs:{shape:x},backend:a});return a.disposeIntermediateTensorInfo(w),a.disposeIntermediateTensorInfo(k),d&&a.disposeIntermediateTensorInfo(c),C}function L2(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a;return sIe(r,s,i,n)}var iIe={kernelName:rp,backendName:"webgl",kernelFunc:L2};function Ss(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{perm:s}=a,i=n,o=r.shape.length,l=new Array(o);for(let c=0;c<l.length;c++)l[c]=r.shape[s[c]];let d;if(i.shouldExecuteOnCPU([r])){let c=i.texData.get(r.dataId).values,f=E4(c,r.shape,r.dtype,s,l);d=i.makeTensorInfo(l,r.dtype);let m=i.texData.get(d.dataId);m.values=f}else d=O2(r,s,i);return d}var oIe={kernelName:Fl,backendName:"webgl",kernelFunc:Ss},P9=1e3;function qv({a:e,b:t,transposeA:n,transposeB:a,backend:r,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let d=e.shape.length,c=t.shape.length,f=n?e.shape[d-2]:e.shape[d-1],m=a?t.shape[c-1]:t.shape[c-2],x=n?e.shape[d-1]:e.shape[d-2],y=a?t.shape[c-2]:t.shape[c-1],b=e.shape.slice(0,-2),w=t.shape.slice(0,-2),S=R.sizeFromShape(b),k=R.sizeFromShape(w),C=fg.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([x,y]);R.assert(f===m,()=>`Error in matMul: inner shapes (${f}) and (${m}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${a} must match.`);let E=n?[S,f,x]:[S,x,f],T=a?[k,y,m]:[k,m,y],_=et({inputs:{x:e},backend:r,attrs:{shape:E}}),A=et({inputs:{x:t},backend:r,attrs:{shape:T}}),$=[_,A],O=Math.max(S,k),z=n?_.shape[1]:_.shape[2],P=s!=null,j=i!=null,G=l==="leakyrelu",X=l!=null?Vy(l,!0):null,J=P||j||G||X!=null,V;if((x===1||y===1)&&z>P9&&J===!1){let F=_,H=A;n&&(F=Ss({inputs:{x:_},backend:r,attrs:{perm:[0,2,1]}}),$.push(F)),a&&(H=Ss({inputs:{x:A},backend:r,attrs:{perm:[0,2,1]}}),$.push(H));let B=y!==1,Y=y===1,ne=F;B&&(ne=et({inputs:{x:F},backend:r,attrs:{shape:[O,z,1]}}),$.push(ne));let ee=y===1?2:1,U=H;Y&&(U=et({inputs:{x:H},backend:r,attrs:{shape:[O,1,z]}}),$.push(U));let oe=A4({inputs:{a:ne,b:U},backend:r});V=L2({inputs:{x:oe},backend:r,attrs:{axis:ee,keepDims:!0}}),$.push(oe)}else{let F=Di(e.dtype,t.dtype),H=new L9(E,T,[O,x,y],n,a,P,X,j,G),B=[_,A];if(s!=null&&B.push(s),j&&B.push(i),G){let Y=r.makeTensorInfo([],"float32",R.createScalarValue(o,"float32"));B.push(Y),$.push(Y)}V=r.runWebGLProgram(H,B,F)}let Q=et({inputs:{x:V},backend:r,attrs:{shape:C}});$.push(V);for(let F of $)r.disposeIntermediateTensorInfo(F);return Q}function lIe(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:d,activation:c,leakyreluAlpha:f}=a;return qv({a:r,b:s,transposeA:l,transposeB:d,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:f,activation:c})}var uIe={kernelName:Nd,backendName:"webgl",kernelFunc:lIe},eB="return abs(x);";function cIe(e){let{inputs:t,backend:n}=e,{x:a}=t;if(n.shouldExecuteOnCPU([a])&&a.dtype!=="complex64"){let s=n.texData.get(a.dataId),i=A9(s.values);return n.makeTensorInfo(a.shape,a.dtype,i)}let r;return fe().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new zu(a.shape,eB):r=new Yo(a.shape,eB),n.runWebGLProgram(r,[a],a.dtype)}var dIe={kernelName:hm,backendName:"webgl",kernelFunc:cIe},hIe=ro+`
1584  if (abs(x) > 1.) {
1585    return NAN;
1586  }
1587  return acos(x);
1588`,pIe=kn({opSnippet:hIe}),fIe={kernelName:Gd,backendName:"webgl",kernelFunc:pIe},mIe=ro+`
1589  if (x < 1.0) return NAN;
1590return log(x + sqrt(x * x - 1.0));`,gIe=kn({opSnippet:mIe}),xIe={kernelName:qd,backendName:"webgl",kernelFunc:gIe},tB="return a + b;",yIe=Gr({opSnippet:tB,packedOpSnippet:tB,supportsComplex:!0,cpuKernelImpl:ECe}),bIe={kernelName:hc,backendName:"webgl",kernelFunc:yIe},vIe=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((r,s)=>`T${s}`);let n=[];this.variableNames.forEach(r=>{n.push(`float v${r} = get${r}AtOutCoords();`)});let a=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
1591      void main() {
1592        ${n.join(`
1593        `)}
1594
1595        float result = ${a};
1596        setOutput(result);
1597      }
1598    `}},wIe=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((r,s)=>`T${s}`);let n=[];this.variableNames.forEach(r=>{n.push(`vec4 v${r} = get${r}AtOutCoords();`)});let a=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
1599      void main() {
1600        ${n.join(`
1601        `)}
1602
1603        vec4 result = ${a};
1604        setOutput(result);
1605      }
1606    `}};function dv(e){let{inputs:t,backend:n}=e,a=t;if(a.length===1)return li({inputs:{x:a[0]},backend:n});if(a.length>fe().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(a.length/2),l=dv({inputs:a.slice(0,o),backend:n}),d=dv({inputs:a.slice(o),backend:n});return dv({inputs:[l,d],backend:n})}let r=a.map(o=>o.dtype).reduce((o,l)=>Di(o,l)),s=a.map(o=>o.shape),i=fe().getBool("WEBGL_PACK")?new wIe(a[0].shape,s):new vIe(a[0].shape,s);return n.runWebGLProgram(i,a,r)}var SIe={kernelName:Kd,backendName:"webgl",kernelFunc:dv};function kIe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a,o=r.shape.length,l=R.parseAxisParam(s,r.shape),d=l,c=W.getAxesPermutation(d,o),f=r;c!=null&&(f=Ss({inputs:{x:r},backend:n,attrs:{perm:c}}),d=W.getInnerMostAxes(d.length,o)),W.assertAxesAreInnerMostDims("all",d,o);let[m,x]=W.computeOutAndReduceShapes(f.shape,d),y=R.sizeFromShape(x),b=et({inputs:{x:f},backend:n,attrs:{shape:[-1,y]}}),w=vp(b,b.dtype,"all",n),S;if(i){let k=W.expandShapeToKeepDim(m,l);S=et({inputs:{x:w},backend:n,attrs:{shape:k}})}else S=et({inputs:{x:w},backend:n,attrs:{shape:m}});return n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(w),c!=null&&n.disposeIntermediateTensorInfo(f),S}var NIe={kernelName:pm,backendName:"webgl",kernelFunc:kIe};function CIe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a,o=r.shape.length,l=R.parseAxisParam(s,r.shape),d=l,c=W.getAxesPermutation(d,o),f=r;c!=null&&(f=Ss({inputs:{x:r},backend:n,attrs:{perm:c}}),d=W.getInnerMostAxes(d.length,o)),W.assertAxesAreInnerMostDims("any",d,o);let[m,x]=W.computeOutAndReduceShapes(f.shape,d),y=R.sizeFromShape(x),b=et({inputs:{x:f},backend:n,attrs:{shape:[-1,y]}}),w=vp(b,b.dtype,"any",n),S;if(i){let k=W.expandShapeToKeepDim(m,l);S=et({inputs:{x:w},backend:n,attrs:{shape:k}})}else S=et({inputs:{x:w},backend:n,attrs:{shape:m}});return n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(w),c!=null&&n.disposeIntermediateTensorInfo(f),S}var EIe={kernelName:fm,backendName:"webgl",kernelFunc:CIe},IIe=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:a,batchSize:r,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[r,s];let i=t==="max"?">":"<",o=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
1607      void main() {
1608        ivec2 coords = getOutputCoords();
1609        int batch = coords[0];
1610        int outIdx = coords[1];
1611        int inOffset = outIdx * ${a};
1612
1613        int bestIndex = inOffset;
1614        float bestValue = getA(batch, bestIndex);
1615
1616        for (int i = 0; i < ${a}; i++) {
1617          int inIdx = ${o};
1618          float candidate = getA(batch, inIdx);
1619          if (candidate ${i} bestValue) {
1620            bestValue = candidate;
1621            bestIndex = inIdx;
1622          }
1623        }
1624        setOutput(float(bestIndex));
1625      }
1626    `}},TIe=class{constructor(e,t,n,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,R.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let r=e[e.length-1],s=Math.ceil(r/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),a||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=ea(o),d=xs("coords",o),c,f;if(s===1){f=o+1;let A=ea(f);c=`
1627        ${A} sourceLocR = ${A}(${d.join()}, 0);
1628        ++${d[o-1]};
1629        ${A} sourceLocG = ${A}(${d.join()}, 0);
1630        ++${d[o-2]};
1631        ${A} sourceLocA = ${A}(${d.join()}, 0);
1632        --${d[o-1]};
1633        ${A} sourceLocB = ${A}(${d.join()}, 0);
1634        --${d[o-2]};`}else f=o,c=`
1635        ${l} sourceLocR = coords;
1636        ++${d[o-1]};
1637        ${l} sourceLocG = coords;
1638        ++${d[o-2]};
1639        ${l} sourceLocA = coords;
1640        --${d[o-1]};
1641        ${l} sourceLocB = coords;
1642        --${d[o-2]};`;let m=["x","y","z","w","u","v"].slice(0,f),x="."+m[f-1],y=m.map(A=>"int "+A),b=xs("sourceLocR",f-1).concat("inIdx.r"),w=xs("sourceLocG",f-1).concat("inIdx.g"),S=xs("sourceLocB",f-1).concat("inIdx.b"),k=xs("sourceLocA",f-1).concat("inIdx.a"),C=n==="max"?"greaterThan":"lessThan",E=a?"":`
1643          inIdx = round(vec4(getBestIndicesAChannel(${b.join()}),
1644                             getBestIndicesAChannel(${w.join()}),
1645                             getBestIndicesAChannel(${S.join()}),
1646                             getBestIndicesAChannel(${k.join()})));`,T=`vec4(
1647            getAChannel(${b.join()}),
1648            hasNextCol ? getAChannel(${w.join()}) : 0.,
1649            hasNextRow ? getAChannel(${S.join()}) : 0.,
1650            hasNextRow && hasNextCol ? getAChannel(${k.join()}) : 0.)`,_=a?"":`
1651      float getBestIndicesAChannel(${y.join()}) {
1652        return getChannel(getBestIndicesA(${m.join()}),
1653                                          vec2(${m.slice(-2).join()}));
1654      }`;this.userCode=`
1655      float getAChannel(${y.join()}) {
1656        return getChannel(getA(${m.join()}),
1657                               vec2(${m.slice(-2).join()}));
1658      }
1659      ${_}
1660      void main() {
1661        ${l} coords = getOutputCoords();
1662        bool hasNextCol = ${d[o-1]} < ${i[o-1]-1};
1663        bool hasNextRow = ${d[o-2]} < ${i[o-2]-1};
1664        ${c}
1665        ivec4 srcIdx = ivec4(sourceLocR${x}, sourceLocG${x},
1666          sourceLocB${x}, sourceLocA${x}) * ${t};
1667        ivec4 inIdx = srcIdx;
1668        vec4 bestIndex = vec4(inIdx);
1669        vec4 bestValue = ${T};
1670
1671        for (int i = 0; i < ${t}; i++) {
1672          inIdx = srcIdx;
1673          ${E}
1674          vec4 candidate = ${T};
1675          bvec4 nan = isnan(candidate);
1676          bvec4 replace = bvec4(
1677            vec4(${C}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));
1678
1679          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,
1680                           replace.y  ? candidate.y : bestValue.y,
1681                           replace.z  ? candidate.z : bestValue.z,
1682                           replace.w  ? candidate.w : bestValue.w);
1683          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));
1684          srcIdx++;
1685        }
1686        setOutput(bestIndex);
1687      }
1688    `}};function z9(e,t,n,a=null){let r=t.shape[0],s=t.shape[1];a!=null&&(r=a.shape[0],s=a.shape[1]);let i=W.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:r,outSize:Math.ceil(s/i)},l=new IIe(o,n,a==null),d=[t];a!=null&&d.push(a);let c=e.runWebGLProgram(l,d,"int32");if(c.shape[1]===1)return c;let f=z9(e,t,n,c);return e.disposeIntermediateTensorInfo(c),f}function U9(e,t,n,a=null){let r=a!=null?a.shape:t.shape,s=r[r.length-1],i=W.computeOptimalWindowSize(s),o=new TIe(r,i,n,a==null),l=a==null?[t]:[t,a],d=e.runWebGLProgram(o,l,"int32");if(d.shape.length===t.shape.length){let c=U9(e,t,n,d);return e.disposeIntermediateTensorInfo(d),c}return d}function W9(e,t,n,a){let r=[n];if(W.assertAxesAreInnerMostDims("arg"+a.charAt(0).toUpperCase()+a.slice(1),r,t.shape.length),!fe().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],i=e.texData.get(t.dataId),o=i!==null&&i.isPacked,l=t;o&&(l=e.unpackTensor(t),s.push(l));let[d,c]=W.computeOutAndReduceShapes(l.shape,r),f=R.sizeFromShape(c),m=et({inputs:{x:l},backend:e,attrs:{shape:[-1,f]}});s.push(m);let x=z9(e,m,a);s.push(x);let y=et({inputs:{x},backend:e,attrs:{shape:d}});return s.forEach(b=>e.disposeIntermediateTensorInfo(b)),y}return U9(e,t,a)}function AIe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s}=a,i=R.parseAxisParam(s,r.shape),o=W.getAxesPermutation(i,r.shape.length),l=r,d=[];o!=null&&(l=Ss({inputs:{x:r},backend:n,attrs:{perm:o}}),d.push(l),i=W.getInnerMostAxes(i.length,l.shape.length)),W.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let c=W9(n,l,i[0],"max");return d.forEach(f=>n.disposeIntermediateTensorInfo(f)),c}var _Ie={kernelName:mm,backendName:"webgl",kernelFunc:AIe};function jIe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s}=a,i=R.parseAxisParam(s,r.shape),o=W.getAxesPermutation(i,r.shape.length),l=r,d=[];o!=null&&(l=Ss({inputs:{x:r},backend:n,attrs:{perm:o}}),d.push(l),i=W.getInnerMostAxes(i.length,l.shape.length)),W.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let c=W9(n,l,i[0],"min");return d.forEach(f=>n.disposeIntermediateTensorInfo(f)),c}var DIe={kernelName:gm,backendName:"webgl",kernelFunc:jIe},RIe=ro+`
1689  if (abs(x) > 1.) {
1690    return NAN;
1691  }
1692  return asin(x);
1693`,MIe=kn({opSnippet:RIe}),$Ie={kernelName:Xd,backendName:"webgl",kernelFunc:MIe},BIe=ro+"return log(x + sqrt(x * x + 1.0));",FIe=kn({opSnippet:BIe}),OIe={kernelName:Yd,backendName:"webgl",kernelFunc:FIe},LIe=ro+`
1694  return atan(x);
1695`,PIe=kn({opSnippet:LIe}),zIe={kernelName:Jd,backendName:"webgl",kernelFunc:PIe},UIe=T4+`
1696  return atan(a, b);
1697`,WIe=`
1698  vec4 result = atan(a, b);
1699  bvec4 isNaNA = isnan(a);
1700  bvec4 isNaNB = isnan(b);
1701  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
1702  `+bp+`
1703  return result;
1704`,VIe=Gr({opSnippet:UIe,packedOpSnippet:WIe}),HIe={kernelName:Zd,backendName:"webgl",kernelFunc:VIe},GIe=ro+`
1705  if ((x < -1.0) || (x > 1.0)) return NAN;
1706return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,qIe=kn({opSnippet:GIe}),KIe={kernelName:Qd,backendName:"webgl",kernelFunc:qIe},Hy=class{constructor(e,t,n,a=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,d=e.dilationWidth,c=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.top,x=e.padInfo.left;this.outputShape=e.outShape;let y=t==="avg",b=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,w=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,S="0.0";if(y||(S="-1.0 / 1e-20"),n){let A=">=";this.userCode=`
1707        const ivec2 strides = ivec2(${i}, ${o});
1708        const ivec2 pads = ivec2(${m}, ${x});
1709
1710        void main() {
1711          ivec4 coords = getOutputCoords();
1712          int batch = coords[0];
1713          int d = coords[3];
1714
1715          ivec2 xRCCorner = coords.yz * strides - pads;
1716          int xRCorner = xRCCorner.x;
1717          int xCCorner = xRCCorner.y;
1718
1719          // max/min x(?, ?, d) to get y(yR, yC, d).
1720          // ? = to be determined
1721          float minMaxValue = 0.0;
1722          float minMaxValueFound = 0.0;
1723          int minMaxPosition = 0;
1724          float avgValue = 0.0;
1725
1726          for (int wR = 0; wR < ${c};
1727              wR += ${l}) {
1728            int xR = xRCorner + wR;
1729
1730            if (xR < 0 || xR >= ${e.inHeight}) {
1731              continue;
1732            }
1733
1734            for (int wC = 0; wC < ${f};
1735                wC += ${d}) {
1736              int xC = xCCorner + wC;
1737
1738              if (xC < 0 || xC >= ${e.inWidth}) {
1739                continue;
1740              }
1741
1742              float value = getX(batch, xR, xC, d);
1743
1744              // If a min / max value has already been found, use it. If not,
1745              // use the current value.
1746              float currMinMaxValue = mix(
1747                  value, minMaxValue, minMaxValueFound);
1748              if (value ${A} currMinMaxValue) {
1749                minMaxValue = value;
1750                minMaxValueFound = 1.0;
1751                minMaxPosition = ${a?r?b:w:`wR * ${f} + wC`};
1752              }
1753            }
1754          }
1755          setOutput(float(minMaxPosition));
1756        }
1757      `;return}let k="max",C=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(C="avgValue / max(count, 1.0)");let E=Math.floor(s/4)*4,T=s%4,_=`
1758      if (${y}) {
1759        avgValue += dot(values, ones);
1760      } else {
1761        minMaxValue = ${k}(values, minMaxValue);
1762      }
1763    `;this.userCode=`
1764      const ivec2 strides = ivec2(${i}, ${o});
1765      const ivec2 pads = ivec2(${m}, ${x});
1766      const float initializationValue = ${S};
1767      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
1768
1769      float count = 0.0;
1770
1771      float getValue(int batch, int xR, int xC, int d) {
1772        if (xC < 0 || xC >= ${e.inWidth}) {
1773          return initializationValue;
1774        }
1775        count += 1.0;
1776        return getX(batch, xR, xC, d);
1777      }
1778
1779      void main() {
1780        ivec4 coords = getOutputCoords();
1781        int batch = coords[0];
1782        int d = coords[3];
1783
1784        ivec2 xRCCorner = coords.yz * strides - pads;
1785        int xRCorner = xRCCorner.x;
1786        int xCCorner = xRCCorner.y;
1787
1788        // max/min x(?, ?, d) to get y(yR, yC, d).
1789        // ? = to be determined
1790        vec4 minMaxValue = vec4(${S});
1791        float avgValue = 0.0;
1792        count = 0.0;
1793
1794        for (int wR = 0; wR < ${c};
1795            wR += ${l}) {
1796          int xR = xRCorner + wR;
1797
1798          if (xR < 0 || xR >= ${e.inHeight}) {
1799            continue;
1800          }
1801
1802          for (int wC = 0; wC < ${E}; wC += 4) {
1803            int xC = xCCorner + wC * ${d};
1804
1805            vec4 values = vec4(
1806              getValue(batch, xR, xC, d),
1807              getValue(batch, xR, xC + ${d}, d),
1808              getValue(batch, xR, xC + 2 * ${d}, d),
1809              getValue(batch, xR, xC + 3 * ${d}, d)
1810            );
1811
1812            ${_}
1813          }
1814
1815          int xC = xCCorner + ${E};
1816          if (${T===1}) {
1817            vec4 values = vec4(
1818              getValue(batch, xR, xC, d),
1819              initializationValue,
1820              initializationValue,
1821              initializationValue
1822            );
1823
1824            ${_}
1825          } else if (${T===2}) {
1826            vec4 values = vec4(
1827              getValue(batch, xR, xC, d),
1828              getValue(batch, xR, xC + ${d}, d),
1829              initializationValue,
1830              initializationValue
1831            );
1832
1833            ${_}
1834          } else if (${T===3}) {
1835            vec4 values = vec4(
1836              getValue(batch, xR, xC, d),
1837              getValue(batch, xR, xC + ${d}, d),
1838              getValue(batch, xR, xC + 2 * ${d}, d),
1839              initializationValue
1840            );
1841
1842            ${_}
1843          }
1844        }
1845        setOutput(${C});
1846      }
1847    `}},_4=class{constructor(e,t,n,a=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,d=e.dilationDepth,c=e.dilationHeight,f=e.dilationWidth,m=e.effectiveFilterDepth,x=e.effectiveFilterHeight,y=e.effectiveFilterWidth,b=e.padInfo.front,w=e.padInfo.top,S=e.padInfo.left;this.outputShape=e.outShape;let k=t==="avg",C="0.0";if(k||(C="-1.0 / 1e-20"),n){let O=">=";this.userCode=`
1848        const ivec3 strides =
1849            ivec3(${i}, ${o}, ${l});
1850        const ivec3 pads = ivec3(${b}, ${w}, ${S});
1851
1852        void main() {
1853          ivec5 coords = getOutputCoords();
1854          int batch = coords.x;
1855          int ch = coords.u;
1856
1857          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
1858          int xDCorner = xCorner.x;
1859          int xRCorner = xCorner.y;
1860          int xCCorner = xCorner.z;
1861
1862          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).
1863          // ? = to be determined
1864          float minMaxValue = 0.0;
1865          float minMaxValueFound = 0.0;
1866          int minMaxPosition = 0;
1867
1868          for (int wD = 0; wD < ${m};
1869              wD += ${d}) {
1870            int xD = xDCorner + wD;
1871
1872            if (xD < 0 || xD >= ${e.inDepth}) {
1873              continue;
1874            }
1875
1876            for (int wR = 0; wR < ${x};
1877                wR += ${c}) {
1878              int xR = xRCorner + wR;
1879
1880              if (xR < 0 || xR >= ${e.inHeight}) {
1881                continue;
1882              }
1883
1884              for (int wC = 0; wC < ${y};
1885                  wC += ${f}) {
1886                int xC = xCCorner + wC;
1887
1888                if (xC < 0 || xC >= ${e.inWidth}) {
1889                  continue;
1890                }
1891
1892                float value = getX(batch, xD, xR, xC, ch);
1893
1894                // If a min / max value has already been found, use it. If not,
1895                // use the current value.
1896                float currMinMaxValue = mix(
1897                    value, minMaxValue, minMaxValueFound);
1898                if (value ${O} currMinMaxValue) {
1899                  minMaxValue = value;
1900                  minMaxValueFound = 1.0;
1901                  minMaxPosition = ${a?r?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${x} * ${y} +
1902                      wR * ${y} + wC`};
1903                }
1904              }
1905            }
1906          }
1907          setOutput(float(minMaxPosition));
1908        }
1909      `;return}let E="max",T=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(T="avgValue / max(count, 1.0)");let _=Math.floor(s/4)*4,A=s%4,$=`
1910      if (${k}) {
1911        avgValue += dot(values, ones);
1912      } else {
1913        minMaxValue = ${E}(values, minMaxValue);
1914      }
1915    `;this.userCode=`
1916      const ivec3 strides =
1917        ivec3(${i}, ${o}, ${l});
1918      const ivec3 pads = ivec3(${b}, ${w}, ${S});
1919      const float initializationValue = ${C};
1920      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
1921
1922      float count = 0.0;
1923
1924      float getValue(int batch, int xD, int xR, int xC, int ch) {
1925        if (xC < 0 || xC >= ${e.inWidth}) {
1926          return initializationValue;
1927        }
1928        count += 1.0;
1929        return getX(batch, xD, xR, xC, ch);
1930      }
1931
1932      void main() {
1933        ivec5 coords = getOutputCoords();
1934        int batch = coords.x;
1935        int ch = coords.u;
1936
1937        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
1938        int xDCorner = xCorner.x;
1939        int xRCorner = xCorner.y;
1940        int xCCorner = xCorner.z;
1941
1942        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
1943        // ? = to be determined
1944        vec4 minMaxValue = vec4(${C});
1945        float avgValue = 0.0;
1946        count = 0.0;
1947
1948        for (int wD = 0; wD < ${m};
1949            wD += ${d}) {
1950          int xD = xDCorner + wD;
1951
1952          if (xD < 0 || xD >= ${e.inDepth}) {
1953            continue;
1954          }
1955
1956          for (int wR = 0; wR < ${x};
1957            wR += ${c}) {
1958            int xR = xRCorner + wR;
1959
1960            if (xR < 0 || xR >= ${e.inHeight}) {
1961              continue;
1962            }
1963
1964            for (int wC = 0; wC < ${_}; wC += 4) {
1965              int xC = xCCorner + wC * ${f};
1966
1967              vec4 values = vec4(
1968                getValue(batch, xD, xR, xC, ch),
1969                getValue(batch, xD, xR, xC + ${f}, ch),
1970                getValue(batch, xD, xR, xC + 2 * ${f}, ch),
1971                getValue(batch, xD, xR, xC + 3 * ${f}, ch)
1972              );
1973
1974              ${$}
1975            }
1976
1977            int xC = xCCorner + ${_};
1978            if (${A===1}) {
1979              vec4 values = vec4(
1980                getValue(batch, xD, xR, xC, ch),
1981                initializationValue,
1982                initializationValue,
1983                initializationValue
1984              );
1985
1986              ${$}
1987            } else if (${A===2}) {
1988              vec4 values = vec4(
1989                getValue(batch, xD, xR, xC, ch),
1990                getValue(batch, xD, xR, xC + ${f}, ch),
1991                initializationValue,
1992                initializationValue
1993              );
1994
1995              ${$}
1996            } else if (${A===3}) {
1997              vec4 values = vec4(
1998                getValue(batch, xD, xR, xC, ch),
1999                getValue(batch, xD, xR, xC + ${f}, ch),
2000                getValue(batch, xD, xR, xC + 2 * ${f}, ch),
2001                initializationValue
2002              );
2003
2004              ${$}
2005            }
2006          }
2007        }
2008        setOutput(${T});
2009      }
2010    `}};function XIe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t;Eg(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=a,d=1;R.assert(W.eitherStridesOrDilationsAreOne(i,d),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${d}'`);let c=W.computePool2DInfo(r.shape,s,i,d,o,l);if(c.filterWidth===1&&c.filterHeight===1&&R.arraysEqual(c.inShape,c.outShape))return li({inputs:{x:r},backend:n});let f=new Hy(c,"avg",!1);return n.runWebGLProgram(f,[r],"float32")}var YIe={kernelName:eh,backendName:"webgl",kernelFunc:XIe};function JIe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:d}=a,c=[1,1,1],f=W.computePool3DInfo(r.shape,s,i,c,o,l,d),m=new _4(f,"avg",!1);return n.runWebGLProgram(m,[r],"float32")}var QIe={kernelName:xm,backendName:"webgl",kernelFunc:JIe},ZIe=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,a=e.strideHeight,r=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,d=o-1-e.padInfo.top,c=l-1-e.padInfo.left,f=1/(t*n);this.userCode=`
2011      const ivec2 pads = ivec2(${d}, ${c});
2012      const float avgMultiplier = float(${f});
2013
2014      void main() {
2015        ivec4 coords = getOutputCoords();
2016        int b = coords[0];
2017        int d = coords[3];
2018
2019        ivec2 dyRCCorner = coords.yz - pads;
2020        int dyRCorner = dyRCCorner.x;
2021        int dyCCorner = dyRCCorner.y;
2022
2023        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
2024        // ? = to be determined. : = across all values in that axis.
2025        float dotProd = 0.0;
2026        for (int wR = 0; wR < ${o};
2027            wR += ${s}) {
2028          float dyR = float(dyRCorner + wR) / ${a}.0;
2029
2030          if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
2031            continue;
2032          }
2033          int idyR = int(dyR);
2034
2035          for (int wC = 0; wC < ${l};
2036            wC+= ${i}) {
2037            float dyC = float(dyCCorner + wC) / ${r}.0;
2038
2039            if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
2040                fract(dyC) > 0.0) {
2041              continue;
2042            }
2043            int idyC = int(dyC);
2044
2045            float dyValue = getDy(b, idyR, idyC, d);
2046
2047            dotProd += dyValue * avgMultiplier;
2048          }
2049        }
2050        setOutput(dotProd);
2051      }
2052    `}},eTe=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,a=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,d=e.dilationWidth,c=e.effectiveFilterDepth,f=e.effectiveFilterHeight,m=e.effectiveFilterWidth,x=c-1-e.padInfo.front,y=f-1-e.padInfo.top,b=m-1-e.padInfo.left,w=1/(t*n*a);this.userCode=`
2053      const ivec3 pads = ivec3(${x}, ${y}, ${b});
2054      const float avgMultiplier = float(${w});
2055
2056      void main() {
2057        ivec5 coords = getOutputCoords();
2058        int batch = coords.x;
2059        int ch = coords.u;
2060
2061        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
2062        int dyDCorner = dyCorner.x;
2063        int dyRCorner = dyCorner.y;
2064        int dyCCorner = dyCorner.z;
2065
2066        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get

2131let m=fe().getBool("WEBGL_PACK_NORMALIZATION")?new lTe(a.shape,r.shape,s.shape,c,f,l):new oTe(a.shape,r.shape,s.shape,c,f,l);return t.runWebGLProgram(m,d,d[0].dtype)},cTe={kernelName:bh,backendName:"webgl",kernelFunc:uTe},dTe=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ea(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let n=hTe(this.rank),a,r=e.map((s,i)=>`sourceLoc.${jE[i]} = start[${i}] + coords.${jE[i]};`);a=`
2132        ${t} sourceLoc;
2133        ${t} coords = getOutputCoords();
2134        ${r.join(`
2135`)}
2136      `,this.userCode=`
2137      void main() {
2138        ${a}
2139        setOutput(getSource(${n}));
2140      }
2141    `}},jE=["x","y","z","w","u","v"];function hTe(e){if(e===1)return"sourceLoc";if(e<=6)return jE.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var pTe=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=ea(this.rank),n=xs("coords",this.rank),a=xs("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${a.slice(-2).join()})`,s=`getChannel(getSource(${a.join()}), ${r})`,i=`
2142      result.x = ${s};
2143      if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
2144        ++${a[this.rank-1]};
2145        result.y = ${s};
2146        --${a[this.rank-1]};
2147      }
2148    `,o=this.rank===1?"":`
2149      --${n[this.rank-1]};
2150      if (++${n[this.rank-2]} < ${e[this.rank-2]}) {
2151        ++${a[this.rank-2]};
2152        result.z = ${s};
2153        if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
2154          ++${a[this.rank-1]};
2155          result.w = ${s};
2156        }
2157      }
2158    `,l=this.rank<=4?`sourceLoc = coords +
2159            ${t}(${e.map((d,c)=>`start[${c}]`).join()});`:e.map((d,c)=>`${a[c]} = ${n[c]} + start[${c}];`).join(`
2160`);this.userCode=`
2161      void main() {
2162        ${t} coords = getOutputCoords();
2163        ${t} sourceLoc;
2164        ${l}
2165        vec4 result = vec4(0.);
2166        ${i}
2167        ${o}
2168        setOutput(result);
2169      }
2170    `}};function fTe(e,t,n,a){let r=a.texData.get(e.dataId),s=a.makeTensorInfo(n,e.dtype),i=a.texData.get(s.dataId);Object.assign(i,r),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=vr.computeFlatOffset(t,R.computeStrides(e.shape));r.slice&&(o+=r.slice.flatOffset),i.slice={flatOffset:o,origDataId:r.slice&&r.slice.origDataId||e.dataId};let l=a.dataRefCount.get(i.slice.origDataId)||1;return a.dataRefCount.set(i.slice.origDataId,l+1),s}function Rg(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{begin:s,size:i}=a,[o,l]=vr.parseSliceParams(r,s,i);if(vr.assertParamsValid(r,o,l),R.sizeFromShape(l)===0)return n.makeTensorInfo(l,r.dtype,[]);if(n.shouldExecuteOnCPU([r])||r.dtype==="string"){let f=n.texData.get(r.dataId),m=rEe(f.values,o,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,m)}let{isPacked:d}=n.texData.get(r.dataId),c=vr.isSliceContinous(r.shape,o,l);if(d||!c){let f=fe().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new pTe(l):new dTe(l),m=[o];return n.runWebGLProgram(f,[r],r.dtype,m)}return n.uploadToGPU(r.dataId),fTe(r,o,l,n)}var mTe={kernelName:ag,backendName:"webgl",kernelFunc:Rg},gTe=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,crops:i}=a;R.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((k,C)=>k*C),l=W.getReshaped(r.shape,s,o),d=W.getPermuted(l.length,s.length),c=W.getReshapedPermuted(r.shape,s,o),f=W.getSliceBeginCoords(i,s.length),m=W.getSliceSize(c,i,s.length),x=[],y=et({inputs:{x:r},backend:n,attrs:{shape:l}}),b=Ss({inputs:{x:y},backend:n,attrs:{perm:d}}),w=et({inputs:{x:b},backend:n,attrs:{shape:c}}),S=Rg({inputs:{x:w},backend:n,attrs:{begin:f,size:m}});return x.push(y),x.push(b),x.push(w),x.forEach(k=>n.disposeIntermediateTensorInfo(k)),S},xTe={kernelName:ym,backendName:"webgl",kernelFunc:gTe};function yTe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i}=a,o=n.readSync(r.dataId),l=n.readSync(s.dataId),d=T9(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,d)}var bTe={kernelName:bm,backendName:"webgl",kernelFunc:yTe},vTe=`
2171  int r = int(a.r) & int(b.r);
2172  int g = int(a.g) & int(b.g);
2173  int rb = int(a.b) & int(b.b);
2174  int ra = int(a.a) & int(b.a);
2175  return vec4(r, g, rb, ra);
2176`,wTe=`
2177  return float(int(a.r) & int(b.r));
2178`;function STe(e){let{inputs:t,backend:n}=e,{a,b:r}=t,s=fe().getBool("WEBGL_PACK_BINARY_OPERATIONS"),i=fe().getNumber("WEBGL_VERSION");if(n.shouldExecuteOnCPU([a,r])||i===1){let l=n.texData.get(a.dataId).values,d=n.texData.get(r.dataId).values,[c,f]=TCe(a.shape,r.shape,l,d,a.dtype),m=n.makeTensorInfo(f,a.dtype),x=n.texData.get(m.dataId);return x.values=c,m}let o;return s?o=new jg(vTe,a.shape,r.shape,!1):o=new zd(wTe,a.shape,r.shape),n.runWebGLProgram(o,[a,r],a.dtype)}var kTe={kernelName:vm,backendName:"webgl",kernelFunc:STe};function NTe(e){let{inputs:t,backend:n}=e,{s0:a,s1:r}=t,s=n.readSync(a.dataId),i=n.readSync(r.dataId),o=W.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return n.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var CTe={kernelName:sb,backendName:"webgl",kernelFunc:NTe},ETe="return float(a != b);",V9=Gr({opSnippet:ETe,cpuKernelImpl:XCe,dtype:"bool"}),ITe={kernelName:Vm,backendName:"webgl",kernelFunc:V9};function t0(e){let{inputs:t,backend:n}=e,{input:a}=t,r=n.texData.get(a.dataId);return li({inputs:{x:r.complexTensorInfos.real},backend:n})}var TTe={kernelName:_w,backendName:"webgl",kernelFunc:t0},ATe="return float(int(x));";function _Te(e,t){let n=new Yo(e.shape,ATe),a=t.runWebGLProgram(n,[e],"int32");return{dataId:a.dataId,shape:a.shape,dtype:a.dtype}}function DE(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{dtype:s}=a;if(s==="complex64"){if(r.dtype==="complex64")return li({inputs:{x:r},backend:n});let i=va(r.shape),o=DE({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=Sc({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(r.dtype==="complex64"){let i=t0({inputs:{input:r},backend:n}),o=DE({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!R.hasEncodingLoss(r.dtype,s)){let i=li({inputs:{x:r},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(n.shouldExecuteOnCPU([r])){let i=n.texData.get(r.dataId).values,[o,l,d]=ACe(i,r.shape,r.dtype,s);return n.makeTensorInfo(o,l,d)}if(s==="int32")return _Te(r,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",R.getTypedArrayFromDType("bool",1)),o=V9({inputs:{a:r,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${s}`)}var jTe={kernelName:nh,backendName:"webgl",kernelFunc:DE},nB="return ceil(x);",DTe=kn({opSnippet:nB,packedOpSnippet:nB,cpuKernelImpl:_Ce}),RTe={kernelName:ah,backendName:"webgl",kernelFunc:DTe},MTe=class{constructor(e){this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=`
2179
2180      void main() {
2181        float value = getAAtOutCoords();
2182        if (isnan(value)) {
2183          setOutput(value);
2184          return;
2185        }
2186
2187        setOutput(clamp(value, minVal, maxVal));
2188      }
2189    `}},$Te=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=`
2190      void main() {
2191        vec4 value = getAAtOutCoords();
2192
2193        if (any(isnan(value))) {
2194          setOutput(value);
2195          return;
2196        }
2197
2198        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
2199      }
2200    `}};function BTe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=a,o;fe().getBool("WEBGL_PACK_CLIP")?o=new $Te(r.shape):o=new MTe(r.shape);let l=[[s],[i]];return n.runWebGLProgram(o,[r],r.dtype,l)}var FTe={kernelName:pc,backendName:"webgl",kernelFunc:BTe},OTe=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
2201      void main() {
2202        float re = abs(getRealAtOutCoords());
2203        float im = abs(getImagAtOutCoords());
2204        float mx = max(re, im);
2205
2206        // sadly the length function in glsl is not underflow-safe
2207        // (at least not on Intel GPUs). So the safe solution is
2208        // to ensure underflow-safety in all cases.
2209        setOutput(
2210          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
2211        );
2212      }
2213    `}};function aB(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function LTe(e){let{inputs:t,backend:n}=e,{x:a}=t,r=n.texData.get(a.dataId),s=new OTe(a.shape),i=[aB(a,r.complexTensorInfos.real),aB(a,r.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var PTe={kernelName:ib,backendName:"webgl",kernelFunc:LTe},zTe=class{constructor(e){this.outputShape=[],this.outputShape=W.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let a=t.length,r=t[t.length-1];n.push(`else setOutput(getT${a}(yR, yC-${r}));`),this.userCode=`
2214      void main() {
2215        ivec2 coords = getOutputCoords();
2216        int yR = coords.x;
2217        int yC = coords.y;
2218
2219        ${n.join(`
2220        `)}
2221      }
2222    `}},UTe=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=W.computeOutShape(e,t);let n=this.outputShape,a=n.length,r=ea(a),s=xs("coords",a),i=["x","y","z","w","u","v"].slice(0,a);this.variableNames=e.map((y,b)=>`T${b}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let y=1;y<o.length;y++)o[y]=o[y-1]+e[y][t];let l=i[t],d=i.slice(-2),c=i.join(),f=`if (${l} < ${o[0]}) {
2223        return getChannel(
2224            getT0(${c}), vec2(${d.join()}));
2225        }`;for(let y=1;y<o.length;y++){let b=o[y-1];f+=`
2226        if (${l} < ${o[y]}  && ${l} >= ${o[y-1]}) {
2227          return getChannel(
2228            getT${y}(${U1(i,l,b)}),
2229            vec2(${U1(d,l,b)}));
2230        }`}let m=o.length,x=o[o.length-1];f+=`
2231        return getChannel(
2232          getT${m}(${U1(i,l,x)}),
2233          vec2(${U1(d,l,x)}));`,this.userCode=`
2234      float getValue(${i.map(y=>"int "+y)}) {
2235        ${f}
2236      }
2237
2238      void main() {
2239        ${r} coords = getOutputCoords();
2240        vec4 result = vec4(getValue(${s}), 0., 0., 0.);
2241
2242        ${s[a-1]} = ${s[a-1]} + 1;
2243        if (${s[a-1]} < ${n[a-1]}) {
2244          result.g = getValue(${s});
2245        }
2246
2247        ${s[a-2]} = ${s[a-2]} + 1;
2248        if (${s[a-2]} < ${n[a-2]}) {
2249          result.a = getValue(${s});
2250        }
2251
2252        ${s[a-1]} = ${s[a-1]} - 1;
2253        if (${s[a-2]} < ${n[a-2]} &&
2254            ${s[a-1]} < ${n[a-1]}) {
2255          result.b = getValue(${s});
2256        }
2257        setOutput(result);
2258      }
2259    `}};function U1(e,t,n){let a=e.indexOf(t);return e.map((r,s)=>s===a?`${r} - ${n}`:r).join()}function P2(e){let{inputs:t,backend:n}=e,{input:a}=t,r=n.texData.get(a.dataId);return li({inputs:{x:r.complexTensorInfos.imag},backend:n})}var WTe={kernelName:Ew,backendName:"webgl",kernelFunc:P2};function Yx(e,t,n){let a=e[0].dtype;if(a==="complex64"){let x=e.map(k=>t0({inputs:{input:k},backend:n})),y=e.map(k=>P2({inputs:{input:k},backend:n})),b=Yx(x,t,n),w=Yx(y,t,n),S=Sc({inputs:{real:b,imag:w},backend:n});return x.forEach(k=>n.disposeIntermediateTensorInfo(k)),y.forEach(k=>n.disposeIntermediateTensorInfo(k)),n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(w),S}let r=n.shouldExecuteOnCPU(e);if(a==="string"&&(r=!0),r){let x=e.map(E=>{let T=[-1,R.sizeFromShape(E.shape.slice(t))];return et({inputs:{x:E},backend:n,attrs:{shape:T}})}),y=x.map(E=>({vals:n.readSync(E.dataId),shape:E.shape})),b=W.computeOutShape(x.map(E=>E.shape),1),w=x[0].shape[0]===1,S=jCe(y,b,a,w),k=W.computeOutShape(e.map(E=>E.shape),t),C=n.makeTensorInfo(k,a,S);return x.forEach(E=>n.disposeIntermediateTensorInfo(E)),C}let s=e.filter(x=>R.sizeFromShape(x.shape)>0),i=fe().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&s[0].shape.length>1;if(s.length===1){let x=i?new Yo(e[0].shape,Mu):new zu(e[0].shape,Mu);return n.runWebGLProgram(x,e,a)}let o=fe().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(s.length>o){let x=[];for(let b=0;b<s.length;b+=o){let w=s.slice(b,b+o);x.push(Yx(w,t,n))}let y=Yx(x,t,n);for(let b of x)n.disposeIntermediateTensorInfo(b);return y}if(i){let x=new UTe(s.map(y=>y.shape),t);return n.runWebGLProgram(x,s,a)}let{tensors2D:l,outShape:d}=VTe(s,t,n),c=new zTe(l.map(x=>x.shape)),f=n.runWebGLProgram(c,l,a);l.forEach(x=>n.disposeIntermediateTensorInfo(x));let m=et({inputs:{x:f},attrs:{shape:d},backend:n});return n.disposeIntermediateTensorInfo(f),m}function VTe(e,t,n){let a=W.computeOutShape(e.map(r=>r.shape),t);return{tensors2D:e.map(r=>et({inputs:{x:r},attrs:{shape:[-1,R.sizeFromShape(r.shape.slice(t))]},backend:n})),outShape:a}}function H9(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a,s=R.parseAxisParam(r,t[0].shape)[0],i=t.map(d=>d.shape);W.assertParamsConsistent(i,s);let o=W.computeOutShape(t.map(d=>d.shape),s);if(R.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(d=>R.sizeFromShape(d.shape)>0);return l.length===1?li({inputs:{x:l[0]},backend:n}):Yx(l,s,n)}var HTe={kernelName:wm,backendName:"webgl",kernelFunc:H9},G9=class{constructor(e,t=!1,n=null,a=!1,r=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,d=e.dilationHeight,c=e.dilationWidth,f=e.filterHeight,m=e.filterWidth,x=Math.floor(e.inChannels/4)*4,y=e.inChannels%4,b=e.dataFormat==="channelsLast",w=b?1:2,S=b?2:3,k=b?3:1,C="",E="";n&&(a?C=`float activation(float a) {
2260          float b = getPreluActivationWeightsAtOutCoords();
2261          ${n}
2262        }`:r?C=`float activation(float a) {
2263          float b = getLeakyreluAlphaAtOutCoords();
2264          ${n}
2265        }`:C=`
2266          float activation(float x) {
2267            ${n}
2268          }
2269        `,E="result = activation(result);");let T=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
2270      ${C}
2271
2272      const ivec2 strides = ivec2(${o}, ${l});
2273      const ivec2 pads = ivec2(${s}, ${i});
2274
2275      void main() {
2276        ivec4 coords = getOutputCoords();
2277        int batch = coords[0];
2278        int d2 = coords[${k}];
2279
2280        ivec2 xRCCorner =
2281            ivec2(coords[${w}], coords[${S}]) * strides - pads;
2282        int xRCorner = xRCCorner.x;
2283        int xCCorner = xRCCorner.y;
2284
2285        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).
2286        // ? = to be determined. : = across all values in that axis.
2287        float dotProd = 0.0;
2288        for (int wR = 0; wR < ${f}; wR++) {
2289          int xR = xRCorner + wR * ${d};
2290
2291          if (xR < 0 || xR >= ${e.inHeight}) {
2292            continue;
2293          }
2294
2295          for (int wC = 0; wC < ${m}; wC++) {
2296            int xC = xCCorner + wC * ${c};
2297
2298            if (xC < 0 || xC >= ${e.inWidth}) {
2299              continue;
2300            }
2301
2302            for (int d1 = 0; d1 < ${x}; d1 += 4) {
2303              vec4 wValues = vec4(
2304                getW(wR, wC, d1, d2),
2305                getW(wR, wC, d1 + 1, d2),
2306                getW(wR, wC, d1 + 2, d2),
2307                getW(wR, wC, d1 + 3, d2)
2308              );
2309
2310              if (${b}) {
2311                vec4 xValues = vec4(
2312                  getX(batch, xR, xC, d1),
2313                  getX(batch, xR, xC, d1 + 1),
2314                  getX(batch, xR, xC, d1 + 2),
2315                  getX(batch, xR, xC, d1 + 3)
2316                );
2317                dotProd += dot(xValues, wValues);
2318              } else {
2319                vec4 xValues = vec4(
2320                  getX(batch, d1, xR, xC),
2321                  getX(batch, d1 + 1, xR, xC),
2322                  getX(batch, d1 + 2, xR, xC),
2323                  getX(batch, d1 + 3, xR, xC)
2324                );
2325                dotProd += dot(xValues, wValues);
2326              }
2327            }
2328
2329            if (${y===1}) {
2330
2331              if (${b}) {
2332                dotProd +=
2333                    getX(batch, xR, xC, ${x}) *
2334                    getW(wR, wC, ${x}, d2);
2335              } else {
2336                dotProd +=
2337                    getX(batch, ${x}, xR, xC) *
2338                    getW(wR, wC, ${x}, d2);
2339              }
2340
2341            } else if (${y===2}) {
2342              vec2 wValues = vec2(
2343                getW(wR, wC, ${x}, d2),
2344                getW(wR, wC, ${x} + 1, d2)
2345              );
2346
2347              if (${b}) {
2348                vec2 xValues = vec2(
2349                  getX(batch, xR, xC, ${x}),
2350                  getX(batch, xR, xC, ${x} + 1)
2351                );
2352                dotProd += dot(xValues, wValues);
2353              } else {
2354                vec2 xValues = vec2(
2355                  getX(batch, ${x}, xR, xC),
2356                  getX(batch, ${x} + 1, xR, xC)
2357                );
2358                dotProd += dot(xValues, wValues);
2359              }
2360
2361            } else if (${y===3}) {
2362              vec3 wValues = vec3(
2363                getW(wR, wC, ${x}, d2),
2364                getW(wR, wC, ${x} + 1, d2),
2365                getW(wR, wC, ${x} + 2, d2)
2366              );
2367
2368              if (${b}) {
2369                vec3 xValues = vec3(
2370                  getX(batch, xR, xC, ${x}),
2371                  getX(batch, xR, xC, ${x} + 1),
2372                  getX(batch, xR, xC, ${x} + 2)
2373                );
2374                dotProd += dot(xValues, wValues);
2375              } else {
2376                vec3 xValues = vec3(
2377                  getX(batch, ${x}, xR, xC),
2378                  getX(batch, ${x} + 1, xR, xC),
2379                  getX(batch, ${x} + 2, xR, xC)
2380                );
2381                dotProd += dot(xValues, wValues);
2382              }
2383
2384            }
2385          }
2386        }
2387
2388        float result = dotProd;
2389        ${T}
2390        ${E}
2391        setOutput(result);
2392      }
2393    `}},GTe=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,a=e.padInfo.left,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,d=e.dilationWidth,c=e.filterDepth,f=e.filterHeight,m=e.filterWidth,x=Math.floor(e.inChannels/4)*4,y=e.inChannels%4;this.userCode=`
2394      const ivec3 strides = ivec3(${r}, ${s}, ${i});
2395      const ivec3 pads = ivec3(${t}, ${n}, ${a});
2396
2397      void main() {
2398        ivec5 coords = getOutputCoords();
2399        int batch = coords.x;
2400        int d2 = coords.u;
2401
2402        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
2403        int xFCorner = xFRCCorner.x;
2404        int xRCorner = xFRCCorner.y;
2405        int xCCorner = xFRCCorner.z;
2406
2407        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get
2408        // y(yF, yR, yC, d2). ? = to be determined. : = across all
2409        // values in that axis.
2410        float dotProd = 0.0;
2411        for (int wF = 0; wF < ${c}; wF++) {
2412          int xF = xFCorner + wF * ${o};
2413
2414          if (xF < 0 || xF >= ${e.inDepth}) {
2415            continue;
2416          }
2417
2418          for (int wR = 0; wR < ${f}; wR++) {
2419            int xR = xRCorner + wR * ${l};
2420
2421            if (xR < 0 || xR >= ${e.inHeight}) {
2422              continue;
2423            }
2424
2425            for (int wC = 0; wC < ${m}; wC++) {
2426              int xC = xCCorner + wC * ${d};
2427
2428              if (xC < 0 || xC >= ${e.inWidth}) {
2429                continue;
2430              }
2431
2432              for (int d1 = 0; d1 < ${x}; d1 += 4) {
2433                vec4 xValues = vec4(
2434                  getX(batch, xF, xR, xC, d1),
2435                  getX(batch, xF, xR, xC, d1 + 1),
2436                  getX(batch, xF, xR, xC, d1 + 2),
2437                  getX(batch, xF, xR, xC, d1 + 3)
2438                );
2439                vec4 wValues = vec4(
2440                  getW(wF, wR, wC, d1, d2),
2441                  getW(wF, wR, wC, d1 + 1, d2),
2442                  getW(wF, wR, wC, d1 + 2, d2),
2443                  getW(wF, wR, wC, d1 + 3, d2)
2444                );
2445
2446                dotProd += dot(xValues, wValues);
2447              }
2448
2449              if (${y===1}) {
2450                dotProd +=
2451                  getX(batch, xF, xR, xC, ${x}) *
2452                  getW(wF, wR, wC, ${x}, d2);
2453              } else if (${y===2}) {
2454                vec2 xValues = vec2(
2455                  getX(batch, xF, xR, xC, ${x}),
2456                  getX(batch, xF, xR, xC, ${x} + 1)
2457                );
2458                vec2 wValues = vec2(
2459                  getW(wF, wR, wC, ${x}, d2),
2460                  getW(wF, wR, wC, ${x} + 1, d2)
2461                );
2462                dotProd += dot(xValues, wValues);
2463              } else if (${y===3}) {
2464                vec3 xValues = vec3(
2465                  getX(batch, xF, xR, xC, ${x}),
2466                  getX(batch, xF, xR, xC, ${x} + 1),
2467                  getX(batch, xF, xR, xC, ${x} + 2)
2468                );
2469                vec3 wValues = vec3(
2470                  getW(wF, wR, wC, ${x}, d2),
2471                  getW(wF, wR, wC, ${x} + 1, d2),
2472                  getW(wF, wR, wC, ${x} + 2, d2)
2473                );
2474                dotProd += dot(xValues, wValues);
2475              }
2476            }
2477          }
2478        }
2479        setOutput(dotProd);
2480      }
2481    `}},q9=class{constructor(e,t=!1,n=null,a=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=ss(this.outputShape.length);let s=e.padInfo.left,i=e.strideWidth,o=e.dilationWidth,l=e.filterHeight,d=e.filterWidth,c=d,f=`
2482       int xR; int xC; int xCOffset;
2483       vec4 wTexel; vec4 previous; vec4 final;`;for(let b=0;b<d;b++)f+=`
2484           vec4 xTexelC${b*2};
2485           int xTexelC${b*2}Ready;
2486           vec4 xTexelC${b*2+1};
2487           int xTexelC${b*2+1}Ready;
2488           vec4 xC${b};`;f+=`
2489     for (int r = 0; r < ${l}; r++) {
2490      for (int d1 = 0; d1 < ${e.inChannels}; d1 += 2) {
2491       `;for(let b=0;b<d;b++)f+=`
2492           xTexelC${b*2} = vec4(0.0);
2493           xTexelC${b*2}Ready = 0;
2494           xTexelC${b*2+1} = vec4(0.0);
2495           xTexelC${b*2+1}Ready = 0;
2496           xC${b} = vec4(0.0);`;f+=`
2497         xR = xRCorner + r * dilations[0];
2498         if (xR >=0 && xR < inDims[0]) {
2499       `;for(let b=0;b<(c+1)/2;b++){let w=b*2;if(f+=`
2500           xC = xCCorner + ${w*o};
2501           `,i===1){if(w<d&&(s%2===1?(f+=`
2502                 xCOffset = xC + 1;
2503                 if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${w}Ready == 0) {
2504                   xTexelC${w} = getX(batch, xR, xCOffset, d1);
2505
2506                   // Need to manually clear unused channels in case
2507                   // we're reading from recycled texture.
2508                   if (xCOffset + 1 >= inDims[1]) {
2509                     xTexelC${w}.zw = vec2(0.0);
2510                   }
2511                   xTexelC${w}Ready = 1;
2512                 }
2513               `,o===1&&w>0?f+=`
2514                 xC${w} = vec4(xTexelC${w-2}.zw, xTexelC${w}.xy);
2515                 `:f+=`
2516                   xCOffset = xC + 1 - 2;
2517
2518                   if (xCOffset >= 0 && xCOffset < inDims[1]) {
2519                     previous = getX(batch, xR, xCOffset, d1);
2520
2521                     // Need to manually clear unused channels in case
2522                     // we're reading from recycled texture.
2523                     if (xCOffset + 1 >= inDims[1]) {
2524                       previous.zw = vec2(0.0);
2525                     }
2526
2527                     xC${w} = vec4(previous.zw, xTexelC${w}.xy);
2528                   } else {
2529                     xC${w} = vec4(0.0, 0.0, xTexelC${w}.xy);
2530                   }
2531                   `):f+=`
2532                 if (xC >= 0 && xC < inDims[1] && xTexelC${w}Ready == 0) {
2533                   xTexelC${w} = getX(batch, xR, xC, d1);
2534                   if (xC + 1 >= inDims[1]) {
2535                     xTexelC${w}.zw = vec2(0.0);
2536                   }
2537                   xTexelC${w}Ready = 1;
2538                 }
2539
2540                 xC${w} = xTexelC${w};
2541                 `,w+1<d)){let S=s%2===0?R.nearestLargerEven(o):o;o%2===0&&s%2===1||o%2!==0&&s%2!==1?(f+=`
2542                   xCOffset = xC + imod(pads[1], 2) + ${S};
2543
2544                   if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${w+1}Ready == 0) {
2545                     xTexelC${w+1} = getX(batch, xR, xCOffset, d1);
2546
2547                     // Need to manually clear unused channels in case
2548                     // we're reading from recycled texture.
2549                     if (xCOffset + 1 >= inDims[1]) {
2550                       xTexelC${w+1}.zw = vec2(0.0);
2551                     }
2552                     xTexelC${w+1}Ready = 1;
2553                   }
2554                   `,o>1?f+=`
2555                     xCOffset -= 2;
2556                     if (xCOffset >= 0 && xCOffset < inDims[1]) {
2557                      previous = getX(batch, xR, xCOffset, d1);
2558                      xC${w+1} = vec4(previous.zw, xTexelC${w+1}.xy);
2559                     } else {
2560                      xC${w+1} = vec4(0.0, 0.0, xTexelC${w+1}.xy);
2561                     }
2562                     `:f+=`
2563                     xC${w+1} = vec4(xTexelC${w}.zw, xTexelC${w+1}.xy);
2564                     `):S===1?f+=`
2565                     xC${w+1} = xTexelC${w};
2566                     `:f+=`
2567                     xCOffset = xC + ${S};
2568
2569                     if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${w+1}Ready == 0) {
2570                       xTexelC${w+1} = getX(batch, xR, xCOffset, d1);
2571                       if (xCOffset + 1 >= inDims[1]) {
2572                         xTexelC${w+1}.zw = vec2(0.0);
2573                       }
2574                       xTexelC${w+1}Ready = 1;
2575                     }
2576
2577                     xC${w+1} = xTexelC${w+1};
2578                     `}}else w<d&&(s%2===1?(f+=`
2579                 xCOffset = xC + 1 - strides[1];
2580                 if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${w}Ready == 0) {
2581                   xTexelC${w} = getX(batch, xR, xCOffset, d1);
2582                   // Need to manually clear unused channels in case
2583                   // we're reading from recycled texture.
2584                   if (xCOffset + 1 >= inDims[1]) {
2585                     xTexelC${w}.zw = vec2(0.0);
2586                   }
2587                   xTexelC${w}Ready = 1;
2588                 }
2589
2590                 if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${w+1}Ready == 0) {
2591                   xTexelC${w+1} = getX(batch, xR, xC + 1, d1);
2592                   // Need to manually clear unused channels in case
2593                   // we're reading from recycled texture.
2594                   if (xC + 2 >= inDims[1]) {
2595                     xTexelC${w+1}.zw = vec2(0.0);
2596                   }
2597                   xTexelC${w+1}Ready = 1;
2598                 }
2599
2600                 xC${w} = vec4(xTexelC${w}.zw, xTexelC${w+1}.zw);
2601               `,w+1<d&&(f+=`
2602                   final = vec4(0.0);
2603                   xCOffset = xC + 1 + strides[1];
2604                   if(xCOffset >= 0 && xCOffset < inDims[1]) {
2605                     final = getX(batch, xR, xCOffset, d1);
2606                   }
2607                   xC${w+1} = vec4(xTexelC${w+1}.xy, final.xy);
2608                 `)):(f+=`
2609                 if(xC >= 0 && xC < inDims[1] && xTexelC${w}Ready == 0) {
2610                   xTexelC${w} = getX(batch, xR, xC, d1);
2611                   if (xC + 1 >= inDims[1]) {
2612                     xTexelC${w}.zw = vec2(0.0);
2613                   }
2614                   xTexelC${w}Ready = 1;
2615                 }
2616
2617                 xCOffset = xC + strides[1];
2618                 if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${w+1}Ready == 0) {
2619                   xTexelC${w+1} = getX(batch, xR, xCOffset, d1);
2620                   if (xCOffset + 1 >= inDims[1]) {
2621                     xTexelC${w+1}.zw = vec2(0.);
2622                   }
2623                   xTexelC${w+1}Ready = 1;
2624                 }
2625
2626                 xC${w} = vec4(
2627                   xTexelC${w}.xy, xTexelC${w+1}.xy);
2628               `,w+1<d&&(f+=`
2629                   xC${w+1} = vec4(xTexelC${w}.zw, xTexelC${w+1}.zw);
2630                 `)));w<d&&(f+=`
2631             wTexel = getW(r, ${w}, d1, d2);
2632             dotProd += xC${w}.xxzz * vec4(wTexel.xy, wTexel.xy);
2633             if(d1 + 1 < ${e.inChannels}) {
2634               dotProd += xC${w}.yyww * vec4(wTexel.zw, wTexel.zw);
2635             }
2636           `,w+1<d&&(f+=`
2637               wTexel = getW(r, ${w+1}, d1, d2);
2638               dotProd += xC${w+1}.xxzz * vec4(wTexel.xy, wTexel.xy);
2639               if(d1 + 1 < ${e.inChannels}) {
2640                 dotProd += xC${w+1}.yyww * vec4(wTexel.zw, wTexel.zw);
2641               }
2642             `))}f+=`
2643     }
2644   `,f+=`
2645     }
2646   `,f+=`
2647     }
2648   `;let m="",x="";n&&(a?m=`vec4 activation(vec4 a) {
2649           vec4 b = getPreluActivationWeightsAtOutCoords();
2650           ${n}
2651         }`:r?m=`vec4 activation(vec4 a) {
2652           vec4 b = getLeakyreluAlphaAtOutCoords();
2653           ${n}
2654         }`:m=`vec4 activation(vec4 x) {
2655           ${n}
2656         }`,x="result = activation(result);");let y=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
2657       ${m}
2658
2659       void main() {
2660         ivec4 coords = getOutputCoords();
2661         int batch = coords.x;
2662         ivec2 xRCCorner = coords.yz * strides - pads;
2663         int d2 = coords.w;
2664         int xRCorner = xRCCorner.x;
2665         int xCCorner = xRCCorner.y;
2666
2667         //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
2668         vec4 dotProd = vec4(0.000000000000001);
2669
2670         ${f}
2671
2672         vec4 result = dotProd - vec4(0.000000000000001);
2673         ${y}
2674         ${x}
2675         setOutput(result);
2676       }
2677     `}},qTe=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec4"},{name:"pad",type:"ivec2"},{name:"stride",type:"ivec2"},{name:"dilation",type:"ivec2"},{name:"inChannels",type:"int"},{name:"itemsPerBlockRow",type:"int"},{name:"outWidth",type:"int"}],this.outputShape=e,this.enableShapeUniforms=ss(this.outputShape.length);let{dataFormat:n}=t,a=Is(),r=n==="channelsLast",s=r?1:2,i=r?2:3,o=this.enableShapeUniforms?"if(blockIndex < outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${e[2]} && pos < ${e[1]}) {`,l="";for(let d=0;d<=1;d++)for(let c=0;c<=1;c++)l+=`
2678          blockIndex = rc.z + ${c};
2679          pos = rc.y + ${d};
2680
2681          ${o}
2682            offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];
2683            d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);
2684
2685            if(d0 < inputShape[${s}] && d0 >= 0) {
2686              // Use custom imod instead mod. On Intel GPU, mod may generate
2687              // unexpected value.
2688              // https://github.com/tensorflow/tfjs/issues/5447
2689              offsetX = imod(blockIndex, outWidth) * stride[1] - pad[