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n=t.child;n!==null;){if(n.tag===5||n.tag===6)e.appendChild(n.stateNode);else if(n.tag!==4&&n.child!==null){n.child.return=n,n=n.child;continue}if(n===t)break;for(;n.sibling===null;){if(n.return===null||n.return===t)return;n=n.return}n.sibling.return=n.return,n=n.sibling}};a_=function(){};h2=function(e,t,n,o){var a=e.memoizedProps;if(a!==o){e=t.stateNode,ta(uo.current);var l=null;switch(n){case"input":a=Pg(e,a),o=Pg(e,o),l=[];break;case"select":a=on({},a,{value:void 0}),o=on({},o,{value:void 0}),l=[];break;case"textarea":a=Ig(e,a),o=Ig(e,o),l=[];break;default:typeof a.onClick!="function"&&typeof o.onClick=="function"&&(e.onclick=Ah)}zg(n,o);var f;n=null;for(g in a)if(!o.hasOwnProperty(g)&&a.hasOwnProperty(g)&&a[g]!=null)if(g==="style"){var _=a[g];for(f in _)_.hasOwnProperty(f)&&(n||(n={}),n[f]="")}else 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hf(e,t){if(!en)switch(e.tailMode){case"hidden":t=e.tail;for(var n=null;t!==null;)t.alternate!==null&&(n=t),t=t.sibling;n===null?e.tail=null:n.sibling=null;break;case"collapsed":n=e.tail;for(var o=null;n!==null;)n.alternate!==null&&(o=n),n=n.sibling;o===null?t||e.tail===null?e.tail=null:e.tail.sibling=null:o.sibling=null}}function Vn(e){var t=e.alternate!==null&&e.alternate.child===e.child,n=0,o=0;if(t)for(var a=e.child;a!==null;)n|=a.lanes|a.childLanes,o|=a.subtreeFlags&14680064,o|=a.flags&14680064,a.return=e,a=a.sibling;else for(a=e.child;a!==null;)n|=a.lanes|a.childLanes,o|=a.subtreeFlags,o|=a.flags,a.return=e,a=a.sibling;return e.subtreeFlags|=o,e.childLanes=n,t}function Nk(e,t,n){var o=t.pendingProps;switch(V_(t),t.tag){case 2:case 16:case 15:case 0:case 11:case 7:case 8:case 12:case 9:case 14:return Vn(t),null;case 1:return li(t.type)&&Ih(),Vn(t),null;case 3:return 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Error(bt(166));if(n=ta(Uf.current),ta(uo.current),rh(t)){if(o=t.stateNode,n=t.memoizedProps,o[ao]=t,(l=o.nodeValue!==n)&&(e=_i,e!==null))switch(e.tag){case 3:th(o.nodeValue,n,(e.mode&1)!==0);break;case 5:e.memoizedProps.suppressHydrationWarning!==!0&&th(o.nodeValue,n,(e.mode&1)!==0)}l&&(t.flags|=4)}else o=(n.nodeType===9?n:n.ownerDocument).createTextNode(o),o[ao]=t,t.stateNode=o}return Vn(t),null;case 13:if(Zr(rn),o=t.memoizedState,e===null||e.memoizedState!==null&&e.memoizedState.dehydrated!==null){if(en&&gi!==null&&t.mode&1&&!(t.flags&128))Fb(),Xl(),t.flags|=98560,l=!1;else if(l=rh(t),o!==null&&o.dehydrated!==null){if(e===null){if(!l)throw Error(bt(318));if(l=t.memoizedState,l=l!==null?l.dehydrated:null,!l)throw Error(bt(317));l[ao]=t}else Xl(),!(t.flags&128)&&(t.memoizedState=null),t.flags|=4;Vn(t),l=!1}else Hi!==null&&(m_(Hi),Hi=null),l=!0;if(!l)return t.flags&65536?t:null}return 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Kr(rn,rn.current&1|2),t.child}e=e.sibling}l.tail!==null&&fn()>eu&&(t.flags|=128,o=!0,hf(l,!1),t.lanes=4194304)}else{if(!o)if(e=Bh(f),e!==null){if(t.flags|=128,o=!0,n=e.updateQueue,n!==null&&(t.updateQueue=n,t.flags|=4),hf(l,!0),l.tail===null&&l.tailMode==="hidden"&&!f.alternate&&!en)return Vn(t),null}else 2*fn()-l.renderingStartTime>eu&&n!==1073741824&&(t.flags|=128,o=!0,hf(l,!1),t.lanes=4194304);l.isBackwards?(f.sibling=t.child,t.child=f):(n=l.last,n!==null?n.sibling=f:t.child=f,l.last=f)}return l.tail!==null?(t=l.tail,l.rendering=t,l.tail=t.sibling,l.renderingStartTime=fn(),t.sibling=null,n=rn.current,Kr(rn,o?n&1|2:n&1),t):(Vn(t),null);case 22:case 23:return u0(),o=t.memoizedState!==null,e!==null&&e.memoizedState!==null!==o&&(t.flags|=8192),o&&t.mode&1?mi&1073741824&&(Vn(t),t.subtreeFlags&6&&(t.flags|=8192)):Vn(t),null;case 24:return null;case 25:return null}throw Error(bt(156,t.tag))}function jk(e,t){switch(V_(t),t.tag){case 1:return li(t.type)&&Ih(),e=t.flags,e&65536?(t.flags=e&-65537|128,t):null;case 3:return Zl(),Zr(ai),Zr(Gn),Z_(),e=t.flags,e&65536&&!(e&128)?(t.flags=e&-65537|128,t):null;case 5:return Y_(t),null;case 13:if(Zr(rn),e=t.memoizedState,e!==null&&e.dehydrated!==null){if(t.alternate===null)throw Error(bt(340));Xl()}return e=t.flags,e&65536?(t.flags=e&-65537|128,t):null;case 19:return Zr(rn),null;case 4:return Zl(),null;case 10:return H_(t.type._context),null;case 22:case 23:return u0(),null;case 24:return null;default:return null}}var oh=!1,Wn=!1,Uk=typeof WeakSet=="function"?WeakSet:Set,jt=null;function Nl(e,t){var n=e.ref;if(n!==null)if(typeof n=="function")try{n(null)}catch(o){cn(e,t,o)}else n.current=null}function l_(e,t,n){try{n()}catch(o){cn(e,t,o)}}var Xv=!1;function Vk(e,t){if(Gg=Ch,e=vb(),j_(e)){if("selectionStart"in e)var n={start:e.selectionStart,end:e.selectionEnd};else e:{n=(n=e.ownerDocument)&&n.defaultView||window;var 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l=t.return;try{u_(t)}catch(h){cn(t,l,h)}break;case 5:var f=t.return;try{u_(t)}catch(h){cn(t,f,h)}}}catch(h){cn(t,t.return,h)}if(t===e){jt=null;break}var _=t.sibling;if(_!==null){_.return=t.return,jt=_;break}jt=t.return}}var Gk=Math.ceil,Uh=zo.ReactCurrentDispatcher,o0=zo.ReactCurrentOwner,zi=zo.ReactCurrentBatchConfig,Ir=0,Pn=null,hn=null,Dn=0,mi=0,jl=Ms(0),Tn=0,qf=null,aa=0,sm=0,s0=0,Cf=null,oi=null,a0=0,eu=1/0,To=null,Vh=!1,f_=null,_s=null,sh=!1,ds=null,Wh=0,Pf=0,p_=null,wh=-1,vh=0;function ei(){return Ir&6?fn():wh!==-1?wh:wh=fn()}function ys(e){return e.mode&1?Ir&2&&Dn!==0?Dn&-Dn:Ck.transition!==null?(vh===0&&(vh=ib()),vh):(e=Rr,e!==0||(e=window.event,e=e===void 0?16:db(e.type)),e):1}function Qi(e,t,n,o){if(50<Pf)throw Pf=0,p_=null,Error(bt(185));Qf(e,n,o),(!(Ir&2)||e!==Pn)&&(e===Pn&&(!(Ir&2)&&(sm|=n),Tn===4&&us(e,Dn)),ui(e,o),n===1&&Ir===0&&!(t.mode&1)&&(eu=fn()+500,rm&&Ts()))}function ui(e,t){var n=e.callbackNode;CT(e,t);var o=Eh(e,e===Pn?Dn:0);if(o===0)n!==null&&cv(n),e.callbackNode=null,e.callbackPriority=0;else if(t=o&-o,e.callbackPriority!==t){if(n!=null&&cv(n),t===1)e.tag===0?Ek(r1.bind(null,e)):$b(r1.bind(null,e)),Mk(function(){!(Ir&6)&&Ts()}),n=null;else{switch(ob(o)){case 1:n=F_;break;case 4:n=rb;break;case 16:n=Sh;break;case 536870912:n=nb;break;default:n=Sh}n=C2(n,b2.bind(null,e))}e.callbackPriority=t,e.callbackNode=n}}function b2(e,t){if(wh=-1,vh=0,Ir&6)throw Error(bt(327));var n=e.callbackNode;if(Hl()&&e.callbackNode!==n)return null;var o=Eh(e,e===Pn?Dn:0);if(o===0)return null;if(o&30||o&e.expiredLanes||t)t=Gh(e,o);else{t=o;var a=Ir;Ir|=2;var l=M2();(Pn!==e||Dn!==t)&&(To=null,eu=fn()+500,ra(e,t));do try{Kk();break}catch(_){x2(e,_)}while(!0);q_(),Uh.current=l,Ir=a,hn!==null?t=0:(Pn=null,Dn=0,t=Tn)}if(t!==0){if(t===2&&(a=Ng(e),a!==0&&(o=a,t=h_(e,a))),t===1)throw 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e.current.memoizedState.isDehydrated&&(ra(e,t).flags|=256),e=Gh(e,t),e!==2&&(t=oi,oi=n,t!==null&&m_(t)),e}function m_(e){oi===null?oi=e:oi.push.apply(oi,e)}function qk(e){for(var t=e;;){if(t.flags&16384){var n=t.updateQueue;if(n!==null&&(n=n.stores,n!==null))for(var o=0;o<n.length;o++){var a=n[o],l=a.getSnapshot;a=a.value;try{if(!Xi(l(),a))return!1}catch{return!1}}}if(n=t.child,t.subtreeFlags&16384&&n!==null)n.return=t,t=n;else{if(t===e)break;for(;t.sibling===null;){if(t.return===null||t.return===e)return!0;t=t.return}t.sibling.return=t.return,t=t.sibling}}return!0}function us(e,t){for(t&=~s0,t&=~sm,e.suspendedLanes|=t,e.pingedLanes&=~t,e=e.expirationTimes;0<t;){var n=31-Ki(t),o=1<<n;e[n]=-1,t&=~o}}function r1(e){if(Ir&6)throw Error(bt(327));Hl();var t=Eh(e,0);if(!(t&1))return ui(e,fn()),null;var n=Gh(e,t);if(e.tag!==0&&n===2){var o=Ng(e);o!==0&&(t=o,n=h_(e,o))}if(n===1)throw n=qf,ra(e,0),us(e,t),ui(e,fn()),n;if(n===6)throw Error(bt(345));return e.finishedWork=e.current.alternate,e.finishedLanes=t,Ys(e,oi,To),ui(e,fn()),null}function l0(e,t){var n=Ir;Ir|=1;try{return e(t)}finally{Ir=n,Ir===0&&(eu=fn()+500,rm&&Ts())}}function la(e){ds!==null&&ds.tag===0&&!(Ir&6)&&Hl();var t=Ir;Ir|=1;var n=zi.transition,o=Rr;try{if(zi.transition=null,Rr=1,e)return e()}finally{Rr=o,zi.transition=n,Ir=t,!(Ir&6)&&Ts()}}function u0(){mi=jl.current,Zr(jl)}function ra(e,t){e.finishedWork=null,e.finishedLanes=0;var n=e.timeoutHandle;if(n!==-1&&(e.timeoutHandle=-1,xk(n)),hn!==null)for(n=hn.return;n!==null;){var o=n;switch(V_(o),o.tag){case 1:o=o.type.childContextTypes,o!=null&&Ih();break;case 3:Zl(),Zr(ai),Zr(Gn),Z_();break;case 5:Y_(o);break;case 4:Zl();break;case 13:Zr(rn);break;case 19:Zr(rn);break;case 10:H_(o.type._context);break;case 22:case 23:u0()}n=n.return}if(Pn=e,hn=e=ws(e.current,null),Dn=mi=t,Tn=0,qf=null,s0=sm=aa=0,oi=Cf=null,ea!==null){for(t=0;t<ea.length;t++)if(n=ea[t],o=n.interleaved,o!==null){n.interleaved=null;var a=o.next,l=n.pending;if(l!==null){var f=l.next;l.next=a,o.next=f}n.pending=o}ea=null}return e}function x2(e,t){do{var n=hn;try{if(q_(),gh.current=jh,Nh){for(var o=nn.memoizedState;o!==null;){var a=o.queue;a!==null&&(a.pending=null),o=o.next}Nh=!1}if(sa=0,Cn=Mn=nn=null,Sf=!1,Vf=0,o0.current=null,n===null||n.return===null){Tn=1,qf=t,hn=null;break}e:{var l=e,f=n.return,_=n,h=t;if(t=Dn,_.flags|=32768,h!==null&&typeof h=="object"&&typeof h.then=="function"){var g=h,M=_,w=M.tag;if(!(M.mode&1)&&(w===0||w===11||w===15)){var C=M.alternate;C?(M.updateQueue=C.updateQueue,M.memoizedState=C.memoizedState,M.lanes=C.lanes):(M.updateQueue=null,M.memoizedState=null)}var k=Vv(f);if(k!==null){k.flags&=-257,Wv(k,f,_,l,t),k.mode&1&&Uv(l,g,t),t=k,h=g;var z=t.updateQueue;if(z===null){var S=new Set;S.add(h),t.updateQueue=S}else z.add(h);break e}else{if(!(t&1)){Uv(l,g,t),c0();break e}h=Error(bt(426))}}else if(en&&_.mode&1){var P=Vv(f);if(P!==null){!(P.flags&65536)&&(P.flags|=256),Wv(P,f,_,l,t),W_(Jl(h,_));break e}}l=h=Jl(h,_),Tn!==4&&(Tn=2),Cf===null?Cf=[l]:Cf.push(l),l=f;do{switch(l.tag){case 3:l.flags|=65536,t&=-t,l.lanes|=t;var y=o2(l,h,t);Dv(l,y);break e;case 1:_=h;var x=l.type,I=l.stateNode;if(!(l.flags&128)&&(typeof x.getDerivedStateFromError=="function"||I!==null&&typeof I.componentDidCatch=="function"&&(_s===null||!_s.has(I)))){l.flags|=65536,t&=-t,l.lanes|=t;var U=s2(l,_,t);Dv(l,U);break e}}l=l.return}while(l!==null)}k2(n)}catch(O){t=O,hn===n&&n!==null&&(hn=n=n.return);continue}break}while(!0)}function M2(){var e=Uh.current;return Uh.current=jh,e===null?jh:e}function c0(){(Tn===0||Tn===3||Tn===2)&&(Tn=4),Pn===null||!(aa&268435455)&&!(sm&268435455)||us(Pn,Dn)}function Gh(e,t){var n=Ir;Ir|=2;var o=M2();(Pn!==e||Dn!==t)&&(To=null,ra(e,t));do try{Hk();break}catch(a){x2(e,a)}while(!0);if(q_(),Ir=n,Uh.current=o,hn!==null)throw Error(bt(261));return Pn=null,Dn=0,Tn}function Hk(){for(;hn!==null;)T2(hn)}function Kk(){for(;hn!==null&&!wT();)T2(hn)}function T2(e){var t=E2(e.alternate,e,mi);e.memoizedProps=e.pendingProps,t===null?k2(e):hn=t,o0.current=null}function k2(e){var t=e;do{var n=t.alternate;if(e=t.return,t.flags&32768){if(n=jk(n,t),n!==null){n.flags&=32767,hn=n;return}if(e!==null)e.flags|=32768,e.subtreeFlags=0,e.deletions=null;else{Tn=6,hn=null;return}}else if(n=Nk(n,t,mi),n!==null){hn=n;return}if(t=t.sibling,t!==null){hn=t;return}hn=t=e}while(t!==null);Tn===0&&(Tn=5)}function Ys(e,t,n){var o=Rr,a=zi.transition;try{zi.transition=null,Rr=1,Qk(e,t,n,o)}finally{zi.transition=a,Rr=o}return null}function Qk(e,t,n,o){do Hl();while(ds!==null);if(Ir&6)throw Error(bt(327));n=e.finishedWork;var a=e.finishedLanes;if(n===null)return null;if(e.finishedWork=null,e.finishedLanes=0,n===e.current)throw Error(bt(177));e.callbackNode=null,e.callbackPriority=0;var l=n.lanes|n.childLanes;if(PT(e,l),e===Pn&&(hn=Pn=null,Dn=0),!(n.subtreeFlags&2064)&&!(n.flags&2064)||sh||(sh=!0,C2(Sh,function(){return Hl(),null})),l=(n.flags&15990)!==0,n.subtreeFlags&15990||l){l=zi.transition,zi.transition=null;var f=Rr;Rr=1;var _=Ir;Ir|=4,o0.current=null,Vk(e,n),w2(n,e),mk(qg),Ch=!!Gg,qg=Gg=null,e.current=n,Wk(n),vT(),Ir=_,Rr=f,zi.transition=l}else e.current=n;if(sh&&(sh=!1,ds=e,Wh=a),l=e.pendingLanes,l===0&&(_s=null),MT(n.stateNode),ui(e,fn()),t!==null)for(o=e.onRecoverableError,n=0;n<t.length;n++)a=t[n],o(a.value,{componentStack:a.stack,digest:a.digest});if(Vh)throw Vh=!1,e=f_,f_=null,e;return Wh&1&&e.tag!==0&&Hl(),l=e.pendingLanes,l&1?e===p_?Pf++:(Pf=0,p_=e):Pf=0,Ts(),null}function Hl(){if(ds!==null){var e=ob(Wh),t=zi.transition,n=Rr;try{if(zi.transition=null,Rr=16>e?16:e,ds===null)var o=!1;else{if(e=ds,ds=null,Wh=0,Ir&6)throw Error(bt(331));var a=Ir;for(Ir|=4,jt=e.current;jt!==null;){var l=jt,f=l.child;if(jt.flags&16){var _=l.deletions;if(_!==null){for(var h=0;h<_.length;h++){var g=_[h];for(jt=g;jt!==null;){var M=jt;switch(M.tag){case 0:case 11:case 15:Ef(8,M,l)}var w=M.child;if(w!==null)w.return=M,jt=w;else for(;jt!==null;){M=jt;var C=M.sibling,k=M.return;if(g2(M),M===g){jt=null;break}if(C!==null){C.return=k,jt=C;break}jt=k}}}var z=l.alternate;if(z!==null){var S=z.child;if(S!==null){z.child=null;do{var P=S.sibling;S.sibling=null,S=P}while(S!==null)}}jt=l}}if(l.subtreeFlags&2064&&f!==null)f.return=l,jt=f;else e:for(;jt!==null;){if(l=jt,l.flags&2048)switch(l.tag){case 0:case 11:case 15:Ef(9,l,l.return)}var y=l.sibling;if(y!==null){y.return=l.return,jt=y;break e}jt=l.return}}var x=e.current;for(jt=x;jt!==null;){f=jt;var I=f.child;if(f.subtreeFlags&2064&&I!==null)I.return=f,jt=I;else e:for(f=x;jt!==null;){if(_=jt,_.flags&2048)try{switch(_.tag){case 0:case 11:case 15:om(9,_)}}catch(O){cn(_,_.return,O)}if(_===f){jt=null;break e}var U=_.sibling;if(U!==null){U.return=_.return,jt=U;break e}jt=_.return}}if(Ir=a,Ts(),lo&&typeof lo.onPostCommitFiberRoot=="function")try{lo.onPostCommitFiberRoot(Yh,e)}catch{}o=!0}return o}finally{Rr=n,zi.transition=t}}return!1}function n1(e,t,n){t=Jl(n,t),t=o2(e,t,1),e=gs(e,t,1),t=ei(),e!==null&&(Qf(e,1,t),ui(e,t))}function cn(e,t,n){if(e.tag===3)n1(e,e,n);else for(;t!==null;){if(t.tag===3){n1(t,e,n);break}else if(t.tag===1){var o=t.stateNode;if(typeof t.type.getDerivedStateFromError=="function"||typeof o.componentDidCatch=="function"&&(_s===null||!_s.has(o))){e=Jl(n,e),e=s2(t,e,1),t=gs(t,e,1),e=ei(),t!==null&&(Qf(t,1,e),ui(t,e));break}}t=t.return}}function Xk(e,t,n){var o=e.pingCache;o!==null&&o.delete(t),t=ei(),e.pingedLanes|=e.suspendedLanes&n,Pn===e&&(Dn&n)===n&&(Tn===4||Tn===3&&(Dn&130023424)===Dn&&500>fn()-a0?ra(e,0):s0|=n),ui(e,t)}function S2(e,t){t===0&&(e.mode&1?(t=Xp,Xp<<=1,!(Xp&130023424)&&(Xp=4194304)):t=1);var n=ei();e=Io(e,t),e!==null&&(Qf(e,t,n),ui(e,n))}function Yk(e){var t=e.memoizedState,n=0;t!==null&&(n=t.retryLane),S2(e,n)}function Zk(e,t){var n=0;switch(e.tag){case 13:var o=e.stateNode,a=e.memoizedState;a!==null&&(n=a.retryLane);break;case 19:o=e.stateNode;break;default:throw Error(bt(314))}o!==null&&o.delete(t),S2(e,n)}var E2;E2=function(e,t,n){if(e!==null)if(e.memoizedProps!==t.pendingProps||ai.current)si=!0;else{if(!(e.lanes&n)&&!(t.flags&128))return si=!1,Bk(e,t,n);si=!!(e.flags&131072)}else si=!1,en&&t.flags&1048576&&Ab(t,Oh,t.index);switch(t.lanes=0,t.tag){case 2:var o=t.type;yh(e,t),e=t.pendingProps;var a=Ql(t,Gn.current);ql(t,n),a=e0(null,t,o,e,a,n);var l=t0();return t.flags|=1,typeof a=="object"&&a!==null&&typeof a.render=="function"&&a.$$typeof===void 0?(t.tag=1,t.memoizedState=null,t.updateQueue=null,li(o)?(l=!0,Fh(t)):l=!1,t.memoizedState=a.state!==null&&a.state!==void 0?a.state:null,Q_(t),a.updater=im,t.stateNode=a,a._reactInternals=t,t_(t,o,e,n),t=i_(null,t,o,!0,l,n)):(t.tag=0,en&&l&&U_(t),Jn(null,t,a,n),t=t.child),t;case 16:o=t.elementType;e:{switch(yh(e,t),e=t.pendingProps,a=o._init,o=a(o._payload),t.type=o,a=t.tag=eS(o),e=Gi(o,e),a){case 0:t=n_(null,t,o,e,n);break e;case 1:t=Hv(null,t,o,e,n);break e;case 11:t=Gv(null,t,o,e,n);break e;case 14:t=qv(null,t,o,Gi(o.type,e),n);break e}throw Error(bt(306,o,""))}return t;case 0:return o=t.type,a=t.pendingProps,a=t.elementType===o?a:Gi(o,a),n_(e,t,o,a,n);case 1:return o=t.type,a=t.pendingProps,a=t.elementType===o?a:Gi(o,a),Hv(e,t,o,a,n);case 3:e:{if(c2(t),e===null)throw Error(bt(387));o=t.pendingProps,l=t.memoizedState,a=l.element,Lb(e,t),Rh(t,o,null,n);var f=t.memoizedState;if(o=f.element,l.isDehydrated)if(l={element:o,isDehydrated:!1,cache:f.cache,pendingSuspenseBoundaries:f.pendingSuspenseBoundaries,transitions:f.transitions},t.updateQueue.baseState=l,t.memoizedState=l,t.flags&256){a=Jl(Error(bt(423)),t),t=Kv(e,t,o,n,a);break e}else if(o!==a){a=Jl(Error(bt(424)),t),t=Kv(e,t,o,n,a);break e}else for(gi=ms(t.stateNode.containerInfo.firstChild),_i=t,en=!0,Hi=null,n=Ob(t,null,o,n),t.child=n;n;)n.flags=n.flags&-3|4096,n=n.sibling;else{if(Xl(),o===a){t=Fo(e,t,n);break e}Jn(e,t,o,n)}t=t.child}return t;case 5:return Rb(t),e===null&&Zg(t),o=t.type,a=t.pendingProps,l=e!==null?e.memoizedProps:null,f=a.children,Hg(o,a)?f=null:l!==null&&Hg(o,l)&&(t.flags|=32),u2(e,t),Jn(e,t,f,n),t.child;case 6:return e===null&&Zg(t),null;case 13:return d2(e,t,n);case 4:return X_(t,t.stateNode.containerInfo),o=t.pendingProps,e===null?t.child=Yl(t,null,o,n):Jn(e,t,o,n),t.child;case 11:return o=t.type,a=t.pendingProps,a=t.elementType===o?a:Gi(o,a),Gv(e,t,o,a,n);case 7:return Jn(e,t,t.pendingProps,n),t.child;case 8:return Jn(e,t,t.pendingProps.children,n),t.child;case 12:return Jn(e,t,t.pendingProps.children,n),t.child;case 10:e:{if(o=t.type._context,a=t.pendingProps,l=t.memoizedProps,f=a.value,Kr(Dh,o._currentValue),o._currentValue=f,l!==null)if(Xi(l.value,f)){if(l.children===a.children&&!ai.current){t=Fo(e,t,n);break e}}else for(l=t.child,l!==null&&(l.return=t);l!==null;){var _=l.dependencies;if(_!==null){f=l.child;for(var h=_.firstContext;h!==null;){if(h.context===o){if(l.tag===1){h=Po(-1,n&-n),h.tag=2;var g=l.updateQueue;if(g!==null){g=g.shared;var M=g.pending;M===null?h.next=h:(h.next=M.next,M.next=h),g.pending=h}}l.lanes|=n,h=l.alternate,h!==null&&(h.lanes|=n),Jg(l.return,n,t),_.lanes|=n;break}h=h.next}}else if(l.tag===10)f=l.type===t.type?null:l.child;else if(l.tag===18){if(f=l.return,f===null)throw Error(bt(341));f.lanes|=n,_=f.alternate,_!==null&&(_.lanes|=n),Jg(f,n,t),f=l.sibling}else f=l.child;if(f!==null)f.return=l;else for(f=l;f!==null;){if(f===t){f=null;break}if(l=f.sibling,l!==null){l.return=f.return,f=l;break}f=f.return}l=f}Jn(e,t,a.children,n),t=t.child}return t;case 9:return a=t.type,o=t.pendingProps.children,ql(t,n),a=Oi(a),o=o(a),t.flags|=1,Jn(e,t,o,n),t.child;case 14:return o=t.type,a=Gi(o,t.pendingProps),a=Gi(o.type,a),qv(e,t,o,a,n);case 15:return a2(e,t,t.type,t.pendingProps,n);case 17:return o=t.type,a=t.pendingProps,a=t.elementType===o?a:Gi(o,a),yh(e,t),t.tag=1,li(o)?(e=!0,Fh(t)):e=!1,ql(t,n),i2(t,o,a),t_(t,o,a,n),i_(null,t,o,!0,e,n);case 19:return f2(e,t,n);case 22:return l2(e,t,n)}throw Error(bt(156,t.tag))};function C2(e,t){return tb(e,t)}function Jk(e,t,n,o){this.tag=e,this.key=n,this.sibling=this.child=this.return=this.stateNode=this.type=this.elementType=null,this.index=0,this.ref=null,this.pendingProps=t,this.dependencies=this.memoizedState=this.updateQueue=this.memoizedProps=null,this.mode=o,this.subtreeFlags=this.flags=0,this.deletions=null,this.childLanes=this.lanes=0,this.alternate=null}function Fi(e,t,n,o){return new Jk(e,t,n,o)}function d0(e){return e=e.prototype,!(!e||!e.isReactComponent)}function eS(e){if(typeof e=="function")return d0(e)?1:0;if(e!=null){if(e=e.$$typeof,e===$_)return 11;if(e===A_)return 14}return 2}function ws(e,t){var n=e.alternate;return n===null?(n=Fi(e.tag,t,e.key,e.mode),n.elementType=e.elementType,n.type=e.type,n.stateNode=e.stateNode,n.alternate=e,e.alternate=n):(n.pendingProps=t,n.type=e.type,n.flags=0,n.subtreeFlags=0,n.deletions=null),n.flags=e.flags&14680064,n.childLanes=e.childLanes,n.lanes=e.lanes,n.child=e.child,n.memoizedProps=e.memoizedProps,n.memoizedState=e.memoizedState,n.updateQueue=e.updateQueue,t=e.dependencies,n.dependencies=t===null?null:{lanes:t.lanes,firstContext:t.firstContext},n.sibling=e.sibling,n.index=e.index,n.ref=e.ref,n}function bh(e,t,n,o,a,l){var f=2;if(o=e,typeof e=="function")d0(e)&&(f=1);else if(typeof e=="string")f=5;else e:switch(e){case Al:return na(n.children,a,l,t);case P_:f=8,a|=8;break;case kg:return e=Fi(12,n,t,a|2),e.elementType=kg,e.lanes=l,e;case Sg:return e=Fi(13,n,t,a),e.elementType=Sg,e.lanes=l,e;case Eg:return e=Fi(19,n,t,a),e.elementType=Eg,e.lanes=l,e;case R1:return am(n,a,l,t);default:if(typeof e=="object"&&e!==null)switch(e.$$typeof){case D1:f=10;break e;case L1:f=9;break e;case $_:f=11;break e;case A_:f=14;break e;case ss:f=16,o=null;break e}throw Error(bt(130,e==null?e:typeof e,""))}return t=Fi(f,n,t,a),t.elementType=e,t.type=o,t.lanes=l,t}function na(e,t,n,o){return e=Fi(7,e,o,t),e.lanes=n,e}function am(e,t,n,o){return e=Fi(22,e,o,t),e.elementType=R1,e.lanes=n,e.stateNode={isHidden:!1},e}function bg(e,t,n){return e=Fi(6,e,null,t),e.lanes=n,e}function xg(e,t,n){return t=Fi(4,e.children!==null?e.children:[],e.key,t),t.lanes=n,t.stateNode={containerInfo:e.containerInfo,pendingChildren:null,implementation:e.implementation},t}function 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b=p.getMappedRange();if(u){let T=u();return T.set(new Uint8Array(b,0,s)),T}else return new Uint8Array(b.slice(0,s))}finally{p.destroy()}},At=class{constructor(r){this.backend=r,this.storageCache=new Map,this.freeBuffers=new Map,this.freeUniformBuffers=new Map,this.buffersForUploadingPending=[],this.buffersPending=[],this.externalBuffers=new Map,this.capturedPendingBuffers=new Map;for(let[i]of Pe)ze.push(i),this.freeBuffers.set(i,[]),this.freeUniformBuffers.set(i,[])}upload(r,i){let s=i.buffer,u=i.byteOffset,c=i.byteLength,p=Oe(c),d=this.storageCache.get(r);if(!d)throw new Error("gpu data for uploading does not exist");if(d.originalSize!==c)throw new Error(`inconsistent data size. gpu data size=${d.originalSize}, data size=${c}`);let b=this.backend.device.createBuffer({mappedAtCreation:!0,size:p,usage:GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC}),T=b.getMappedRange();new Uint8Array(T).set(new Uint8Array(s,u,c)),b.unmap();let E=this.backend.getCommandEncoder();this.backend.endComputePass(),E.copyBufferToBuffer(b,0,d.gpuData.buffer,0,p),Br("verbose",()=>`[WebGPU] GpuDataManager.upload(id=${r})`),this.buffersForUploadingPending.push(b)}memcpy(r,i){let s=this.storageCache.get(r);if(!s)throw new Error("source gpu data for memcpy does not exist");let u=this.storageCache.get(i);if(!u)throw new Error("destination gpu data for memcpy does not exist");if(s.originalSize!==u.originalSize)throw new Error("inconsistent source and destination gpu data size");let c=Oe(s.originalSize),p=this.backend.getCommandEncoder();this.backend.endComputePass(),p.copyBufferToBuffer(s.gpuData.buffer,0,u.gpuData.buffer,0,c)}registerExternalBuffer(r,i,s){let u;if(s){if(u=this.externalBuffers.get(s),u===void 0)throw new Error("previous buffer is not registered");if(r===s)return Br("verbose",()=>`[WebGPU] GpuDataManager.registerExternalBuffer(size=${i}) => id=${u}, buffer is the same, 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13:if(i>1)throw new Error("currently not supported vecX of uint64 yet");return["vec2<u32>","u32"];case 9:if(i!==4)throw new Error("bool must be vec4");return["u32","vec4<bool>"];default:throw new Error(`Unknown data type: ${r}`)}},Tr=(r,i=1)=>{let s=gn(r,i);return typeof s=="string"?s:s[0]},kr=(r,i=1)=>{let s=gn(r,i);return typeof s=="string"?s:s[1]},Ct=(...r)=>{let i=[];return r.forEach(s=>{s.length!==0&&i.push({type:12,data:s},{type:12,data:st.computeStrides(s)})}),i},wr=r=>r%4===0?4:r%2===0?2:1,zr=(r="f32",i,s="0")=>!i||i===1?`${r}(${s})`:`vec${i}<${r}>(${s})`,Gr=(r,i,s)=>r==="f32"?s:i===1?`f32(${s})`:`vec${i}<f32>(${s})`,Nn=(r,i)=>i===4?`(${r}.x + ${r}.y + ${r}.z + ${r}.w)`:i===2?`(${r}.x + ${r}.y)`:i===3?`(${r}.x + ${r}.y + ${r}.z)`:r,Dt=(r,i,s,u)=>r.startsWith("uniforms.")&&s>4?typeof i=="string"?u==="f16"?`${r}[(${i}) / 8][(${i}) % 8 / 4][(${i}) % 8 % 4]`:`${r}[(${i}) / 4][(${i}) % 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    let rest${pt} = current % ${Dt(be,pt,d)};
    indices[${pt}] = dim${pt};
    current = rest${pt};
    `;he+=`indices[${d-1}] = current;`;let Fe=d<2?"":`
  fn o2i_${r}(offset: u32) -> ${v.indices} {
    var indices: ${v.indices};
    var current = offset;
    ${he}
    return indices;
  }`,xe=pt=>(re.offsetToIndices=!0,d<2?pt:`o2i_${r}(${pt})`),Ie=[];if(d>=2)for(let pt=d-1;pt>=0;pt--)Ie.push(`${Dt(be,pt,d)} * (indices[${pt}])`);let ct=d<2?"":`
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  fn get_${r}ByIndices(indices: ${v.indices}) -> ${q} {
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  fn get_${r}(${pt}) -> ${q} {
    return get_${r}ByIndices(${vt(zt)});
  }`})(),jr=(...pt)=>{if(pt.length!==d)throw new Error(`indices length must be ${d}`);let zt=pt.map(ne).join(",");return d===0?yr("0u"):d===1?yr(zt[0]):(re.get=!0,re.getByIndices=!0,re.indicesToOffset=!0,`get_${r}(${zt})`)},It=pt=>d<2?yr(pt):(re.getByIndices=!0,re.indicesToOffset=!0,`get_${r}ByIndices(${pt})`),tr=d<2?"":`
  fn set_${r}ByIndices(indices: ${v.indices}, value: ${q}) {
    ${nr(`i2o_${r}(indices)`,"value")}
  }`,er=d<2?"":(()=>{let pt=b.map(ir=>`d${ir}: u32`).join(", "),zt=b.map(ir=>`d${ir}`).join(", ");return`
  fn set_${r}(${pt}, value: ${q}) {
    set_${r}ByIndices(${vt(zt)}, value);
  }`})();return{impl:()=>{let pt=[],zt=!1;return re.offsetToIndices&&(pt.push(Fe),zt=!0),re.indicesToOffset&&(pt.push(ct),zt=!0),re.broadcastedIndicesToOffset&&(Object.values(pr).forEach(ir=>pt.push(ir)),zt=!0),re.set&&(pt.push(er),zt=!0),re.setByIndices&&(pt.push(tr),zt=!0),re.get&&(pt.push(Sr),zt=!0),re.getByIndices&&(pt.push(qr),zt=!0),!p&&zt&&pt.unshift(`const ${_e} = ${v.indices}(${s.join(",")});`,`const ${be} = ${v.indices}(${st.computeStrides(s).join(",")});`),pt.join(`
`)},type:v,offsetToIndices:xe,indicesToOffset:et,broadcastedIndicesToOffset:ar,indices:vt,indicesGet:Ft,indicesSet:Lt,set:(...pt)=>{if(pt.length!==d+1)throw new Error(`indices length must be ${d}`);let zt=pt[d];if(typeof zt!="string")throw new Error("value must be string");let ir=pt.slice(0,d).map(ne).join(",");return d===0?nr("0u",zt):d===1?nr(ir[0],zt):(re.set=!0,re.setByIndices=!0,re.indicesToOffset=!0,`set_${r}(${ir}, ${zt})`)},setByOffset:nr,setByIndices:(pt,zt)=>d<2?nr(pt,zt):(re.setByIndices=!0,re.indicesToOffset=!0,`set_${r}ByIndices(${pt}, ${zt});`),get:jr,getByOffset:yr,getByIndices:It,usage:u,name:r,strides:be,shape:_e,rank:d}},gt=(r,i,s,u=1)=>Es(r,i,s,"input",u),Vt=(r,i,s,u=1)=>Es(r,i,s,"output",u),da=(r,i,s,u=1)=>Es(r,i,s,"internal",u),fa=class{constructor(r,i){this.normalizedDispatchGroup=r,this.limits=i,this.internalVariables=[],this.variables=[],this.uniforms=[],this.variableIndex=0}guardAgainstOutOfBoundsWorkgroupSizes(r){return`if (global_idx >= ${typeof r=="number"?`${r}u`:r}) { return; }`}mainStart(r=Bn){let i=typeof r=="number"?r:r[0],s=typeof r=="number"?1:r[1],u=typeof r=="number"?1:r[2];if(i>this.limits.maxComputeWorkgroupSizeX||s>this.limits.maxComputeWorkgroupSizeY||u>this.limits.maxComputeWorkgroupSizeZ)throw new Error(`workgroup size [${i}, ${s}, ${u}] exceeds the maximum workgroup size [${this.limits.maxComputeWorkgroupSizeX}, ${this.limits.maxComputeWorkgroupSizeY}, ${this.limits.maxComputeWorkgroupSizeZ}].`);if(i*s*u>this.limits.maxComputeInvocationsPerWorkgroup)throw new Error(`workgroup size [${i}, ${s}, ${u}] exceeds the maximum workgroup invocations ${this.limits.maxComputeInvocationsPerWorkgroup}.`);let c=this.normalizedDispatchGroup[1]===1&&this.normalizedDispatchGroup[2]===1,p=c?`@builtin(global_invocation_id) global_id : vec3<u32>,
    @builtin(workgroup_id) workgroup_id : vec3<u32>,
    @builtin(local_invocation_id) local_id : vec3<u32>`:`@builtin(global_invocation_id) global_id : vec3<u32>,
                                             @builtin(local_invocation_id) local_id : vec3<u32>,
    @builtin(local_invocation_index) local_idx : u32,
    @builtin(workgroup_id) workgroup_id : vec3<u32>,
    @builtin(num_workgroups) num_workgroups : vec3<u32>`,d=c?"let global_idx = global_id.x; let local_idx = local_id.x;":`let global_idx = (workgroup_id.z * num_workgroups[0] * num_workgroups[1] +
          workgroup_id.y * num_workgroups[0] + workgroup_id.x) * ${i*s*u}u + local_idx;`;return`@compute @workgroup_size(${i}, ${s}, ${u})
  fn main(${p}) {
    ${d}
  `}appendVariableUniforms(r){r.rank!==0&&(r.shape.startsWith("uniforms.")&&this.uniforms.push({name:r.shape.replace("uniforms.",""),type:"u32",length:r.rank}),r.strides.startsWith("uniforms.")&&this.uniforms.push({name:r.strides.replace("uniforms.",""),type:"u32",length:r.rank}))}declareVariable(r,i){if(r.usage==="internal")throw new Error("cannot use internal variable with declareVariable(). use registerInternalVariables() instead.");this.variables.push(r),this.appendVariableUniforms(r);let s=r.usage==="input"?"read":"read_write",u=r.type.storage;return`@group(0) @binding(${i}) var<storage, ${s}> ${r.name}: array<${u}>;`}declareVariables(...r){return r.map(i=>this.declareVariable(i,this.variableIndex++)).join(`
`)}registerInternalVariable(r){if(r.usage!=="internal")throw new Error("cannot use input or output variable with registerInternalVariable(). use declareVariables() instead.");this.internalVariables.push(r),this.appendVariableUniforms(r)}registerInternalVariables(...r){return r.forEach(i=>this.registerInternalVariable(i)),this}registerUniform(r,i,s=1){return this.uniforms.push({name:r,type:i,length:s}),this}registerUniforms(r){return this.uniforms=this.uniforms.concat(r),this}uniformDeclaration(){if(this.uniforms.length===0)return"";let r=[];for(let{name:i,type:s,length:u}of this.uniforms)if(u&&u>4)s==="f16"?r.push(`@align(16) ${i}:array<mat2x4<${s}>, ${Math.ceil(u/8)}>`):r.push(`${i}:array<vec4<${s}>, ${Math.ceil(u/4)}>`);else{let c=u==null||u===1?s:`vec${u}<${s}>`;r.push(`${i}:${c}`)}return`
      struct Uniforms { ${r.join(", ")} };
      @group(0) @binding(${this.variableIndex}) var<uniform> uniforms: Uniforms;`}get additionalImplementations(){return this.uniformDeclaration()+this.variables.map(r=>r.impl()).join(`
`)+this.internalVariables.map(r=>r.impl()).join(`
`)}get variablesInfo(){if(this.uniforms.length===0)return;let r=i=>[12,10,1,6][["u32","f16","f32","i32"].indexOf(i)];return this.uniforms.map(i=>[r(i.type),i.length??1])}},su=(r,i)=>new fa(r,i),go=(r,i)=>{let s=r.length,u=[];for(let c=0;c<s;c++){let p=s-1-c,d=r[p]||1;(i[i.length-1-c]||1)>1&&d===1&&u.unshift(p)}return u}}),au,pa,Wo,lu,fi,uu,ha,_o=h(()=>{Xt(),Yt(),mr(),or(),au=r=>{if(!r||r.length!==1)throw new Error("Transpose requires 1 input.")},pa=(r,i)=>i&&i.length!==r?[...new Array(r).keys()].reverse():i,Wo=(r,i)=>st.sortBasedOnPerm(r,pa(r.length,i)),lu=(r,i,s,u)=>{let c=[];c.push(`fn perm(i: ${u.type.indices}) -> ${s.type.indices} {
    var a: ${s.type.indices};`);for(let p=0;p<i;++p)c.push(s.indicesSet("a",r[p],`i[${p}]`));return c.push("return a;}"),c.join(`
`)},fi=(r,i)=>{let s=r.dataType,u=r.dims.length,c=pa(u,i),p=Wo(r.dims,c),d=Vt("output",s,p.length),b=gt("a",s,u),T;if(c.length===2&&c[0]===1&&c[1]===0){let E=d.type.value,q=[16,16,1];T=H=>`
  ${H.registerUniform("output_size","u32").declareVariables(b,d)}
  var<workgroup> tile : array<array<${E}, ${q[0]+1}>, ${q[0]}>;
  ${H.mainStart(q)}
    var x = workgroup_id.x * ${q[0]}u + local_id.x;
    var y = workgroup_id.y * ${q[0]}u + local_id.y;
    let width = uniforms.output_shape[0];
    let height = uniforms.output_shape[1];
    if (x < width && y < height) {
      tile[local_id.y][local_id.x] = ${b.getByOffset("y * width + x")};
    }
    workgroupBarrier();
    x = workgroup_id.y * ${q[0]}u + local_id.x;
    y = workgroup_id.x * ${q[0]}u + local_id.y;
    if (x < height && y < width) {
      ${d.setByOffset("y * height + x","tile[local_id.x][local_id.y]")}
    }
  }`}else T=E=>`
  ${E.registerUniform("output_size","u32").declareVariables(b,d)}

  ${lu(c,u,b,d)}

  ${E.mainStart()}
    ${E.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}

    let indices = ${d.offsetToIndices("global_idx")};
    let aIndices = perm(indices);

    ${d.setByOffset("global_idx",b.getByIndices("aIndices"))}
  }`;return{name:"Transpose",shaderCache:{hint:`${i}`,inputDependencies:["rank"]},getRunData:E=>{let q=st.size(p);return{outputs:[{dims:p,dataType:E[0].dataType}],dispatchGroup:{x:Math.ceil(q/64)},programUniforms:[{type:12,data:q},...Ct(E[0].dims,p)]}},getShaderSource:T}},uu=(r,i)=>{au(r.inputs),r.compute(fi(r.inputs[0],i.perm))},ha=r=>Gt({perm:r.perm})}),cu,du,fu,pu,ma,hu,mu,ga,gu,_u,Hn,yu,wu,_a,vu,bu,ya,xu,Mu,wa,Tu,ep=h(()=>{Xt(),Yt(),or(),Sa(),_o(),cu={max:"select(bestValue, candidate, candidate > bestValue)",min:"select(bestValue, candidate, candidate < bestValue)",mean:"bestValue + candidate",sum:"bestValue + candidate",prod:"bestValue * candidate",sumSquare:"bestValue + candidate * candidate",logSumExp:"bestValue + exp(candidate)",l1:"bestValue + abs(candidate)",l2:"bestValue + candidate * candidate",logSum:"bestValue + candidate"},du={max:"select(bestValue, candidate, candidate > bestValue)",min:"select(bestValue, candidate, candidate < bestValue)",mean:"bestValue + candidate",sum:"bestValue + candidate",prod:"bestValue * candidate",sumSquare:"bestValue + candidate",logSumExp:"bestValue + candidate",l1:"bestValue + candidate",l2:"bestValue + candidate",logSum:"bestValue + candidate"},fu={max:"_A[offset]",min:"_A[offset]",mean:"0",sum:"0",prod:"1",sumSquare:"0",logSumExp:"0",l1:"0",l2:"0",logSum:"0"},pu={max:"bestValue",min:"bestValue",sum:"bestValue",prod:"bestValue",sumSquare:"bestValue",logSumExp:"log(bestValue)",l1:"bestValue",l2:"sqrt(bestValue)",logSum:"log(bestValue)"},ma=(r,i)=>{let s=[];for(let u=i-r;u<i;++u)s.push(u);return s},hu=(r,i)=>{let s=[],u=r.length;for(let p=0;p<u;p++)i.indexOf(p)===-1&&s.push(r[p]);let c=i.map(p=>r[p]);return[s,c]},mu=(r,i)=>{let s=r.length+i.length,u=[],c=0;for(let p=0;p<s;p++)i.indexOf(p)===-1?u.push(r[c++]):u.push(1);return u},ga=(r,i)=>{for(let s=0;s<r.length;++s)if(r[r.length-s-1]!==i-1-s)return!1;return!0},gu=(r,i)=>{let s=[];if(!ga(r,i)){for(let u=0;u<i;++u)r.indexOf(u)===-1&&s.push(u);r.forEach(u=>s.push(u))}return s},_u=(r,i,s,u,c,p,d)=>{let b=s[0].dims,T=st.size(p),E=st.size(d),q=gt("_A",s[0].dataType,b),H=Vt("output",c,p),v=32,ne=`
          var<workgroup> aBestValues : array<f32, ${v}>;
       `;return{name:r,shaderCache:i,getShaderSource:re=>`
        ${re.registerUniform("reduceSize","u32").declareVariables(q,H)}
        ${ne}
        fn DIV_CEIL(a : u32, b : u32) -> u32 {
          return ((a - 1u) / b + 1u);
         }
         ${re.mainStart(v)}

          let outputIndex = global_idx / ${v};
          let offset = outputIndex * uniforms.reduceSize;

          var bestValue = f32(${fu[u]});
          let Length = uniforms.reduceSize;
          for (var k = local_idx; k < Length; k = k + ${v}) {
           let candidate = f32(${q.getByOffset("offset + k")});
           bestValue = ${cu[u]};
          }
          aBestValues[local_idx] = bestValue;
          workgroupBarrier();

         var reduceSize = min(Length, ${v}u);
         for (var currentSize = reduceSize / 2u; reduceSize > 1u;
             currentSize = reduceSize / 2u) {
           let interval = DIV_CEIL(reduceSize, 2u);
           if (local_idx < currentSize) {
            let candidate = aBestValues[local_idx + interval];
            bestValue = ${du[u]};
            aBestValues[local_idx] = bestValue;
           }
           reduceSize = interval;
           workgroupBarrier();
         }

         if (local_idx == 0u) {
          ${H.setByOffset("outputIndex",`${u==="mean"?`${H.type.storage}(bestValue / f32(uniforms.reduceSize))`:`${H.type.storage}(${pu[u]})`}`)};
         }
        }`,getRunData:()=>({outputs:[{dims:p,dataType:c}],dispatchGroup:{x:T},programUniforms:[{type:12,data:E}]})}},Hn=(r,i,s,u)=>{let c=r.inputs.length===1?s:Ps(r.inputs,s),p=c.axes;p.length===0&&!c.noopWithEmptyAxes&&(p=r.inputs[0].dims.map((ne,re)=>re));let d=st.normalizeAxes(p,r.inputs[0].dims.length),b=d,T=r.inputs[0],E=gu(b,r.inputs[0].dims.length);E.length>0&&(T=r.compute(fi(r.inputs[0],E),{inputs:[0],outputs:[-1]})[0],b=ma(b.length,T.dims.length));let[q,H]=hu(T.dims,b),v=q;c.keepDims&&(v=mu(q,d)),r.compute(_u(i,{hint:c.cacheKey,inputDependencies:["type"]},[T],u,r.inputs[0].dataType,v,H),{inputs:[T]})},yu=(r,i)=>{Hn(r,"ReduceMeanShared",i,"mean")},wu=(r,i)=>{Hn(r,"ReduceL1Shared",i,"l1")},_a=(r,i)=>{Hn(r,"ReduceL2Shared",i,"l2")},vu=(r,i)=>{Hn(r,"ReduceLogSumExpShared",i,"logSumExp")},bu=(r,i)=>{Hn(r,"ReduceMaxShared",i,"max")},ya=(r,i)=>{Hn(r,"ReduceMinShared",i,"min")},xu=(r,i)=>{Hn(r,"ReduceProdShared",i,"prod")},Mu=(r,i)=>{Hn(r,"ReduceSumShared",i,"sum")},wa=(r,i)=>{Hn(r,"ReduceSumSquareShared",i,"sumSquare")},Tu=(r,i)=>{Hn(r,"ReduceLogSumShared",i,"logSum")}}),Kn,ku,Cs,Ps,ni,Su,va,Eu,Cu,ba,Pu,$u,xa,Au,Iu,Qn,Fu,zu,Ma,Ou,Du,Ta,Lu,Ru,ka,Bu,Sa=h(()=>{Xt(),Yt(),mr(),or(),ep(),Kn=r=>{if(!r||r.length===0||r.length>2)throw new Error("Reduce op requires 1 or 2 inputs.");if(r.length===2&&r[1].dims.length!==1)throw new Error("Invalid axes input dims.")},ku=r=>["","",`var value = ${r.getByIndices("input_indices")};`,""],Cs=(r,i,s,u,c,p,d=!1,b=!1)=>{let T=[],E=s[0].dims,q=E.length,H=st.normalizeAxes(c,q),v=!b&&H.length===0;E.forEach((ce,_e)=>{v||H.indexOf(_e)>=0?d&&T.push(1):T.push(ce)});let ne=T.length,re=st.size(T);return{name:r,shaderCache:i,getShaderSource:ce=>{let _e=[],be=gt("_A",s[0].dataType,q),he=Vt("output",p,ne),Fe=u(be,he,H),xe=Fe[2];for(let Ie=0,ct=0;Ie<q;Ie++)v||H.indexOf(Ie)>=0?(d&&ct++,xe=`for(var j${Ie}: u32 = 0; j${Ie} < ${E[Ie]}; j${Ie}++) {
                  ${Fe[2].includes("last_index")?`let last_index = j${Ie};`:""}
                  ${be.indicesSet("input_indices",Ie,`j${Ie}`)}
                  ${xe}
                }`):(_e.push(`${be.indicesSet("input_indices",Ie,he.indicesGet("output_indices",ct))};`),ct++);return`

        ${ce.registerUniform("output_size","u32").declareVariables(be,he)}

        ${ce.mainStart()}
          ${ce.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
          var input_indices: ${be.type.indices};
          let output_indices = ${he.offsetToIndices("global_idx")};

          ${_e.join(`
`)}
          ${Fe[0]}       // init ops for reduce max/min
          ${Fe[1]}
          ${xe}
          ${Fe[3]}
          ${Fe.length===4?he.setByOffset("global_idx","value"):Fe.slice(4).join(`
`)}
        }`},getRunData:()=>({outputs:[{dims:T,dataType:p}],dispatchGroup:{x:Math.ceil(re/64)},programUniforms:[{type:12,data:re},...Ct(E,T)]})}},Ps=(r,i)=>{let s=[];return r[1].dims[0]>0&&r[1].getBigInt64Array().forEach(u=>s.push(Number(u))),Gt({axes:s,keepDims:i.keepDims,noopWithEmptyAxes:i.noopWithEmptyAxes})},ni=(r,i,s,u)=>{let c=r.inputs,p=c.length===1?s:Ps(c,s);r.compute(Cs(i,{hint:p.cacheKey,inputDependencies:["rank"]},[c[0]],p.noopWithEmptyAxes&&p.axes.length===0?ku:u,p.axes,c[0].dataType,p.keepDims,p.noopWithEmptyAxes),{inputs:[0]})},Su=(r,i)=>{Kn(r.inputs),ni(r,"ReduceLogSum",i,(s,u)=>[`var value = ${u.type.storage}(0);`,"",`value += ${s.getByIndices("input_indices")};`,"value = log(value);"])},va=(r,i)=>{Kn(r.inputs),ni(r,"ReduceL1",i,(s,u)=>[`var value = ${u.type.storage}(0);`,"",`value += abs(${s.getByIndices("input_indices")});`,""])},Eu=(r,i)=>{Kn(r.inputs),ni(r,"ReduceL2",i,(s,u)=>[`var t = ${u.type.value}(0); var value = ${u.type.value}(0);`,"",`t = ${s.getByIndices("input_indices")}; value += (t * t);`,"value = sqrt(value);"])},Cu=(r,i)=>{Kn(r.inputs),ni(r,"ReduceLogSumExp",i,(s,u)=>[`var value = ${u.type.storage}(0);`,"",`value += exp(${s.getByIndices("input_indices")});`,"value = log(value);"])},ba=(r,i)=>{Kn(r.inputs),ni(r,"ReduceMax",i,(s,u,c)=>{let p=[];for(let d=0;d<s.rank;d++)(c.indexOf(d)>=0||c.length===0)&&p.push(s.indicesSet("input_indices",d,0));return[`${p.join(`
`)}`,`var value = ${s.getByIndices("input_indices")};`,`value = max(value, ${s.getByIndices("input_indices")});`,""]})},Pu=(r,i)=>{Kn(r.inputs),ni(r,"ReduceMean",i,(s,u,c)=>{let p=1;for(let d=0;d<s.rank;d++)(c.indexOf(d)>=0||c.length===0)&&(p*=r.inputs[0].dims[d]);return["var sum = f32(0);","",`sum += f32(${s.getByIndices("input_indices")});`,`let value = ${u.type.value}(sum / ${p});`]})},$u=(r,i)=>{Kn(r.inputs),ni(r,"ReduceMin",i,(s,u,c)=>{let p=[];for(let d=0;d<s.rank;d++)(c.indexOf(d)>=0||c.length===0)&&p.push(`input_indices[${d}] = 0;`);return[`${p.join(`
`)}`,`var value = ${s.getByIndices("input_indices")};`,`value = min(value, ${s.getByIndices("input_indices")});`,""]})},xa=(r,i)=>{Kn(r.inputs),ni(r,"ReduceProd",i,(s,u)=>[`var value = ${u.type.storage}(1);`,"",`value *= ${s.getByIndices("input_indices")};`,""])},Au=(r,i)=>{Kn(r.inputs),ni(r,"ReduceSum",i,(s,u)=>[`var value = ${u.type.storage}(0);`,"",`value += ${s.getByIndices("input_indices")};`,""])},Iu=(r,i)=>{Kn(r.inputs),ni(r,"ReduceSumSquare",i,(s,u)=>[`var t = ${u.type.value}(0); var value = ${u.type.value}(0);`,"",`t = ${s.getByIndices("input_indices")}; value += t * t;`,""])},Qn=(r,i,s)=>{if(i.length===0)return s;let u=1,c=1;for(let p=0;p<i.length;p++)i.indexOf(p)===-1?u*=r[p]:c*=r[p];return c<32&&u>1024},Fu=(r,i)=>{Qn(r.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Pu(r,i):yu(r,i)},zu=(r,i)=>{Qn(r.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?va(r,i):wu(r,i)},Ma=(r,i)=>{Qn(r.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Eu(r,i):_a(r,i)},Ou=(r,i)=>{Qn(r.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Cu(r,i):vu(r,i)},Du=(r,i)=>{Qn(r.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?ba(r,i):bu(r,i)},Ta=(r,i)=>{Qn(r.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?$u(r,i):ya(r,i)},Lu=(r,i)=>{Qn(r.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?xa(r,i):xu(r,i)},Ru=(r,i)=>{Qn(r.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Au(r,i):Mu(r,i)},ka=(r,i)=>{Qn(r.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Iu(r,i):wa(r,i)},Bu=(r,i)=>{Qn(r.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Su(r,i):Tu(r,i)}}),$s,Nu,ju,As,tp=h(()=>{Xt(),mr(),Sa(),$s=r=>{if(!r||r.length===0||r.length>2)throw new Error("ArgMinMaxOp op requires 1 or 2 inputs.");if(r[0].dataType!==1)throw new Error("Invalid input type.")},Nu=(r,i)=>{$s(r.inputs);let s=(u,c,p)=>{let d=[];for(let b=0;b<u.rank;b++)(p.indexOf(b)>=0||p.length===0)&&d.push(`input_indices[${b}] = 0;`);return[`${d.join(`
`)}`,`var value = ${u.getByIndices("input_indices")};
var best_index : i32 = 0;`,`if (${u.getByIndices("input_indices")} ${i.selectLastIndex>0?"<=":"<"} value) {
         value = ${u.getByIndices("input_indices")};
         best_index = i32(last_index);
       }`,"",c.setByOffset("global_idx","best_index")]};r.compute(Cs("ArgMin",{hint:i.cacheKey,inputDependencies:["rank"]},[r.inputs[0]],s,[i.axis],7,i.keepDims),{inputs:[0]})},ju=(r,i)=>{$s(r.inputs);let s=(u,c,p)=>{let d=[];for(let b=0;b<u.rank;b++)(p.indexOf(b)>=0||p.length===0)&&d.push(`input_indices[${b}] = 0;`);return[`${d.join(`
`)}`,`var value = ${u.getByIndices("input_indices")};
var best_index : i32 = 0;`,`if (${u.getByIndices("input_indices")} ${i.selectLastIndex>0?">=":">"} value) {
         value = ${u.getByIndices("input_indices")};
         best_index = i32(last_index);
       }`,"",c.setByOffset("global_idx","best_index")]};r.compute(Cs("argMax",{hint:i.cacheKey,inputDependencies:["rank"]},[r.inputs[0]],s,[i.axis],7,i.keepDims),{inputs:[0]})},As=r=>Gt(r)}),Uu,Ea,Vu,Wu,yo,Gu,qu,Is=h(()=>{Xt(),Yt(),fe(),or(),Uu=(r,i)=>{let s=r[0],u=r[1],c=r[2],p=r[3],d=r[4],b=r[5];if(d&&b)throw new Error("Attention cannot have both past and attention_bias");if(s.dims.length!==3)throw new Error('Input "input" must have 3 dimensions');let T=s.dims[0],E=s.dims[1],q=s.dims[2];if(c.dims.length!==1)throw new Error('Input "bias" is expected to have 1 dimensions');if(u.dims.length!==2)throw new Error('Input "weights" is expected to have 2 dimensions');if(u.dims[0]!==q)throw new Error("Input 1 dimension 0 should have same length as dimension 2 of input 0");if(c.dims[0]!==u.dims[1])throw new Error('Input "bias" dimension 0 should have same length as dimension 1 of input "weights"');let H=c.dims[0]/3,v=H,ne=v;if(i.qkvHiddenSizes.length>0){if(i.qkvHiddenSizes.length!==3)throw new Error("qkv_hidden_sizes attribute should have 3 elements");for(let Fe of i.qkvHiddenSizes)if(Fe%i.numHeads!==0)throw new Error("qkv_hidden_sizes should be divisible by num_heads");H=i.qkvHiddenSizes[0],v=i.qkvHiddenSizes[1],ne=i.qkvHiddenSizes[2]}let re=E;if(H!==v)throw new Error("qkv_hidden_sizes first element should be same as the second");if(c.dims[0]!==H+v+ne)throw new Error('Input "bias" dimension 0 should have same length as sum of Q/K/V hidden sizes');let ce=0;if(d){if(v!==ne)throw new Error('Input "past" expect k_hidden_size == v_hidden_size');if(d.dims.length!==5)throw new Error('Input "past" must have 5 dimensions');if(d.dims[0]!==2)throw new Error('Input "past" first dimension must be 2');if(d.dims[1]!==T)throw new Error('Input "past" second dimension must be batch_size');if(d.dims[2]!==i.numHeads)throw new Error('Input "past" third dimension must be num_heads');if(d.dims[4]!==v/i.numHeads)throw new Error('Input "past" fifth dimension must be k_hidden_size / num_heads');i.pastPresentShareBuffer||(ce=d.dims[3])}let _e=re+ce,be=-1,he=0;if(p)throw new Error("Mask not supported");if(d)throw new Error("past is not supported");if(b){if(b.dims.length!==4)throw new Error('Input "attention_bias" must have 4 dimensions');if(b.dims[0]!==T||b.dims[1]!==i.numHeads||b.dims[2]!==E||b.dims[3]!==_e)throw new Error('Expect "attention_bias" shape (batch_size, num_heads, sequence_length, total_sequence_length)')}return{batchSize:T,sequenceLength:E,pastSequenceLength:ce,kvSequenceLength:re,totalSequenceLength:_e,maxSequenceLength:be,inputHiddenSize:q,hiddenSize:H,vHiddenSize:ne,headSize:Math.floor(H/i.numHeads),vHeadSize:Math.floor(ne/i.numHeads),numHeads:i.numHeads,isUnidirectional:!1,pastPresentShareBuffer:!1,maskFilterValue:i.maskFilterValue,maskType:he,scale:i.scale,broadcastResPosBias:!1,passPastInKv:!1,qkvFormat:1}},Ea=(r,i,s)=>{let u=wr(s),c=64,p=s/u;p<c&&(c=32);let d=Math.ceil(s/u/c),b=[{type:1,data:1/s},{type:12,data:p},{type:12,data:d}],T=Tr(r.dataType,u),E=kr(1,u),q=["type"],H=v=>{let ne=Vt("x",r.dataType,r.dims,u),re=kr(r.dataType),ce=[{name:"d_inv",type:"f32"},{name:"d_comp",type:"u32"},{name:"elements_per_thread",type:"u32"}];return`
  var<workgroup> thread_max: array<f32, ${c}>;
  var<workgroup> thread_sum: array<f32, ${c}>;
  ${v.registerUniforms(ce).declareVariables(ne)}
  ${v.mainStart([c,1,1])}
    let local_offset = local_idx * uniforms.elements_per_thread;
    let offset = (global_idx / ${c}) * uniforms.d_comp + local_offset;

    var thread_max_vector = ${E}(-3.402823e+38f);
    for (var i: u32 = 0; i < uniforms.elements_per_thread && i + local_offset < uniforms.d_comp; i++) {
      thread_max_vector = max(${E}(x[offset + i]), thread_max_vector);
    }
    thread_max[local_idx] = ${(()=>{switch(u){case 1:return"thread_max_vector";case 2:return"max(thread_max_vector.x, thread_max_vector.y)";case 4:return"max(max(thread_max_vector.x, thread_max_vector.y), max(thread_max_vector.z, thread_max_vector.w))";default:throw new Error(`Unsupported components: ${u}`)}})()};
    workgroupBarrier();

    var max_value =  f32(-3.402823e+38f);
    for (var i = 0u; i < ${c}; i++) {
      max_value = max(thread_max[i], max_value);
    }

    var sum_vector = ${E}(0);
    for (var i: u32 = 0; i < uniforms.elements_per_thread && i + local_offset < uniforms.d_comp; i++) {
      sum_vector += exp(${E}(x[offset + i]) - max_value);
    }
    thread_sum[local_idx] = ${(()=>{switch(u){case 1:return"sum_vector";case 2:return"sum_vector.x + sum_vector.y";case 4:return"sum_vector.x + sum_vector.y + sum_vector.z + sum_vector.w";default:throw new Error(`Unsupported components: ${u}`)}})()};
    workgroupBarrier();

    var sum: f32 = 0;
    for (var i = 0u; i < ${c}; i++) {
      sum += thread_sum[i];
    }

    if (sum == 0) {
      for (var i: u32 = 0; i < uniforms.elements_per_thread && i + local_offset < uniforms.d_comp; i++) {
        x[offset + i] = ${ne.type.value}(${re}(uniforms.d_inv));
      }
    } else {
      for (var i: u32 = 0; i < uniforms.elements_per_thread && i + local_offset < uniforms.d_comp; i++) {
        var f32input = ${E}(x[offset + i]);
        x[offset + i] = ${ne.type.value}(exp(f32input - max_value) / sum);
      }
    }
  }`};return{name:"AttentionProbsSoftmax",shaderCache:{hint:`${c};${T};${u}`,inputDependencies:q},getShaderSource:H,getRunData:()=>({outputs:[],dispatchGroup:{x:i},programUniforms:b})}},Vu=(r,i,s,u,c,p,d,b)=>{let T=b+p.kvSequenceLength,E=[p.batchSize,p.numHeads,p.sequenceLength,T],q=p.kvNumHeads===void 0&&r>1&&u,H=q?[p.batchSize,p.numHeads,T,p.headSize]:void 0,v=d.scale===0?1/Math.sqrt(p.headSize):d.scale,ne=wr(p.headSize),re=p.headSize/ne,ce=12,_e={x:Math.ceil(T/ce),y:Math.ceil(p.sequenceLength/ce),z:p.batchSize*p.numHeads},be=[{type:12,data:p.sequenceLength},{type:12,data:re},{type:12,data:T},{type:12,data:p.numHeads},{type:1,data:v},{type:12,data:b},{type:12,data:p.kvSequenceLength}],he=q&&u&&st.size(u.dims)>0,Fe=["type","type"];he&&Fe.push("type"),c&&Fe.push("type");let xe=[{dims:E,dataType:i.dataType,gpuDataType:0}];q&&xe.push({dims:H,dataType:i.dataType,gpuDataType:0});let Ie=ct=>{let et=gt("q",i.dataType,i.dims,ne),vt=gt("key",s.dataType,s.dims,ne),Ft=[et,vt];if(he){let yr=gt("past_key",u.dataType,u.dims,ne);Ft.push(yr)}c&&Ft.push(gt("attention_bias",c.dataType,c.dims));let Lt=Vt("output",i.dataType,E),pr=[Lt];q&&pr.push(Vt("present_key",i.dataType,H,ne));let ar=kr(1,ne),nr=[{name:"M",type:"u32"},{name:"K",type:"u32"},{name:"N",type:"u32"},{name:"num_heads",type:"u32"},{name:"alpha",type:"f32"},{name:"past_sequence_length",type:"u32"},{name:"kv_sequence_length",type:"u32"}];return`
  const TILE_SIZE = ${ce}u;

  var<workgroup> tileQ: array<${et.type.storage}, ${ce*ce}>;
  var<workgroup> tileK: array<${et.type.storage}, ${ce*ce}>;
  ${ct.registerUniforms(nr).declareVariables(...Ft,...pr)}
  ${ct.mainStart([ce,ce,1])}
    // x holds the N and y holds the M
    let headIdx = workgroup_id.z;
    let m = workgroup_id.y * TILE_SIZE;
    let n = workgroup_id.x * TILE_SIZE;
    let qOffset = uniforms.M * uniforms.K * headIdx + m * uniforms.K;
    ${he&&q?`
    let kOffset = uniforms.kv_sequence_length * uniforms.K * headIdx;
    let pastKeyOffset = uniforms.past_sequence_length * uniforms.K * headIdx;`:`
    let kOffset = uniforms.N * uniforms.K * headIdx + n * uniforms.K;`}
    ${q?"let presentKeyOffset = headIdx * uniforms.N * uniforms.K;":""}
    var value = ${ar}(0);
    for (var w: u32 = 0u; w < uniforms.K; w += TILE_SIZE) {
      if (global_id.y < uniforms.M && w + local_id.x < uniforms.K) {
        tileQ[TILE_SIZE * local_id.y + local_id.x] = q[qOffset + local_id.y * uniforms.K + w + local_id.x];
      }
      if (n + local_id.y < uniforms.N && w + local_id.x < uniforms.K) {
        var idx = TILE_SIZE * local_id.y + local_id.x;
      ${he&&q?`
              if (n + local_id.y < uniforms.past_sequence_length) {
                tileK[idx] = past_key[pastKeyOffset + (n + local_id.y) * uniforms.K + w + local_id.x];
              } else {
                tileK[idx] =
                         key[kOffset + (n + local_id.y - uniforms.past_sequence_length) * uniforms.K + w + local_id.x];
              }`:"tileK[idx] = key[kOffset + local_id.y * uniforms.K + w + local_id.x];"}
      ${q?"present_key[presentKeyOffset + (n + local_id.y) * uniforms.K + w + local_id.x] = tileK[idx];":""}
      }
      workgroupBarrier();

      for (var k: u32 = 0u; k < TILE_SIZE && w+k < uniforms.K; k++) {
        value += ${ar}(tileQ[TILE_SIZE * local_id.y + k] * tileK[TILE_SIZE * local_id.x + k]);
      }

      workgroupBarrier();
    }

    let headOffset = headIdx * uniforms.M * uniforms.N;
    if (global_id.y < uniforms.M && global_id.x < uniforms.N) {
      let outputIdx = headOffset + global_id.y * uniforms.N + global_id.x;
      var sum: f32 = ${(()=>{switch(ne){case 1:return"value";case 2:return"value.x + value.y";case 4:return"value.x + value.y + value.z + value.w";default:throw new Error(`Unsupported components: ${ne}`)}})()};
        output[outputIdx] = ${Lt.type.value} (sum * uniforms.alpha) + ${c?"attention_bias[outputIdx]":"0.0"};
    }
  }`};return{name:"AttentionProbs",shaderCache:{hint:`${ne};${c!==void 0};${u!==void 0};${r}`,inputDependencies:Fe},getRunData:()=>({outputs:xe,dispatchGroup:_e,programUniforms:be}),getShaderSource:Ie}},Wu=(r,i,s,u,c,p)=>{let d=p+c.kvSequenceLength,b=c.nReps?c.nReps:1,T=c.vHiddenSize*b,E=c.kvNumHeads==null&&r>1&&u,q=E?[c.batchSize,c.numHeads,d,c.headSize]:void 0,H=[c.batchSize,c.sequenceLength,T],v=12,ne={x:Math.ceil(c.vHeadSize/v),y:Math.ceil(c.sequenceLength/v),z:c.batchSize*c.numHeads},re=[{type:12,data:c.sequenceLength},{type:12,data:d},{type:12,data:c.vHeadSize},{type:12,data:c.numHeads},{type:12,data:T},{type:12,data:p},{type:12,data:c.kvSequenceLength}],ce=E&&u&&st.size(u.dims)>0,_e=["type","type"];ce&&_e.push("type");let be=[{dims:H,dataType:i.dataType,gpuDataType:0}];E&&be.push({dims:q,dataType:i.dataType,gpuDataType:0});let he=Fe=>{let xe=gt("probs",i.dataType,i.dims),Ie=gt("v",s.dataType,s.dims),ct=[xe,Ie];ce&&ct.push(gt("past_value",u.dataType,u.dims));let et=[Vt("output",i.dataType,H)];E&&et.push(Vt("present_value",i.dataType,q));let vt=[{name:"M",type:"u32"},{name:"K",type:"u32"},{name:"N",type:"u32"},{name:"num_heads",type:"u32"},{name:"v_hidden_size",type:"u32"},{name:"past_sequence_length",type:"u32"},{name:"kv_sequence_length",type:"u32"}];return`
  const TILE_SIZE = ${v}u;
  var<workgroup> tileQ: array<${xe.type.value}, ${v*v}>;
  var<workgroup> tileK: array<${xe.type.value}, ${v*v}>;
  ${Fe.registerUniforms(vt).declareVariables(...ct,...et)}
  ${Fe.mainStart([v,v,1])}
   let headIdx = workgroup_id.z;
   let m = global_id.y;
   let n = global_id.x;

   let offsetA = headIdx * (uniforms.M * uniforms.K) + m * uniforms.K;
   ${ce&&E?`
    let pastValueOffset = headIdx * uniforms.N * uniforms.past_sequence_length + n;
    let vOffset = headIdx * uniforms.N * uniforms.kv_sequence_length + n;
      `:`
   let offsetB = headIdx * uniforms.N * uniforms.K + n;
            `}
    ${E?"let presentValueOffset = headIdx * uniforms.N * uniforms.K + n;":""}
   var value = ${xe.type.storage}(0);
   for (var w: u32 = 0u; w < uniforms.K; w += TILE_SIZE) {
      if (m < uniforms.M && w + local_id.x < uniforms.K) {
        tileQ[TILE_SIZE * local_id.y + local_id.x] = probs[offsetA + w + local_id.x];
      }
      if (n < uniforms.N && w + local_id.y < uniforms.K) {
        var idx = TILE_SIZE * local_id.y + local_id.x;
        ${ce&&E?`
        if (w + local_id.y < uniforms.past_sequence_length) {
          tileK[idx] = past_value[pastValueOffset + (w + local_id.y) * uniforms.N];
        } else {
          tileK[idx] = v[vOffset + (w + local_id.y - uniforms.past_sequence_length) * uniforms.N];
        }
      `:`
        tileK[idx] = v[offsetB + (w + local_id.y) * uniforms.N];
      `}
        ${E?"present_value[presentValueOffset + (w + local_id.y) * uniforms.N] = tileK[idx];":""}
      }
     workgroupBarrier();
     for (var k: u32 = 0u; k < TILE_SIZE && w+k < uniforms.K; k++) {
       value += tileQ[TILE_SIZE * local_id.y + k] * tileK[TILE_SIZE * k + local_id.x];
     }
     workgroupBarrier();
   }

   // we need to transpose output from BNSH_v to BSND_v
   let batchIdx = workgroup_id.z / uniforms.num_heads;
   let currentBatchHeadNumber = workgroup_id.z % uniforms.num_heads;
   if (m < uniforms.M && n < uniforms.N) {
     let outputIdx = batchIdx * uniforms.M * uniforms.v_hidden_size + m * uniforms.v_hidden_size
       + currentBatchHeadNumber * uniforms.N + n;
     output[outputIdx] = value;
   }
  }`};return{name:"AttentionScore",shaderCache:{hint:`${u!==void 0};${r}`,inputDependencies:_e},getRunData:()=>({outputs:be,dispatchGroup:ne,programUniforms:re}),getShaderSource:he}},yo=(r,i,s,u,c,p,d,b,T,E,q)=>{let H=Math.min(r.outputCount,1+(d?1:0)+(b?1:0)),v=E.kvNumHeads!==void 0||H>1?E.pastSequenceLength:0,ne=v+E.kvSequenceLength,re=T&&st.size(T.dims)>0?T:void 0,ce=[i,s];E.kvNumHeads===void 0&&H>1&&d&&st.size(d.dims)>0&&ce.push(d),re&&ce.push(re);let _e=r.compute(Vu(H,i,s,d,re,E,q,v),{inputs:ce,outputs:E.kvNumHeads===void 0&&H>1?[-1,1]:[-1]})[0];r.compute(Ea(_e,E.batchSize*E.numHeads*E.sequenceLength,ne),{inputs:[_e],outputs:[]});let be=[_e,u];E.kvNumHeads===void 0&&H>1&&b&&st.size(b.dims)>0&&be.push(b),r.compute(Wu(H,_e,u,b,E,v),{inputs:be,outputs:E.kvNumHeads===void 0&&H>1?[0,2]:[0]})},Gu=(r,i)=>{let s=[i.batchSize,i.numHeads,i.sequenceLength,i.headSize],u=i.sequenceLength,c=i.inputHiddenSize,p=i.headSize,d=12,b={x:Math.ceil(i.headSize/d),y:Math.ceil(i.sequenceLength/d),z:i.batchSize*i.numHeads},T=[r.inputs[0],r.inputs[1],r.inputs[2]],E=[{type:12,data:u},{type:12,data:c},{type:12,data:p},{type:12,data:i.numHeads},{type:12,data:i.headSize},{type:12,data:i.hiddenSize},{type:12,data:i.hiddenSize+i.hiddenSize+i.vHiddenSize}],q=H=>{let v=Vt("output_q",T[0].dataType,s),ne=Vt("output_k",T[0].dataType,s),re=Vt("output_v",T[0].dataType,s),ce=gt("input",T[0].dataType,T[0].dims),_e=gt("weight",T[1].dataType,T[1].dims),be=gt("bias",T[2].dataType,T[2].dims),he=ce.type.storage,Fe=[{name:"M",type:"u32"},{name:"K",type:"u32"},{name:"N",type:"u32"},{name:"num_heads",type:"u32"},{name:"head_size",type:"u32"},{name:"hidden_size",type:"u32"},{name:"ldb",type:"u32"}];return`
  const TILE_SIZE = ${d}u;
  var<workgroup> tileInput: array<${he}, ${d*d}>;
  var<workgroup> tileWeightQ: array<${he}, ${d*d}>;
  var<workgroup> tileWeightK: array<${he}, ${d*d}>;
  var<workgroup> tileWeightV: array<${he}, ${d*d}>;
  ${H.registerUniforms(Fe).declareVariables(ce,_e,be,v,ne,re)}
  ${H.mainStart([d,d,1])}
    let batchIndex = workgroup_id.z / uniforms.num_heads;
    let headNumber = workgroup_id.z % uniforms.num_heads;
    let m = global_id.y;
    let n = global_id.x;

    let inputOffset = batchIndex * (uniforms.M * uniforms.K) + m * uniforms.K;
    let biasOffsetQ = headNumber * uniforms.head_size;
    let biasOffsetK = uniforms.hidden_size + biasOffsetQ;
    let biasOffsetV = uniforms.hidden_size + biasOffsetK;

    var valueQ = ${he}(0);
    var valueK = ${he}(0);
    var valueV = ${he}(0);
    for (var w: u32 = 0u; w < uniforms.K; w += TILE_SIZE) {
      if (m < uniforms.M && w + local_id.x < uniforms.K) {
        tileInput[TILE_SIZE * local_id.y + local_id.x] = input[inputOffset + w + local_id.x];
      }
      if (n < uniforms.N && w + local_id.y < uniforms.K) {
        let offset = n + (w + local_id.y) * uniforms.ldb;
        tileWeightQ[TILE_SIZE * local_id.y + local_id.x] = weight[biasOffsetQ + offset];
        tileWeightK[TILE_SIZE * local_id.y + local_id.x] = weight[biasOffsetK + offset];
        tileWeightV[TILE_SIZE * local_id.y + local_id.x] = weight[biasOffsetV + offset];
      }
      workgroupBarrier();
      for (var k: u32 = 0u; k<TILE_SIZE && w+k < uniforms.K; k++) {
        let inputTileOffset = TILE_SIZE * local_id.y + k;
        let weightTileOffset = TILE_SIZE * k + local_id.x;
        valueQ += tileInput[inputTileOffset] * tileWeightQ[weightTileOffset];
        valueK += tileInput[inputTileOffset] * tileWeightK[weightTileOffset];
        valueV += tileInput[inputTileOffset] * tileWeightV[weightTileOffset];
      }

      workgroupBarrier();
    }

    let headOffset = (m * uniforms.N + n) % uniforms.head_size;
    valueQ += bias[headOffset + biasOffsetQ];
    valueK += bias[headOffset + biasOffsetK];
    valueV += bias[headOffset + biasOffsetV];

    let offset = workgroup_id.z * uniforms.M * uniforms.N;
    if (m < uniforms.M && n < uniforms.N) {
      let outputIdx = offset + m * uniforms.N + n;
      output_q[outputIdx] = valueQ;
      output_k[outputIdx] = valueK;
      output_v[outputIdx] = valueV;
    }
  }`};return r.compute({name:"AttentionPrepare",shaderCache:{inputDependencies:["type","type","type"]},getRunData:()=>({outputs:[{dims:s,dataType:r.inputs[0].dataType,gpuDataType:0},{dims:s,dataType:r.inputs[0].dataType,gpuDataType:0},{dims:s,dataType:r.inputs[0].dataType,gpuDataType:0}],dispatchGroup:b,programUniforms:E}),getShaderSource:q},{inputs:T,outputs:[-1,-1,-1]})},qu=(r,i)=>{let s=Uu(r.inputs,i),[u,c,p]=Gu(r,s);return yo(r,u,c,p,r.inputs[4],void 0,void 0,void 0,r.inputs[5],s,i)}}),Hu,Ku,Qu,Xu,Yu=h(()=>{Z(),Xt(),Yt(),mr(),or(),Hu=(r,i)=>{if(!r||r.length!==5)throw new Error("BatchNormalization requires 5 inputs");let s=(u,c,p)=>{let d=c.length;if(d!==u.length)throw new Error(`${p}: num dimensions != ${d}`);c.forEach((b,T)=>{if(b!==u[T])throw new Error(`${p}: dim[${T}] do not match`)})};if(r[0].dims.length>1){let u=i.format==="NHWC"?i.spatial?r[0].dims.slice(-1):r[0].dims.slice(-1).concat(r[0].dims.slice(1,r[0].dims.length-1)):r[0].dims.slice(1,i.spatial?2:void 0);s(r[1].dims,u,"Invalid input scale"),s(r[2].dims,u,"Invalid input B"),s(r[3].dims,u,"Invalid input mean"),s(r[4].dims,u,"Invalid input var")}else s(r[1].dims,[1],"Invalid input scale"),s(r[2].dims,[1],"Invalid input B"),s(r[3].dims,[1],"Invalid input mean"),s(r[4].dims,[1],"Invalid input var")},Ku=(r,i)=>{let{epsilon:s,spatial:u,format:c}=i,p=r[0].dims,d=u?wr(p[p.length-1]):1,b=c==="NHWC"&&p.length>1?d:1,T=st.size(p)/d,E=u,q=E?p.length:p,H=gt("x",r[0].dataType,r[0].dims,d),v=gt("scale",r[1].dataType,r[1].dims,b),ne=gt("bias",r[2].dataType,r[2].dims,b),re=gt("inputMean",r[3].dataType,r[3].dims,b),ce=gt("inputVar",r[4].dataType,r[4].dims,b),_e=Vt("y",r[0].dataType,q,d),be=()=>{let Fe="";if(u)Fe=`let cOffset = ${p.length===1?"0u":c==="NHWC"?`outputIndices[${p.length-1}] / ${d}`:"outputIndices[1]"};`;else if(c==="NCHW")Fe=`
            ${_e.indicesSet("outputIndices","0","0")}
            let cOffset = ${_e.indicesToOffset("outputIndices")};`;else{Fe=`var cIndices = ${v.type.indices}(0);
                       cIndices[0] = outputIndices[${p.length-1}];`;for(let xe=1;xe<v.rank;xe++)Fe+=`cIndices[${xe}] = outputIndices[${xe}];`;Fe+=`let cOffset = ${v.indicesToOffset("cIndices")};`}return Fe},he=Fe=>`
  const epsilon = ${s};
  ${Fe.registerUniform("outputSize","u32").declareVariables(H,v,ne,re,ce,_e)}
  ${Fe.mainStart()}
  ${Fe.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}
    var outputIndices = ${_e.offsetToIndices(`global_idx * ${d}`)};
    ${be()}
    let scale = ${v.getByOffset("cOffset")};
    let bias = ${ne.getByOffset("cOffset")};
    let inputMean = ${re.getByOffset("cOffset")};
    let inputVar = ${ce.getByOffset("cOffset")};
    let x = ${H.getByOffset("global_idx")};
    let value = (x - inputMean) * inverseSqrt(inputVar + epsilon) * scale + bias;
    ${_e.setByOffset("global_idx","value")}
  }`;return{name:"BatchNormalization",shaderCache:{hint:`${i.epsilon}_${i.format}_${u}_${d}`,inputDependencies:E?["rank","type","type","type","type"]:void 0},getShaderSource:he,getRunData:()=>({outputs:[{dims:r[0].dims,dataType:r[0].dataType}],dispatchGroup:{x:Math.ceil(T/64)},programUniforms:E?[{type:12,data:T},...Ct(p)]:[{type:12,data:T}]})}},Qu=r=>Gt(r),Xu=(r,i)=>{let{inputs:s,outputCount:u}=r,c=Qu({...i,outputCount:u});if(D.webgpu.validateInputContent&&Hu(s,c),i.trainingMode)throw new Error("BatchNormalization trainingMode is not supported yet.");r.compute(Ku(s,c))}}),Zu,Ju,Ca,rp=h(()=>{Yt(),or(),Zu=r=>{if(r[0].dims.length!==3)throw new Error("input should have 3 dimensions");if(![320,640,1280].includes(r[0].dims[2]))throw new Error("number of channels should be 320, 640 or 1280");if(r[1].dims.length!==1)throw new Error("bias is expected to have 1 dimensions");if(r[0].dims[2]!==r[1].dims[0])throw new Error("last dimension of input and bias are not the same")},Ju=r=>{let i=r[0].dims,s=r[0].dims[2],u=st.size(i)/4,c=r[0].dataType,p=gt("input",c,i,4),d=gt("bias",c,[s],4),b=gt("residual",c,i,4),T=Vt("output",c,i,4);return{name:"BiasAdd",getRunData:()=>({outputs:[{dims:i,dataType:r[0].dataType}],dispatchGroup:{x:Math.ceil(u/64)}}),getShaderSource:E=>`
  const channels = ${s}u / 4;
  ${E.declareVariables(p,d,b,T)}

  ${E.mainStart()}
    ${E.guardAgainstOutOfBoundsWorkgroupSizes(u)}
    let value = ${p.getByOffset("global_idx")}
      + ${d.getByOffset("global_idx % channels")} + ${b.getByOffset("global_idx")};
    ${T.setByOffset("global_idx","value")}
  }`}},Ca=r=>{Zu(r.inputs),r.compute(Ju(r.inputs))}}),ec,vr,tc,rc,Pa,nc,ic,$a,oc,sc,Fs,ac,lc,uc,Aa,cc,wo,dc,zs,fc,Ia,pc,hc,mc,Fa,gc,_c,za,yc,wc,Oa,vc,bc,Da,xc,La,Ra,Ba,Na,Mc,Tc,ja,kc,Sc,Ec,Ua=h(()=>{Xt(),Yt(),mr(),or(),ec=(r,i,s,u,c,p)=>{let d=Math.ceil(i/4),b="";typeof c=="string"?b=`${c}(a)`:b=c("a");let T=gt("inputData",s,[d],4),E=Vt("outputData",u,[d],4);return`
      ${r.registerUniform("vec_size","u32").declareVariables(T,E)}

  ${p??""}

  ${r.mainStart()}
    ${r.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.vec_size")}

    let a = ${T.getByOffset("global_idx")};
    ${E.setByOffset("global_idx",b)}
  }`},vr=(r,i,s,u,c,p=r.dataType)=>({name:i,shaderCache:{hint:c,inputDependencies:["type"]},getShaderSource:d=>ec(d,st.size(r.dims),r.dataType,p,s,u),getRunData:d=>({outputs:[{dims:r.dims,dataType:p}],dispatchGroup:{x:Math.ceil(st.size(d[0].dims)/64/4)},programUniforms:[{type:12,data:Math.ceil(st.size(r.dims)/4)}]})}),tc=r=>{r.compute(vr(r.inputs[0],"Abs","abs"))},rc=r=>{r.compute(vr(r.inputs[0],"Acos","acos"))},Pa=r=>{r.compute(vr(r.inputs[0],"Acosh","acosh"))},nc=r=>{r.compute(vr(r.inputs[0],"Asin","asin"))},ic=r=>{r.compute(vr(r.inputs[0],"Asinh","asinh"))},$a=r=>{r.compute(vr(r.inputs[0],"Atan","atan"))},oc=r=>{r.compute(vr(r.inputs[0],"Atanh","atanh"))},sc=r=>Gt(r),Fs=(r,i)=>{let s;switch(i.to){case 10:s="vec4<f16>";break;case 1:s="vec4<f32>";break;case 12:s="vec4<u32>";break;case 6:s="vec4<i32>";break;case 9:s="vec4<bool>";break;default:throw new RangeError(`not supported type (specified in attribute 'to' from 'Cast' operator): ${i.to}`)}r.compute(vr(r.inputs[0],"Cast",s,void 0,i.cacheKey,i.to))},ac=r=>{let i=r.length>=2&&r[1].data!==0?r[1].getFloat32Array()[0]:an,s=r.length>=3&&r[2].data!==0?r[2].getFloat32Array()[0]:$n;return Gt({min:i,max:s})},lc=(r,i)=>{let s=r.inputs.length===1?i:ac(r.inputs),u=kr(r.inputs[0].dataType);r.compute(vr(r.inputs[0],"Clip",c=>`clamp(${c}, clip_min_, clip_max_)`,`
    const clip_min_: vec4<${u}> = vec4(${u}(${s.min}));
    const clip_max_: vec4<${u}> = vec4(${u}(${s.max}));
`,s.cacheKey),{inputs:[0]})},uc=r=>{r.compute(vr(r.inputs[0],"Ceil","ceil"))},Aa=r=>{r.compute(vr(r.inputs[0],"Cos","cos"))},cc=r=>{r.compute(vr(r.inputs[0],"Cosh","cosh"))},wo=r=>Gt(r),dc=(r,i)=>{let s=kr(r.inputs[0].dataType);r.compute(vr(r.inputs[0],"Elu",u=>`elu_vf32(${u})`,`
  const elu_alpha_ = ${s}(${i.alpha});

  fn elu_f32(a: ${s}) -> ${s} {
  return select((exp(a) - 1.0) * elu_alpha_, a, a >= 0.0);
  }

  fn elu_vf32(v: vec4<${s}>) -> vec4<${s}> {
  return vec4(elu_f32(v.x), elu_f32(v.y), elu_f32(v.z), elu_f32(v.w));
  }`,i.cacheKey))},zs=(r="f32")=>`
const r0: ${r} = 0.3275911;
const r1: ${r} = 0.254829592;
const r2: ${r} = -0.284496736;
const r3: ${r} = 1.421413741;
const r4: ${r} = -1.453152027;
const r5: ${r} = 1.061405429;

fn erf_vf32(v: vec4<${r}>) -> vec4<${r}> {
  let absv = abs(v);
  let x = 1.0 / (1.0 + r0 * absv);
  return sign(v) * (1.0 - ((((r5 * x + r4) * x + r3) * x + r2) * x + r1) * x * exp(-absv * absv));
}`,fc=r=>{let i=kr(r.inputs[0].dataType);r.compute(vr(r.inputs[0],"Erf",s=>`erf_vf32(${s})`,zs(i)))},Ia=r=>{r.compute(vr(r.inputs[0],"Exp","exp"))},pc=r=>{r.compute(vr(r.inputs[0],"Floor","floor"))},hc=r=>{let i=kr(r.inputs[0].dataType);r.compute(vr(r.inputs[0],"Gelu",s=>`0.5 * ${s} * (1.0 + erf_vf32(${s} * 0.7071067811865475))`,zs(i)))},mc=(r,i)=>{let s=kr(r.inputs[0].dataType);r.compute(vr(r.inputs[0],"LeakyRelu",u=>`select(leaky_relu_alpha_ * ${u}, ${u}, ${u} >= vec4<${s}>(0.0))`,`const leaky_relu_alpha_ = ${s}(${i.alpha});`,i.cacheKey))},Fa=r=>{r.compute(vr(r.inputs[0],"Not",i=>`!${i}`))},gc=r=>{r.compute(vr(r.inputs[0],"Neg",i=>`-${i}`))},_c=r=>{r.compute(vr(r.inputs[0],"Reciprocal",i=>`1.0/${i}`))},za=r=>{let i=kr(r.inputs[0].dataType);r.compute(vr(r.inputs[0],"Relu",s=>`select(vec4<${i}>(0.0), ${s}, ${s} > vec4<${i}>(0.0))`))},yc=r=>{r.compute(vr(r.inputs[0],"Sigmoid",i=>`(1.0 / (1.0 + exp(-${i})))`))},wc=r=>Gt(r),Oa=(r,i)=>{let s=kr(r.inputs[0].dataType);r.compute(vr(r.inputs[0],"HardSigmoid",u=>`max(vec4<${s}>(0.0), min(vec4<${s}>(1.0), ${i.alpha} * ${u} + vec4<${s}>(${i.beta})))`,void 0,i.cacheKey))},vc=r=>{r.compute(vr(r.inputs[0],"Sin","sin"))},bc=r=>{r.compute(vr(r.inputs[0],"Sinh","sinh"))},Da=r=>{r.compute(vr(r.inputs[0],"Sqrt","sqrt"))},xc=r=>{r.compute(vr(r.inputs[0],"Tan","tan"))},La=r=>`sign(${r}) * (1 - exp(-2 * abs(${r}))) / (1 + exp(-2 * abs(${r})))`,Ra=r=>{r.compute(vr(r.inputs[0],"Tanh",La))},Ba=(r="f32")=>`
const fast_gelu_a: ${r} = 0.5;
const fast_gelu_b: ${r} = 0.7978845608028654;
const fast_gelu_c: ${r} = 0.035677408136300125;

fn tanh_v(v: vec4<${r}>) -> vec4<${r}> {
  return ${La("v")};
}
`,Na=r=>`(fast_gelu_a + fast_gelu_a * tanh_v(${r} * (fast_gelu_c * ${r} * ${r} + fast_gelu_b))) * ${r}`,Mc=r=>{let i=kr(r.inputs[0].dataType);r.compute(vr(r.inputs[0],"FastGelu",Na,Ba(i),void 0,r.inputs[0].dataType))},Tc=(r,i)=>{let s=kr(r.inputs[0].dataType);return r.compute(vr(r.inputs[0],"ThresholdedRelu",u=>`select(vec4<${s}>(0.0), ${u}, ${u} > thresholded_relu_alpha_)`,`const thresholded_relu_alpha_ = vec4<${s}>(${i.alpha});`,i.cacheKey)),0},ja=r=>{r.compute(vr(r.inputs[0],"Log","log"))},kc=(r,i)=>`
const alpha = vec4<${r}>(${i});
const one = ${r}(1.0);
const zero = ${r}(0.0);

fn quick_gelu_impl(x: vec4<${r}>) -> vec4<${r}> {
  let v = x *alpha;
  var x1 : vec4<${r}>;
  for (var i = 0; i < 4; i = i + 1) {
    if (v[i] >= zero) {
      x1[i] = one / (one + exp(-v[i]));
    } else {
      x1[i] = one - one / (one + exp(v[i]));
    }
  }
  return x * x1;
}
`,Sc=r=>`quick_gelu_impl(${r})`,Ec=(r,i)=>{let s=kr(r.inputs[0].dataType);r.compute(vr(r.inputs[0],"QuickGelu",Sc,kc(s,i.alpha),i.cacheKey,r.inputs[0].dataType))}}),Va,Cc,Pc,$c=h(()=>{Yt(),or(),Ua(),Va=r=>{if(r[0].dims.length!==3)throw new Error("input should have 3 dimensions");if(![2560,5120,10240].includes(r[0].dims[2]))throw new Error("hidden state should be 2560, 5120 or 10240");if(r[1].dims.length!==1)throw new Error("bias is expected to have 1 dimensions");if(r[0].dims[2]!==r[1].dims[0])throw new Error("last dimension of input and bias are not the same")},Cc=r=>{let i=r[0].dims.slice();i[2]=i[2]/2;let s=gt("input",r[0].dataType,r[0].dims,4),u=gt("bias",r[0].dataType,[r[0].dims[2]],4),c=Vt("output",r[0].dataType,i,4),p=st.size(i)/4,d=Tr(r[0].dataType);return{name:"BiasSplitGelu",getRunData:()=>({outputs:[{dims:i,dataType:r[0].dataType}],dispatchGroup:{x:Math.ceil(p/64)}}),getShaderSource:b=>`
  const M_SQRT2 = sqrt(2.0);
  const halfChannels = ${r[0].dims[2]/4/2}u;

  ${b.declareVariables(s,u,c)}

  ${zs(d)}

  ${b.mainStart()}
    ${b.guardAgainstOutOfBoundsWorkgroupSizes(p)}
    let biasIdx = global_idx % halfChannels;
    let batchIndex = global_idx / halfChannels;
    let inputOffset = biasIdx + batchIndex * halfChannels * 2;
    let valueLeft = input[inputOffset] + bias[biasIdx];
    let valueRight = input[inputOffset + halfChannels] + bias[biasIdx + halfChannels];
    let geluRight = valueRight * 0.5 * (erf_vf32(valueRight / M_SQRT2) + 1);

    ${c.setByOffset("global_idx","valueLeft * geluRight")}
  }`}},Pc=r=>{Va(r.inputs),r.compute(Cc(r.inputs))}}),Ac,Ic,Xn,Fc,zc,Wa,Oc,Dc,Lc,Rc,Bc,Nc,Ga,np=h(()=>{Xt(),Yt(),or(),Ac=(r,i,s,u,c,p,d,b,T,E,q,H)=>{let v,ne;typeof b=="string"?v=ne=(he,Fe)=>`${b}((${he}),(${Fe}))`:typeof b=="function"?v=ne=b:(v=b.scalar,ne=b.vector);let re=Vt("outputData",q,u.length,4),ce=gt("aData",T,i.length,4),_e=gt("bData",E,s.length,4),be;if(c)if(p){let he=st.size(i)===1,Fe=st.size(s)===1,xe=i.length>0&&i[i.length-1]%4===0,Ie=s.length>0&&s[s.length-1]%4===0;he||Fe?be=re.setByOffset("global_idx",ne(he?`${ce.type.value}(${ce.getByOffset("0")}.x)`:ce.getByOffset("global_idx"),Fe?`${_e.type.value}(${_e.getByOffset("0")}.x)`:_e.getByOffset("global_idx"))):be=`
            let outputIndices = ${re.offsetToIndices("global_idx * 4u")};
            let offsetA = ${ce.broadcastedIndicesToOffset("outputIndices",re)};
            let offsetB = ${_e.broadcastedIndicesToOffset("outputIndices",re)};
            ${re.setByOffset("global_idx",ne(d||xe?ce.getByOffset("offsetA / 4u"):`${ce.type.value}(${ce.getByOffset("offsetA / 4u")}[offsetA % 4u])`,d||Ie?_e.getByOffset("offsetB / 4u"):`${_e.type.value}(${_e.getByOffset("offsetB / 4u")}[offsetB % 4u])`))}
          `}else be=re.setByOffset("global_idx",ne(ce.getByOffset("global_idx"),_e.getByOffset("global_idx")));else{if(!p)throw new Error("no necessary to use scalar implementation for element-wise binary op implementation.");let he=(Fe,xe,Ie="")=>{let ct=`aData[indexA${xe}][componentA${xe}]`,et=`bData[indexB${xe}][componentB${xe}]`;return`
            let outputIndices${xe} = ${re.offsetToIndices(`global_idx * 4u + ${xe}u`)};
            let offsetA${xe} = ${ce.broadcastedIndicesToOffset(`outputIndices${xe}`,re)};
            let offsetB${xe} = ${_e.broadcastedIndicesToOffset(`outputIndices${xe}`,re)};
            let indexA${xe} = offsetA${xe} / 4u;
            let indexB${xe} = offsetB${xe} / 4u;
            let componentA${xe} = offsetA${xe} % 4u;
            let componentB${xe} = offsetB${xe} % 4u;
            ${Fe}[${xe}] = ${Ie}(${v(ct,et)});
          `};q===9?be=`
            var data = vec4<u32>(0);
            ${he("data",0,"u32")}
            ${he("data",1,"u32")}
            ${he("data",2,"u32")}
            ${he("data",3,"u32")}
            outputData[global_idx] = dot(vec4<u32>(0x1, 0x100, 0x10000, 0x1000000), vec4<u32>(data));`:be=`
            ${he("outputData[global_idx]",0)}
            ${he("outputData[global_idx]",1)}
            ${he("outputData[global_idx]",2)}
            ${he("outputData[global_idx]",3)}
          `}return`
        ${r.registerUniform("vec_size","u32").declareVariables(ce,_e,re)}

        ${H??""}

        ${r.mainStart()}
        ${r.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.vec_size")}
        ${be}
      }`},Ic=(r,i,s,u,c,p,d=s.dataType)=>{let b=!st.areEqual(s.dims,u.dims),T=s.dims,E=st.size(s.dims),q=!1,H=!1,v=[b];if(b){let ne=pn.calcShape(s.dims,u.dims,!1);if(!ne)throw new Error("Can't perform binary op on the given tensors");T=ne,E=st.size(T);let re=st.size(s.dims)===1,ce=st.size(u.dims)===1,_e=s.dims.length>0&&s.dims[s.dims.length-1]%4===0,be=u.dims.length>0&&u.dims[u.dims.length-1]%4===0;v.push(re),v.push(ce),v.push(_e),v.push(be);let he=1;for(let Fe=1;Fe<T.length;Fe++){let xe=s.dims[s.dims.length-Fe]??1,Ie=u.dims[u.dims.length-Fe]??1;if(xe===Ie)he*=xe;else break}he%4===0?(H=!0,q=!0):(re||ce||_e||be)&&(q=!0)}else q=!0;return v.push(q),{name:r,shaderCache:{hint:i+v.map(ne=>ne.toString()).join("_"),inputDependencies:["rank","rank"]},getShaderSource:ne=>Ac(ne,s.dims,u.dims,T,q,b,H,c,s.dataType,u.dataType,d,p),getRunData:()=>({outputs:[{dims:T,dataType:d}],dispatchGroup:{x:Math.ceil(E/64/4)},programUniforms:[{type:12,data:Math.ceil(st.size(T)/4)},...Ct(s.dims,u.dims,T)]})}},Xn=(r,i,s,u,c,p)=>{r.compute(Ic(i,c??"",r.inputs[0],r.inputs[1],s,u,p))},Fc=r=>{Xn(r,"Add",(i,s)=>`${i}+${s}`)},zc=r=>{Xn(r,"Div",(i,s)=>`${i}/${s}`)},Wa=r=>{Xn(r,"Equal",{scalar:(i,s)=>`u32(${i}==${s})`,vector:(i,s)=>`vec4<u32>(${i}==${s})`},void 0,void 0,9)},Oc=r=>{Xn(r,"Mul",(i,s)=>`${i}*${s}`)},Dc=r=>{let i=gt("input",r.inputs[0].dataType,r.inputs[0].dims).type.value;Xn(r,"Pow",{scalar:(s,u)=>`pow_custom(${s},${u})`,vector:(s,u)=>`pow_vector_custom(${s},${u})`},`
    fn pow_custom(a : ${i}, b : ${i}) -> ${i} {
      if (b == ${i}(0.0)) {
        return ${i}(1.0);
      } else if (a < ${i}(0.0) && f32(b) != floor(f32(b))) {
        return ${i}(pow(f32(a), f32(b))); // NaN
      }
      return select(sign(a), ${i}(1.0), round(f32(abs(b) % ${i}(2.0))) != 1.0) * ${i}(${i==="i32"?"round":""}(pow(f32(abs(a)), f32(b))));
    }
    fn pow_vector_custom(a : vec4<${i}>, b : vec4<${i}>) -> vec4<${i}> {
      // TODO: implement vectorized pow
      return vec4<${i}>(pow_custom(a.x, b.x), pow_custom(a.y, b.y), pow_custom(a.z, b.z), pow_custom(a.w, b.w));
    }
      `)},Lc=r=>{Xn(r,"Sub",(i,s)=>`${i}-${s}`)},Rc=r=>{Xn(r,"Greater",{scalar:(i,s)=>`u32(${i}>${s})`,vector:(i,s)=>`vec4<u32>(${i}>${s})`},void 0,void 0,9)},Bc=r=>{Xn(r,"Less",{scalar:(i,s)=>`u32(${i}<${s})`,vector:(i,s)=>`vec4<u32>(${i}<${s})`},void 0,void 0,9)},Nc=r=>{Xn(r,"GreaterOrEqual",{scalar:(i,s)=>`u32(${i}>=${s})`,vector:(i,s)=>`vec4<u32>(${i}>=${s})`},void 0,void 0,9)},Ga=r=>{Xn(r,"LessOrEqual",{scalar:(i,s)=>`u32(${i}<=${s})`,vector:(i,s)=>`vec4<u32>(${i}<=${s})`},void 0,void 0,9)}}),jc,qa,Uc,Vc,Ni,Wc,ip=h(()=>{Xt(),Yt(),mr(),or(),jc=(r,i)=>{if(!r||r.length<1)throw new Error("too few inputs");let s=0,u=r[s],c=u.dataType,p=u.dims.length;r.forEach((d,b)=>{if(b!==s){if(d.dataType!==c)throw new Error("input tensors should be one type");if(d.dims.length!==p)throw new Error("input tensors should have the same shape");d.dims.forEach((T,E)=>{if(E!==i&&T!==u.dims[E])throw new Error("non concat dimensions must match")})}})},qa=(r,i)=>`
  fn calculateInputIndex(index: u32) -> u32 {
    let sizeInConcatAxis = array<u32, ${r}u>(${i});
    for (var i: u32 = 0u; i < ${r}; i += 1u ) {
      if (index < sizeInConcatAxis[i]) {
        return i;
      }
    }
    return ${r}u;
  }`,Uc=(r,i)=>{let s=r.length,u=[];for(let c=0;c<s;++c){let p=i.setByOffset("global_idx",r[c].getByIndices("indices"));s===1?u.push(p):c===0?u.push(`if (inputIndex == ${c}u) { ${p} }`):c===s-1?u.push(`else { ${p} }`):u.push(`else if (inputIndex == ${c}) { ${p} }`)}return u.join(`
`)},Vc=(r,i,s,u)=>{let c=st.size(s),p=new Array(r.length),d=new Array(r.length),b=0,T=[],E=[],q=[{type:12,data:c}];for(let ce=0;ce<r.length;++ce)b+=r[ce].dims[i],p[ce]=b,E.push(r[ce].dims.length),d[ce]=gt(`input${ce}`,u,E[ce]),T.push("rank"),q.push({type:12,data:p[ce]});for(let ce=0;ce<r.length;++ce)q.push(...Ct(r[ce].dims));q.push(...Ct(s));let H=Vt("output",u,s.length),v=H.indicesGet("indices",i),ne=Array.from(Array(p.length).keys()).map(ce=>`uniforms.sizeInConcatAxis${ce}`).join(","),re=ce=>`

  ${(()=>{ce.registerUniform("outputSize","u32");for(let _e=0;_e<r.length;_e++)ce.registerUniform(`sizeInConcatAxis${_e}`,"u32");return ce.declareVariables(...d,H)})()}

  ${qa(p.length,ne)}

  ${ce.mainStart()}
    ${ce.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}

    var indices = ${H.offsetToIndices("global_idx")};

    let inputIndex = calculateInputIndex(${v});
    if (inputIndex != 0u) {
      let sizeInConcatAxis = array<u32, ${p.length}u>(${ne});
      ${v} -= sizeInConcatAxis[inputIndex - 1u];
    }

    ${Uc(d,H)}
  }`;return{name:"Concat",shaderCache:{hint:`${i}`,inputDependencies:T},getRunData:()=>({outputs:[{dims:s,dataType:u}],dispatchGroup:{x:Math.ceil(c/64)},programUniforms:q}),getShaderSource:re}},Ni=(r,i)=>{let s=r.inputs,u=s[0].dims,c=st.normalizeAxis(i.axis,u.length);jc(s,c);let p=u.slice();p[c]=s.reduce((b,T)=>b+(T.dims.length>c?T.dims[c]:0),0);let d=s.filter(b=>st.size(b.dims)>0);r.compute(Vc(d,c,p,s[0].dataType),{inputs:d})},Wc=r=>Gt({axis:r.axis})}),ji,Ui,ki,Ha,Vi=h(()=>{Xt(),Yt(),ji=(r,i,s="f32")=>{switch(r.activation){case"Relu":return`value = max(value, ${i}(0.0));`;case"Sigmoid":return`value = (${i}(1.0) / (${i}(1.0) + exp(-value)));`;case"Clip":return`value = clamp(value, ${i}(${s}(uniforms.clip_min)), ${i}(${s}(uniforms.clip_max)));`;case"HardSigmoid":return`value = max(${i}(0.0), min(${i}(1.0), ${s}(uniforms.alpha) * value + ${s}(uniforms.beta)));`;case"LeakyRelu":return`value = select(${s}(uniforms.alpha) * value, value, value >= ${i}(0.0));`;case"Tanh":return`let e2x = exp(-2.0 * abs(value));
              value = sign(value) * (1.0 - e2x) / (1.0 + e2x);
        `;case"":return"";default:throw new Error(`Unsupported activation ${r.activation}`)}},Ui=(r,i)=>{r.activation==="Clip"?i.push({type:1,data:r.clipMax},{type:1,data:r.clipMin}):r.activation==="HardSigmoid"?i.push({type:1,data:r.alpha},{type:1,data:r.beta}):r.activation==="LeakyRelu"&&i.push({type:1,data:r.alpha})},ki=(r,i)=>{r.activation==="Clip"?i.push({name:"clip_max",type:"f32"},{name:"clip_min",type:"f32"}):r.activation==="HardSigmoid"?i.push({name:"alpha",type:"f32"},{name:"beta",type:"f32"}):r.activation==="LeakyRelu"&&i.push({name:"alpha",type:"f32"})},Ha=r=>{let i=(r==null?void 0:r.activation)||"";if(i==="HardSigmoid"){let[s,u]=(r==null?void 0:r.activation_params)||[.2,.5];return{activation:i,alpha:s,beta:u}}else if(i==="Clip"){let[s,u]=(r==null?void 0:r.activation_params)||[an,$n];return{activation:i,clipMax:u,clipMin:s}}else if(i==="LeakyRelu"){let[s]=(r==null?void 0:r.activation_params)||[.01];return{activation:i,alpha:s}}return{activation:i}}}),_n,Ka,vo=h(()=>{_n=(r,i)=>{switch(r){case 1:return i;case 2:return`vec2<${i}>`;case 3:return`vec3<${i}>`;case 4:return`vec4<${i}>`;default:throw new Error(`${r}-component is not supported.`)}},Ka=r=>`
      ${r?"value = value + getBiasByOutputCoords(coords);":""}
      `}),Qa,Gc=h(()=>{Qa=r=>`
fn getIndexFromCoords4D(coords : vec4<i32>, shape : vec4<i32>) -> i32 {
  return dot(coords, vec4<i32>(
      shape.y * shape.z * shape.w, shape.z * shape.w, shape.w, 1));
}
fn getOutputIndexFromCoords(coords : vec4<i32>) -> i32 {
  return dot(coords, vec4<i32>(
    i32(${r}.x), i32(${r}.y), i32(${r}.z), 1));
}
`}),qc,Go,Os,Xa,Hc,Ds,Ls,Ya,Rs=h(()=>{Xt(),Yt(),or(),Vi(),vo(),qc=(r,i)=>r?`
        mm_Asub[inputRow][inputCol] = mm_readA(batch,
          kStart + inputRow,
          globalRowStart / innerElementSize + inputCol${i?", batchIndices":""});
        `:`
        mm_Asub[inputRow][inputCol] = mm_readA(batch,
          globalRow + innerRow,
          kStart / innerElementSize + inputCol${i?", batchIndices":""});
        `,Go=(r,i)=>r?`
        let ACached0 = mm_Asub[k * innerElementSize][localRow];
        let ACached1 = mm_Asub[k * innerElementSize + 1][localRow];
        let ACached2 = mm_Asub[k * innerElementSize + 2][localRow];
        ${i===3?"":"let ACached3 = mm_Asub[k * innerElementSize + 3][localRow];"}
        for (var i = 0; i < rowPerThread; i = i + 1) {
          acc[i] = BCached0 * ACached0[i] + acc[i];
          acc[i] = BCached1 * ACached1[i] + acc[i];
          acc[i] = BCached2 * ACached2[i] + acc[i];
          ${i===3?"":"acc[i] = BCached3 * ACached3[i] + acc[i];"}
        }`:`
        for (var i = 0; i < rowPerThread; i = i + 1) {
          let ACached = mm_Asub[tileRow + i][k];
          acc[i] = BCached0 * ACached.x + acc[i];
          acc[i] = BCached1 * ACached.y + acc[i];
          acc[i] = BCached2 * ACached.z + acc[i];
          ${i===3?"":"acc[i] = BCached3 * ACached.w + acc[i];"}
        }`,Os=(r,i,s="f32",u,c=!1,p=32,d=!1,b=32)=>{let T=i[1]*r[1],E=i[0]*r[0],q=c?T:p,H=c?p:T,v=q/i[0],ne=p/i[1];if(!((c&&v===4&&r[1]===4||!c&&(v===3||v===4))&&q%i[0]===0&&p%i[1]===0&&r[0]===4))throw new Error(`If transposeA ${c} is true, innerElementSize ${v} and workPerThread[1] ${r[1]} must be 4.
      Otherwise, innerElementSize ${v} must be 3 or 4.
  tileAWidth ${q} must be divisible by workgroupSize[0]${i[0]}. tileInner ${p} must be divisible by workgroupSize[1] ${i[1]}. colPerThread ${r[0]} must be 4.`);return`
var<workgroup> mm_Asub: array<array<vec${v}<${s}>, ${q/v}>, ${H}>;
var<workgroup> mm_Bsub: array<array<vec4<${s}>, ${E/r[0]}>, ${p}>;

const rowPerThread = ${r[1]};
const colPerThread = ${r[0]};
const innerElementSize = ${v};
const tileInner = ${p};

@compute @workgroup_size(${i[0]}, ${i[1]}, ${i[2]})
fn main(@builtin(local_invocation_id) localId : vec3<u32>,
        @builtin(global_invocation_id) globalId : vec3<u32>,
        @builtin(workgroup_id) workgroupId : vec3<u32>) {
  let localRow = i32(localId.y);
  let tileRow = localRow * rowPerThread;
  let tileCol = i32(localId.x);

  let globalRow =i32(globalId.y) * rowPerThread;
  let globalCol = i32(globalId.x);
  let batch = ${d?"0":"i32(globalId.z)"};
  ${u?`let batchIndices = ${u.offsetToIndices("u32(batch)")};`:""}
  let globalRowStart = i32(workgroupId.y) * ${T};

  let num_tiles = ${d?`${Math.ceil(b/p)}`:"(uniforms.dim_inner - 1) / tileInner + 1"};
  var kStart = ${d?`i32(globalId.z) * ${b}`:"0"};

  var acc: array<vec4<${s}>, rowPerThread>;

  // Loop over shared dimension.
  let tileRowB = localRow * ${ne};
  for (var t = 0; t < num_tiles; t = t + 1) {
      // Load one tile of A into local memory.
      for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
          let inputRow = tileRow + innerRow;
          let inputCol = tileCol;
          ${qc(c,u)}
      }

      // Load one tile of B into local memory.
      for (var innerRow = 0; innerRow < ${ne}; innerRow = innerRow + 1) {
          let inputRow = tileRowB + innerRow;
          let inputCol = tileCol;
          mm_Bsub[inputRow][inputCol] = mm_readB(batch, kStart + inputRow, globalCol${u?", batchIndices":""});
      }
      kStart = kStart + tileInner;
      workgroupBarrier();

      // Compute acc values for a single thread.
      for (var k = 0; k < tileInner / innerElementSize; k = k + 1) {
          let BCached0 = mm_Bsub[k * innerElementSize][tileCol];
          let BCached1 = mm_Bsub[k * innerElementSize + 1][tileCol];
          let BCached2 = mm_Bsub[k * innerElementSize + 2][tileCol];
          ${v===3?"":"let BCached3 = mm_Bsub[k * innerElementSize + 3][tileCol];"}

          ${Go(c,v)}
      }

      workgroupBarrier();
  }

  for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
      mm_write(batch, globalRow + innerRow, globalCol, acc[innerRow]);
  }
}`},Xa=(r,i)=>r?`
            mm_Asub[inputRow][inputCol] = mm_readA(batch,
              kStart + inputRow,
              globalRowStart + inputCol${i?", batchIndices":""});
            `:`
            mm_Asub[inputRow][inputCol] = mm_readA(batch,
              globalRowStart + inputRow,
              kStart + inputCol${i?", batchIndices":""});
            `,Hc=r=>r?"let ACached = mm_Asub[k][tileRow + innerRow];":"let ACached = mm_Asub[tileRow + innerRow][k];",Ds=(r,i,s="f32",u,c=!1,p=32,d=!1,b=32,T=!1)=>{let E=r[1]*i[1],q=r[0]*i[0],H=c?E:p,v=c?p:E;if(!(v%i[1]===0&&H%i[0]===0&&p%i[1]===0))throw new Error(`tileAHight ${v} must be divisible by workgroupSize[1]${i[1]}, tileAWidth ${H} must be divisible by workgroupSize[0]${i[0]}, tileInner ${p} must be divisible by workgroupSize[1]${i[1]}`);let ne=v/i[1],re=H/i[0],ce=p/i[1],_e=T?`
    let localRow = i32(localId.y);
    let localCol = i32(localId.x);
    let globalRowStart = i32(workgroupId.y) * ${E};
    let globalColStart = i32(workgroupId.x) * ${q};

    // Loop over shared dimension.
    for (var t = 0; t < num_tiles; t = t + 1) {
      // Load one tile of A into local memory.
      for (var inputRow = localRow; inputRow < ${v}; inputRow = inputRow + ${i[1]}) {
        for (var inputCol = localCol; inputCol < ${H}; inputCol = inputCol + ${i[0]}) {
          ${Xa(c,u)}
        }
      }
      // Load one tile of B into local memory.
      for (var inputRow = localRow; inputRow < ${p}; inputRow = inputRow + ${i[1]}) {
            for (var inputCol = localCol; inputCol < ${q}; inputCol = inputCol + ${i[0]}) {
          mm_Bsub[inputRow][inputCol] = mm_readB(batch,
            kStart + inputRow,
            globalColStart + inputCol${u?", batchIndices":""});
        }
      }
      kStart = kStart + tileInner;
      workgroupBarrier();

      // Compute acc values for a single thread.
      var BCached : array<${s}, colPerThread>;
      for (var k = 0; k < tileInner; k = k + 1) {
        for (var inner = 0; inner < colPerThread; inner = inner + 1) {
          BCached[inner] = mm_Bsub[k][localCol + inner * ${i[0]}];
        }
        for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
          let ACached = ${c?`mm_Asub[k][localRow + innerRow * ${i[1]}];`:`mm_Asub[localRow + innerRow * ${i[1]}][k];`}
          for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) {
            acc[innerRow][innerCol] = acc[innerRow][innerCol] +
                ACached * BCached[innerCol];
          }
        }
      }
      workgroupBarrier();
    }
    for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
      let gRow = globalRowStart + localRow + innerRow * ${i[1]};
      for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) {
        let gCol = globalColStart + localCol + innerCol * ${i[0]};
        mm_write(batch, gRow, gCol, acc[innerRow][innerCol]);
      }
    }
    `:`
let tileRow = i32(localId.y) * rowPerThread;
let tileCol = i32(localId.x) * colPerThread;

let globalRow = i32(globalId.y) * rowPerThread;
let globalCol = i32(globalId.x) * colPerThread;
let globalRowStart = i32(workgroupId.y) * ${E};

let tileRowA = i32(localId.y) * ${ne};
let tileColA = i32(localId.x) * ${re};
let tileRowB = i32(localId.y) * ${ce};
// Loop over shared dimension.
for (var t = 0; t < num_tiles; t = t + 1) {
  // Load one tile of A into local memory.
  for (var innerRow = 0; innerRow < ${ne}; innerRow = innerRow + 1) {
    for (var innerCol = 0; innerCol < ${re}; innerCol = innerCol + 1) {
      let inputRow = tileRowA + innerRow;
      let inputCol = tileColA + innerCol;
      ${Xa(c,u)}
    }
  }

  // Load one tile of B into local memory.
  for (var innerRow = 0; innerRow < ${ce}; innerRow = innerRow + 1) {
    for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) {
      let inputRow = tileRowB + innerRow;
      let inputCol = tileCol + innerCol;
      mm_Bsub[inputRow][inputCol] = mm_readB(batch,
        kStart + inputRow,
        globalCol + innerCol${u?", batchIndices":""});
    }
  }
  kStart = kStart + tileInner;
  workgroupBarrier();

  // Compute acc values for a single thread.
  var BCached : array<${s}, colPerThread>;
  for (var k = 0; k < tileInner; k = k + 1) {
    for (var inner = 0; inner < colPerThread; inner = inner + 1) {
      BCached[inner] = mm_Bsub[k][tileCol + inner];
    }

    for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
      ${Hc(c)}
      for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) {
        acc[innerRow][innerCol] = acc[innerRow][innerCol] + ACached * BCached[innerCol];
      }
    }
  }

  workgroupBarrier();
}

for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
  for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) {
    mm_write(batch, globalRow + innerRow, globalCol + innerCol,
        acc[innerRow][innerCol]);
  }
}
`;return`
  var<workgroup> mm_Asub : array<array<${s}, ${H}>, ${v}>;
  var<workgroup> mm_Bsub : array<array<${s}, ${q}>, ${p}>;
  const rowPerThread = ${r[1]};
  const colPerThread = ${r[0]};
  const tileInner = ${p};

@compute @workgroup_size(${i[0]}, ${i[1]}, ${i[2]})
fn main(@builtin(local_invocation_id) localId : vec3<u32>,
        @builtin(global_invocation_id) globalId : vec3<u32>,
        @builtin(workgroup_id) workgroupId : vec3<u32>) {
    let batch = ${d?"0":"i32(globalId.z)"};
    ${u?`let batchIndices = ${u.offsetToIndices("u32(batch)")};`:""}
    let num_tiles = ${d?`${Math.ceil(b/p)}`:"(uniforms.dim_inner - 1) / tileInner + 1"};
    var kStart = ${d?`i32(globalId.z) * ${b}`:"0"};

    var acc : array<array<${s}, colPerThread>, rowPerThread>;
    ${_e}
  }
`},Ls=(r,i,s,u,c,p=!1)=>{let[d,b,T]=c,[E,q,H,v]=u,ne=go(d,T),re=go(b,T),ce=Tr(u[0].type.tensor),_e=()=>{let he=q.rank,Fe=E.rank,xe=`var aIndices: ${q.type.indices};`;for(let Ie=he-2-1,ct=Fe-1;Ie>=0;Ie--,ct--)xe+=`
aIndices[${Ie}] = ${Fe>1?`batchIndices[${ct}]`:"batchIndices"};`;return ne.forEach(Ie=>{xe+=`
aIndices[${Ie}] = 0;`}),xe+=`
aIndices[${he-2}] = u32(row);
                   aIndices[${he-1}] = u32(colIn);`,xe},be=()=>{let he=H.rank,Fe=E.rank,xe=`var bIndices: ${H.type.indices};`;for(let Ie=he-2-1,ct=Fe-1;Ie>=0;Ie--,ct--)xe+=`
bIndices[${Ie}] = ${Fe>1?`batchIndices[${ct}]`:"batchIndices"};`;return re.forEach(Ie=>{xe+=`
bIndices[${Ie}] = 0;`}),xe+=`
bIndices[${he-2}] = u32(row);
                   bIndices[${he-1}] = u32(colIn);`,xe};return`
    fn mm_readA(batch: i32, row: i32, colIn: i32, batchIndices: ${E.type.indices}) -> ${_n(r,ce)} {
      var value = ${_n(r,ce)}(0.0);
      let col = colIn * ${r};
      if(row < uniforms.dim_a_outer && col < uniforms.dim_inner)
      {
        ${_e()}
        value = ${q.getByIndices("aIndices")};
      }
      return value;
    }

    fn mm_readB(batch: i32, row: i32, colIn: i32, batchIndices: ${E.type.indices}) -> ${_n(r,ce)} {
      var value = ${_n(r,ce)}(0.0);
      let col = colIn * ${r};
      if(row < uniforms.dim_inner && col < uniforms.dim_b_outer)
      {
        ${be()}
        value = ${H.getByIndices("bIndices")};
      }
      return value;
    }

    fn mm_write(batch: i32, row: i32, colIn: i32, valueIn: ${_n(r,ce)}) {
      let col = colIn * ${r};
      if (row < uniforms.dim_a_outer && col < uniforms.dim_b_outer) {
        var value = valueIn;
        let coords = vec3<i32>(batch, row, colIn);
        ${i?`value = value + ${p?"bias[colIn]":`${_n(r,ce)}(bias[row])`};`:""}
        ${s}
        ${v.setByIndices("vec3<u32>(coords)","value")}
      }
    }
    `},Ya=(r,i,s,u,c=!1)=>{let p=r[0].dims,d=r[1].dims,b=p.slice(0,-2),T=d.slice(0,-2),E=u?u.slice(0,-2):s.slice(0,-2),q=st.size(E),H=p[p.length-2],v=p[p.length-1],ne=d[d.length-1],re=v%4===0&&ne%4===0,ce=H<=8?[4,1,1]:[4,4,1],_e=[8,8,1],be=[Math.ceil(ne/_e[0]/ce[0]),Math.ceil(H/_e[1]/ce[1]),Math.ceil(q/_e[2]/ce[2])],he=re?4:1,Fe=[...b,H,v/he],xe=Fe.length,Ie=[...T,v,ne/he],ct=Ie.length,et=[q,H,ne/he],vt=[{type:6,data:H},{type:6,data:ne},{type:6,data:v}];Ui(i,vt),vt.push(...Ct(E,Fe,Ie));let Ft=["rank","rank"],Lt=r.length>2;Lt&&(vt.push(...Ct(r[2].dims)),Ft.push("rank")),vt.push(...Ct(et));let pr=ar=>{let nr=E.length,yr=da("batchDims",r[0].dataType,nr,1),qr=Tr(r[0].dataType),Sr=gt("a",r[0].dataType,xe,he),jr=gt("b",r[1].dataType,ct,he),It=Vt("result",r[0].dataType,et.length,he),tr=[Sr,jr];if(Lt){let Hr=c?he:1;tr.push(gt("bias",r[2].dataType,r[2].dims.length,Hr))}let er=[{name:"dim_a_outer",type:"i32"},{name:"dim_b_outer",type:"i32"},{name:"dim_inner",type:"i32"}];ki(i,er);let pt=Tr(It.type.tensor),zt=ji(i,It.type.value,pt),ir=Ls(he,Lt,zt,[yr,Sr,jr,It],[b,T,E],c);return`
  ${ar.registerUniforms(er).registerInternalVariables(yr).declareVariables(...tr,It)}
  ${ir}
  ${re?Os(ce,_e,qr,yr):Ds(ce,_e,qr,yr)}
                   `};return{name:"MatMul",shaderCache:{hint:`${ce};${i.activation};${re};${c}`,inputDependencies:Ft},getRunData:()=>({outputs:[{dims:s,dataType:r[0].dataType}],dispatchGroup:{x:be[0],y:be[1],z:be[2]},programUniforms:vt}),getShaderSource:pr}}}),Kc,op,sp=h(()=>{Xt(),Rn(),or(),Vi(),vo(),Gc(),Rs(),Kc=(r,i,s,u,c=!1,p,d=4,b=4,T=4,E="f32")=>{let q=Ft=>{switch(Ft){case 1:return"resData = x[xIndex];";case 3:return`resData = vec3<${E}>(x[xIndex], x[xIndex + 1], x[xIndex + 2]);`;case 4:return"resData = x[xIndex / 4];";default:throw new Error(`innerElementSize ${Ft} is not supported.`)}},H=Ft=>{switch(Ft){case 1:return"return w[row * i32(uniforms.w_shape[3]) + colIn];";case 4:return"return w[row * i32(uniforms.w_shape[3]) / 4 + colIn];";default:throw new Error(`innerElementSize ${Ft} is not supported.`)}},v=r?`
    let coord = vec4<i32>(batch, xRow, xCol, xCh);
    `:`
    let coord = vec4<i32>(batch, xCh, xRow, xCol);
    `,ne=r?`
    let coords = vec4<i32>(
      batch,
      row / outWidth,
      row % outWidth,
      col);
    `:`
    let coords = vec4<i32>(
      batch,
      row,
      col / outWidth,
      col % outWidth);
    `,re=r?"i32(uniforms.x_shape[1])":"i32(uniforms.x_shape[2])",ce=r?"i32(uniforms.x_shape[2])":"i32(uniforms.x_shape[3])",_e=r?"row":"col",be=r?"col":"row",he=`
    let inChannels = i32(uniforms.w_shape[2]);
    let outWidth = ${r?"i32(uniforms.result_shape[2])":"i32(uniforms.result_shape[3])"};
    let outRow = ${_e} / outWidth;
    let outCol = ${_e} % outWidth;

    let WRow = ${be} / (i32(uniforms.w_shape[1]) * inChannels);
    let WCol = ${be} / inChannels % i32(uniforms.w_shape[1]);
    let xRow = outRow * uniforms.stride[0] + uniforms.dilation[0] * WRow - uniforms.pad[0];
    let xCol = outCol * uniforms.stride[1] + uniforms.dilation[1] * WCol - uniforms.pad[1];
    let xCh = ${be} % inChannels;
    var resData = ${_n(d,E)}(0.0);
    // The bounds checking is always needed since we use it to pad zero for
    // the 'same' padding type.
    if (xRow >= 0 && xRow < ${re} && xCol >= 0 && xCol < ${ce}) {
      ${v}
      let xIndex = getIndexFromCoords4D(coord, vec4<i32>(uniforms.x_shape));
      ${q(d)}
    }
    return resData;`,Fe=r?i&&u?`
    let col = colIn * ${d};
    ${he}`:`
    let col = colIn * ${d};
    if (row < uniforms.dim_a_outer && col < uniforms.dim_inner) {
      ${he}
    }
    return ${_n(d,E)}(0.0);`:u&&s?`
    let col = colIn * ${d};
    ${he}`:`
    let col = colIn * ${d};
    if (row < uniforms.dim_inner && col < uniforms.dim_b_outer) {
      ${he}
    }
    return ${_n(d,E)}(0.0);`,xe=`${H(b)}`,Ie=_n(T,E),ct=_n(r?d:b,E),et=_n(r?b:d,E),vt=ji(p,Ie,E);return`
    fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${ct} {
      ${r?Fe:xe}
    }

    fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${et} {
      ${r?xe:Fe}
    }

    fn mm_write(batch: i32, row : i32, colIn : i32, valueIn : ${Ie}) {
      let col = colIn * ${T};
      if (row < uniforms.dim_a_outer && col < uniforms.dim_b_outer)
      {
      var value = valueIn;
      let outWidth = ${r?"i32(uniforms.result_shape[2])":"i32(uniforms.result_shape[3])"};
      ${ne}
      ${Ka(c)}
      ${vt}
      setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
      }
    }`},op=(r,i,s,u,c,p,d,b)=>{let T=i.format==="NHWC",E=T?r[0].dims[3]:r[0].dims[1],q=s[0],H=T?s[2]:s[3],v=T?s[1]:s[2],ne=T?s[3]:s[1],re=T&&(E%4===0||E%3===0)&&ne%4===0,ce=T?ne:H*v,_e=T?H*v:ne,be=[8,8,1],he=u<=8?[4,1,1]:[4,4,1],Fe=[Math.ceil(ce/be[0]/he[0]),Math.ceil(_e/be[1]/he[1]),Math.ceil(q/be[2]/he[2])];Br("verbose",()=>`[conv2d_mm_webgpu] dispatch = ${Fe}`);let xe=re?T&&E%4!==0?3:4:1,Ie=be[1]*he[1],ct=be[0]*he[0],et=Math.max(be[0]*xe,be[1]),vt=u%Ie===0,Ft=c%ct===0,Lt=p%et===0,pr=re?[xe,4,4]:[1,1,1],ar=[{type:6,data:u},{type:6,data:c},{type:6,data:p},{type:6,data:[i.pads[0],i.pads[1]]},{type:6,data:i.strides},{type:6,data:i.dilations}];Ui(i,ar),ar.push(...Ct(r[0].dims,r[1].dims));let nr=["rank","rank"];d&&(ar.push(...Ct(r[2].dims)),nr.push("rank")),ar.push(...Ct(s));let yr=qr=>{let Sr=[{name:"dim_a_outer",type:"i32"},{name:"dim_b_outer",type:"i32"},{name:"dim_inner",type:"i32"},{name:"pad",type:"i32",length:2},{name:"stride",type:"i32",length:2},{name:"dilation",type:"i32",length:2}];ki(i,Sr);let jr=re?4:1,It=Tr(r[0].dataType),tr=`
      fn setOutputAtIndex(flatIndex : i32, value : ${re?`vec4<${It}>`:It}) {
        result[flatIndex] = ${re?`vec4<${It}>`:It}(value);
      }
      fn setOutputAtCoords(d0 : i32, d1 : i32, d2 : i32, d3 : i32, value : ${re?`vec4<${It}>`:It}) {
        let flatIndex = getOutputIndexFromCoords(vec4<i32>(d0, d1, d2, d3));
        setOutputAtIndex(flatIndex ${re?"/ 4":""}, value);
      }`,er=gt("x",r[0].dataType,r[0].dims.length,xe===3?1:xe),pt=gt("w",r[1].dataType,r[1].dims.length,jr),zt=[er,pt],ir=Vt("result",r[0].dataType,s.length,jr);if(d){let Hr=gt("bias",r[2].dataType,r[2].dims.length,jr);zt.push(Hr),tr+=`
        fn getBiasByOutputCoords(coords : vec4<i32>) -> ${re?`vec4<${It}>`:It} {
          return bias[coords.${T?"w":"y"}${re?"/ 4":""}];
        }`}return`
        ${Qa("uniforms.result_strides")}
        //struct Uniforms { xShape : vec4<i32>, wShape : vec4<i32>, outShape : vec4<i32>,
        //  outShapeStrides: vec3<i32>, filterDims : vec2<i32>, pad : vec2<i32>, stride : vec2<i32>,
        //  dilation : vec2<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32 };
        ${qr.registerUniforms(Sr).declareVariables(...zt,ir)}
        ${tr}
        ${Kc(T,vt,Ft,Lt,d,i,pr[0],pr[1],pr[2],It)}
        ${re?Os(he,be,It,void 0,!T,et):Ds(he,be,It,void 0,!T,et,!1,void 0,b)}`};return{name:"Conv2DMatMul",shaderCache:{hint:`${i.cacheKey};${xe};${re};${vt};${Ft};${Lt};${Ie};${ct};${et}`,inputDependencies:nr},getRunData:()=>({outputs:[{dims:s,dataType:r[0].dataType}],dispatchGroup:{x:Fe[0],y:Fe[1],z:Fe[2]},programUniforms:ar}),getShaderSource:yr}}}),Qc,Za,Si,Xc,Ja,Yc,Zc,Jc,el=h(()=>{Xt(),Rn(),Yt(),or(),Vi(),vo(),Qc=r=>{let i=1;for(let s=0;s<r.length;s++)i*=r[s];return i},Za=r=>typeof r=="number"?[r,r,r]:r,Si=(r,i)=>i<=1?r:r+(r-1)*(i-1),Xc=(r,i,s,u=1)=>{let c=Si(i,u);return Math.floor((r[0]*(s-1)-s+c)/2)},Ja=(r,i,s,u,c)=>{c==null&&(c=Xc(r,i[0],u[0]));let p=[0,0,0,s];for(let d=0;d<3;d++)r[d]+2*c>=i[d]&&(p[d]=Math.trunc((r[d]-i[d]+2*c)/u[d]+1));return p},Yc=(r,i,s,u,c,p,d,b,T,E)=>{let q,H,v,ne;if(r==="VALID"&&(r=0),typeof r=="number"){q={top:r,bottom:r,left:r,right:r,front:r,back:r};let re=Ja([i,s,u,1],[b,T,E],1,[c,p,d],r);H=re[0],v=re[1],ne=re[2]}else if(Array.isArray(r)){if(!r.every((ce,_e,be)=>ce===be[0]))throw Error(`Unsupported padding parameter: ${r}`);q={top:r[0],bottom:r[1],left:r[2],right:r[3],front:r[4],back:r[5]};let re=Ja([i,s,u,1],[b,T,E],1,[c,p,d],r[0]);H=re[0],v=re[1],ne=re[2]}else if(r==="SAME_UPPER"){H=Math.ceil(i/c),v=Math.ceil(s/p),ne=Math.ceil(u/d);let re=(H-1)*c+b-i,ce=(v-1)*p+T-s,_e=(ne-1)*d+E-u,be=Math.floor(re/2),he=re-be,Fe=Math.floor(ce/2),xe=ce-Fe,Ie=Math.floor(_e/2),ct=_e-Ie;q={top:Fe,bottom:xe,left:Ie,right:ct,front:be,back:he}}else throw Error(`Unknown padding parameter: ${r}`);return{padInfo:q,outDepth:H,outHeight:v,outWidth:ne}},Zc=(r,i,s,u,c,p=!1,d="channelsLast")=>{let b,T,E,q,H;if(d==="channelsLast")[b,T,E,q,H]=r;else if(d==="channelsFirst")[b,H,T,E,q]=r;else throw new Error(`Unknown dataFormat ${d}`);let[v,,ne,re,ce]=i,[_e,be,he]=Za(s),[Fe,xe,Ie]=Za(u),ct=Si(ne,Fe),et=Si(re,xe),vt=Si(ce,Ie),{padInfo:Ft,outDepth:Lt,outHeight:pr,outWidth:ar}=Yc(c,T,E,q,_e,be,he,ct,et,vt),nr=p?v*H:v,yr=[0,0,0,0,0];return d==="channelsFirst"?yr=[b,nr,Lt,pr,ar]:d==="channelsLast"&&(yr=[b,Lt,pr,ar,nr]),{batchSize:b,dataFormat:d,inDepth:T,inHeight:E,inWidth:q,inChannels:H,outDepth:Lt,outHeight:pr,outWidth:ar,outChannels:nr,padInfo:Ft,strideDepth:_e,strideHeight:be,strideWidth:he,filterDepth:ne,filterHeight:re,filterWidth:ce,effectiveFilterDepth:ct,effectiveFilterHeight:et,effectiveFilterWidth:vt,dilationDepth:Fe,dilationHeight:xe,dilationWidth:Ie,inShape:r,outShape:yr,filterShape:i}},Jc=(r,i,s,u,c,p)=>{let d=p==="channelsLast";d?r[0].dims[3]:r[0].dims[1];let b=[64,1,1],T={x:s.map((_e,be)=>be)},E=[Math.ceil(Qc(T.x.map(_e=>s[_e]))/b[0]),1,1];Br("verbose",()=>`[conv3d_naive_webgpu] dispatch = ${E}`);let q=1,H=st.size(s),v=[{type:12,data:H},{type:12,data:u},{type:12,data:c},{type:12,data:i.strides},{type:12,data:i.dilations}];Ui(i,v),v.push(...Ct(r[0].dims,r[1].dims));let ne=["rank","rank"],re=r.length===3;re&&(v.push(...Ct(r[2].dims)),ne.push("rank")),v.push(...Ct(s));let ce=_e=>{let be=[{name:"output_size",type:"u32"},{name:"filter_dims",type:"u32",length:u.length},{name:"pads",type:"u32",length:c.length},{name:"strides",type:"u32",length:i.strides.length},{name:"dilations",type:"u32",length:i.dilations.length}];ki(i,be);let he=1,Fe=Tr(r[0].dataType),xe=gt("x",r[0].dataType,r[0].dims.length,q),Ie=gt("W",r[1].dataType,r[1].dims.length,he),ct=[xe,Ie],et=Vt("result",r[0].dataType,s.length,he),vt="";if(re){let pr=gt("bias",r[2].dataType,r[2].dims.length,he);ct.push(pr),vt+=`
        fn getBiasByOutputCoords(coords : array<u32, 5>) -> ${Fe} {
          return bias[${d?Dt("coords",4,5):Dt("coords",1,5)}];
        }`}let Ft=_n(q,Fe),Lt=ji(i,Ft,Fe);return`
            ${vt}
            fn getX(d0 : u32, d1 : u32, d2 : u32, d3 : u32, d4 : u32) -> f32 {
              let aIndices = array<u32, 5>(d0, d1, d2, d3, d4);
              return ${xe.getByIndices("aIndices")};
            }
            fn getW(d0 : u32, d1 : u32, d2 : u32, d3 : u32, d4 : u32) -> f32 {
              let aIndices = array<u32, 5>(d0, d1, d2, d3, d4);
              return ${Ie.getByIndices("aIndices")};
            }
          ${_e.registerUniforms(be).declareVariables(...ct,et)}
          ${_e.mainStart()}
          ${_e.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
              let coords = ${et.offsetToIndices("global_idx")};
              let batch = ${Dt("coords",0,xe.rank)};
              let d2 = ${d?Dt("coords",xe.rank-1,xe.rank):Dt("coords",1,xe.rank)};
              let xFRCCorner = vec3<u32>(${d?Dt("coords",1,xe.rank):Dt("coords",2,xe.rank)},
              ${d?Dt("coords",2,xe.rank):Dt("coords",3,xe.rank)},
              ${d?Dt("coords",3,xe.rank):Dt("coords",4,xe.rank)}) * uniforms.strides - uniforms.pads;
              let xFCorner = xFRCCorner.x;
              let xRCorner = xFRCCorner.y;
              let xCCorner = xFRCCorner.z;
              let xShapeY = ${d?Dt("uniforms.x_shape",1,xe.rank):Dt("uniforms.x_shape",2,xe.rank)};
              let xShapeZ = ${d?Dt("uniforms.x_shape",2,xe.rank):Dt("uniforms.x_shape",3,xe.rank)};
              let xShapeW = ${d?Dt("uniforms.x_shape",3,xe.rank):Dt("uniforms.x_shape",4,xe.rank)};
              let xShapeU = ${d?Dt("uniforms.x_shape",4,xe.rank):Dt("uniforms.x_shape",1,xe.rank)};
              let inputDepthNearestVec4 = (xShapeU / 4) * 4;
              let inputDepthVec4Remainder = xShapeU % 4;

              var value = 0.0;
              for (var wF = 0u; wF < uniforms.filter_dims[0]; wF++) {
                let xF = xFCorner + wF * uniforms.dilations[0];
                if (xF < 0 || xF >= xShapeY) {
                  continue;
                }

                for (var wR = 0u; wR < uniforms.filter_dims[1]; wR++) {
                  let xR = xRCorner + wR * uniforms.dilations[1];
                  if (xR < 0 || xR >= xShapeZ) {
                    continue;
                  }

                  for (var wC = 0u; wC < uniforms.filter_dims[2]; wC++) {
                    let xC = xCCorner + wC * uniforms.dilations[2];
                    if (xC < 0 || xC >= xShapeW) {
                      continue;
                    }

                    for (var d1 = 0u; d1 < inputDepthNearestVec4; d1 += 4) {
                      ${d?`let xValues = vec4<f32>(
                               getX(batch, xF, xR, xC, d1),
                               getX(batch, xF, xR, xC, d1 + 1),
                               getX(batch, xF, xR, xC, d1 + 2),
                               getX(batch, xF, xR, xC, d1 + 3));
                            `:`let xValues = vec4<f32>(
                               getX(batch, d1, xF, xR, xC),
                               getX(batch, d1 + 1, xF, xR, xC),
                               getX(batch, d1 + 2, xF, xR, xC),
                               getX(batch, d1 + 3, xF, xR, xC));
                            `}
                            let wValues = vec4<f32>(
                              getW(d2, d1, wF, wR, wC),
                              getW(d2, d1 + 1, wF, wR, wC),
                              getW(d2, d1 + 2, wF, wR, wC),
                              getW(d2, d1 + 3, wF, wR, wC));
                      value += dot(xValues, wValues);
                    }
                    if (inputDepthVec4Remainder == 1) {
                        ${d?`value += getX(batch, xF, xR, xC, inputDepthNearestVec4)
                          * getW(d2, inputDepthNearestVec4, wF, wR, wC);`:`value += getX(batch, inputDepthNearestVec4, xF, xR, xC)
                          * getW(d2, inputDepthNearestVec4, wF, wR, wC);`}
                    } else if (inputDepthVec4Remainder == 2) {
                      ${d?`let xValues = vec2<f32>(
                        getX(batch, xF, xR, xC, inputDepthNearestVec4),
                        getX(batch, xF, xR, xC, inputDepthNearestVec4 + 1));
                      `:`let xValues = vec2<f32>(
                        getX(batch, inputDepthNearestVec4, xF, xR, xC),
                        getX(batch, inputDepthNearestVec4 + 1, xF, xR, xC));
                    `}
                    let wValues = vec2<f32>(
                      getW(d2, inputDepthNearestVec4, wF, wR, wC),
                      getW(d2, inputDepthNearestVec4 + 1, wF, wR, wC));
                      value += dot(xValues, wValues);
                    } else if (inputDepthVec4Remainder == 3) {
                      ${d?`let xValues = vec3<f32>(
                        getX(batch, xF, xR, xC, inputDepthNearestVec4),
                        getX(batch, xF, xR, xC, inputDepthNearestVec4 + 1),
                        getX(batch, xF, xR, xC, inputDepthNearestVec4 + 2));
                      `:`let xValues = vec3<f32>(
                        getX(batch, inputDepthNearestVec4, xF, xR, xC),
                        getX(batch, inputDepthNearestVec4 + 1, xF, xR, xC),
                        getX(batch, inputDepthNearestVec4 + 2, xF, xR, xC));
                    `}
                    let wValues = vec3<f32>(
                      getW(d2, inputDepthNearestVec4, wF, wR, wC),
                      getW(d2, inputDepthNearestVec4 + 1, wF, wR, wC),
                      getW(d2, inputDepthNearestVec4 + 2, wF, wR, wC));
                      value += dot(xValues, wValues);
                    }
                  }
                }
              }
              ${re?"value = value + getBiasByOutputCoords(coords)":""};
              ${Lt}
              result[global_idx] = f32(value);
          }`};return{name:"Conv3DNaive",shaderCache:{hint:`${i.cacheKey};${d};${q};${re}`,inputDependencies:ne},getRunData:()=>({outputs:[{dims:s,dataType:r[0].dataType}],dispatchGroup:{x:E[0],y:E[1],z:E[2]},programUniforms:v}),getShaderSource:ce}}}),ed,td,ap=h(()=>{Xt(),Yt(),or(),sd(),Vi(),ed=(r,i,s)=>{let u=r.length>2,c=u?"value += b[output_channel];":"",p=r[0].dims,d=r[1].dims,b=d[0]/i.group,T=i.format==="NHWC",E=Bs(p,d,i.dilations,i.pads,i.strides,T),q=st.size(E),H=[{type:12,data:q},{type:12,data:i.dilations},{type:12,data:[i.strides[0],i.strides[1]]},{type:12,data:[i.pads[0],i.pads[1]]},{type:12,data:b}];Ui(i,H),H.push(...Ct(p,d));let v=["rank","rank"];u&&(H.push(...Ct(r[2].dims)),v.push("rank")),H.push(...Ct(E));let ne=re=>{let ce=Vt("output",r[0].dataType,E.length),_e=Tr(ce.type.tensor),be=ji(i,ce.type.value,_e),he=gt("x",r[0].dataType,p.length),Fe=gt("w",r[1].dataType,d.length),xe=[he,Fe];u&&xe.push(gt("b",r[2].dataType,r[2].dims.length));let Ie=[{name:"output_size",type:"u32"},{name:"dilations",type:"u32",length:i.dilations.length},{name:"strides",type:"u32",length:2},{name:"pads",type:"u32",length:2},{name:"output_channels_per_group",type:"u32"}];return ki(i,Ie),`
  ${re.registerUniforms(Ie).declareVariables(...xe,ce)}

  ${re.mainStart()}
    ${re.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}

    let outputIndices = ${ce.offsetToIndices("global_idx")};
    let batch: u32 = outputIndices[0];
    let output_channel: u32 = outputIndices[${T?3:1}];
    let xRCCorner: vec2<u32> = vec2<u32>(outputIndices[${T?1:2}], outputIndices[${T?2:3}]) * uniforms.strides - uniforms.pads;
    let group_id: u32 = output_channel / uniforms.output_channels_per_group;

    var value: ${ce.type.value} = ${ce.type.value}(0);
    for (var wInChannel: u32 = 0u; wInChannel < uniforms.w_shape[1]; wInChannel++) {
      let input_channel = group_id * uniforms.w_shape[1] + wInChannel;
      for (var wHeight: u32 = 0u; wHeight < uniforms.w_shape[2]; wHeight++) {
        let xHeight = xRCCorner.x + wHeight * uniforms.dilations[0];

        if (xHeight < 0u || xHeight >= uniforms.x_shape[${T?1:2}]) {
          continue;
        }

        for (var wWidth: u32 = 0u; wWidth < uniforms.w_shape[3]; wWidth++) {
          let xWidth = xRCCorner.y + wWidth * uniforms.dilations[1];
          if (xWidth < 0u || xWidth >= uniforms.x_shape[${T?2:3}]) {
            continue;
          }

          let xVal = ${T?he.get("batch","xHeight","xWidth","input_channel"):he.get("batch","input_channel","xHeight","xWidth")};
          let wVal = ${Fe.get("output_channel","wInChannel","wHeight","wWidth")};
          value += xVal*wVal;
        }
      }
    }
    ${c}
    ${be}
    ${ce.setByOffset("global_idx","value")}
  }`};return{name:"GroupedConv",shaderCache:{hint:i.cacheKey,inputDependencies:v},getRunData:()=>({outputs:[{dims:s?s(E):E,dataType:r[0].dataType}],dispatchGroup:{x:Math.ceil(q/64)},programUniforms:H}),getShaderSource:ne}},td=(r,i,s)=>{let u=r.length>2,c=wr(s[3]),p=wr(s[2]),d=st.size(s)/c/p,b=[r[0].dims[0],r[0].dims[1],r[0].dims[2],r[0].dims[3]/c],T=[r[1].dims[0],r[1].dims[1],r[1].dims[2],r[1].dims[3]/c],E=[s[0],s[1],s[2],s[3]/c],q=[{type:12,data:d},{type:6,data:[i.strides[0],i.strides[1]]},{type:6,data:[i.pads[0],i.pads[1]]}];Ui(i,q),q.push(...Ct(b,T,E));let H=(p-1)*i.strides[1]+T[1],v=ne=>{let re=Vt("output",r[0].dataType,E.length,c),ce=Tr(re.type.tensor),_e=ji(i,re.type.value,ce),be=gt("x",r[0].dataType,b.length,c),he=gt("w",r[1].dataType,T.length,c),Fe=[be,he];u&&Fe.push(gt("b",r[2].dataType,r[2].dims,c));let xe=u?"value += b[output_channel];":"",Ie=[{name:"output_size",type:"u32"},{name:"strides",type:"i32",length:2},{name:"pads",type:"i32",length:2}];return ki(i,Ie),`
  ${ne.registerUniforms(Ie).declareVariables(...Fe,re)}
  ${ne.mainStart()}
    ${ne.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
    let width0 = uniforms.output_shape[3];
    let output_channel = global_idx % width0;
    var index1 = global_idx / width0;
    let width1 = uniforms.output_shape[2] / ${p}u;
    let col = (index1 % width1) * ${p}u;
    index1 = index1 / width1;
    let row = index1 % uniforms.output_shape[1];
    let batch = index1 / uniforms.output_shape[1];

    let x_corner = vec2<i32>(i32(row), i32(col)) * uniforms.strides - uniforms.pads;

    var x_vals: array<${be.type.value}, ${H}>;
    var values: array<${re.type.value}, ${p}>;
    let input_channel = output_channel;
    // Use constant instead of uniform can give better performance for w's height/width.
    for (var w_height: u32 = 0u; w_height < ${T[0]}; w_height++) {
      let x_height = x_corner.x + i32(w_height);
      if (x_height >= 0 && u32(x_height) < uniforms.x_shape[1]) {
        for (var i = 0; i < ${H}; i++) {
          let x_width = x_corner.y + i;
          if (x_width >= 0 && u32(x_width) < uniforms.x_shape[2]) {
            x_vals[i] = ${be.get("batch","u32(x_height)","u32(x_width)","input_channel")};
          } else {
            x_vals[i] = ${be.type.value}(0);
          }
        }
        for (var w_width: u32 = 0u; w_width < ${T[1]}; w_width++) {
          let w_val = ${he.get("w_height","w_width","0","output_channel")};
          for (var i = 0u; i < ${p}u; i++) {
            values[i] = fma(x_vals[i * u32(uniforms.strides[1]) + w_width], w_val, values[i]);
          }
        }
      }
    }

    for (var i = 0u; i < ${p}u; i++) {
      var value = values[i];
      ${xe}
      ${_e}
      ${re.set("batch","row","col + i","output_channel","value")};
    }
  }`};return{name:"GroupedConv-Vectorize",shaderCache:{hint:`${i.cacheKey};${c};${p};${H};${T[0]};${T[1]}`,inputDependencies:u?["rank","rank","type"]:["rank","rank"]},getRunData:()=>({outputs:[{dims:s,dataType:r[0].dataType}],dispatchGroup:{x:Math.ceil(d/64)},programUniforms:q}),getShaderSource:v}}}),tl,rd,nd,rl=h(()=>{Xt(),Yt(),Rs(),or(),Vi(),tl=(r,i,s,u,c=!1)=>{let p=r[0].dims,d=r[1].dims,b=p[p.length-2],T=d[d.length-1],E=p[p.length-1],q=wr(T),H=wr(E),v=wr(b),ne=st.size(s)/q/v,re=r.length>2,ce=u?u.slice(0,-2):s.slice(0,-2),_e=[st.size(ce),b,T],be=[{type:12,data:ne},{type:12,data:b},{type:12,data:T},{type:12,data:E}];Ui(i,be),be.push(...Ct(ce,p,d)),re&&be.push(...Ct(r[2].dims)),be.push(...Ct(_e));let he=Fe=>{let xe=da("batch_dims",r[0].dataType,ce.length),Ie=gt("a",r[0].dataType,p.length,H),ct=gt("b",r[1].dataType,d.length,q),et=Vt("output",r[0].dataType,_e.length,q),vt=Tr(et.type.tensor),Ft=ji(i,et.type.value,vt),Lt=[Ie,ct],pr="";if(re){let tr=c?q:1;Lt.push(gt("bias",r[2].dataType,r[2].dims.length,tr)),pr=`${c?`value += bias[col / ${tr}];`:`value += ${et.type.value}(bias[row + i]);`}`}let ar=p.slice(0,-2),nr=d.slice(0,-2),yr=go(ar,ce),qr=go(nr,ce),Sr=[{name:"output_size",type:"u32"},{name:"M",type:"u32"},{name:"N",type:"u32"},{name:"K",type:"u32"}];ki(i,Sr);let jr=(tr,er)=>{let pt=tr.rank,zt=tr.name;if(pt===2)return`var ${zt}_indices = ${tr.type.indices}(0u, 0u);`;let ir=xe.rank,Hr=`var ${zt}_indices: ${tr.type.indices};`;for(let un=pt-2-1,xn=ir-1;un>=0;un--,xn--)Hr+=`
${zt}_indices[${un}] = ${ir>1?`batch_indices[${xn}]`:"batch_indices"};`;return er.forEach(un=>{Hr+=`
${zt}_indices[${un}] = 0;`}),Hr+=`${zt}_indices[${pt-2}] = 0u;
                     ${zt}_indices[${pt-1}] = 0u;`,Hr},It=()=>{let tr=`var a_data: ${Ie.type.value};`;for(let er=0;er<H;er++)tr+=`
              let b_data${er} = b[(b_offset + (k + ${er}) * uniforms.N + col) / ${q}];`;for(let er=0;er<v;er++){tr+=`a_data = a[(a_offset + (row + ${er}) * uniforms.K + k) / ${H}];`;for(let pt=0;pt<H;pt++)tr+=`
            values[${er}] = fma(${ct.type.value}(a_data${H===1?"":`[${pt}]`}), b_data${pt}, values[${er}]);
`}return tr};return`
  ${Fe.registerUniforms(Sr).registerInternalVariables(xe).declareVariables(...Lt,et)}
  ${Fe.mainStart()}
    ${Fe.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
    let col = (global_idx % (uniforms.N / ${q})) * ${q};
    var index1 = global_idx / (uniforms.N / ${q});
    let stride1 = uniforms.M / ${v};
    let row = (index1 % stride1) * ${v};
    let batch = index1 / stride1;

    ${s.length===2?"":`let batch_indices = ${xe.offsetToIndices("batch")};`}
    ${jr(Ie,yr)}
    let a_offset = ${Ie.indicesToOffset("a_indices")};
    ${jr(ct,qr)}
    let b_offset = ${ct.indicesToOffset("b_indices")};
    var values: array<${et.type.value}, ${v}>;
    for (var k: u32 = 0u; k < uniforms.K; k = k + ${H}) {
      ${It()}
    }
    for (var i = 0u; i < ${v}u; i++) {
      var value = values[i];
      ${pr}
      ${Ft}
      let cur_indices = ${et.type.indices}(batch, row + i, col);
      let offset = ${et.indicesToOffset("cur_indices")};
      ${et.setByOffset(`offset / ${q}`,"value")};
    }
  }
  `};return{name:"MatMulNaive",shaderCache:{hint:`${i.activation};${q};${H};${v};${c}`,inputDependencies:re?["rank","rank","rank"]:["rank","rank"]},getRunData:()=>({outputs:[{dims:s,dataType:r[0].dataType}],dispatchGroup:{x:Math.ceil(ne/64)},programUniforms:be}),getShaderSource:he}},rd=r=>{if(!r||r.length!==2)throw new Error("MatMul requires 2 inputs.");if(r[0].dims[r[0].dims.length-1]!==r[1].dims[r[1].dims.length-2])throw new Error("shared dimension does not match.")},nd=r=>{rd(r.inputs);let i=pn.calcShape(r.inputs[0].dims,r.inputs[1].dims,!0);if(!i)throw new Error("Can't use matmul on the given tensors");let s=i[i.length-1],u=r.inputs[0].dims[r.inputs[0].dims.length-1];s<8&&u<8?r.compute(tl(r.inputs,{activation:""},i)):r.compute(Ya(r.inputs,{activation:""},i))}}),Bs,Ns,nl,js,il,ol,id,od,qo,sd=h(()=>{Yt(),sp(),el(),Rs(),ap(),Vi(),rl(),_o(),Bs=(r,i,s,u,c,p)=>{let d=r[0],b=r.slice(p?1:2,p?3:4),T=b.length,E=i[0],q=i.slice(2).map((v,ne)=>v+(v-1)*(s[ne]-1)),H=b.map((v,ne)=>v+u[ne]+u[ne+T]).map((v,ne)=>Math.floor((v-q[ne]+c[ne])/c[ne]));return H.splice(0,0,d),H.splice(p?3:1,0,E),H},Ns=[2,3,1,0],nl=(r,i)=>{if(!r||r.length!==2&&r.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(r[0].dims.length>5)throw new Error("greater than 5D is not supported");if(r[0].dims.length!==r[1].dims.length)throw new Error("filter does not have same dimension as input");let s=r[0].dims[i.format==="NHWC"?r[0].dims.length-1:1],u=r[1].dims[1]*i.group;if(s!==u)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");if(r.length===3&&(r[2].dims.length!==1||r[1].dims[0]!==r[2].dims[0]))throw new Error("invalid bias");let c=r[0].dims.length-2;if(i.dilations.length!==c)throw new Error(`dilations should be ${c}D`);if(i.strides.length!==c)throw new Error(`strides should be ${c}D`);if(i.pads.length!==c*2)throw new Error(`pads should be ${c*2}D`);if(i.kernelShape.length!==0&&i.kernelShape.length!==r[1].dims.length-2)throw new Error("invalid kernel shape")},js=(r,i)=>{let s=r.kernelShape.slice();for(let p=2;p<i[1].dims.length;++p)s[p-2]===0&&(s[p-2]=i[1].dims[p]);let u=r.pads.slice();qn.adjustPadsBasedOnAutoPad(i[0].dims,r.strides,r.dilations,s,u,r.format==="NHWC",r.autoPad);let c=Object.assign({},r);return Object.assign(c,{kernelShape:s,pads:u}),c},il=r=>{let i=Ha(r),s=r.format,u=["NOTSET","VALID","SAME_UPPER","SAME_LOWER"][r.auto_pad],c=r.dilations,p=r.group,d=r.kernel_shape,b=r.pads,T=r.strides,E=r.w_is_const();return{autoPad:u,format:s,dilations:c,group:p,kernelShape:d,pads:b,strides:T,wIsConst:E,...i,cacheKey:`${r.format};${i.activation};`}},ol=(r,i,s)=>{let u=js(s,i),c=s.format==="NHWC";if(s.group!==1){if(!r.adapterInfo.isArchitecture("ampere")&&c&&i[1].dims[0]===s.group&&i[1].dims[1]===1&&s.dilations[0]===1&&s.dilations[1]===1){let ct=Bs(i[0].dims,i[1].dims,s.dilations,u.pads,s.strides,c),et=r.kernelCustomData.wT??r.compute(fi(i[1],Ns),{inputs:[1],outputs:[s.wIsConst?-2:-1]})[0];s.wIsConst&&!r.kernelCustomData.wT&&(r.kernelCustomData.wT=et);let vt=[i[0],et];i.length===3&&vt.push(i[2]),r.compute(td(vt,u,ct),{inputs:vt})}else r.compute(ed(i,u));return}let p=i.length===3,d=i[0].dims[c?1:2],b=i[0].dims[c?2:3],T=i[0].dims[c?3:1],E=i[1].dims[2],q=i[1].dims[3],H=Bs(i[0].dims,i[1].dims,s.dilations,u.pads,s.strides,c),v=H[c?1:2],ne=H[c?2:3],re=H[c?3:1],ce=c&&E===d&&q===b&&s.pads[0]===0&&s.pads[1]===0;if(ce||E===1&&q===1&&s.dilations[0]===1&&s.dilations[1]===1&&s.strides[0]===1&&s.strides[1]===1&&s.pads[0]===0&&s.pads[1]===0){let ct=H[0],et,vt,Ft,Lt=[];if(c){let nr=r.kernelCustomData.wT??r.compute(fi(i[1],Ns),{inputs:[1],outputs:[s.wIsConst?-2:-1]})[0];if(s.wIsConst&&!r.kernelCustomData.wT&&(r.kernelCustomData.wT=nr),ce){let yr=d*b*T;et=i[0].reshape([1,ct,yr]),vt=nr.reshape([1,yr,re]),Ft=[1,ct,re]}else et=i[0].reshape([ct,d*b,T]),vt=nr.reshape([1,T,re]),Ft=[ct,v*ne,re];Lt.push(et),Lt.push(vt)}else et=i[0].reshape([ct,T,d*b]),vt=i[1].reshape([1,re,T]),Ft=[ct,re,v*ne],Lt.push(vt),Lt.push(et);p&&Lt.push(i[2]);let pr=Ft[2],ar=Lt[0].dims[Lt[0].dims.length-1];pr<8&&ar<8?r.compute(tl(Lt,u,H,Ft,c),{inputs:Lt}):r.compute(Ya(Lt,u,H,Ft,c),{inputs:Lt});return}let _e=!0,be=r.kernelCustomData.wT??r.compute(fi(i[1],Ns),{inputs:[1],outputs:[s.wIsConst?-2:-1]})[0];s.wIsConst&&!r.kernelCustomData.wT&&(r.kernelCustomData.wT=be);let he=[i[0],be];p&&he.push(i[2]);let Fe=c?v*ne:re,xe=c?re:v*ne,Ie=E*q*T;r.compute(op(he,u,H,Fe,xe,Ie,p,_e),{inputs:he})},id=(r,i)=>{let s=i.format==="NHWC",u=[r.inputs[0].reshape(s?[r.inputs[0].dims[0],1,r.inputs[0].dims[1],r.inputs[0].dims[2]]:[r.inputs[0].dims[0],r.inputs[0].dims[1],1,r.inputs[0].dims[2]]),r.inputs[1].reshape([r.inputs[1].dims[0],r.inputs[1].dims[1],1,r.inputs[1].dims[2]])];r.inputs.length===3&&u.push(r.inputs[2]);let c=[0,i.pads[0],0,i.pads[1]],p=[1].concat(i.strides),d=[1].concat(i.dilations),b=[1].concat(i.kernelShape),T=js({...i,pads:c,strides:p,dilations:d,kernelShape:b},u);r.compute(ed(u,T,E=>s?[E[0],E[2],E[3]]:[E[0],E[1],E[3]]))},od=(r,i,s)=>{let u=s.format==="NHWC"?"channelsLast":"channelsFirst",c=js(s,i),p=s.autoPad==="NOTSET"?s.pads:s.autoPad,d=Zc(i[0].dims,i[1].dims,s.strides,s.dilations,p,!1,u);r.compute(Jc(i,c,d.outShape,[d.filterDepth,d.filterHeight,d.filterWidth],[d.padInfo.front,d.padInfo.top,d.padInfo.left],u))},qo=(r,i)=>{nl(r.inputs,i),r.inputs[0].dims.length===3?id(r,i):r.inputs[0].dims.length===5?od(r,r.inputs,i):ol(r,r.inputs,i)}}),ad,ld,lp=h(()=>{Xt(),Rn(),or(),Vi(),vo(),Gc(),Rs(),ad=(r,i=!1,s,u,c=4)=>{let p=_e=>{switch(_e){case 1:return"return w[getIndexFromCoords4D(coord, vec4<i32>(uniforms.w_shape))];";case 4:return`
            let coord1 = vec4<i32>(coordX, coordY, col + 1, rowInner);
            let coord2 = vec4<i32>(coordX, coordY, col + 2, rowInner);
            let coord3 = vec4<i32>(coordX, coordY, col + 3, rowInner);
            let v0 = w[getIndexFromCoords4D(coord, vec4<i32>(uniforms.w_shape))];
            let v1 = w[getIndexFromCoords4D(coord1, vec4<i32>(uniforms.w_shape))];
            let v2 = w[getIndexFromCoords4D(coord2, vec4<i32>(uniforms.w_shape))];
            let v3 = w[getIndexFromCoords4D(coord3, vec4<i32>(uniforms.w_shape))];
            return ${u}(v0, v1, v2, v3);
            `;default:throw new Error(`innerElementSize ${_e} is not supported.`)}},d=r?`
      let coord = vec4<i32>(batch, iXR, iXC, xCh);
      `:`
      let coord = vec4<i32>(batch, xCh, iXR, iXC);
      `,b=r?`
    let coords = vec4<i32>(
      batch,
      row / outWidth,
      row % outWidth,
      col);
    `:`
    let coords = vec4<i32>(
      batch,
      row,
      col / outWidth,
      col % outWidth);
    `,T=r?"i32(uniforms.x_shape[1])":"i32(uniforms.x_shape[2])",E=r?"i32(uniforms.x_shape[2])":"i32(uniforms.x_shape[3])",q=r?"row":"col",H=r?"col":"row",v=`
      let inChannels = ${r?"i32(uniforms.x_shape[3])":"i32(uniforms.x_shape[1])"};
      let outWidth = ${r?"i32(uniforms.result_shape[2])":"i32(uniforms.result_shape[3])"};
      let outRow = ${q} / outWidth;
      let outCol = ${q} % outWidth;

      let WRow = ${H} / (uniforms.filter_dims[1] * inChannels);
      let WCol = ${H} / inChannels % uniforms.filter_dims[1];
      let xR = f32(outRow - uniforms.pads[0] + uniforms.dilations[0] * WRow) / f32(uniforms.strides[0]);
      let xC = f32(outCol - uniforms.pads[1] + uniforms.dilations[1] * WCol) / f32(uniforms.strides[1]);
      if (xR < 0.0 || xR >= f32(${T}) || fract(xR) > 0.0) {
        return ${u}(0.0);
      }
      if (xC < 0.0 || xC >= f32(${E}) || fract(xC) > 0.0) {
        return ${u}(0.0);
      }
      let iXR = i32(xR);
      let iXC = i32(xC);
      let xCh = ${H} % inChannels;
      ${d}
      return x[getIndexFromCoords4D(coord, vec4<i32>(uniforms.x_shape))/${c}];`,ne=r?`
      let col = colIn * ${c};
      if (row < uniforms.dim_a_outer && col < uniforms.dim_inner) {
        ${v}
      }
      return ${u}(0.0);`:`
      let col = colIn * ${c};
      if (row < uniforms.dim_inner && col < uniforms.dim_b_outer) {
        ${v}
      }
      return ${u}(0.0);`,re=`
      let col = colIn * ${c};
      let inChannels = ${r?"i32(uniforms.x_shape[3])":"i32(uniforms.x_shape[1])"};
      let coordX = uniforms.filter_dims[0] - 1 - row / (uniforms.filter_dims[1] * inChannels);
      let coordY = uniforms.filter_dims[1] - 1 - (row / inChannels) % uniforms.filter_dims[1];
      if (${r?"row < uniforms.dim_inner && col < uniforms.dim_b_outer":"row < uniforms.dim_inner && col < uniforms.dim_a_outer"}  && coordX >= 0 && coordY >= 0) {
        let rowInner = row % inChannels;
        let coord = vec4<i32>(coordX, coordY, col, rowInner);
        ${p(c)}
      }
      return ${u}(0.0);
      `,ce=ji(s,u);return`
  fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${u} {
    ${r?ne:re}
  }

  fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${u} {
    ${r?re:ne}
  }

  fn mm_write(batch: i32, row : i32, colIn : i32, valueInput : ${u}) {
    let col = colIn * ${c};
    if (row < uniforms.dim_a_outer && col < uniforms.dim_b_outer) {
      var value = valueInput;
      let outWidth = ${r?"i32(uniforms.result_shape[2])":"i32(uniforms.result_shape[3])"};
      ${b}
      ${Ka(i)}
      ${ce}
      result[getIndexFromCoords4D(coords, vec4<i32>(uniforms.result_shape))/${c}] = value;
    }
  }`},ld=(r,i,s,u,c,p,d,b)=>{let T=i.format==="NHWC",E=T?r[0].dims[3]:r[0].dims[1],q=s[0],H=T?s[2]:s[3],v=T?s[1]:s[2],ne=T?s[3]:s[1],re=T&&E%4===0&&E%3&&ne%4===0,ce=T?ne:H*v,_e=T?H*v:ne,be=[8,8,1],he=u<=8?[4,1,1]:[4,4,1],Fe=[Math.ceil(ce/be[0]/he[0]),Math.ceil(_e/be[1]/he[1]),Math.ceil(q/be[2]/he[2])];Br("verbose",()=>`[conv_backprop_mm_webgpu] dispatch = ${Fe}`);let xe=re?4:1,Ie=Math.max(be[0]*xe,be[1]),ct=re?4:1,et=[i.kernelShape[T?1:2],i.kernelShape[T?2:3]],vt=[et[0]+(i.dilations[0]<=1?0:(et[0]-1)*(i.dilations[0]-1)),et[1]+(i.dilations[1]<=1?0:(et[1]-1)*(i.dilations[1]-1))],Ft=[vt[0]-1-Math.floor((i.pads[0]+i.pads[2])/2),vt[1]-1-Math.floor((i.pads[1]+i.pads[3])/2)],Lt=[{type:6,data:u},{type:6,data:c},{type:6,data:p},{type:6,data:i.strides},{type:6,data:i.dilations},{type:6,data:et},{type:6,data:Ft}];Ui(i,Lt),Lt.push(...Ct(r[0].dims,r[1].dims));let pr=["rank","rank"];d&&(Lt.push(...Ct(r[2].dims)),pr.push("rank")),Lt.push(...Ct(s));let ar=nr=>{let yr=gt("x",r[0].dataType,r[0].dims.length,ct),qr=gt("w",r[1].dataType,r[1].dims.length,1),Sr=Vt("result",r[0].dataType,s.length,ct),jr=[yr,qr],It="";if(d){let pt=gt("bias",r[2].dataType,r[2].dims.length,ct);jr.push(pt),It+=`
          fn getBiasByOutputCoords(coords : vec4<i32>) -> ${pt.type.value} {
            return bias[coords.${T?"w":"y"}${re?"/ 4":""}];
          }`}let tr=[{name:"dim_a_outer",type:"i32"},{name:"dim_b_outer",type:"i32"},{name:"dim_inner",type:"i32"},{name:"strides",type:"i32",length:2},{name:"dilations",type:"i32",length:2},{name:"filter_dims",type:"i32",length:et.length},{name:"pads",type:"i32",length:Ft.length}];ki(i,tr);let er=Tr(r[0].dataType,1);if(er!=="f16"&&er!=="f32")throw new Error(`elemType ${er} is not supported.`);return`
        ${Qa("uniforms.result_strides")}
        ${nr.registerUniforms(tr).declareVariables(...jr,Sr)};
        ${It}
        ${ad(T,d,i,yr.type.value,xe)}
        ${re?Os(he,be,er,void 0,!T,Ie):Ds(he,be,er,void 0,!T,Ie,!1,void 0,b)}`};return{name:"Conv2DTransposeMatMul",shaderCache:{hint:`${i.cacheKey};${he};${be};${re}`,inputDependencies:pr},getRunData:()=>({outputs:[{dims:s,dataType:r[0].dataType}],dispatchGroup:{x:Fe[0],y:Fe[1],z:Fe[2]},programUniforms:Lt}),getShaderSource:ar}}}),sl,Ho,fm=h(()=>{Xt(),Rn(),Yt(),or(),sl=(r,i,s,u,c,p=!1,d,b,T=!1)=>{let E=T?1:2,q=T?2:3,H=T?3:1,v=p?2:1,ne=`
  fn setOutputAtIndex(flatIndex : u32, value : ${p?`vec4<${d}>`:d}) {
    result[flatIndex] = ${p?`vec4<${d}>`:d}(value);
  }`;u&&(ne+=`
    fn getBiasByOutputCoords(coords : vec4<u32>) -> ${p?`vec4<${d}>`:d} {
      return bias[coords.${T?"w":"y"}${p?"/ 4":""}];
    }`);let re=p?4:1,ce=gt("W",i[1].dataType,i[1].dims.length,re),_e=gt("Dy",i[0].dataType,i[0].dims.length,re),be=[_e,ce];u&&be.push(gt("bias",i[2].dataType,[s[H]].length,re));let he=Vt("result",i[0].dataType,s.length,re),Fe=`{
        let batch: u32 = ${c?"global_id.z":"workgroup_id.z"} / uniforms.result_shape[1];
        let r = ${c?"global_id.z":"workgroup_id.z"} % uniforms.result_shape[1];
        let c = ${c?"global_id.y":"workgroup_id.y"} * ${v};
        let d1: u32 = ${c?"global_id.x":"workgroup_id.x"} * 4;

        let dyCorner = vec2<i32>(i32(r), i32(c)) - vec2<i32>(uniforms.pads);

        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
        // ? = to be determined. : = across all values in that axis.
        var dotProd: array<vec4<${d}>, ${v}>;
        for (var i = 0; i < ${v}; i++) {
          dotProd[i] = vec4<${d}>(0.0);
        }
        for (var wR: u32 = 0; wR < uniforms.filter_dims[0]; wR = wR + 1) {
          var dyR = (${d}(dyCorner.x) + ${d}(wR)) / ${d}(uniforms.strides.x);
          let wRPerm = uniforms.filter_dims[0] - 1 - wR;
          if (dyR < 0.0 || dyR >= ${d}(uniforms.Dy_shape[1]) ||
              fract(dyR) > 0.0 || wRPerm < 0) {
            continue;
          }
          let idyR: u32 = u32(dyR);

          for (var wC: u32 = 0; wC < uniforms.filter_dims[1]; wC = wC + 1) {
            let dyC = (${d}(dyCorner.y) + ${d}(wC)) / ${d}(uniforms.strides.y);
            let dyC2 = (${d}(dyCorner.y) + 1.0 + ${d}(wC)) / ${d}(uniforms.strides.y);
            let wCPerm = uniforms.filter_dims[1] - 1 - wC;
            if (wCPerm < 0) {
              continue;
            }
            var bDyCVal = true;
            var bDyCVal2 = true;
            if (dyC < 0.0 || dyC >= ${d}(uniforms.Dy_shape[2]) ||
                fract(dyC) > 0.0) {
              bDyCVal = false;
            }
            if (dyC2 < 0.0 || dyC2 >= ${d}(uniforms.Dy_shape[2]) ||
                fract(dyC2) > 0.0) {
              bDyCVal2 = false;
            }

            let idyC: u32 = u32(dyC);
            let idyC2: u32 = u32(dyC2);
            if (bDyCVal && bDyCVal2) {
              let d2Length = uniforms.Dy_shape[3];
              for (var d2 :u32 = 0; d2 < d2Length; d2 = d2 + 4) {
                let wValue0 = ${ce.get("u32(wRPerm)","u32(wCPerm)","d1","d2")};
                let wValue1 = ${ce.get("u32(wRPerm)","u32(wCPerm)","d1 + 1","d2")};
                let wValue2 = ${ce.get("u32(wRPerm)","u32(wCPerm)","d1 + 2","d2")};
                let wValue3 = ${ce.get("u32(wRPerm)","u32(wCPerm)","d1 + 3","d2")};

                var xValue = ${_e.get("batch","idyR","idyC","d2")};
                let tmpval = vec4<${d}>(dot(xValue, wValue0),
                                      dot(xValue, wValue1),
                                      dot(xValue, wValue2),
                                      dot(xValue, wValue3));
                dotProd[0] = dotProd[0] + tmpval;

                xValue =  ${_e.get("batch","idyR","idyC2","d2")};

                dotProd[1] = dotProd[1] + vec4<${d}>(dot(xValue, wValue0),
                                                    dot(xValue, wValue1),
                                                    dot(xValue, wValue2),
                                                    dot(xValue, wValue3));
              }
            } else if (bDyCVal) {
              let d2Length = uniforms.Dy_shape[${H}];
              for (var d2: u32 = 0; d2 < d2Length; d2 = d2 + 4) {
                let wValue0 = ${ce.get("u32(wRPerm)","u32(wCPerm)","d1","d2")};
                let wValue1 = ${ce.get("u32(wRPerm)","u32(wCPerm)","d1 + 1","d2")};
                let wValue2 = ${ce.get("u32(wRPerm)","u32(wCPerm)","d1 + 2","d2")};
                let wValue3 = ${ce.get("u32(wRPerm)","u32(wCPerm)","d1 + 3","d2")};

                var xValue = ${_e.get("batch","idyR","idyC","d2")};
                let tmpval = vec4<${d}>(dot(xValue, wValue0),
                                      dot(xValue, wValue1),
                                      dot(xValue, wValue2),
                                      dot(xValue, wValue3));
                dotProd[0] = dotProd[0] + tmpval;
              }
            } else if (bDyCVal2) {
              let d2Length = uniforms.Dy_shape[3];
              for (var d2: u32 = 0; d2 < d2Length; d2 = d2 + 4) {
                let wValue0 = ${ce.get("u32(wRPerm)","u32(wCPerm)","d1","d2")};
                let wValue1 = ${ce.get("u32(wRPerm)","u32(wCPerm)","d1 + 1","d2")};
                let wValue2 = ${ce.get("u32(wRPerm)","u32(wCPerm)","d1 + 2","d2")};
                let wValue3 = ${ce.get("u32(wRPerm)","u32(wCPerm)","d1 + 3","d2")};

                var xValue = ${_e.get("batch","idyR","idyC2","d2")};
                let tmpval = vec4<${d}>(dot(xValue, wValue0),
                                      dot(xValue, wValue1),
                                      dot(xValue, wValue2),
                                      dot(xValue, wValue3));
                dotProd[1] = dotProd[1] + tmpval;
              }
            }
          }
        }

        for (var i: u32 = 0; i < ${v}; i = i + 1) {
          let value = dotProd[i] + ${u?"bias[c+i]":`vec4<${d}>(0.0)`};
          ${he.set("batch","r","c + i","d1","value")};
        }
      }`,xe=`
          let outputIndices = ${he.offsetToIndices("global_idx")};
          let batch = ${he.indicesGet("outputIndices",0)};
          let d1 = ${he.indicesGet("outputIndices",H)};
          let r = ${he.indicesGet("outputIndices",E)};
          let c = ${he.indicesGet("outputIndices",q)};
          let dyCorner = vec2<i32>(i32(r), i32(c)) - uniforms.pads;
          let dyRCorner = dyCorner.x;
          let dyCCorner = dyCorner.y;
          let groupId = d1 / uniforms.output_channels_per_group;
          let wOutChannel = d1 - groupId * uniforms.output_channels_per_group;
          // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
          // ? = to be determined. : = across all values in that axis.
          var dotProd = ${d}(0.0);
          for (var wR: u32 = 0; wR < uniforms.effective_filter_dims.x; wR = wR + 1) {
            if (wR % uniforms.dilations.x != 0) {
              continue;
            }
            let dyR = (${d}(dyRCorner) + ${d}(wR)) / ${d}(uniforms.strides[0]);
            let wRPerm = uniforms.filter_dims.x - 1 - wR / uniforms.dilations.x;
            if (dyR < 0.0 || dyR >= ${d}(uniforms.Dy_shape[${E}]) || fract(dyR) > 0.0 ||
                wRPerm < 0) {
              continue;
            }
            let idyR: u32 = u32(dyR);

            for (var wC: u32 = 0; wC < uniforms.effective_filter_dims.y; wC = wC + 1) {
              if (wC % uniforms.dilations.y != 0) {
                continue;
              }
              let dyC = (${d}(dyCCorner) + ${d}(wC)) / ${d}(uniforms.strides.y);
              let wCPerm = uniforms.filter_dims.y - 1 - wC / uniforms.dilations.y;
              if (dyC < 0.0 || dyC >= ${d}(uniforms.Dy_shape[${q}]) ||
                  fract(dyC) > 0.0 || wCPerm < 0) {
                continue;
              }
              let idyC: u32 = u32(dyC);
              var inputChannel = groupId * uniforms.input_channels_per_group;
              for (var d2: u32 = 0; d2 < uniforms.input_channels_per_group; d2 = d2 + 1) {
                let xValue = ${T?_e.get("batch","idyR","idyC","inputChannel"):_e.get("batch","inputChannel","idyR","idyC")};
                let wValue = ${ce.get("inputChannel","wOutChannel","u32(wRPerm)","u32(wCPerm)")};
                dotProd = dotProd + xValue * wValue;
                inputChannel = inputChannel + 1;
              }
            }
          }
          let value = dotProd + ${u?"bias[d1]":`${d}(0.0)`};
          ${he.setByOffset("global_idx","value")};
        `;return`
  ${r.registerUniforms(b).declareVariables(...be,he)}
  ${ne}

    ${r.mainStart()}
    ${r.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")};
  ${p?Fe:xe}}`},Ho=(r,i,s)=>{let u=r.length>2,c=i.outputShape,p=st.size(c),d=[Math.ceil(p/64),1,1];Br("verbose",()=>`[conv2d_backprop_webgpu] dispatch = ${d}`);let b=i.format==="NHWC",T=["rank","rank"],E=[i.strides[0],i.strides[1]],q=[i.kernelShape[b?1:2],i.kernelShape[b?2:3]],H=[i.dilations[0],i.dilations[1]],v=[q[0]+(i.dilations[0]<=1?0:(i.kernelShape[b?1:2]-1)*(i.dilations[0]-1)),q[1]+(i.dilations[1]<=1?0:(i.kernelShape[b?2:3]-1)*(i.dilations[1]-1))],ne=[v[0]-1-Math.floor((i.pads[0]+i.pads[2])/2),v[1]-1-Math.floor(i.pads[1]+i.pads[3])/2],re=!1,ce=i.group,_e=r[1].dims,be=_e[0]/ce,he=_e[1],Fe=[{type:12,data:p},{type:12,data:E},{type:12,data:q},{type:12,data:H},{type:12,data:v},{type:6,data:ne},{type:12,data:be},{type:12,data:he},...Ct(r[0].dims,r[1].dims)];u&&(Fe.push(...Ct(r[2].dims)),T.push("rank")),Fe.push(...Ct(c));let xe=d[1]===1&&d[2]===1,Ie=ct=>{let et=[{name:"output_size",type:"u32"},{name:"strides",type:"u32",length:E.length},{name:"filter_dims",type:"u32",length:q.length},{name:"dilations",type:"u32",length:q.length},{name:"effective_filter_dims",type:"u32",length:v.length},{name:"pads",type:"i32",length:ne.length},{name:"input_channels_per_group",type:"u32"},{name:"output_channels_per_group",type:"u32"}],vt=Tr(r[0].dataType);return`${sl(ct,r,c,u,xe,re,vt,et,b)}`};return{name:"ConvTranspose2D",shaderCache:{hint:`${i.cacheKey};`,inputDependencies:T},getRunData:()=>({dispatchGroup:{x:d[0],y:d[1],z:d[2]},outputs:[{dims:s?s(c):c,dataType:r[0].dataType}],programUniforms:Fe}),getShaderSource:Ie}}}),ud,cd,al,ll,dd,ul,fd,pd,cl,up,pm=h(()=>{lp(),fm(),Vi(),_o(),ud=(r,i,s,u,c,p)=>(r-1)*i+s+(u-1)*c+1-p,cd=(r,i,s,u,c)=>{let p=Math.floor(r/2);i==="SAME_UPPER"?(s[u]=p,s[c]=r-p):i==="SAME_LOWER"&&(s[u]=r-p,s[c]=p)},al=(r,i,s,u,c,p,d,b,T,E)=>{let q=r.length-2,H=E.length===0;if(T.length===0)for(let re=0;re<q;++re)T.push(0);let v=r[0],ne=i[b?3:1]*c;for(let re=0,ce=r.length-q-(b?1:0);re<q;++re,++ce){let _e=r[ce],be=H?_e*d[re]:E[re],he=ud(_e,d[re],p[re],i[ce],s[re],be);cd(he,u,p,re,re+q),H&&E.push(d[re]*(_e-1)+T[re]+(i[ce]-1)*s[re]+1-p[re]-p[re+q])}E.splice(0,0,v),E.splice(b?3:1,0,ne)},ll=(r,i)=>{let s=r.kernelShape.slice();if(r.kernelShape.length===0||r.kernelShape.reduce((H,v)=>H*v,1)===0){s.length=0;for(let H=2;H<i[1].dims.length;++H)s.push(i[1].dims[H])}let u=r.format==="NHWC";s.splice(0,0,i[1].dims[0]),s.splice(u?3:1,0,i[1].dims[1]);let c=r.pads.slice(),p=r.outputShape.slice(),d=r.outputPadding.slice(),b=i[0].dims,T=r.dilations.slice();if(T.reduce((H,v)=>H+v,0)===0){let H=i[0].dims.length-2;T=new Array(H).fill(1)}let E=r.strides.slice();if(E.reduce((H,v)=>H+v,0)===0){let H=i[0].dims.length-2;E=new Array(H).fill(1)}al(b,s,T,r.autoPad,r.group,c,E,u,d,p);let q=Object.assign({},r);return Object.assign(q,{kernelShape:s,pads:c,outputPadding:d,outputShape:p,dilations:T,strides:E}),q},dd=r=>{let i=Ha(r),s=r.format,u=["NOTSET","VALID","SAME_UPPER","SAME_LOWER"][typeof r.autoPad>"u"?0:r.autoPad],c=r.dilations,p=r.group,d=r.kernelShape,b=r.pads,T=r.strides,E=r.wIsConst(),q=r.outputPadding,H=r.outputShape;return{autoPad:u,format:s,dilations:c,group:p,kernelShape:d,outputPadding:q,outputShape:H,pads:b,strides:T,wIsConst:E,...i,cacheKey:`${r.format};${i.activation};`}},ul=(r,i)=>{if(!r||r.length!==2&&r.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(r[0].dims.length!==4&&r[0].dims.length!==3)throw new Error("currently only support 2-dimensional conv");if(r[0].dims.length!==r[1].dims.length)throw new Error("filter does not have same dimension as input");let s=r[0].dims[i.format==="NHWC"?r[0].dims.length-1:1],u=r[1].dims[0];if(s!==u)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");let c=r[1].dims[1]*i.group;if(r.length===3&&(r[2].dims.length!==1||r[2].dims[0]!==c))throw new Error("invalid bias");let p=r[0].dims.length-2;if(i.dilations.reduce((d,b)=>d+b,0)>0&&i.dilations.length!==p)throw new Error(`dilations should be ${p}D`);if(i.strides.reduce((d,b)=>d+b,0)>0&&i.strides.length!==p)throw new Error(`strides should be ${p}D`);if(i.pads.reduce((d,b)=>d+b,0)>0&&i.pads.length!==p*2)throw new Error(`pads should be ${p*2}D`);if(i.outputPadding.length!==p&&i.outputPadding.length!==0)throw new Error(`output_padding should be ${p}D`);if(i.kernelShape.reduce((d,b)=>d+b,0)>0&&i.kernelShape.length!==0&&i.kernelShape.length!==r[1].dims.length-2)throw new Error("invalid kernel shape");if(i.outputShape.length!==0&&i.outputShape.length!==r[0].dims.length-2)throw new Error("invalid output shape")},fd=[2,3,1,0],pd=(r,i,s)=>{let u=ll(s,i),c=s.format==="NHWC",p=u.outputShape,d=p[c?3:1],b=i[0].dims[c?3:1];if(u.group!==1||d===1&&b===1){r.compute(Ho(i,u));return}let T=p[c?1:2],E=p[c?2:3],q=i[1].dims[2],H=i[1].dims[3],v=c?T*E:d,ne=c?d:T*E,re=q*H*b,ce=!0,_e=r.kernelCustomData.wT??r.compute(fi(i[1],fd),{inputs:[1],outputs:[s.wIsConst?-2:-1]})[0];s.wIsConst&&!r.kernelCustomData.wT&&(r.kernelCustomData.wT=_e);let be=[i[0],_e],he=i.length===3;he&&(!c&&i[2].dims.length===1?be.push(i[2].reshape([i[2].dims[0],1,1])):be.push(i[2])),r.compute(ld(be,u,p,v,ne,re,he,ce),{inputs:be})},cl=(r,i)=>{let s=i.format==="NHWC",u=[r.inputs[0].reshape(s?[r.inputs[0].dims[0],1,r.inputs[0].dims[1],r.inputs[0].dims[2]]:[r.inputs[0].dims[0],r.inputs[0].dims[1],1,r.inputs[0].dims[2]]),r.inputs[1].reshape([r.inputs[1].dims[0],r.inputs[1].dims[1],1,r.inputs[1].dims[2]])];r.inputs.length===3&&u.push(r.inputs[2]);let c=i.kernelShape;(c.length===0||c[0]===0)&&(c=[r.inputs[1].dims[2]]);let p=i.dilations;(p.length===0||p[0]===0)&&(p=[1]);let d=i.strides;(d.length===0||d[0]===0)&&(d=[1]);let b=i.pads;b.length===0&&(b=[0,0]),b=[0,b[0],0,b[1]],d=[1].concat(d),p=[1].concat(p),c=[1].concat(c);let T=ll({...i,pads:b,strides:d,dilations:p,kernelShape:c},u);r.compute(Ho(u,T,E=>s?[E[0],E[2],E[3]]:[E[0],E[1],E[3]]))},up=(r,i)=>{ul(r.inputs,i),r.inputs[0].dims.length===3?cl(r,i):pd(r,r.inputs,i)}}),dl,fl,hd,cp=h(()=>{Xt(),Yt(),mr(),or(),dl=(r,i,s,u)=>{let c=st.size(i),p=i.length,d=gt("input",r,p),b=Vt("output",r,p),T=s.dataType===6?s.getInt32Array()[0]:Number(s.getBigInt64Array()[0]),E=st.normalizeAxis(T,p),q=H=>{let v=` i32(${d.indicesGet("inputIndices","uniforms.axis")}) `,ne=Dt("uniforms.input_shape","uniforms.axis",p),re=u.reverse?v+(u.exclusive?" + 1":""):"0",ce=u.reverse?ne:v+(u.exclusive?"":" + 1");return`
                ${H.registerUniform("outputSize","u32").registerUniform("axis","u32").declareVariables(d,b)}
                ${H.mainStart()}
                  ${H.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}
                  var inputIndices = ${b.offsetToIndices("global_idx")};
                  var sum = ${b.type.value}(0);
                  let first : i32 = ${re};
                  let last : i32 = ${ce};
                  for (var i : i32 = first; i < last; i++) {
                    ${d.indicesSet("inputIndices","uniforms.axis","u32(i)")};
                    sum = sum + ${d.getByIndices("inputIndices")};
                  }
                  ${b.setByOffset("global_idx","sum")};
                }`};return{name:"CumSum",shaderCache:{hint:u.cacheKey,inputDependencies:["rank"]},getRunData:()=>({outputs:[{dims:i,dataType:r}],dispatchGroup:{x:Math.ceil(c/64)},programUniforms:[{type:12,data:c},{type:12,data:E},...Ct(i,i)]}),getShaderSource:q}},fl=(r,i)=>{let s=r.inputs[0].dims,u=r.inputs[0].dataType,c=r.inputs[1];r.compute(dl(u,s,c,i),{inputs:[0]})},hd=r=>{let i=r.exclusive===1,s=r.reverse===1;return Gt({exclusive:i,reverse:s})}}),pl,md,gd,hl,_d,dp=h(()=>{Xt(),Yt(),mr(),or(),pl=r=>{if(!r||r.length!==1)throw new Error("DepthToSpace requires 1 input.");if(r[0].dims.length!==4)throw new Error("DepthToSpace requires 4D input.")},md=(r,i,s,u)=>{let c=[];c.push(`fn perm(i: ${u.type.indices}) -> ${s.type.indices} {
    var a: ${s.type.indices};`);for(let p=0;p<i;++p)c.push(s.indicesSet("a",r[p],`i[${p}]`));return c.push("return a;}"),c.join(`
`)},gd=(r,i)=>{let s,u,c,p,d,b,T=i.format==="NHWC",E=i.blocksize,q=i.mode==="DCR";T?([s,u,c,p]=r.dims,d=q?[s,u,c,E,E,p/E**2]:[s,u,c,p/E**2,E,E],b=q?[0,1,3,2,4,5]:[0,1,4,2,5,3]):([s,u,c,p]=[r.dims[0],r.dims[2],r.dims[3],r.dims[1]],d=q?[s,E,E,p/E**2,u,c]:[s,p/E**2,E,E,u,c],b=q?[0,3,4,1,5,2]:[0,1,4,2,5,3]);let H=r.reshape(d),v=H.dims.length,ne=r.dataType,re=gt("a",ne,v),ce=Vt("output",ne,v),_e=be=>`
  ${be.registerUniform("output_size","u32").declareVariables(re,ce)}

  ${md(b,v,re,ce)}

  ${be.mainStart()}
    ${be.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}

    let indices = ${ce.offsetToIndices("global_idx")};
    let aIndices = perm(indices);

    ${ce.setByOffset("global_idx",re.getByIndices("aIndices"))}
  }`;return{name:"DepthToSpace",shaderCache:{hint:`${r.dims};${i.blocksize};${i.mode}`,inputDependencies:["rank"]},getRunData:be=>{let he=T?[s,u*E,c*E,p/E**2]:[s,p/E**2,u*E,c*E],Fe=st.size(he),xe=H.dims,Ie=st.sortBasedOnPerm(xe,b);return{outputs:[{dims:he,dataType:be[0].dataType}],dispatchGroup:{x:Math.ceil(Fe/64)},programUniforms:[{type:12,data:Fe},...Ct(xe,Ie)]}},getShaderSource:_e}},hl=(r,i)=>{pl(r.inputs),r.compute(gd(r.inputs[0],i))},_d=r=>Gt({blocksize:r.blocksize,mode:r.mode,format:r.format})}),Ko,Qo,ml,Or,fp,pp,hp,Us,yd,wd,vd,mp=h(()=>{Xt(),Yt(),mr(),or(),Ko="[a-zA-Z]|\\.\\.\\.",Qo="("+Ko+")+",ml="^"+Qo+"$",Or="("+Qo+",)*"+Qo,fp="^"+Or+"$",pp=class{constructor(r=-1){this.symbolToIndices=new Map,this.inputIndex=r}addSymbol(r,i){let s=this.symbolToIndices.get(r);s===void 0?s=[i]:s.push(i),this.symbolToIndices.set(r,s)}},hp=class{constructor(r,i){var c;this.equation=i,this.hasEllipsis=!1,this.symbolToInfo=new Map,this.lhs=new Array,this.outputDims=[];let[s,u]=i.includes("->")?i.split("->",2):[i,""];if(!s.match(RegExp(fp)))throw new Error("Invalid LHS term");if(s.split(",").forEach((p,d)=>{let b=r[d].dims.slice();if(!p.match(RegExp(ml)))throw new Error("Invalid LHS term");let T=this.processTerm(p,!0,b,d);this.lhs.push(T)}),u==="")u+=[...this.symbolToInfo.entries()].filter(([p,d])=>d.count===1||p==="...").map(([p])=>p).join("");else if(!u.match(RegExp(Qo)))throw new Error("Invalid RHS");(c=u.match(RegExp(Ko,"g")))==null||c.forEach(p=>{if(p==="...")this.outputDims=this.outputDims.concat(this.ellipsisDims);else{let d=this.symbolToInfo.get(p);if(d===void 0)throw new Error("Invalid RHS symbol");this.outputDims.push(d.dimValue)}}),this.rhs=this.processTerm(u,!1,this.outputDims)}addSymbol(r,i,s){let u=this.symbolToInfo.get(r);if(u!==void 0){if(u.dimValue!==i&&u.count!==1)throw new Error("Dimension mismatch");u.count++,u.inputIndices.push(s)}else u={count:1,dimValue:i,inputIndices:[s]};this.symbolToInfo.set(r,u)}processTerm(r,i,s,u=-1){let c=s.length,p=!1,d=[],b=0;if(!r.match(RegExp(ml))&&!i&&r!=="")throw new Error("Invalid LHS term");let T=r.match(RegExp(Ko,"g")),E=new pp(u);return T==null||T.forEach((q,H)=>{if(q==="..."){if(p)throw new Error("Only one ellipsis is allowed per input term");p=!0;let v=c-T.length+1;if(v<0)throw new Error("Ellipsis out of bounds");if(d=s.slice(b,b+v),this.hasEllipsis){if(this.ellipsisDims.length!==d.length||this.ellipsisDims.toString()!==d.toString())throw new Error("Ellipsis dimensions mismatch")}else if(i)this.hasEllipsis=!0,this.ellipsisDims=d;else throw new Error("Ellipsis must be specified in the LHS");for(let ne=0;ne<d.length;ne++){let re=String.fromCharCode(48+ne);E.addSymbol(re,H+ne),this.addSymbol(re,s[b++],u)}}else E.addSymbol(q,H+(this.hasEllipsis?this.ellipsisDims.length-1:0)),this.addSymbol(q,s[b++],u)}),E}},Us=r=>r+"_max",yd=(r,i,s,u)=>{let c=r.map(E=>E.length).map((E,q)=>gt(`input${q}`,i,E)),p=st.size(u),d=Vt("output",i,u.length),b=[...s.symbolToInfo.keys()].filter(E=>!s.rhs.symbolToIndices.has(E)),T=E=>{let q=[],H="var prod = 1.0;",v="var sum = 0.0;",ne="sum += prod;",re=[],ce=[],_e=[],be=[],he=s.symbolToInfo.size===s.rhs.symbolToIndices.size;s.symbolToInfo.forEach((xe,Ie)=>{var ct;if(s.rhs.symbolToIndices.has(Ie)){let et=(ct=s.rhs.symbolToIndices.get(Ie))==null?void 0:ct[0];et!==void 0&&s.lhs.forEach((vt,Ft)=>{if(xe.inputIndices.includes(Ft)){let Lt=vt.symbolToIndices.get(Ie);if(Lt===void 0)throw new Error("Invalid symbol error");Lt.forEach(pr=>{q.push(`${c[Ft].indicesSet(`input${Ft}Indices`,pr,d.indicesGet("outputIndices",et))}`)})}})}else s.lhs.forEach((et,vt)=>{if(xe.inputIndices.includes(vt)){let Ft=et.symbolToIndices.get(Ie);if(Ft===void 0)throw new Error("Invalid symbol error");Ft.forEach(Lt=>{re.push(`${c[vt].indicesSet(`input${vt}Indices`,Lt,`${Ie}`)}`)}),be.push(`prod *= ${c[vt].getByIndices(`input${vt}Indices`)};`)}}),ce.push(`for(var ${Ie}: u32 = 0; ${Ie} < uniforms.${Us(Ie)}; ${Ie}++) {`),_e.push("}")});let Fe=he?[...q,`let sum = ${c.map((xe,Ie)=>xe.getByIndices(`input${Ie}Indices`)).join(" * ")};`]:[...q,v,...ce,...re,H,...be,ne,..._e];return`
            ${E.registerUniforms(b.map(xe=>({name:`${Us(xe)}`,type:"u32"}))).registerUniform("outputSize","u32").declareVariables(...c,d)}

            ${E.mainStart()}
            ${E.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}
            var outputIndices = ${d.offsetToIndices("global_idx")};
            ${c.map((xe,Ie)=>`var input${Ie}Indices: ${c[Ie].type.indices};`).join(`
`)}
            ${Fe.join(`
`)};
            ${d.setByOffset("global_idx","sum")};
          }`};return{name:"Einsum",shaderCache:{hint:s.equation,inputDependencies:r.map(()=>"rank")},getRunData:()=>{let E=b.filter(H=>s.symbolToInfo.has(H)).map(H=>{var v;return{type:12,data:((v=s.symbolToInfo.get(H))==null?void 0:v.dimValue)||0}});E.push({type:12,data:p});let q=r.map((H,v)=>[...Ct(H)]).reduce((H,v)=>H.concat(v),E);return q.push(...Ct(u)),{outputs:[{dims:u,dataType:i}],dispatchGroup:{x:Math.ceil(p/64)},programUniforms:q}},getShaderSource:T}},wd=(r,i)=>{let s=new hp(r.inputs,i.equation),u=s.outputDims,c=r.inputs.map((p,d)=>p.dims);r.compute(yd(c,r.inputs[0].dataType,s,u))},vd=r=>{let i=r.equation.replace(/\s+/g,"");return Gt({equation:i})}}),gl,Vs,bd,xd,_l,hm=h(()=>{Xt(),Yt(),or(),gl=r=>{if(!r||r.length!==2)throw new Error("Expand requires 2 input.");let i=r[0].dims,s=Array.from(r[1].getBigInt64Array(),Number),u=s.length<i.length?0:s.length-i.length,c=i.length<s.length?0:i.length-s.length;for(;u<s.length&&c<i.length;++u,++c)if(s[u]!==i[c]&&s[u]!==1&&i[c]!==1)throw new Error("Expand requires shape to be broadcastable to input")},Vs=(r,i)=>{let s=r.length-i.length,u=[];for(let c=0;c<s;++c)u.push(r[c]);for(let c=0;c<i.length;++c)u.push(i[c]===1?r[c+s]:i[c]);return u},bd=(r,i)=>r.length>i.length?Vs(r,i):Vs(i,r),xd=r=>{let i=r[0].dims,s=Array.from(r[1].getBigInt64Array(),Number),u=bd(i,s),c=r[0].dataType,p=c===9?4:1,d=Math.ceil(st.size(u)/p),b=E=>{let q=gt("input",c,i.length,p),H=Vt("output",c,u.length,p),v;if(c===9){let ne=(re,ce,_e="")=>`
          let outputIndices${ce} = ${H.offsetToIndices(`outputOffset + ${ce}u`)};
          let offset${ce} = ${q.broadcastedIndicesToOffset(`outputIndices${ce}`,H)};
          let index${ce} = offset${ce} / 4u;
          let component${ce} = offset${ce} % 4u;
          ${re}[${ce}] = ${_e}(${q.getByOffset(`index${ce}`)}[component${ce}]);
        `;v=`
        let outputOffset = global_idx * ${p};
        var data = vec4<u32>(0);
        ${ne("data",0,"u32")}
        ${ne("data",1,"u32")}
        ${ne("data",2,"u32")}
        ${ne("data",3,"u32")}
        ${H.setByOffset("global_idx","data")}
      }`}else v=`
        let outputIndices = ${H.offsetToIndices("global_idx")};
        let inputOffset = ${q.broadcastedIndicesToOffset("outputIndices",H)};
        ${H.setByOffset("global_idx",q.getByOffset("inputOffset"))}
      }`;return`
    ${E.registerUniform("vec_size","u32").declareVariables(q,H)}
    ${E.mainStart()}
    ${E.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.vec_size")}
    ${v}`},T=[{type:12,data:d},...Ct(i,u)];return{name:"Expand",shaderCache:{hint:`${u.length}`,inputDependencies:["rank"]},getShaderSource:b,getRunData:()=>({outputs:[{dims:u,dataType:r[0].dataType}],dispatchGroup:{x:Math.ceil(d/64)},programUniforms:T})}},_l=r=>{gl(r.inputs),r.compute(xd(r.inputs),{inputs:[0]})}}),gp,Md,_p=h(()=>{Xt(),Yt(),or(),Ua(),gp=r=>{let i=r[0].dataType,s=st.size(r[0].dims),u=st.size(r[1].dims),c=u%4===0,p=d=>{let b=gt("x",i,[1],4),T=gt("bias",i,[1],4),E=Vt("y",i,[1],4),q=[{name:"output_vec_size",type:"u32"},{name:"bias_size",type:"u32"}],H=ne=>`
      let bias${ne}_offset: u32 = (global_idx * 4 + ${ne}) % uniforms.bias_size;
      let bias${ne} = ${T.getByOffset(`bias${ne}_offset / 4`)}[bias${ne}_offset % 4];`,v=c?`
      let bias = ${T.getByOffset("global_idx % (uniforms.bias_size / 4)")};`:`${H(0)}${H(1)}${H(2)}${H(3)}
      let bias = ${b.type.value}(bias0, bias1, bias2, bias3);`;return`${d.registerUniforms(q).declareVariables(b,T,E)}

    ${Ba(kr(i))}

    ${d.mainStart(Bn)}
      ${d.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_vec_size")}

      let x = ${b.getByOffset("global_idx")};
      ${v}
      let x_in = x + bias;
      ${E.setByOffset("global_idx",Na("x_in"))}
    }`};return{name:"FastGeluWithBias",shaderCache:{hint:`${c}`,inputDependencies:["type","type"]},getShaderSource:p,getRunData:d=>({outputs:[{dims:d[0].dims,dataType:d[0].dataType}],programUniforms:[{type:12,data:Math.ceil(s/4)},{type:12,data:u}],dispatchGroup:{x:Math.ceil(s/Bn/4)}})}},Md=r=>{r.inputs.length<2||st.size(r.inputs[1].dims)===0?Mc(r):r.compute(gp(r.inputs))}}),Td,kd,Sd,Ed,yp=h(()=>{Xt(),Yt(),mr(),or(),Td=r=>{if(!r||r.length!==2)throw new Error("Gather requires 2 inputs.")},kd=(r,i)=>{let s=r[0].dims,u=r[1].dims,c=s.length,p=st.normalizeAxis(i.axis,c),d=s.slice(0);d.splice(p,1,...u);let b=s[p],T=r[0].dataType===9?4:1,E=Math.ceil(st.size(d)/T),q=[{type:12,data:E},{type:6,data:b},{type:12,data:p},...Ct(r[0].dims,r[1].dims,d)],H=v=>{let ne=gt("data",r[0].dataType,r[0].dims.length,T),re=gt("inputIndices",r[1].dataType,r[1].dims.length),ce=Vt("output",r[0].dataType,d.length,T),_e=he=>{let Fe=u.length,xe=`var indicesIndices${he}  = ${re.type.indices}(0);`;for(let Ie=0;Ie<Fe;Ie++)xe+=`${Fe>1?`indicesIndices${he}[${Ie}]`:`indicesIndices${he}`} = ${d.length>1?`outputIndices${he}[uniforms.axis + ${Ie}]`:`outputIndices${he}`};`;xe+=`
          var idx${he} = ${re.getByIndices(`indicesIndices${he}`)};
          if (idx${he} < 0) {
            idx${he} = idx${he} + uniforms.axisDimLimit;
          }
          var dataIndices${he} : ${ne.type.indices};
        `;for(let Ie=0,ct=0;Ie<c;Ie++)Ie===p?(xe+=`${c>1?`dataIndices${he}[${Ie}]`:`dataIndices${he}`} = u32(idx${he});`,ct+=Fe):(xe+=`${c>1?`dataIndices${he}[${Ie}]`:`dataIndices${he}`} = ${d.length>1?`outputIndices${he}[${ct}]`:`outputIndices${he}`};`,ct++);return xe},be;if(r[0].dataType===9){let he=(Fe,xe,Ie="")=>`
          let outputIndices${xe} = ${ce.offsetToIndices(`outputOffset + ${xe}u`)};
          ${_e(xe)};
          let offset${xe} = ${ne.indicesToOffset(`dataIndices${xe}`)};
          let index${xe} = offset${xe} / 4u;
          let component${xe} = offset${xe} % 4u;
          ${Fe}[${xe}] = ${Ie}(${ne.getByOffset(`index${xe}`)}[component${xe}]);
        `;be=`
        let outputOffset = global_idx * ${T};
        var value = vec4<u32>(0);
        ${he("value",0,"u32")}
        ${he("value",1,"u32")}
        ${he("value",2,"u32")}
        ${he("value",3,"u32")}
        ${ce.setByOffset("global_idx","value")}
      `}else be=`
      let outputIndices = ${ce.offsetToIndices("global_idx")};
      ${_e("")};
      let value = ${ne.getByIndices("dataIndices")};
      ${ce.setByOffset("global_idx","value")};
      `;return`
      ${v.registerUniform("outputSize","u32").registerUniform("axisDimLimit","i32").registerUniform("axis","u32").declareVariables(ne,re,ce)}
      ${v.mainStart()}
        ${v.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}
        ${be}
      }`};return{name:"Gather",shaderCache:{hint:i.cacheKey,inputDependencies:["rank","rank"]},getRunData:()=>({outputs:[{dims:d,dataType:r[0].dataType}],dispatchGroup:{x:Math.ceil(E/64)},programUniforms:q}),getShaderSource:H}},Sd=r=>Gt({axis:r.axis}),Ed=(r,i)=>{let s=r.inputs;Td(s),r.compute(kd(r.inputs,i))}}),Cd,Pd,$d,Ad,wp=h(()=>{Xt(),Yt(),mr(),or(),Cd=r=>{if(!r||r.length!==2)throw new Error("GatherElements requires 2 inputs.");if(r[0].dims.length<1)throw new Error("GatherElements requires that the data input be rank >= 1.");if(r[0].dims.length!==r[1].dims.length)throw new Error(`GatherElements requires that the data input and
                     indices input tensors be of same rank.`)},Pd=(r,i)=>{let s=r[0].dims,u=r[0].dataType,c=s.length,p=r[1].dims,d=r[1].dataType,b=st.normalizeAxis(i.axis,c),T=s[b],E=p.slice(0),q=st.size(E),H=gt("input",u,c),v=gt("indicesInput",d,p.length),ne=Vt("output",u,E.length),re=[{type:12,data:q},{type:6,data:T},{type:12,data:b}];return re.push(...Ct(s,p,E)),{name:"GatherElements",shaderCache:{inputDependencies:["rank","rank"]},getRunData:()=>({outputs:[{dims:E,dataType:r[0].dataType}],dispatchGroup:{x:Math.ceil(q/64)},programUniforms:re}),getShaderSource:ce=>`
      ${ce.registerUniform("outputSize","u32").registerUniform("axisDimLimit","i32").registerUniform("axis","u32").declareVariables(H,v,ne)}
      ${ce.mainStart()}
      ${ce.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}

      let outputIndices = ${ne.offsetToIndices("global_idx")};

      var idx = ${v.getByOffset("global_idx")};
      if (idx < 0) {
        idx = idx + uniforms.axisDimLimit;
      }
      var inputIndices = ${H.type.indices}(outputIndices);
      ${H.indicesSet("inputIndices","uniforms.axis","u32(idx)")};
      let value = ${H.getByIndices("inputIndices")};

      ${ne.setByOffset("global_idx","value")};
  }`}},$d=r=>Gt({axis:r.axis}),Ad=(r,i)=>{let s=r.inputs;Cd(s),r.compute(Pd(r.inputs,i))}}),Id,Fd,zd,vp,Od=h(()=>{Xt(),Yt(),or(),Id=r=>{if(!r)throw new Error("Input is missing");if(r.length<2||r.length>3)throw new Error("Invaid input number.");if(r.length===3&&r[2].dims.length>2)throw new Error("Invalid input shape of C");if(r[0].dataType!==r[1].dataType||r.length===3&&r[0].dataType!==r[2].dataType)throw new Error("Input types are mismatched")},Fd=(r,i)=>{let s=r[0].dims.slice(),u=r[1].dims.slice(),[c,p,d]=xr.getShapeOfGemmResult(s,i.transA,u,i.transB,r.length===3?r[2].dims:void 0),b=[c,p];if(!b)throw new Error("Can't use gemm on the given tensors");let T=st.size(b),E=[{type:12,data:T},{type:12,data:c},{type:12,data:p},{type:12,data:d},{type:1,data:i.alpha},{type:1,data:i.beta}],q=["type","type"];r.length===3&&(E.push(...Ct(r[2].dims)),q.push("rank")),E.push(...Ct(b));let H=v=>{let ne="";i.transA&&i.transB?ne="value += a[k * uniforms.M + m] * b[n * uniforms.K + k];":i.transA&&!i.transB?ne="value += a[k * uniforms.M + m] * b[k * uniforms.N + n];":!i.transA&&i.transB?ne="value += a[m * uniforms.K + k] * b[n * uniforms.K + k];":!i.transA&&!i.transB&&(ne="value += a[m * uniforms.K + k] * b[k * uniforms.N + n];");let re=i.alpha===1?"":"value *= uniforms.alpha;",ce=gt("a",r[0].dataType,r[0].dims),_e=gt("b",r[1].dataType,r[1].dims),be=ce.type.value,he=null,Fe=[ce,_e];r.length===3&&(he=gt("c",r[2].dataType,r[2].dims.length),Fe.push(he));let xe=Vt("output",r[0].dataType,b.length);Fe.push(xe);let Ie=[{name:"output_size",type:"u32"},{name:"M",type:"u32"},{name:"N",type:"u32"},{name:"K",type:"u32"},{name:"alpha",type:"f32"},{name:"beta",type:"f32"}];return`
  ${v.registerUniforms(Ie).declareVariables(...Fe)}

  ${v.mainStart()}
    ${v.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}

    let m = global_idx / uniforms.N;
    let n = global_idx % uniforms.N;

    var value = ${be}(0);
    for (var k: u32 = 0u; k < uniforms.K; k++) {
      ${ne}
    }

    ${re}
    ${he!=null?`let cOffset = ${he.broadcastedIndicesToOffset("vec2(m, n)",xe)}; value += ${be}(uniforms.beta) * ${he.getByOffset("cOffset")};`:""}
    output[global_idx] = value;
  }`};return{name:"Gemm",shaderCache:{hint:`${i.cacheKey}`,inputDependencies:q},getRunData:()=>({outputs:[{dims:b,dataType:r[0].dataType}],dispatchGroup:{x:Math.ceil(T/64)},programUniforms:E}),getShaderSource:H}},zd=r=>{let i=r.transA,s=r.transB,u=r.alpha,c=r.beta;return{transA:i,transB:s,alpha:u,beta:c,cacheKey:`${r.transA};${r.transB};${r.alpha===1}`}},vp=(r,i)=>{Id(r.inputs),r.compute(Fd(r.inputs,i))}}),Sn,Dd,Ld,yl,Rd,Xo,Bd,Nd=h(()=>{Xt(),Yt(),mr(),fe(),Is(),or(),_o(),Sn=(r,i)=>r.length>i&&r[i].dims.length>0?r[i]:void 0,Dd=(r,i)=>{let s=r[0],u=Sn(r,1),c=Sn(r,2),p=Sn(r,3),d=Sn(r,4),b=Sn(r,5),T=Sn(r,6),E=Sn(r,7);if(s.dims.length!==3&&s.dims.length!==5)throw new Error("Input query is expected to have 3 or 5 dimensions");let q=s.dims[0],H=s.dims[1],v=s.dims.length===3?s.dims[2]:i.numHeads*s.dims[4],ne=H,re=0,ce=0,_e=Math.floor(v/i.numHeads);if(T&&E){if(T.dims.length!==4)throw new Error('Input "past_key" is expected to have 4 dimensions');if(T.dims[0]!==q||T.dims[1]!==i.numHeads||T.dims[3]!==_e)throw new Error('Input "past_key" shape (batch_size, num_heads, past_sequence_length, head_size)');if(E.dims[0]!==q||E.dims[1]!==i.numHeads||E.dims[3]!==_e)throw new Error('Input "past_value" shape (batch_size, num_heads, past_sequence_length, head_size)');if(T.dims[2]!==E.dims[2])throw new Error('Input "past_key" and "past_value" shall have same dim 2 (past_sequence_length)');if(E.dims.length!==4)throw new Error('Input "past_value" is expected to have 4 dimensions');re=T.dims[2],ce=T.dims[2]}else if(T||E)throw new Error('Input "past_key" and "past_value" shall be both present or both absent');let be;if(u){if(s.dims.length!==3)throw new Error('Input "query" is expected to have 3 dimensions when key is given');if(u.dims.length<3||u.dims.length>5)throw new Error('Input "key" is expected to have 3, 4, or 5 dimensions');if(s.dims[0]!==u.dims[0])throw new Error('Input "query" and "key" shall have same dim 0 (batch size)');if(u.dims.length===3){if(u.dims[2]!==s.dims[2])throw new Error('Input "query" and "key" shall have same dim 2 (hidden_size)');be=2,ne=u.dims[1]}else if(u.dims.length===5){if(u.dims[2]!==i.numHeads||u.dims[3]!==2||u.dims[4]!==_e)throw new Error('Expect "key" shape (batch_size, kv_sequence_length, num_heads, 2, head_size) for packed kv');if(c)throw new Error('Expect "value" be none when "key" has packed kv format.');be=5,ne=u.dims[1]}else{if(u.dims[1]!==i.numHeads||u.dims[3]!==_e)throw new Error('Expect "key" shape (batch_size, num_heads, kv_sequence_length, head_size) for past_key');be=0,ne=u.dims[2]}}else{if(s.dims.length!==5)throw new Error('Input "query" is expected to have 5 dimensions when key is empty');if(s.dims[2]!==i.numHeads||s.dims[3]!==3)throw new Error('Expect "query" shape (batch_size, kv_sequence_length, num_heads, 3, head_size) for packed kv');be=3}if(p){if(p.dims.length!==1)throw new Error('Input "bias" is expected to have 1 dimension');if(u&&u.dims.length===5&&u.dims[3]===2)throw new Error("bias is not allowed for packed kv.")}let he=re+ne,Fe=0;if(d){Fe=8;let et=d.dims;throw et.length===1?et[0]===q?Fe=1:et[0]===3*q+2&&(Fe=3):et.length===2&&et[0]===q&&et[1]===he&&(Fe=5),Fe===8?new Error('Input "key_padding_mask" shape shall be (batch_size) or (batch_size, total_sequence_length)'):new Error("Mask not supported")}let xe=!1,Ie=v;if(c){if(c.dims.length!==3&&c.dims.length!==4)throw new Error('Input "value" is expected to have 3 or 4 dimensions');if(s.dims[0]!==c.dims[0])throw new Error('Input "query" and "value" shall have same dim 0 (batch_size)');if(c.dims.length===3){if(ne!==c.dims[1])throw new Error('Input "key" and "value" shall have the same dim 1 (kv_sequence_length)');Ie=c.dims[2]}else{if(ne!==c.dims[2])throw new Error('Input "key" and "value" shall have the same dim 2 (kv_sequence_length)');Ie=c.dims[1]*c.dims[3],xe=!0}}let ct=!1;if(d)throw new Error("Key padding mask is not supported");if(b){if(b.dims.length!==4)throw new Error('Input "attention_bias" is expected to have 4 dimensions');if(b.dims[0]!==q||b.dims[1]!==i.numHeads||b.dims[2]!==H||b.dims[3]!==he)throw new Error('Expect "attention_bias" shape (batch_size, num_heads, sequence_length, total_sequence_length)')}return{batchSize:q,sequenceLength:H,pastSequenceLength:re,kvSequenceLength:ne,totalSequenceLength:he,maxSequenceLength:ce,inputHiddenSize:0,hiddenSize:v,vHiddenSize:Ie,headSize:_e,vHeadSize:Math.floor(Ie/i.numHeads),numHeads:i.numHeads,isUnidirectional:!1,pastPresentShareBuffer:!1,maskFilterValue:i.maskFilterValue,maskType:Fe,scale:i.scale,broadcastResPosBias:ct,passPastInKv:xe,qkvFormat:be}},Ld=r=>Gt({...r}),yl=Gt({perm:[0,2,1,3]}),Rd=(r,i,s,u,c,p,d)=>{let b=[u,c,p],T=st.size(b),E=[{type:12,data:T},{type:12,data:d},{type:12,data:p}],q=H=>{let v=Vt("qkv_with_bias",i.dataType,b),ne=gt("qkv",i.dataType,b),re=gt("bias",s.dataType,b),ce=[{name:"output_size",type:"u32"},{name:"bias_offset",type:"u32"},{name:"hidden_size",type:"u32"}];return`
  ${H.registerUniforms(ce).declareVariables(ne,re,v)}
  ${H.mainStart()}
    ${H.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
    let bias_offset_idx = (global_idx % uniforms.hidden_size) + uniforms.bias_offset;

    qkv_with_bias[global_idx] = qkv[global_idx] + bias[bias_offset_idx];
  }`};return r.compute({name:"MultiHeadAttentionAddBias",shaderCache:{inputDependencies:["type","type"]},getRunData:()=>({outputs:[{dims:b,dataType:i.dataType,gpuDataType:0}],dispatchGroup:{x:Math.ceil(T/64)},programUniforms:E}),getShaderSource:q},{inputs:[i,s],outputs:[-1]})[0]},Xo=(r,i,s,u,c,p,d,b)=>{let T=p;if(d){if(u===1)throw new Error("AddBiasReshape is not implemented. Please export your model with packed QKV or KV");return T=Rd(r,p,d,i,u,s*c,b),T=T.reshape([i,u,s,c]),r.compute(fi(T,yl.perm),{inputs:[T],outputs:[-1]})[0]}else return p.dims.length===3&&(T=p.reshape([i,u,s,c])),r.compute(fi(T,yl.perm),{inputs:[T],outputs:[-1]})[0]},Bd=(r,i)=>{let s=Dd(r.inputs,i),u=r.inputs[0],c=Sn(r.inputs,1),p=Sn(r.inputs,2),d=Sn(r.inputs,3),b=Sn(r.inputs,4),T=Sn(r.inputs,5),E=Sn(r.inputs,6),q=Sn(r.inputs,7);if(u.dims.length===5)throw new Error("Packed QKV is not implemented");if((c==null?void 0:c.dims.length)===5)throw new Error("Packed KV is not implemented");let H=c&&p&&c.dims.length===4&&p.dims.length===4,v=Xo(r,s.batchSize,s.numHeads,s.sequenceLength,s.headSize,u,d,0);if(H)return yo(r,v,c,p,b,void 0,E,q,T,s,i);if(!c||!p)throw new Error("key and value must be provided");let ne=Xo(r,s.batchSize,s.numHeads,s.kvSequenceLength,s.headSize,c,d,s.hiddenSize),re=Xo(r,s.batchSize,s.numHeads,s.kvSequenceLength,s.vHeadSize,p,d,2*s.hiddenSize);yo(r,v,ne,re,b,void 0,E,q,T,s,i)}}),wl,jd,Ud,vl,Vd,Wd=h(()=>{Xt(),Yt(),or(),wl=r=>Array.from(r.getBigInt64Array(),Number),jd=r=>{if(!r||r.length!==2)throw new Error("Tile requires 2 inputs.");if(r[0].dataType!==1&&r[0].dataType!==10&&r[0].dataType!==6&&r[0].dataType!==12)throw new Error("Tile only support float, float16, int32, and uint32 data types");if(r[1].dataType!==7)throw new Error("Tile `repeats` input should be of int64 data type");if(r[1].dims.length!==1)throw new Error("Tile `repeats` input should be 1-D");if(wl(r[1]).length!==r[0].dims.length)throw new Error("Tile `repeats` input should have same number of elements as rank of input data tensor")},Ud=(r,i)=>{let s=[];for(let u=0;u<r.length;++u)s.push(r[u]*i[u]);return s},vl=(r,i)=>{let s=r[0].dims,u=i??wl(r[1]),c=Ud(s,u),p=st.size(c),d=r[0].dataType,b=gt("input",d,s.length),T=Vt("output",d,c.length),E=q=>`
      const inputShape = ${b.indices(...s)};
      ${q.registerUniform("output_size","u32").declareVariables(b,T)}
      ${q.mainStart()}
      ${q.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
      let output_indices = ${T.offsetToIndices("global_idx")};
      var input_indices: ${b.type.indices};
      for (var i = 0; i < ${s.length}; i++) {
        let input_dim_i = ${b.indicesGet("uniforms.input_shape","i")};
        let input_dim_value = ${T.indicesGet("output_indices","i")}  % input_dim_i;

        ${b.indicesSet("input_indices","i","input_dim_value")}
      }
      ${T.setByOffset("global_idx",b.getByIndices("input_indices"))}
    }`;return{name:"Tile",shaderCache:{hint:`${u}`,inputDependencies:["rank"]},getRunData:()=>({outputs:[{dims:c,dataType:r[0].dataType}],dispatchGroup:{x:Math.ceil(p/64)},programUniforms:[{type:12,data:p},...Ct(r[0].dims,c)]}),getShaderSource:E}},Vd=r=>{jd(r.inputs),r.compute(vl(r.inputs),{inputs:[0]})}}),Gd,bl,qd,Hd,xl,Kd,bp=h(()=>{Xt(),Yt(),mr(),Is(),or(),Nd(),Wd(),_o(),Gd=(r,i)=>{let s=r[0],u=r[1],c=r[2],p=r[3],d=r[4];if(s.dims.length!==3&&s.dims.length!==5)throw new Error("Input query is expected to have 3 or 5 dimensions");let b=!1,T=s.dims[0],E=s.dims[1],q=s.dims.length===3?b?s.dims[2]/3:s.dims[2]:i.numHeads*s.dims[4],H=E,v=0,ne=0,re=Math.floor(q/i.numHeads),ce=p&&p.dims.length!==0,_e=d&&d.dims.length!==0,be=!0;if(ce&&_e){if(p.dims.length!==4)throw new Error('Input "past_key" is expected to have 4 dimensions');if(d.dims.length!==4)throw new Error('Input "past_value" is expected to have 4 dimensions');v=p.dims[1],ne=p.dims[1]}else if(ce||_e)throw new Error('Input "past_key" and "past_value" shall be both present or both absent');let he;if(u){if(s.dims.length!==3)throw new Error('Input "query" is expected to have 3 dimensions when key is given');if(u.dims.length<3||u.dims.length>5)throw new Error('Input "key" is expected to have 3, 4, or 5 dimensions');if(s.dims[0]!==u.dims[0])throw new Error('Input "query" and "key" shall have same dim 0 (batch size)');if(u.dims.length===3){if(s.dims[2]%u.dims[2]!==0)throw new Error('Dimension 2 of "query" should be a multiple of "key"');he=2,H=u.dims[1]}else if(u.dims.length===5){if(u.dims[2]!==i.numHeads||u.dims[3]!==2||u.dims[4]!==re)throw new Error('Expect "key" shape (batch_size, kv_sequence_length, num_heads, 2, head_size) for packed kv');if(c)throw new Error('Expect "value" be none when "key" has packed kv format.');he=5,H=u.dims[1]}else{if(u.dims[1]!==i.numHeads||u.dims[3]!==re)throw new Error('Expect "key" shape (batch_size, num_heads, kv_sequence_length, head_size) for past_key');he=0,H=u.dims[2]}}else{if(s.dims.length!==3&&s.dims.length!==5)throw new Error('Input "query" is expected to have 3 or 5 dimensions when key is empty');if(s.dims.length===5&&(s.dims[2]!==i.numHeads||s.dims[3]!==3))throw new Error('Expect "query" shape (batch_size, kv_sequence_length, num_heads, 3, head_size) for packed kv');he=3}let Fe=0,xe=!1,Ie=q;if(c){if(c.dims.length!==3&&c.dims.length!==4)throw new Error('Input "value" is expected to have 3 or 4 dimensions');if(s.dims[0]!==c.dims[0])throw new Error('Input "query" and "value" shall have same dim 0 (batch_size)');if(c.dims.length===3){if(H!==c.dims[1])throw new Error('Input "key" and "value" shall have the same dim 1 (kv_sequence_length)');Ie=c.dims[2]}else{if(H!==c.dims[2])throw new Error('Input "past_key" and "past_value" shall have the same dim 2 (kv_sequence_length)');Ie=c.dims[1]*c.dims[3],xe=!0}}let ct=v+H;return{batchSize:T,sequenceLength:E,pastSequenceLength:v,kvSequenceLength:H,totalSequenceLength:ct,maxSequenceLength:ne,inputHiddenSize:0,hiddenSize:q,vHiddenSize:Ie,headSize:re,vHeadSize:Math.floor(Ie/i.kvNumHeads),numHeads:i.numHeads,kvNumHeads:i.kvNumHeads,nReps:i.numHeads/i.kvNumHeads,pastPresentShareBuffer:!1,maskType:Fe,scale:i.scale,broadcastResPosBias:!1,passPastInKv:xe,qkvFormat:he,isPastkvBSNH:be}},bl=(r,i,s,u)=>{let c=[u.batchSize,u.totalSequenceLength,u.kvNumHeads,u.headSize],p=4,d=st.size(c)/p,b=u.totalSequenceLength,T=Vt("present_kv",s,c.length,p),E=gt("new_kv",r.dataType,r.dims.length,p),q=i?gt("past_kv",i.dataType,i.dims.length,p):void 0,H=Math.ceil(u.headSize/p),v={x:b,y:r.dims[0],z:1},ne=i?["rank","rank"]:["rank"],re=[{type:12,data:d},{type:12,data:u.pastSequenceLength},{type:12,data:u.kvSequenceLength},{type:12,data:u.totalSequenceLength}],ce=[E];q?(re.push(...Ct(r.dims),...Ct(i.dims),...Ct(c)),ce.push(q)):re.push(...Ct(r.dims),...Ct(c));let _e=[{name:"output_size",type:"u32"},{name:"past_seqlen",type:"u32"},{name:"new_seqlen",type:"u32"},{name:"present_seqlen",type:"u32"}],be=`      let past_batch_stride = uniforms.past_seqlen * num_heads * H;
        var past_head_stride = uniforms.past_seqlen * H;
        if (is_bsnh) {
          past_head_stride = H;
        }
        let in_offset = b * past_batch_stride + s * row_stride + n * past_head_stride + h;
        present_kv[out_offset] = past_kv[in_offset];`,he=`      let new_batch_stride = uniforms.new_seqlen * num_heads * H;
        let new_row_stride = num_heads * H;
        let new_head_stride = H;
        let in_offset = b * new_batch_stride + (s - past_seqlen) * new_row_stride + n * new_head_stride + h;
        present_kv[out_offset] = new_kv[in_offset];`,Fe=i?`if (s < past_seqlen) {
        ${be}
        } else if (s < past_seqlen + uniforms.new_seqlen) {
        ${he}
        }`:`if (s < past_seqlen + uniforms.new_seqlen) {
          ${he}
        }`,xe=Ie=>`

  ${Ie.registerUniforms(_e).declareVariables(...ce,T)}
  ${Ie.mainStart([H,u.kvNumHeads,1])}
    ${Ie.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
    var indices = ${T.offsetToIndices("global_idx")};
    let h = local_id.x;
    let n = local_id.y;
    let s = workgroup_id.x;
    let b = workgroup_id.y;
    let num_heads = ${u.kvNumHeads}u;
    let H = ${H}u;

    let present_seqlen = uniforms.present_seqlen;
    let present_batch_stride = present_seqlen * num_heads * H;
    var row_stride = H;
    let is_bsnh = ${u.isPastkvBSNH};

    if (is_bsnh) {
      row_stride = num_heads * H;
    }
    var present_head_stride = present_seqlen * H;
    if (is_bsnh) {
      present_head_stride = H;
    }

    let past_seqlen = uniforms.past_seqlen;

    let out_offset = b * present_batch_stride + s * row_stride + n * present_head_stride + h;
    ${Fe}
  }`;return{name:"ConcatPastNew",shaderCache:{hint:`${u.kvNumHeads}${H}${!!i}`,inputDependencies:ne},getRunData:()=>({outputs:[{dims:c,dataType:s}],dispatchGroup:v,programUniforms:re}),getShaderSource:xe}},qd=r=>Gt({...r}),Hd=Gt({perm:[0,2,1,3]}),xl=(r,i,s,u,c)=>{let p=i,d=u.kvNumHeads,b=u.nReps;return i.dims.length===3&&u.kvSequenceLength!==0&&(p=i.reshape([u.batchSize,u.kvSequenceLength,d,u.headSize])),s?p=r.compute(bl(p,s,p.dataType,u),{inputs:[p,s],outputs:[u.isPastkvBSNH?c:-1]})[0]:p=r.compute(bl(p,void 0,p.dataType,u),{inputs:[p],outputs:[u.isPastkvBSNH?c:-1]})[0],b!==1&&(p=r.compute(vl([p],[1,1,1,b]),{inputs:[p],outputs:[-1]})[0],p=p.reshape([u.batchSize,u.totalSequenceLength,d*b,u.headSize])),r.compute(fi(p,Hd.perm),{inputs:[p],outputs:[-1]})[0]},Kd=(r,i)=>{var T;let s=Gd(r.inputs,i);if(r.inputs[0].dims.length===5)throw new Error("Packed QKV is not implemented");if(((T=r.inputs[1])==null?void 0:T.dims.length)===5)throw new Error("Packed KV is not implemented");let u=Xo(r,s.batchSize,s.numHeads,s.sequenceLength,s.headSize,r.inputs[0],void 0,0),c=r.inputs[3]&&r.inputs[3].dims.length!==0?r.inputs[3]:void 0,p=r.inputs[4]&&r.inputs[4].dims.length!==0?r.inputs[4]:void 0,d=xl(r,r.inputs[1],c,s,1),b=xl(r,r.inputs[2],p,s,2);yo(r,u,d,b,void 0,void 0,void 0,void 0,void 0,s,i)}}),Qd,Xd,Yd,Zd,mm=h(()=>{Xt(),Yt(),or(),Qd=(r,i)=>{let s=r[0].dims,u=s,c=2,p=st.sizeToDimension(s,c),d=st.sizeFromDimension(s,c),b=wr(d),T=d/b,E=[s[0],s[1],T],q=["rank","type","type"],H=[{type:12,data:d},{type:12,data:T}];H.push(...Ct(E,E));let v=ne=>{let re=gt("x",r[0].dataType,E.length,b),ce=gt("scale",r[1].dataType,r[1].dims),_e=gt("bias",r[2].dataType,r[2].dims),be=Vt("output",r[0].dataType,E.length,b),he=[re,ce,_e,be],Fe=re.type.value,xe=b===1?"f32":`vec${b}<f32>`,Ie=64,ct=[{name:"normSize",type:"u32"},{name:"normPackedSize",type:"u32"}];return`
  var<workgroup> meanShared : f32;
  var<workgroup> squaredNormShared : f32;
  var<workgroup> workgroupShared : array<${xe}, ${Ie}>;
  const workgroupSize = ${Ie}u;
  ${ne.registerUniforms(ct).declareVariables(...he)}
  ${ne.mainStart(Ie)}
    let norm = global_idx / workgroupSize;
    let batch = norm / uniforms.x_shape[1];
    let channel = norm % uniforms.x_shape[1];
    let localIndex = local_id.x;

    // initialize workgroup memory
    var initial = ${xe}(0);
    for (var h = localIndex; h < uniforms.normPackedSize; h += workgroupSize) {
      initial = initial + ${xe}(${re.get("batch","channel","h")});
    }
    workgroupShared[localIndex] = initial;
    workgroupBarrier();

    // Calculate the mean of current channel data.
    for (var currSize = workgroupSize >> 1;  currSize > 0; currSize = currSize >> 1) {
      if (localIndex < currSize) {
        workgroupShared[localIndex] = workgroupShared[localIndex] + workgroupShared[localIndex + currSize];
      }
      workgroupBarrier();
    }
    if (localIndex == 0) {
      meanShared = ${Nn("workgroupShared[0]",b)} / f32(uniforms.normSize);
    }
    workgroupBarrier();

    // reinitialize workgroup memory.
    initial = ${xe}(0);
    for (var h = localIndex; h < uniforms.normPackedSize; h += workgroupSize) {
      let deviation =  ${xe}(${re.get("batch","channel","h")}) - ${xe}(meanShared);
      initial = initial + deviation * deviation;
    }
    workgroupShared[localIndex] = initial;
    workgroupBarrier();

    // Calculate the sum of square of deviation of current channel data.
    for (var currSize = workgroupSize >> 1;  currSize > 0; currSize = currSize >> 1) {
      if (localIndex < currSize) {
        workgroupShared[localIndex] = workgroupShared[localIndex] + workgroupShared[localIndex + currSize];
      }
      workgroupBarrier();
    }
    if (localIndex == 0) {
      squaredNormShared = ${Nn("workgroupShared[0]",b)};
    }
    workgroupBarrier();

    let invStdDev = inverseSqrt(squaredNormShared / f32(uniforms.normSize) + f32(${i.epsilon}));
    let channelScale = invStdDev * f32(${ce.getByOffset("channel")});
    let channelShift = f32(${_e.getByOffset("channel")}) - meanShared * channelScale;
    for (var h = localIndex; h < uniforms.normPackedSize; h += workgroupSize) {
      let value = ${re.get("batch","channel","h")} * ${Fe}(${xe}(channelScale)) + ${Fe}(${xe}(channelShift));
      ${be.set("batch","channel","h","value")};
    }
  }`};return{name:"InstanceNormalization",shaderCache:{hint:`${i.epsilon};${b}`,inputDependencies:q},getRunData:()=>({outputs:[{dims:u,dataType:r[0].dataType}],dispatchGroup:{x:p},programUniforms:H}),getShaderSource:v}},Xd=(r,i,s,u,c,p,d,b)=>{let T=wr(d),E=64,q=T===1?"vec2f":`mat2x${T}f`,H=T===1?"f32":`vec${T}f`,v=(ct,et)=>`${q}(${ct}, ${et})`,ne=c*d/T,re=Math.ceil(p/E),ce=["type"],_e=[{type:12,data:re},{type:12,data:p},{type:12,data:Math.floor(d/T)},{type:12,data:Math.floor(p*d/T)}],be=ct=>{let et=gt("input",i.dataType,i.dims,T);return`
  ${ct.declareVariables(et)}
  @group(0) @binding(1) var<storage, read_write> output : array<${q}>;
  struct Uniforms {wg_size:u32, H:u32, C:u32, image_size:u32};
  @group(0) @binding(2) var<uniform> uniforms: Uniforms;

  ${ct.mainStart(E)}
    let currentImageNumber = global_idx / ${E} / uniforms.C;
    let currentChannelNumber = (global_idx / ${E}) % uniforms.C;
    let wgOffset = local_id.x * uniforms.wg_size;
    if (wgOffset >= uniforms.H) {
        return;
    }
    let wgMax = min(wgOffset + uniforms.wg_size, uniforms.H);

    let offset = currentImageNumber * uniforms.image_size + currentChannelNumber;
    var sum = ${zr("f32",T)};
    var squaredSum = ${zr("f32",T)};
    for (var i: u32 = wgOffset; i < wgMax; i++) {
        let value = ${H}(input[offset + i * uniforms.C]);
        sum += value;
        squaredSum += value * value;
    }
    output[global_idx] = ${v("sum","squaredSum")};
  }`},he=r.compute({name:"InstanceNormComputeMean",shaderCache:{hint:`${T}`,inputDependencies:ce},getRunData:()=>({outputs:[{dims:[c,d,E,2],dataType:1}],dispatchGroup:{x:c*d/T},programUniforms:_e}),getShaderSource:be},{inputs:[i],outputs:[-1]})[0],Fe=[{type:12,data:ne},{type:12,data:p},{type:12,data:Math.floor(d/T)},{type:12,data:Math.floor(E*d/T)}],xe=["type","type","type"],Ie=ct=>{let et=gt("scale",s.dataType,s.dims,T),vt=gt("bias",u.dataType,u.dims,T);return`
  @group(0) @binding(0) var<storage, read> input : array<${q}>;
  @group(0) @binding(1) var<storage, read> scale : array<${et.type.storage}>;
  @group(0) @binding(2) var<storage, read> bias : array<${vt.type.storage}>;
  @group(0) @binding(3) var<storage, read_write> output : array<${q}>;
  struct Uniforms {units_of_work : u32, H: u32, C : u32, image_size : u32};
  @group(0) @binding(4) var<uniform> uniforms: Uniforms;

  ${ct.mainStart()}
    ${ct.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.units_of_work")}
    let currentImageNumber = global_idx / uniforms.C;
    let currentChannelNumber = global_idx % uniforms.C;

    let offset = currentImageNumber * uniforms.image_size;
    var sum = ${zr("f32",T)};
    var squaredSum = ${zr("f32",T)};
    for (var i: u32 = 0; i < min(${E}, uniforms.H); i++) {
        let value = input[offset + i + currentChannelNumber * ${E}];
        sum += value[0];
        squaredSum += value[1];
    }
    sum = sum / f32(uniforms.H);
    squaredSum = squaredSum / f32(uniforms.H);
    let invStdDev = inverseSqrt(squaredSum - sum * sum + f32(${b}));
    let channelScale = invStdDev * ${H}(scale[currentChannelNumber]);
    let channelShift = ${H}(bias[currentChannelNumber]) - sum * channelScale;

    output[global_idx] = ${v("channelScale","channelShift")};
  }`};return r.compute({name:"InstanceNormComputeChannelScaleShift",shaderCache:{hint:`${T};${b}`,inputDependencies:xe},getRunData:()=>({outputs:[{dims:[c,d,2],dataType:1}],dispatchGroup:{x:Math.ceil(ne/64)},programUniforms:Fe}),getShaderSource:Ie},{inputs:[he,s,u],outputs:[-1]})[0]},Yd=(r,i,s)=>{let u=i[0].dims,c=u,p=u[0],d=u[u.length-1],b=st.sizeFromDimension(u,1)/d,T=wr(d),E=st.size(c)/T,q=[{type:12,data:b},{type:12,data:Math.floor(d/T)}],H=["type","type"],v=Xd(r,i[0],i[1],i[2],p,b,d,s.epsilon),ne=re=>{let ce=Tr(i[0].dataType),_e=T===1?"vec2f":`mat2x${T}f`,be=T===1?ce:`vec${T}<${ce}>`,he=gt("input",i[0].dataType,i[0].dims,T),Fe=Vt("output",i[0].dataType,c,T);return`
  @group(0) @binding(0) var<storage, read> input : array<${he.type.storage}>;
  @group(0) @binding(1) var<storage, read> scaleInput : array<${_e}>;
  @group(0) @binding(2) var<storage, read_write> output : array<${Fe.type.storage}>;
  struct Uniforms {H: u32, C : u32};
  @group(0) @binding(3) var<uniform> uniforms: Uniforms;

  ${re.mainStart()}
    let currentImageNumber = global_idx / (uniforms.C * uniforms.H);
    let currentChannelNumber = global_idx % uniforms.C;

    let scaleOffset = currentImageNumber * uniforms.C + currentChannelNumber;
    let scale = scaleInput[scaleOffset];
    output[global_idx] = fma(input[global_idx], ${be}(scale[0]), ${be}(scale[1]));
  }`};r.compute({name:"InstanceNormalizationNHWC",shaderCache:{hint:`${T}`,inputDependencies:H},getRunData:()=>({outputs:[{dims:c,dataType:i[0].dataType}],dispatchGroup:{x:Math.ceil(E/64)},programUniforms:q}),getShaderSource:ne},{inputs:[i[0],v]})},Zd=(r,i)=>{i.format==="NHWC"?Yd(r,r.inputs,i):r.compute(Qd(r.inputs,i))}}),ur,Jd,dn,yn=h(()=>{Xt(),Yt(),or(),ur=r=>{if(!r||r.length<2)throw new Error("layerNorm requires at least 2 inputs.")},Jd=(r,i,s)=>{let u=i.simplified,c=r[0].dims,p=r[1],d=!u&&r[2],b=c,T=st.normalizeAxis(i.axis,c.length),E=st.sizeToDimension(c,T),q=st.sizeFromDimension(c,T),H=st.size(p.dims),v=d?st.size(d.dims):0;if(H!==q||d&&v!==q)throw new Error(`Size of X.shape()[axis:] == ${q}.
       Size of scale and bias (if provided) must match this.
       Got scale size of ${H} and bias size of ${v}`);let ne=[];for(let Ie=0;Ie<c.length;++Ie)Ie<T?ne.push(c[Ie]):ne.push(1);let re=wr(q),ce=["type","type"],_e=[{type:12,data:E},{type:1,data:q},{type:12,data:Math.floor(q/re)},{type:1,data:i.epsilon}];d&&ce.push("type");let be=s>1,he=s>2,Fe=Ie=>{let ct=Tr(r[0].dataType),et=[gt("x",r[0].dataType,r[0].dims,re),gt("scale",p.dataType,p.dims,re)];d&&et.push(gt("bias",d.dataType,d.dims,re)),et.push(Vt("output",r[0].dataType,b,re)),be&&et.push(Vt("mean_data_output",1,ne)),he&&et.push(Vt("inv_std_output",1,ne));let vt=[{name:"norm_count",type:"u32"},{name:"norm_size",type:"f32"},{name:"norm_size_vectorized",type:"u32"},{name:"epsilon",type:"f32"}];return`
  ${Ie.registerUniforms(vt).declareVariables(...et)}
  ${Ie.mainStart()}
    ${Ie.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.norm_count")}
    let offset = global_idx * uniforms.norm_size_vectorized;
    var mean_vector = ${zr("f32",re)};
    var mean_square_vector = ${zr("f32",re)};

    for (var h: u32 = 0u; h < uniforms.norm_size_vectorized; h++) {
      let value = ${Gr(ct,re,"x[h + offset]")};
      mean_vector += value;
      mean_square_vector += value * value;
    }
    let mean = ${Nn("mean_vector",re)} / uniforms.norm_size;
    let inv_std_dev = inverseSqrt(${Nn("mean_square_vector",re)} / uniforms.norm_size ${u?"":"- mean * mean"} + uniforms.epsilon);

    for (var j: u32 = 0; j < uniforms.norm_size_vectorized; j++) {
      let f32input = ${Gr(ct,re,"x[j + offset]")};
      let f32scale = ${Gr(ct,re,"scale[j]")};
      output[j + offset] = ${et[0].type.value}((f32input ${u?"":"- mean"}) * inv_std_dev * f32scale
        ${d?`+ ${Gr(ct,re,"bias[j]")}`:""}
      );
    }

    ${be?"mean_data_output[global_idx] = mean":""};
    ${he?"inv_std_output[global_idx] = inv_std_dev":""};
  }`},xe=[{dims:b,dataType:r[0].dataType}];return be&&xe.push({dims:ne,dataType:1}),he&&xe.push({dims:ne,dataType:1}),{name:"LayerNormalization",shaderCache:{hint:`${re};${s};${u}`,inputDependencies:ce},getRunData:()=>({outputs:xe,dispatchGroup:{x:Math.ceil(E/64)},programUniforms:_e}),getShaderSource:Fe}},dn=(r,i)=>{ur(r.inputs),r.compute(Jd(r.inputs,i,r.outputCount))}}),wn,Ji,xp,ef,Mp=h(()=>{Xt(),Yt(),mr(),or(),wn=(r,i)=>{if(r.length<3||r.length>4)throw new Error("MatMulNBits requires 3 or 4 inputs");let s=r[0],u=s.dims.length;if(s.dims[u-1]!==i.k)throw new Error("The last dim of input shape does not match the k value");let c=Math.floor((i.k+i.blockSize-1)/i.blockSize),p=i.blockSize/8*i.bits,d=r[1];if(!st.areEqual(d.dims,[i.n,c,p]))throw new Error("The second inputs must be 3D tensor with shape N X nBlocksPerCol X blobSize");let b=r[2].dims;if(st.size(b)!==i.n*c)throw new Error("scales input size error.");if(r.length===4){let T=r[3].dims,E=i.bits>4?i.n*c:i.n*Math.floor((c+1)/2);if(st.size(T)!==E)throw new Error("zeroPoints input size error.")}},Ji=(r,i,s,u)=>{let c=r[0].dims,p=c.length,d=Math.floor((i.k+i.blockSize-1)/i.blockSize),b=c[p-2],T=i.k,E=i.n,q=c.slice(0,p-2),H=st.size(q),v=i.blockSize/8*i.bits/4,ne=r[0].dataType,re=wr(b),ce=wr(i.k),_e=wr(v),be=Mi(ne,b*d),he=Math.floor(u/be),Fe=d<=s[0]&&he>0,xe=!Fe||he>=4?wr(E):he>=2&&wr(E)>=2?2:1,Ie=q.concat([b,E]),ct=st.size(Ie)/xe/re,et=Fe?[]:[{type:12,data:ct},{type:12,data:i.blockSize}],vt=[H,b,T/ce],Ft=st.convertShape(r[1].dims).slice();Ft.splice(-1,1,v/_e),et.push(...Ct(vt)),et.push(...Ct(Ft)),et.push(...Ct(r[2].dims)),r.length===4&&et.push(...Ct(st.convertShape(r[3].dims)));let Lt=[H,b,E/xe];et.push(...Ct(Lt));let pr=ar=>{let nr=vt.length,yr=gt("a",r[0].dataType,nr,ce),qr=gt("b",12,Ft.length,_e),Sr=gt("scales",r[2].dataType,r[2].dims.length),jr=[yr,qr,Sr],It=r.length===4?gt("zero_points",12,r[3].dims.length):void 0;It&&jr.push(It);let tr=Lt.length,er=Vt("output",r[0].dataType,tr,xe),pt=[{name:"output_size",type:"u32"},{name:"block_size",type:"u32"}],zt=Tr(r[0].dataType),ir=(()=>{switch(ce){case 1:return`array<${zt}, 8>`;case 2:return`mat4x2<${zt}>`;case 4:return`mat2x4<${zt}>`;default:throw new Error(`${ce}-component is not supported.`)}})(),Hr=`
        for (var word: u32 = 0; word < ${v}; word += ${_e}) {
          ${qr.indicesSet("b_indices","2","word")};
          let b_data = ${qr.getByIndices("b_indices")};
          for (var i: u32 = 0; i < ${_e}; i++) {
            let b_value: u32 = ${_e===1?"b_data":"b_data[word + i]"};
            let b_mask: u32 = 0x0F0F0F0Fu;
            let b_value_lower: vec4<u32> = unpack4xU8(b_value & b_mask);
            let b_value_upper: vec4<u32> = unpack4xU8((b_value >> 4) & b_mask);
            let b_quantized_values = ${ir}(${Array.from({length:4},(xn,Yn)=>`${zt}(b_value_lower[${Yn}]), ${zt}(b_value_upper[${Yn}])`).join(", ")});
            let b_dequantized_values = ${ce===1?`${ir}(${Array.from({length:8},(xn,Yn)=>`(b_quantized_values[${Yn}] - zero_point) * scale`).join(", ")});`:`(b_quantized_values - ${ir}(${Array(8).fill("zero_point").join(",")})) * scale;`};
            // Number of B elements per 32-bit word is 32/bits = 32/4 = 8
            for (var m: u32 = 0; m < ${Fe?b:re}u; m++) {
              ${yr.indicesSet("a_indices",nr-2,Fe?"m":`row * ${re} + m`)};
              ${yr.indicesSet("a_indices",nr-1,"word_offset")};
              var input_offset = ${yr.indicesToOffset("a_indices")};
              var a_data: ${ir};
              for (var j: u32 = 0; j < ${8/ce}; j++) {
                a_data[j] = ${yr.getByOffset("input_offset")};
                input_offset++;
              }
              ${Fe?"workgroup_shared[workgroup_shared_offset + m]":"output_values[m]"}${xe>1?"[c]":""} += ${Array.from({length:8/ce},(xn,Yn)=>`${ce===1?`a_data[${Yn}] * b_dequantized_values[${Yn}]`:`dot(a_data[${Yn}], b_dequantized_values[${Yn}])`}`).join(" + ")};
            }
            word_offset += ${8/ce};
          }
        }`,un=It?`
          zero_point_offset += 4;
          if (zero_point_offset == 32) {
            zero_point_offset = 0;
            zero_point_index++;
            zero_point_word = ${It.getByOffset("zero_point_index")};
          }`:"";return Fe?`
        var<workgroup> workgroup_shared: array<${er.type.value}, ${b*d}>;
        ${ar.declareVariables(...jr,er)}
        ${ar.mainStart([d,1,1])}
          var a_indices: ${yr.type.indices};
          var block = local_id.x;
          var col = workgroup_id.y;
          var batch = workgroup_id.z;
          ${yr.indicesSet("a_indices","0","batch")};
          // Two zero points are packed into one byte when uniforms.bits is 4.
          for (var c: u32 = 0; c < ${xe}; c++) {
            let col_times_components_plus_c = col * ${xe} + c;
              ${It?`
            var zero_point_bytes_per_col: u32 = (${d} + 1) / 2;
            var zero_point_byte_count: u32 = col_times_components_plus_c * zero_point_bytes_per_col + (block >> 0x1u);
            var zero_point_word_index: u32 = zero_point_byte_count >> 0x2u;
            var zero_point_byte_offset: u32 = zero_point_byte_count & 0x3u;
            var zero_point_nibble_offset: u32 = block & 0x1u;
            var zero_point_bits_offset: u32 = (zero_point_byte_offset << 3) + (zero_point_nibble_offset << 2);
            var zero_point_word: u32 = ${It.getByOffset("zero_point_word_index")} >> zero_point_bits_offset;`:""}
            var b_indices: ${qr.type.indices};
            ${qr.indicesSet("b_indices","0","col_times_components_plus_c")};
            // The scale and zero points are computed per block.
            var scales_index = col_times_components_plus_c * ${d} + block;
            let scale = ${Sr.getByOffset("scales_index")};
            // The default zero point is 8 for unsigned 4-bit quantization.
            let zero_point = ${zt}(${It?"(zero_point_word) & 0xFu":8});
            ${qr.indicesSet("b_indices","1","block")};
            var word_offset: u32 = block * ${i.blockSize/ce};
            var workgroup_shared_offset: u32 = block * ${b};
            ${Hr}
          }
          workgroupBarrier();
          var output_indices: ${er.type.indices};
          var elements_per_thread: u32 = ${Math.ceil(b/d)};
          ${er.indicesSet("output_indices","0","batch")};
          ${er.indicesSet("output_indices",tr-1,"col")};
          ${er.indicesSet("output_indices",tr-2,"local_id.x * elements_per_thread")};
          var output_offset = ${er.indicesToOffset("output_indices")};
          for (var m: u32 = 0u; m < elements_per_thread; m++) {
            var row = m + local_id.x * elements_per_thread;
            if (row < ${b}) {
              var output_value: ${er.type.value} = ${er.type.value}(0);
              var workgroup_shared_offset: u32 = row;
              for (var b: u32 = 0u; b < ${d}u; b++) {
                output_value += workgroup_shared[workgroup_shared_offset];
                workgroup_shared_offset += ${b};
              }
              ${er.setByOffset("output_offset","output_value")};
              output_offset += ${E/xe};
            }
          }
        }`:`
        ${ar.registerUniforms(pt).declareVariables(...jr,er)}
        ${ar.mainStart()}
          ${ar.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
          var output_values: array<${er.type.value}, ${re}>;
          var output_indices = ${er.offsetToIndices("global_idx")};
          var col = ${er.indicesGet("output_indices",tr-1)};
          var row = ${er.indicesGet("output_indices",tr-2)};
          var a_indices: ${yr.type.indices} = output_indices;
          // Two zero points are packed into one byte because uniforms.bits <= 4.
          // zero_point_offset is either 0 or 4. It is bit offset within one byte.
          // TODO support zero_point_offset for bits > 4
          ${It?`
          var zero_point_abs_offset = col * ${xe} * ((${d} + 1) / 2);
          var zero_point_index: u32 = zero_point_abs_offset / 4;
          var zero_point_word: u32 = ${It.getByOffset("zero_point_index")};
          var zero_point_offset: u32 = (zero_point_abs_offset % 4) * 8;`:""}
          var scale_index = col * ${d*xe};
          var b_indices: ${qr.type.indices};
          for (var c: u32 = 0; c < ${xe}; c++) {
            ${qr.indicesSet("b_indices","0",`col * ${xe} + c`)};
            var block_offset: u32 = 0;
            for (var block: u32 = 0; block < ${d}; block++) {
              // The scale and zero points are computed per block.
              let scale = ${Sr.getByOffset("scale_index")};
              // The default zero point is 8 for unsigned 4-bit quantization.
              let zero_point = ${zt}(${It?"extractBits(zero_point_word, zero_point_offset, 4)":8});
              ${qr.indicesSet("b_indices","1","block")};
              var word_offset: u32 = block_offset;
              ${Hr}
              scale_index++;
              ${un}
              block_offset += uniforms.block_size / ${ce};
            }
            // Drop the trailing 4 bits if the zero_poit_offset is not a byte boundary to align with the next byte.
            ${It?`if (zero_point_offset % 8 > 0) {
                ${un}
              }`:""}
            }
            for (var k: u32 = 0u; k < ${re}u; k++) {
              ${er.indicesSet("output_indices",tr-2,`${re} * row + k`)};
              ${er.setByIndices("output_indices","output_values[k]")}
            }
        }`};return{name:Fe?"BlockwiseMatMulNBits":"MatMulNBits",shaderCache:{hint:`${i.cacheKey};${b};${ne};${r.length}`,inputDependencies:Array(r.length).fill("rank")},getRunData:()=>({outputs:[{dims:Ie,dataType:ne}],name:Fe?"BlockwiseMatMulNBits":"MatMulNBits",dispatchGroup:Fe?{x:1,y:Math.ceil(E/xe),z:H}:{x:Math.ceil(ct/64)},programUniforms:et}),getShaderSource:pr}},xp=(r,i)=>{wn(r.inputs,i);let s=r.getMaxComputeWorkgroupSizes(),u=r.getMaxComputeWorkgroupStoragesize();r.compute(Ji(r.inputs,i,s,u))},ef=r=>Gt(r)}),V,G,ie,Ee,Ze,it,_t,Et,Wt,cr=h(()=>{Xt(),Yt(),or(),V=r=>{if(!r||r.length<1)throw new Error("Too few inputs");if(r[0].dataType!==1&&r[0].dataType!==10)throw new Error("Input type must be float or float16.");if(r.length>=2){let i=r[0].dims.length*2===r[1].dims[0];if(r.length===4&&(i=r[3].dims[0]*2===r[1].dims[0]),!i)throw new Error("The pads should be a 1D tensor of shape [2 * input_rank] or [2 * num_axes].")}},G=(r,i,s)=>{let u="";for(let c=i-1;c>=0;--c)u+=`
            k = i32(${r.indicesGet("indices",c)}) - ${Dt("uniforms.pads",c,s)};
            if (k < 0) {
              break;
            }
            if (k >= i32(${Dt("uniforms.x_shape",c,i)})) {
              break;
            }
            offset += k * i32(${Dt("uniforms.x_strides",c,i)});
        `;return`
          value = ${r.type.value}(uniforms.constant_value);
          for (var i = 0; i < 1; i++) {
            var offset = 0;
            var k = 0;
            ${u}
            value = x[offset];
          }
      `},ie=(r,i,s)=>{let u="";for(let c=i-1;c>=0;--c)u+=`
                k = i32(${r.indicesGet("indices",c)}) - ${Dt("uniforms.pads",c,s)};
                if (k < 0) {
                  k = -k;
                }
                {
                  let _2n_1 = 2 * (i32(${Dt("uniforms.x_shape",c,i)}) - 1);
                  k = k % _2n_1;
                  if(k >= i32(${Dt("uniforms.x_shape",c,i)})) {
                    k = _2n_1 - k;
                  }
                }
                offset += k * i32(${Dt("uniforms.x_strides",c,i)});
            `;return`
              var offset = 0;
              var k = 0;
              ${u}
              value = x[offset];
          `},Ee=(r,i,s)=>{let u="";for(let c=i-1;c>=0;--c)u+=`
                k = i32(${r.indicesGet("indices",c)}) - ${Dt("uniforms.pads",c,s)};
                if (k < 0) {
                  k = 0;
                }
                if (k >= i32(${Dt("uniforms.x_shape",c,i)})) {
                  k = i32(${Dt("uniforms.x_shape",c,i)}) - 1;
                }
                offset += k * i32(${Dt("uniforms.x_strides",c,i)});
            `;return`
              var offset = 0;
              var k = 0;
              ${u}
              value = x[offset];
          `},Ze=(r,i,s)=>{let u="";for(let c=i-1;c>=0;--c)u+=`
                k = i32(${r.indicesGet("indices",c)}) - ${Dt("uniforms.pads",c,s)};
                if (k < 0)  {
                  k += i32(${Dt("uniforms.x_shape",c,i)}]);
                }
                if (k >= i32(${Dt("uniforms.x_shape",c,i)})) {
                  k -= i32(${Dt("uniforms.x_shape",c,i)});
                }
                offset += k * i32(${Dt("uniforms.x_strides",c,i)});
            `;return`
              var offset = 0;
              var k = 0;
              ${u}
              value = x[offset];
          `},it=(r,i,s)=>{switch(s.mode){case 0:return G(r,i,s.pads.length);case 1:return ie(r,i,s.pads.length);case 2:return Ee(r,i,s.pads.length);case 3:return Ze(r,i,s.pads.length);default:throw new Error("Invalid mode")}},_t=(r,i)=>{let s=st.padShape(r[0].dims.slice(),i.pads),u=r[0].dims,c=st.size(s),p=[{type:12,data:c},{type:6,data:i.pads}];i.mode===0&&p.push({type:r[0].dataType,data:i.value}),p.push(...Ct(r[0].dims,s));let d=["rank"],b=T=>{let E=Vt("output",r[0].dataType,s.length),q=gt("x",r[0].dataType,u.length),H=q.type.value,v=it(E,u.length,i),ne=[{name:"output_size",type:"u32"},{name:"pads",type:"i32",length:i.pads.length}];return i.mode===0&&ne.push({name:"constant_value",type:H}),`
            ${T.registerUniforms(ne).declareVariables(q,E)}
            ${T.mainStart()}
            ${T.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}

            let indices = ${E.offsetToIndices("global_idx")};

            var value = ${H}(0);
            ${v}
            output[global_idx] = value;
        }`};return{name:"Pad",shaderCache:{hint:`${i.mode}`,inputDependencies:d},getRunData:()=>({outputs:[{dims:s,dataType:r[0].dataType}],dispatchGroup:{x:Math.ceil(st.size(s)/64)},programUniforms:p}),getShaderSource:b}},Et=(r,i)=>{if(r.length>1){let s=r[1].getBigInt64Array(),u=r.length>=3&&r[2].data?r[2].getFloat32Array()[0]:0,c=r[0].dims.length,p=new Int32Array(2*c).fill(0);if(r.length>=4){let b=r[3].getBigInt64Array();for(let T=0;T<b.length;T++)p[Number(b[T])]=Number(s[T]),p[Number(b[T])+c]=Number(s[T+b.length])}else s.forEach((b,T)=>p[Number(T)]=Number(b));let d=[];return p.forEach(b=>d.push(b)),{mode:i.mode,value:u,pads:d}}else return i},Wt=(r,i)=>{V(r.inputs);let s=Et(r.inputs,i);r.compute(_t(r.inputs,s),{inputs:[0]})}}),sr,$r,dr,_r,fr,gr,br,Dr,En,An,Ei,vn,ln,bn,Ws,Gs,Ml,gm,pi,Yo=h(()=>{Z(),Xt(),Yt(),or(),sr=r=>{if(D.webgpu.validateInputContent&&(!r||r.length!==1))throw new Error("Pool ops requires 1 input.")},$r=(r,i,s)=>{let u=i.format==="NHWC",c=r.dims.slice();u&&c.splice(1,0,c.pop());let p=Object.hasOwnProperty.call(i,"dilations"),d=i.kernelShape.slice(),b=i.strides.slice(),T=p?i.dilations.slice():[],E=i.pads.slice();qn.adjustPoolAttributes(s,c,d,b,T,E);let q=qn.computePoolOutputShape(s,c,b,T,d,E,i.autoPad),H=Object.assign({},i);p?Object.assign(H,{kernelShape:d,strides:b,pads:E,dilations:T,cacheKey:i.cacheKey}):Object.assign(H,{kernelShape:d,strides:b,pads:E,cacheKey:i.cacheKey});let v=q.slice();return v.push(v.splice(1,1)[0]),[H,u?v:q]},dr=(r,i)=>{let s=i.format==="NHWC",u=st.size(r),c=st.size(i.kernelShape),p=[{type:12,data:u},{type:12,data:c}],d=[{name:"outputSize",type:"u32"},{name:"kernelSize",type:"u32"}];if(i.kernelShape.length<=2){let b=i.kernelShape[i.kernelShape.length-1],T=i.strides[i.strides.length-1],E=i.pads[i.pads.length/2-1],q=i.pads[i.pads.length-1],H=!!(E+q);p.push({type:12,data:b},{type:12,data:T},{type:12,data:E},{type:12,data:q}),d.push({name:"kw",type:"u32"},{name:"sw",type:"u32"},{name:"pwStart",type:"u32"},{name:"pwEnd",type:"u32"});let v=!1;if(i.kernelShape.length===2){let ne=i.kernelShape[i.kernelShape.length-2],re=i.strides[i.strides.length-2],ce=i.pads[i.pads.length/2-2],_e=i.pads[i.pads.length-2];v=!!(ce+_e),p.push({type:12,data:ne},{type:12,data:re},{type:12,data:ce},{type:12,data:_e}),d.push({name:"kh",type:"u32"},{name:"sh",type:"u32"},{name:"phStart",type:"u32"},{name:"phEnd",type:"u32"})}return[p,d,!0,H,v]}else{if(s)throw new Error("Pooling with kernelShape.length > 2 is not supported for NHWC format.");let b=st.computeStrides(i.kernelShape);p.push({type:12,data:b},{type:12,data:i.pads},{type:12,data:i.strides}),d.push({name:"kernelStrides",type:"u32",length:b.length},{name:"pads",type:"u32",length:i.pads.length},{name:"strides",type:"u32",length:i.strides.length});let T=i.pads.reduce((E,q)=>E+q);return[p,d,!!T,!1,!1]}},_r=(r,i,s,u,c,p,d,b,T,E,q,H)=>{let v=c.format==="NHWC",ne=i.type.value,re=Vt("output",i.type.tensor,u);if(c.kernelShape.length<=2){let ce="",_e="",be="",he=s-(v?2:1);if(q?ce=`
                for (var i: u32 = 0u; i < uniforms.kw; i++) {
                  xIndices[${he}] = indices[${he}] * uniforms.sw - uniforms.pwStart + i;
                  if (xIndices[${he}] < 0 || xIndices[${he}]
                      >= uniforms.x_shape[${he}]) {
                    pad++;
                    continue;
                  }
                  let x_val = x[${i.indicesToOffset("xIndices")}];
                  ${p}
                }`:ce=`
                for (var i: u32 = 0u; i < uniforms.kw; i++) {
                  xIndices[${he}] = indices[${he}] * uniforms.sw - uniforms.pwStart + i;
                  let x_val = x[${i.indicesToOffset("xIndices")}];
                  ${p}
                }`,c.kernelShape.length===2){let Fe=s-(v?3:2);H?_e=`
                for (var j: u32 = 0u; j < uniforms.kh; j++) {
                  xIndices[${Fe}] = indices[${Fe}] * uniforms.sh - uniforms.phStart + j;
                  if (xIndices[${Fe}] < 0 || xIndices[${Fe}] >= uniforms.x_shape[${Fe}]) {
                    pad += i32(uniforms.kw);
                    continue;
                  }
              `:_e=`
                for (var j: u32 = 0u; j < uniforms.kh; j++) {
                  xIndices[${Fe}] = indices[${Fe}] * uniforms.sh - uniforms.phStart + j;
                `,be=`
              }
            `}return`
            ${r.registerUniforms(T).declareVariables(i,re)}

            ${r.mainStart()}
              ${r.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}

              let indices = ${re.offsetToIndices("global_idx")};
              var xIndices = ${re.offsetToIndices("global_idx")};

              var value = ${ne}(${b});
              var pad = 0;
              ${_e}
              ${ce}
              ${be}
              ${d}

              output[global_idx] = value;
            }`}else{if(v)throw new Error("Pooling with kernelShape.length > 2 is not supported for NHWC format.");let ce=c.kernelShape.length,_e=c.pads.length,be="";return E?be=`
                if (xIndices[j] >= uniforms.x_shape[j]) {
                  pad++;
                  isPad = true;
                  break;
                }
              }
              if (!isPad) {
                let x_val = x[${i.indicesToOffset("xIndices")}];
                ${p}
              }`:be=`
              }
              let x_val = x[${i.indicesToOffset("xIndices")}];
              ${p}
            `,`
            ${r.registerUniforms(T).declareVariables(i,re)}

            ${r.mainStart()}
              ${r.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}
              let indices = ${re.offsetToIndices("global_idx")};
              var xIndices = ${re.offsetToIndices("global_idx")};

              var offsets: array<u32, ${ce}>;

              var value = ${ne}(${b});
              var pad = 0;
              var isPad = false;

              for (var i: u32 = 0u; i < uniforms.kernelSize; i++) {
                var offset = i;
                for (var j = 0u; j < ${ce-1}u; j++) {
                  offsets[j] = offset / ${Dt("uniforms.kernelStrides","j",ce)};
                  offset -= offsets[j] * ${Dt("uniforms.kernelStrides","j",ce)};
                }
                offsets[${ce-1}] = offset;

                isPad = false;
                for (var j = ${s-ce}u; j < ${s}u; j++) {
                  xIndices[j] = indices[j] * ${Dt("uniforms.strides",`j - ${s-ce}u`,ce)}
                    + offsets[j - ${s-ce}u] - ${Dt("uniforms.pads","j - 2u",_e)};
                  ${be}
              }
              ${d}

              output[global_idx] = value;
            }`}},fr=r=>`${r.format};${r.ceilMode};${r.autoPad};${r.kernelShape.length}`,gr=r=>`${fr(r)};${r.countIncludePad}`,br=r=>`${fr(r)};${r.storageOrder};${r.dilations}`,Dr=r=>({format:r.format,autoPad:["NOTSET","VALID","SAME_UPPER","SAME_LOWER"][r.auto_pad],ceilMode:r.ceil_mode,kernelShape:r.kernel_shape,strides:r.strides,pads:r.pads}),En=(r,i,s,u)=>{let[c,p]=$r(i,u,s),d=gt("x",i.dataType,i.dims.length),b=d.type.value,T="value += x_val;",E="";c.countIncludePad?E+=`value /= ${b}(uniforms.kernelSize);`:E+=`value /= ${b}(i32(uniforms.kernelSize) - pad);`;let[q,H,v,ne,re]=dr(p,c);q.push(...Ct(i.dims,p));let ce=["rank"];return{name:r,shaderCache:{hint:`${u.cacheKey};${v};${ne};${re}`,inputDependencies:ce},getRunData:()=>({outputs:[{dims:p,dataType:i.dataType}],dispatchGroup:{x:Math.ceil(st.size(p)/64)},programUniforms:q}),getShaderSource:_e=>_r(_e,d,i.dims.length,p.length,c,T,E,0,H,v,ne,re)}},An=r=>{let i=r.count_include_pad!==0,s=Dr(r);if(s.ceilMode!==0)throw new Error("using ceil() in shape computation is not yet supported for AveragePool");let u={countIncludePad:i,...s,cacheKey:""};return{...u,cacheKey:gr(u)}},Ei=(r,i)=>{sr(r.inputs),r.compute(En("AveragePool",r.inputs[0],!1,i))},vn={autoPad:"",ceilMode:0,countIncludePad:!1,kernelShape:[],strides:[],pads:[],storageOrder:0,dilations:[]},ln=r=>{let i=r.format;return{format:i,...vn,cacheKey:i}},bn=(r,i)=>{sr(r.inputs),r.compute(En("GlobalAveragePool",r.inputs[0],!0,i))},Ws=(r,i,s,u)=>{let[c,p]=$r(i,u,s),d=`
      value = max(x_val, value);
    `,b="",T=gt("x",i.dataType,i.dims.length),E=["rank"],[q,H,v,ne,re]=dr(p,c);return q.push(...Ct(i.dims,p)),{name:r,shaderCache:{hint:`${u.cacheKey};${v};${ne};${re}`,inputDependencies:E},getRunData:()=>({outputs:[{dims:p,dataType:i.dataType}],dispatchGroup:{x:Math.ceil(st.size(p)/64)},programUniforms:q}),getShaderSource:ce=>_r(ce,T,i.dims.length,p.length,c,d,b,i.dataType===10?-65504:-1e5,H,v,ne,re)}},Gs=(r,i)=>{sr(r.inputs),r.compute(Ws("MaxPool",r.inputs[0],!1,i))},Ml=r=>{let i=r.storage_order,s=r.dilations,u=Dr(r);if(i!==0)throw new Error("column major storage order is not yet supported for MaxPool");if(u.ceilMode!==0)throw new Error("using ceil() in shape computation is not yet supported for MaxPool");let c={storageOrder:i,dilations:s,...u,cacheKey:""};return{...c,cacheKey:br(c)}},gm=r=>{let i=r.format;return{format:i,...vn,cacheKey:i}},pi=(r,i)=>{sr(r.inputs),r.compute(Ws("GlobalMaxPool",r.inputs[0],!0,i))}}),Tp,kp,Sp,tf,J2=h(()=>{Xt(),Yt(),mr(),or(),Tp=(r,i)=>{if(r.length<2||r.length>3)throw new Error("DequantizeLinear requires 2 or 3 inputs.");if(r.length===3&&r[1].dims===r[2].dims)throw new Error("x-scale and x-zero-point must have the same shape.");if(r.length===3&&r[0].dataType!==r[2].dataType)throw new Error("x and x-zero-point must have the same data type.");if(r[0].dataType===6&&r.length>2)throw new Error("In the case of dequantizing int32 there is no zero point.");if(r[1].dims.length!==0&&r[1].dims.length!==1&&r[1].dims.length!==r[0].dims.length)throw new Error("scale input must be a scalar, a 1D tensor, or have the same rank as the input tensor.");if(r.length>2){if(r[0].dataType!==r[2].dataType)throw new Error("x and x-zero-point must have the same data type.");if(r[1].dims.length!==r[2].dims.length)throw new Error("scale and zero-point inputs must have the same rank.");if(!r[1].dims.map((s,u)=>s===r[2].dims[u]).reduce((s,u)=>s&&u,!0))throw new Error("scale and zero-point inputs must have the same shape.")}if(i.blockSize>0){if(r[1].dims.length===0||r[1].dims.length===1&&r[1].dims[0]===1)throw new Error("blockSize must be set only for block quantization.");if(!r[1].dims.map((c,p)=>p===i.axis||c===r[0].dims[p]).reduce((c,p)=>c&&p,!0))throw new Error("For block qunatization, scale input shape to match the input shape except for the axis");if(r[1].dims.length!==r[0].dims.length)throw new Error("For block qunatization the scale input rank must be the same as the x rank.");let s=r[0].dims[i.axis],u=r[1].dims[i.axis];if(i.blockSize<Math.ceil(s/u)||i.blockSize>Math.ceil(s/(u-1)-1))throw new Error("blockSize must be with in the range [ceil(dI / Si), ceil(dI / (Si - 1) - 1)].")}},kp=(r,i)=>{let s=st.normalizeAxis(i.axis,r[0].dims.length),u=r[0].dataType,c=u===3,p=r[0].dims,d=r[1].dataType,b=st.size(p),T=u===3||u===2,E=T?[Math.ceil(st.size(r[0].dims)/4)]:r[0].dims,q=r[1].dims,H=r.length>2?r[2]:void 0,v=H?T?[Math.ceil(st.size(H.dims)/4)]:H.dims:void 0,ne=q.length===0||q.length===1&&q[0]===1,re=ne===!1&&q.length===1,ce=wr(b),_e=ne&&(!T||ce===4),be=_e?ce:1,he=_e&&!T?ce:1,Fe=gt("input",T?12:u,E.length,he),xe=gt("scale",d,q.length),Ie=H?gt("zero_point",T?12:u,v.length):void 0,ct=Vt("output",d,p.length,be),et=[Fe,xe];Ie&&et.push(Ie);let vt=[E,q];H&&vt.push(v);let Ft=[{type:12,data:b/be},{type:12,data:s},{type:12,data:i.blockSize},...Ct(...vt,p)],Lt=pr=>{let ar=[{name:"output_size",type:"u32"},{name:"axis",type:"u32"},{name:"block_size",type:"u32"}];return`
      ${pr.registerUniforms(ar).declareVariables(...et,ct)}
      ${pr.mainStart()}
          ${pr.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
          let output_indices = ${ct.offsetToIndices("global_idx")};

          // Set input x
          ${T?`
            let input = ${Fe.getByOffset("global_idx / 4")};
            let x_vec = ${c?"unpack4xI8(input)":"unpack4xU8(input)"};
            let x_value = ${be===1?"x_vec[global_idx % 4]":"x_vec"};`:`let x_value = ${Fe.getByOffset("global_idx")};`};

          // Set scale input
          ${ne?`let scale_value= ${xe.getByOffset("0")}`:re?`
            let scale_index = ${ct.indicesGet("output_indices","uniforms.axis")};
            let scale_value= ${xe.getByOffset("scale_index")};`:`
            var scale_indices: ${xe.type.indices} = output_indices;
            let index = ${xe.indicesGet("scale_indices","uniforms.axis")} / uniforms.block_size;
            ${xe.indicesSet("scale_indices","uniforms.axis","index")};
            let scale_value= ${xe.getByIndices("scale_indices")};`};

          // Set zero-point input
          ${Ie?ne?T?`
                let zero_point_input = ${Ie.getByOffset("0")};
                let zero_point_vec =  ${c?"unpack4xI8(zero_point_input)":"unpack4xU8(zero_point_input)"};
                let zero_point_value= zero_point_vec[0]`:`let zero_point_value = ${Ie.getByOffset("0")}`:re?T?`
                let zero_point_index = ${ct.indicesGet("output_indices","uniforms.axis")};
                let zero_point_input = ${Ie.getByOffset("zero_point_index / 4")};
                let zero_point_vec =  ${c?"unpack4xI8(zero_point_input)":"unpack4xU8(zero_point_input)"};
                let zero_point_value = zero_point_vec[zero_point_index % 4]`:`
                let zero_point_index = ${ct.indicesGet("output_indices","uniforms.axis")};
                let zero_point_value = ${Ie.getByOffset("zero_point_index")};`:T?`
                let zero_point_offset = ${xe.indicesToOffset("scale_indices")};
                let zero_point_input = ${Ie.getByOffset("zero_point_offset / 4")};
                let zero_point_vec = ${c?"unpack4xI8(zero_point_input)":"unpack4xU8(zero_point_input)"};
                let zero_point_value = zero_point_vec[zero_point_offset % 4];`:`let zero_point_value = ${Ie.getByIndices("scale_indices")};`:`let zero_point_value = ${T?c?"i32":"u32":Fe.type.value}(0);`};
      // Compute and write output
      ${ct.setByOffset("global_idx",`${ct.type.value}(x_value - zero_point_value) * scale_value`)};
      }`};return{name:"DequantizeLinear",shaderCache:{hint:i.cacheKey,inputDependencies:Ie?["rank","rank","rank"]:["rank","rank"]},getShaderSource:Lt,getRunData:()=>({outputs:[{dims:p,dataType:d}],dispatchGroup:{x:Math.ceil(b/be/64),y:1,z:1},programUniforms:Ft})}},Sp=(r,i)=>{Tp(r.inputs,i),r.compute(kp(r.inputs,i))},tf=r=>Gt({axis:r.axis,blockSize:r.blockSize})}),_0,y0,w0,ex=h(()=>{Z(),Xt(),or(),_0=(r,i,s)=>{let u=r===i,c=r<i&&s<0,p=r>i&&s>0;if(u||c||p)throw new Error("Range these inputs' contents are invalid.")},y0=(r,i,s,u)=>{let c=Math.abs(Math.ceil((i-r)/s)),p=[c],d=c,b=[{type:12,data:d},{type:u,data:r},{type:u,data:s},...Ct(p)],T=E=>{let q=Vt("output",u,p.length),H=q.type.value,v=[{name:"outputSize",type:"u32"},{name:"start",type:H},{name:"delta",type:H}];return`
        ${E.registerUniforms(v).declareVariables(q)}
        ${E.mainStart()}
        ${E.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}
        output[global_idx] = uniforms.start + ${H}(global_idx) * uniforms.delta;
      }`};return{name:"Range",shaderCache:{hint:`${u}`},getShaderSource:T,getRunData:()=>({outputs:[{dims:p,dataType:u}],dispatchGroup:{x:Math.ceil(d/64)},programUniforms:b})}},w0=r=>{let i=0,s=0,u=0;r.inputs[0].dataType===6?(i=r.inputs[0].getInt32Array()[0],s=r.inputs[1].getInt32Array()[0],u=r.inputs[2].getInt32Array()[0]):r.inputs[0].dataType===1&&(i=r.inputs[0].getFloat32Array()[0],s=r.inputs[1].getFloat32Array()[0],u=r.inputs[2].getFloat32Array()[0]),D.webgpu.validateInputContent&&_0(i,s,u),r.compute(y0(i,s,u,r.inputs[0].dataType),{inputs:[]})}}),v0,b0,x0,M0,T0,k0,S0,E0,C0,P0,$0,_m,A0,I0,F0,z0,O0,D0,L0,tx=h(()=>{Xt(),Yt(),mr(),or(),v0=(r,i)=>{if(r.every(s=>s>0||(()=>{throw new Error("Resize requires scales input values to be positive")})),r.length>0){if(i.mode==="linear"){if(!(r.length===2||r.length===3||r.length===4&&r[0]===1&&r[1]===1||r.length===4&&r[0]===1&&r[3]===1||r.length===5&&r[0]===1&&r[1]===1))throw new Error(`For linear mode, Resize requires scales to be 2D, 3D, 4D with either two outermost or one innermost and
            one outermost scale values equal to 1, or 5D with two outermost scale values equal to 1`)}else if(i.mode==="cubic"&&!(r.length===2||r.length===4&&r[0]===1&&r[1]===1||r.length===4&&r[0]===1&&r[3]===1))throw new Error("Resize requires scales input size to be 2 or 4 for cubic mode")}},b0=(r,i,s)=>{i.every(c=>c>=0&&c<s||(()=>{throw new Error("Resize requires axes input values to be positive and less than rank")}));let u=new Array(s).fill(1);return i.forEach((c,p)=>u[c]=r[p]),u},x0=(r,i,s,u,c,p)=>{let[d,b,T]=s>10?[1,2,3]:[-1,r.length>1?1:-1,-1],E=r[0].dims.length;if(d>0&&r.length>d&&r[d].dims.length>0)r[d].getFloat32Array().forEach(q=>p.push(q));else if(i.coordinateTransformMode==="tf_crop_and_resize")throw new Error("Resize requires RoI input to be specified when coordinateTransformMode is tfCropAndResize");if(b>0&&r.length>b&&r[b].dims.length>0){if(r[b].getFloat32Array().forEach(q=>u.push(q)),u.length!==0&&u.length!==E&&s>=18&&u.length!==i.axes.length)throw new Error("Resize requires scales input size to be same as input rank or axes size for opset 18 and up");v0(u,i),i.axes.length>0&&b0(u,i.axes,E).forEach((q,H)=>u[H]=q)}if(T>0&&r.length>T&&(r[T].getBigInt64Array().forEach(q=>c.push(Number(q))),c.length!==E||s>=18&&c.length===i.axes.length))throw new Error("Resize requires sizes input size to be same as input rank or axes size for opset 18 and up");if(i.axes.length>0){if(u.length!==i.axes.length)throw new Error('Resize requires "scales" input size to be of axes rank when axes attributes is specified');if(c.length!==i.axes.length)throw new Error('Resize requires "sizes" input size to be of rank axes rank when axes attributes is specified')}if(typeof u<"u"&&typeof c<"u"&&u.length>0&&c.length>E)throw new Error("Resize requires only of scales or sizes to be specified")},M0=(r,i)=>`fn getOriginalCoordinateFromResizedCoordinate(xResized: u32, xScale: f32, lengthResized: u32,
     lengthOriginal: u32, roiStart: f32, roiEnd: f32) -> ${i} { `+(()=>{switch(r){case"asymmetric":return`return ${i}(xResized) / ${i}(xScale);`;case"pytorch_half_pixel":return`if (lengthResized > 1) {
                    return (${i}(xResized) + 0.5) / ${i}(xScale) - 0.5;
                  } else {
                    return 0.0;
                  }`;case"tf_half_pixel_for_nn":return`return (${i}(xResized) + 0.5) / ${i}(xScale);`;case"align_corners":return`if (lengthResized == 1) {
                    return 0.0;
                  } else {
                    // The whole part and the fractional part are calculated separately due to inaccuracy of floating
                    // point division. As an example, f32(21) / f32(7) may evaluate to 2.99... instead of 3, causing an
                    // offset-by-one error later in floor().
                    let whole = ${i}(xResized * (lengthOriginal - 1) / (lengthResized - 1));
                    let fract =
                        ${i}(xResized * (lengthOriginal - 1) % (lengthResized - 1)) / ${i}(lengthResized - 1);
                    return whole + fract;
                  }`;case"tf_crop_and_resize":return`if (lengthResized > 1) {
                    return ${i}(roiStart) * ${i}(lengthOriginal - 1) +
                        (${i}(xResized) * ${i}(roiEnd - roiStart) * ${i}(lengthOriginal - 1)) /
                        ${i}(lengthResized - 1);
                  } else {
                    return 0.5 * ${i}(roiStart + roiEnd) * ${i}(lengthOriginal - 1);
                  }`;case"half_pixel_symmetric":return`const outputWidth = ${i}xScale * ${i}(lengthResized);
                  const adjustment = ${i}(lengthResized) / outputWidth;
                  const center = ${i}(lengthOriginal) / 2;
                  const offset = center * (1 - adjustment);
                  return offset + ((${i}(xResized) + 0.5) / ${i}(xScale)) - 0.5;`;case"half_pixel":return`return ((${i}(xResized) + 0.5) / ${i}(xScale)) - 0.5;`;default:throw new Error(`Coordinate transform mode ${r} is not supported`)}})()+"}",T0=(r,i,s)=>`fn getNearestPixelFromOriginal(xOriginal: ${s}, isDownSample: bool) -> ${s} {`+(()=>{switch(r){case"round_prefer_ceil":return"if (fract(xOriginal) == 0.5) {             return ceil(xOriginal);           } else {             return round(xOriginal);           }";case"floor":return"return floor(xOriginal);";case"ceil":return"return ceil(xOriginal);";case"round_prefer_floor":return"if (fract(xOriginal) == 0.5) {                     return floor(xOriginal);                   } else {                     return round(xOriginal);                   }";case"simple":default:if(i<11)return"if (isDownSample)                     {                       return ceil(xOriginal);                     } else {                       return xOriginal;                     }";throw new Error(`Nearest mode ${r} is not supported`)}})()+"}",k0=(r,i,s)=>{let u=new Array(s).fill(0).concat(new Array(s).fill(1)),c=r.length===0?u:r.slice();return i.length>0?(i.forEach((p,d)=>{u[p]=c[d],u[d+s]=c[i.length+d]}),u):c},S0=(r,i,s,u)=>{let c=[];if(s.length>0)if(u.length>0){if(r.forEach(p=>c.push(p)),Math.max(...u)>r.length)throw new Error("axes is out of bound");u.forEach((p,d)=>c[p]=s[d])}else s.forEach(p=>c.push(p));else{if(i.length===0)throw new Error("Resize requires either scales or sizes.");c=r.map((p,d)=>Math.round(p*i[d]))}return c},E0=(r,i,s)=>{let u=(()=>{switch(s.keepAspectRatioPolicy){case"not_larger":return s.axes.length>0?Math.min(...s.axes.map(p=>i[p]),Number.MAX_VALUE):Math.min(...i,Number.MAX_VALUE);case"not_smaller":return s.axes.length>0?Math.max(...s.axes.map(p=>i[p]),Number.MIN_VALUE):Math.max(...i,Number.MIN_VALUE);default:throw new Error(`Keep aspect ratio policy ${s.keepAspectRatioPolicy} is not supported`)}})();i.fill(1,0,i.length);let c=r.slice();return s.axes.length>0?(s.axes.forEach(p=>i[p]=u),s.axes.forEach(p=>c[p]=Math.round(r[p]*i[p]))):(i.fill(u,0,i.length),c.forEach((p,d)=>c[d]=Math.round(p*i[d]))),c},C0=(r,i,s,u,c)=>`
    fn calculateOriginalIndicesFromOutputIndices(output_indices: ${r.type.indices}) -> array<${r.type.value}, ${s.length}> {
      var original_indices: array<${r.type.value}, ${s.length}>;
      for (var i:u32 = 0; i < ${s.length}; i++) {
        var output_index = ${r.indicesGet("output_indices","i")};
        var scale = ${Dt("uniforms.scales","i",u)};
        var roi_low = ${Dt("uniforms.roi","i",c)};
        var roi_hi = ${Dt("uniforms.roi",`i + ${i.length}`,c)};
        if (scale == 1.0) {
          original_indices[i] = ${r.type.value}(output_index);
        } else {
          var input_shape_i = ${Dt("uniforms.input_shape","i",i.length)};
          var output_shape_i = ${Dt("uniforms.output_shape","i",s.length)};
          original_indices[i] = getOriginalCoordinateFromResizedCoordinate(output_index, scale, output_shape_i,
                                                                           input_shape_i, roi_low, roi_hi);
        }
      }
      return original_indices;
    }`,P0=(r,i,s,u,c,p,d)=>`
    fn calculateInputIndicesFromOutputIndices(output_indices: ${i.type.indices}) -> ${r.type.indices} {
      var input_indices: ${r.type.indices};
      for (var i:u32 = 0; i < ${u.length}; i++) {
        var output_index = ${i.indicesGet("output_indices","i")};
        var input_index: u32;
        var scale = ${Dt("uniforms.scales","i",c)};
        if (scale == 1.0) {
          input_index = output_index;
        } else {
          var roi_low = ${Dt("uniforms.roi","i",p)};
          var roi_hi = ${Dt("uniforms.roi",`i + ${s.length}`,p)};
          var input_shape_i = ${Dt("uniforms.input_shape","i",s.length)};
          var output_shape_i = ${Dt("uniforms.output_shape","i",u.length)};
          var original_idx = getOriginalCoordinateFromResizedCoordinate(output_index, scale, output_shape_i,
                                                                        input_shape_i, roi_low, roi_hi);
          if (!${d} || (original_idx >= 0 && original_idx < ${i.type.value}(input_shape_i))) {
            if (original_idx < 0) {
              input_index = 0;
            } else if (original_idx > ${i.type.value}(input_shape_i - 1)) {
              input_index = input_shape_i - 1;
            } else {
              input_index = u32(getNearestPixelFromOriginal(original_idx, scale < 1));
            }
          } else {
            input_index = u32(original_idx);
          }
        }
        ${r.indicesSet("input_indices","i"," input_index")}
      }
      return input_indices;
    }`,$0=(r,i)=>`
    fn checkInputIndices(input_indices: ${r.type.indices}) -> bool {
      for (var i:u32 = 0; i < ${i.length}; i++) {
        var input_index = ${r.indicesGet("input_indices","i")};
        if (input_index < 0 || input_index >= ${Dt("uniforms.input_shape","i",i.length)}) {
          return false;
        }
      }
      return true;
    }`,_m=(r,i,s,u)=>r.rank>u?`
    ${r.indicesSet("input_indices",i,"channel")};
    ${r.indicesSet("input_indices",s,"batch")};
`:"",A0=(r,i,s,u,c)=>{let[p,d,b,T]=s.length===2?[-1,0,1,-1]:[0,2,3,1],E=r.type.value;return`
    fn getInputValue(batch: u32, channel: u32, row: u32, col: u32) -> ${E} {
      var input_indices: ${r.type.indices};
      ${r.indicesSet("input_indices",d,`max(0, min(row, ${s[d]} - 1))`)};
      ${r.indicesSet("input_indices",b,`max(0, min(col, ${s[b]} - 1))`)};
      ${_m(r,T,p,2)}
      return ${r.getByIndices("input_indices")};
    }

    fn bilinearInterpolation(output_indices: ${i.type.indices}) -> ${E} {
      var originalIndices = calculateOriginalIndicesFromOutputIndices(output_indices);
      var row:${E} = originalIndices[${d}];
      var col:${E} = originalIndices[${b}];
      ${u?`if (row < 0 || row > (${s[d]} - 1) || col < 0 || col > (${s[b]} - 1)) {
        return ${c};
      }`:""};
      row = max(0, min(row, ${s[d]} - 1));
      col = max(0, min(col, ${s[b]} - 1));
      var row1: u32 = u32(row);
      var col1: u32 = u32(col);
      var row2: u32 = u32(row + 1);
      var col2: u32 = u32(col + 1);
      var channel: u32 = ${s.length>2?`u32(originalIndices[${T}])`:"0"};
      var batch: u32 =  ${s.length>2?`u32(originalIndices[${p}])`:"0"};
      var x11: ${E} = getInputValue(batch, channel, row1, col1);
      var x12: ${E} = getInputValue(batch, channel, row1, col2);
      var x21: ${E} = getInputValue(batch, channel, row2, col1);
      var x22: ${E} = getInputValue(batch, channel, row2, col2);
      var dx1: ${E} = abs(row - ${E}(row1));
      var dx2: ${E} = abs(${E}(row2) - row);
      var dy1: ${E} = abs(col - ${E}(col1));
      var dy2: ${E} = abs(${E}(col2) - col);
      if (row1 == row2) {
        dx1 = 0.5;
        dx2 = 0.5;
      }
      if (col1 == col2) {
        dy1 = 0.5;
        dy2 = 0.5;
      }
      return (x11 * dx2 * dy2 + x12 * dx2 * dy1 + x21 * dx1 * dy2 + x22 * dx1 * dy1);
    }`},I0=(r,i,s,u,c,p,d,b,T,E)=>{let q=s.length===2,[H,v]=q?[0,1]:[2,3],ne=r.type.value,re=ce=>{let _e=ce===H?"row":"col";return`
      fn ${_e}CubicInterpolation(input_indices: ${r.type.indices}, output_indices: ${i.type.indices}) -> ${ne} {
        var output_index = ${i.indicesGet("output_indices",ce)};
        var originalIdx: ${ne} = getOriginalCoordinateFromResizedCoordinate(output_index, ${c[ce]},
        ${u[ce]}, ${s[ce]}, ${p[ce]}, ${p[ce]} + ${s.length});
        var fractOriginalIdx: ${ne} = originalIdx - floor(originalIdx);
        var coefs = getCubicInterpolationCoefs(fractOriginalIdx);

        if (${b} && (originalIdx < 0 || originalIdx > (${s[ce]} - 1))) {
          return ${T};
        }
        var data: array<${ne}, 4> = array<${ne}, 4>(0.0, 0.0, 0.0, 0.0);
        for (var i: i32 = -1; i < 3; i++) {
          var ${_e}: ${ne} = originalIdx + ${ne}(i);
          if (${_e} < 0 || ${_e} >= ${s[ce]}) {
            ${E?`coefs[i + 1] = 0.0;
                        continue;`:b?`return ${T};`:`${_e} = max(0, min(${_e}, ${s[ce]} - 1));`};
          }
        var input_indices_copy: ${r.type.indices} = input_indices;
          ${r.indicesSet("input_indices_copy",ce,`u32(${_e})`)};
          data[i + 1] = ${ce===H?r.getByIndices("input_indices_copy"):"rowCubicInterpolation(input_indices_copy, output_indices)"};
        }
        return cubicInterpolation1D(data, coefs);
      }`};return`
    ${re(H)};
    ${re(v)};
  fn getCubicInterpolationCoefs(s: ${ne}) -> array<${ne}, 4> {
    var absS = abs(s);
    var coeffs: array<${ne}, 4> = array<${ne}, 4>(0.0, 0.0, 0.0, 0.0);
    var oneMinusAbsS: ${ne} = 1.0 - absS;
    var twoMinusAbsS: ${ne} = 2.0 - absS;
    var onePlusAbsS: ${ne} = 1.0 + absS;
    coeffs[0] = ((${d} * onePlusAbsS - 5 * ${d}) * onePlusAbsS + 8 * ${d}) * onePlusAbsS - 4 * ${d};
    coeffs[1] = ((${d} + 2) * absS - (${d} + 3)) * absS * absS + 1;
    coeffs[2] = ((${d} + 2) * oneMinusAbsS - (${d} + 3)) * oneMinusAbsS * oneMinusAbsS + 1;
    coeffs[3] = ((${d} * twoMinusAbsS - 5 * ${d}) * twoMinusAbsS + 8 * ${d}) * twoMinusAbsS - 4 * ${d};
    return coeffs;
  }

  fn cubicInterpolation1D(x: array<${ne}, 4>, coefs: array<${ne}, 4>) -> ${ne} {
    var coefsSum: ${ne} = coefs[0] + coefs[1] + coefs[2] + coefs[3];
    return (x[0] * coefs[0] + x[1] * coefs[1]+ x[2] * coefs[2]+ x[3] * coefs[3]) / coefsSum;
  }

  fn bicubicInterpolation(output_indices: ${i.type.indices}) -> ${ne} {
    var input_indices: ${r.type.indices} = output_indices;
    return colCubicInterpolation(input_indices, output_indices);
  }
    `},F0=(r,i,s,u,c)=>{let[p,d,b,T,E]=s.length===3?[-1,0,1,2,-1]:[0,2,3,4,1],q=r.type.value;return`
    fn getInputValue(batch: u32, channel: u32, depth:u32, height: u32, width: u32) -> ${q} {
      var input_indices: ${r.type.indices};
      ${r.indicesSet("input_indices",d,`max(0, min(depth, ${s[d]} - 1))`)};
      ${r.indicesSet("input_indices",b,`max(0, min(height, ${s[b]} - 1))`)};
      ${r.indicesSet("input_indices",T,`max(0, min(width, ${s[T]} - 1))`)};
      ${_m(r,E,p,3)}
      return ${r.getByIndices("input_indices")};
    }

    fn trilinearInterpolation(output_indices: ${i.type.indices}) -> ${q} {
      var originalIndices = calculateOriginalIndicesFromOutputIndices(output_indices);
      var depth:${q} = originalIndices[${d}];
      var height:${q} = originalIndices[${b}];
      var width:${q} = originalIndices[${T}];
      ${u?`if (depth < 0 || depth > (${s[d]} - 1) || height < 0 || height > (${s[b]} - 1) || width < 0 || (width > ${s[T]} - 1)) {
      return ${c};
        }`:""};

    depth = max(0, min(depth, ${s[d]} - 1));
      height = max(0, min(height, ${s[b]} - 1));
      width = max(0, min(width, ${s[T]} - 1));
      var depth1: u32 = u32(depth);
      var height1: u32 = u32(height);
      var width1: u32 = u32(width);
      var depth2: u32 = u32(depth + 1);
      var height2: u32 = u32(height + 1);
      var width2: u32 = u32(width + 1);
      var channel: u32 = ${s.length>3?`u32(originalIndices[${E}])`:"0"};
      var batch: u32 =  ${s.length>3?`u32(originalIndices[${p}])`:"0"};

      var x111: ${q} = getInputValue(batch, channel, depth1, height1, width1);
      var x112: ${q} = getInputValue(batch, channel, depth1, height1, width2);
      var x121: ${q} = getInputValue(batch, channel, depth1, height2, width1);
      var x122: ${q} = getInputValue(batch, channel, depth1, height2, width2);
      var x211: ${q} = getInputValue(batch, channel, depth2, height1, width1);
      var x212: ${q} = getInputValue(batch, channel, depth2, height1, width2);
      var x221: ${q} = getInputValue(batch, channel, depth2, height2, width1);
      var x222: ${q} = getInputValue(batch, channel, depth2, height2, width2);
      var dx1: ${q} = abs(depth - ${q}(depth1));
      var dx2: ${q} = abs(${q}(depth2) - depth);
      var dy1: ${q} = abs(height - ${q}(height1));
      var dy2: ${q} = abs(${q}(height2) - height);
      var dz1: ${q} = abs(width - ${q}(width1));
      var dz2: ${q} = abs(${q}(width2) - width);
      if (depth1 == depth2) {
        dx1 = 0.5;
        dx2 = 0.5;
      }
      if (height1 == height2) {
        dy1 = 0.5;
        dy2 = 0.5;
      }
      if (width1 == width2) {
        dz1 = 0.5;
        dz2 = 0.5;
      }
      return (x111 * dx2 * dy2 * dz2 + x112 * dx2 * dy2 * dz1 + x121 * dx2 * dy1 *dz2 + x122 * dx2 * dy1 * dz1 +
              x211 * dx1 * dy2 * dz2 + x212 * dx1 * dy2 * dz1 + x221 * dx1 * dy1 *dz2 + x222 * dx1 * dy1 * dz1);
    }`},z0=(r,i,s,u,c,p)=>{let d=r.dims,b=k0(p,i.axes,d.length),T=S0(d,u,c,i.axes),E=u.slice();u.length===0&&(E=d.map((he,Fe)=>he===0?1:T[Fe]/he),i.keepAspectRatioPolicy!=="stretch"&&(T=E0(d,E,i)));let q=Vt("output",r.dataType,T.length),H=gt("input",r.dataType,d.length),v=st.size(T),ne=d.length===T.length&&d.every((he,Fe)=>he===T[Fe]),re=i.coordinateTransformMode==="tf_crop_and_resize",ce=i.extrapolationValue,_e=H.type.value,be=he=>`
      ${ne?"":`
      ${M0(i.coordinateTransformMode,_e)};
      ${(()=>{switch(i.mode){case"nearest":return`
              ${$0(H,d)};
              ${T0(i.nearestMode,s,_e)};
              ${P0(H,q,d,T,E.length,b.length,re)};
              `;case"linear":return`
              ${C0(q,d,T,E.length,b.length)};
              ${(()=>{if(d.length===2||d.length===4)return`${A0(H,q,d,re,ce)}`;if(d.length===3||d.length===5)return`${F0(H,q,d,re,ce)}`;throw Error("Linear mode only supports input dims 2, 3, 4 and 5 are supported in linear mode.")})()};
            `;case"cubic":return`
            ${(()=>{if(d.length===2||d.length===4)return`${I0(H,q,d,T,E,b,i.cubicCoeffA,re,i.extrapolationValue,i.excludeOutside)}`;throw Error("Cubic mode only supports input dims 2 and 4 are supported in linear mode.")})()};
            `;default:throw Error("Invalid resize mode")}})()};
      `}
      ${he.registerUniform("output_size","u32").registerUniform("scales","f32",E.length).registerUniform("roi","f32",b.length).declareVariables(H,q)}
      ${he.mainStart()}
        ${he.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
        ${ne?"output[global_idx] = input[global_idx];":`
        let output_indices = ${q.offsetToIndices("global_idx")};
        var input_indices: ${H.type.indices};
        ${(()=>{switch(i.mode){case"nearest":return`input_indices = calculateInputIndicesFromOutputIndices(output_indices);
                if (checkInputIndices(input_indices)) {
                  output[global_idx] = ${H.getByIndices("input_indices")};
                } else {
                  output[global_idx] = ${i.extrapolationValue};
                }`;case"linear":return`output[global_idx] = ${d.length===2||d.length===4?"bilinearInterpolation":"trilinearInterpolation"}(output_indices);`;case"cubic":return"output[global_idx] = bicubicInterpolation(output_indices);";default:throw Error(`Unsupported resize mode: ${i.mode}`)}})()};
`}
      }`;return{name:"Resize",shaderCache:{hint:`${i.cacheKey}|${s}|${E.length>0?E:""}|${c.length>0?c:""}|${b.length>0?b:""}|${ne}|${d}`,inputDependencies:["rank"]},getShaderSource:be,getRunData:()=>({outputs:[{dims:T,dataType:r.dataType}],dispatchGroup:{x:Math.ceil(v/64)},programUniforms:[{type:12,data:v},{type:1,data:E},{type:1,data:b},...Ct(d,T)]})}},O0=r=>{let i=r.customDataBuffer;return new Uint32Array(i,i.byteOffset,1)[0]},D0=(r,i)=>{let s=[],u=[],c=[],p=O0(r);if(i.antialias!==0)throw Error("Only default value (0) for Antialias attribute is supported");x0(r.inputs,i,p,s,u,c),r.compute(z0(r.inputs[0],i,p,s,u,c),{inputs:[0]})},L0=r=>{let i=r.antialias,s=r.axes,u=r.coordinateTransformMode,c=r.cubicCoeffA,p=r.excludeOutside!==0,d=r.extrapolationValue,b=r.keepAspectRatioPolicy,T=r.mode,E=r.nearestMode===""?"simple":r.nearestMode;return Gt({antialias:i,axes:s,coordinateTransformMode:u,cubicCoeffA:c,excludeOutside:p,extrapolationValue:d,keepAspectRatioPolicy:b,mode:T,nearestMode:E})}}),R0,B0,N0,rx=h(()=>{Xt(),Yt(),mr(),or(),R0=(r,i)=>{let[s,u,c,p]=r,{numHeads:d,rotaryEmbeddingDim:b}=i;if(s.dims.length!==3&&s.dims.length!==4)throw new Error(`Input 'x' is expected to have 3 or 4 dimensions, got ${s.dims.length}`);if(!st.areEqual(u.dims,[])&&!st.areEqual(u.dims,[1])&&u.dims.length!==2)throw new Error(`Input 'position_ids' is expected to have 0, 1, or 2 dimensions, got ${u.dims.length}`);if(c.dims.length!==2)throw new Error(`Input 'cos_cache' is expected to have 2 dimensions, got ${c.dims.length}`);if(p.dims.length!==2)throw new Error(`Input 'sin_cache' is expected to have 2 dimensions, got ${p.dims.length}`);if(!st.areEqual(c.dims,p.dims))throw new Error("Inputs 'cos_cache' and 'sin_cache' are expected to have the same shape");if(b>0&&d===0)throw new Error("num_heads must be provided if rotary_embedding_dim is specified");let T=s.dims[0],E=s.dims[s.dims.length-2],q=c.dims[0],H=st.sizeFromDimension(s.dims,1)/E,v=b===0?c.dims[1]*2:H/d;if(b>v)throw new Error("rotary_embedding_dim must be less than or equal to head_size");if(u.dims.length===2){if(T!==u.dims[0])throw new Error(`Input 'position_ids' dimension 0 should be of size batch_size, got ${u.dims[0]}`);if(E!==u.dims[1])throw new Error(`Input 'position_ids' dimension 1 should be of size sequence_length, got ${u.dims[1]}`)}if(v/2!==c.dims[1]&&b/2!==c.dims[1])throw new Error(`Input 'cos_cache' dimension 1 should be same as head_size / 2 or rotary_embedding_dim / 2, got ${c.dims[1]}`);if(E>q)throw new Error("Updating cos_cache and sin_cache in RotaryEmbedding is not currently supported")},B0=(r,i)=>{let{interleaved:s,numHeads:u,rotaryEmbeddingDim:c,scale:p}=i,d=r[0].dims[0],b=st.sizeFromDimension(r[0].dims,1),T=r[0].dims[r[0].dims.length-2],E=b/T,q=r[2].dims[1],H=c===0?q*2:E/u,v=new Array(d,T,E/H,H-q),ne=st.computeStrides(v),re=[{type:1,data:p},{type:12,data:v},{type:12,data:ne},...r[0].dims.length===3?new Array({type:12,data:[b,E,H,1]}):[],...r[0].dims.length===4?new Array({type:12,data:[b,H,T*H,1]}):[],...Ct(r[0].dims,r[1].dims,r[2].dims,r[3].dims,r[0].dims)],ce=_e=>{let be=gt("input",r[0].dataType,r[0].dims.length),he=gt("position_ids",r[1].dataType,r[1].dims.length),Fe=gt("cos_cache",r[2].dataType,r[2].dims.length),xe=gt("sin_cache",r[3].dataType,r[3].dims.length),Ie=Vt("output",r[0].dataType,r[0].dims.length);return _e.registerUniforms([{name:"scale",type:"f32"},{name:"global_shape",type:"u32",length:v.length},{name:"global_strides",type:"u32",length:ne.length},{name:"input_output_strides",type:"u32",length:ne.length}]),`
        ${_e.declareVariables(be,he,Fe,xe,Ie)}

        ${_e.mainStart(Bn)}
          let half_rotary_emb_dim = uniforms.${Fe.name}_shape[1];
          let bsnh = global_idx / uniforms.global_strides % uniforms.global_shape;
          let size = uniforms.global_shape[0] * uniforms.global_strides[0];
          ${_e.guardAgainstOutOfBoundsWorkgroupSizes("size")}

          if (bsnh[3] < half_rotary_emb_dim) {
            let position_ids_idx =
                ${he.broadcastedIndicesToOffset("bsnh.xy",Vt("",he.type.tensor,2))};
            let position_id =
                u32(${he.getByOffset("position_ids_idx")}) + select(0, bsnh[1], position_ids_idx == 0);
            let i = dot(bsnh, uniforms.input_output_strides) + select(0, bsnh[3], ${s});
            let j = i + select(half_rotary_emb_dim, 1, ${s});
            let re = ${be.getByOffset("i")} * ${Fe.get("position_id","bsnh[3]")} -
                ${be.getByOffset("j")} * ${xe.get("position_id","bsnh[3]")};
            ${Ie.setByOffset("i","re")}
            let im = ${be.getByOffset("i")} * ${xe.get("position_id","bsnh[3]")} +
                ${be.getByOffset("j")} * ${Fe.get("position_id","bsnh[3]")};
            ${Ie.setByOffset("j","im")}
          } else {
            let k = dot(bsnh, uniforms.input_output_strides) + half_rotary_emb_dim;
            ${Ie.setByOffset("k",be.getByOffset("k"))}
          }
        }`};return{name:"RotaryEmbedding",shaderCache:{hint:Gt({interleaved:s}).cacheKey,inputDependencies:["rank","rank","rank","rank"]},getShaderSource:ce,getRunData:()=>({outputs:[{dims:r[0].dims,dataType:r[0].dataType}],dispatchGroup:{x:Math.ceil(st.size(v)/Bn)},programUniforms:re})}},N0=(r,i)=>{R0(r.inputs,i),r.compute(B0(r.inputs,i))}}),j0,U0,V0,nx=h(()=>{Xt(),Yt(),or(),j0=r=>{if(!r||r.length<3)throw new Error("layerNorm requires at least 3 inputs.");let i=r[0],s=r[1],u=r[2];if(i.dataType!==s.dataType||i.dataType!==u.dataType)throw new Error("All inputs must have the same data type");if(i.dims.length!==3&&i.dims.length!==2)throw new Error("Input must be 2D or 3D");if(s.dims.length!==3&&s.dims.length!==2)throw new Error("Skip must be 2D or 3D");let c=i.dims[i.dims.length-1],p=i.dims[i.dims.length-2];if(s.dims[s.dims.length-1]!==c)throw new Error("Skip must have the same hidden size as input");if(s.dims[s.dims.length-2]!==p)throw new Error("Skip must have the same sequence length as input");if(u.dims.length!==1)throw new Error("Gamma must be 1D");if(u.dims[u.dims.length-1]!==c)throw new Error("Gamma must have the same hidden size as input");if(r.length>3){let d=r[3];if(d.dims.length!==1)throw new Error("Beta must be 1D");if(d.dims[d.dims.length-1]!==c)throw new Error("Beta must have the same hidden size as input")}if(r.length>4){let d=r[4];if(d.dims.length!==1)throw new Error("Bias must be 1D");if(d.dims[d.dims.length-1]!==c)throw new Error("Bias must have the same hidden size as input")}},U0=(r,i,s,u)=>{let c=i.simplified,p=r[0].dims,d=st.size(p),b=p,T=d,E=p.slice(-1)[0],q=u?p.slice(0,-1).concat(1):[],H=!c&&r.length>3,v=r.length>4,ne=u&&s>1,re=u&&s>2,ce=s>3,_e=64,be=wr(E),he=[{type:12,data:T},{type:12,data:be},{type:12,data:E},{type:1,data:i.epsilon}],Fe=Ie=>{let ct=[{name:"output_size",type:"u32"},{name:"components",type:"u32"},{name:"hidden_size",type:"u32"},{name:"epsilon",type:"f32"}],et=[gt("x",r[0].dataType,r[0].dims,be),gt("skip",r[1].dataType,r[1].dims,be),gt("gamma",r[2].dataType,r[2].dims,be)];H&&et.push(gt("beta",r[3].dataType,r[3].dims,be)),v&&et.push(gt("bias",r[4].dataType,r[4].dims,be)),et.push(Vt("output",r[0].dataType,b,be)),ne&&et.push(Vt("mean_output",1,q)),re&&et.push(Vt("inv_std_output",1,q)),ce&&et.push(Vt("input_skip_bias_sum",r[0].dataType,b,be));let vt=Tr(r[0].dataType),Ft=Tr(1,be);return`

      ${Ie.registerUniforms(ct).declareVariables(...et)}
      var<workgroup> sum_shared : array<${Ft}, ${_e}>;
      var<workgroup> sum_squared_shared : array<${Ft}, ${_e}>;

      ${Ie.mainStart([_e,1,1])}
        let ix = local_id.x;
        let iy = global_id.x / ${_e};

        let hidden_size_vectorized: u32 = uniforms.hidden_size / uniforms.components;
        var stride = hidden_size_vectorized / ${_e};
        let offset = ix * stride + iy * hidden_size_vectorized;
        let offset1d = stride * ix;
        if (ix == ${_e-1}) {
          stride = hidden_size_vectorized - stride * ix;
        }
        for (var i: u32 = 0; i < stride; i++) {
          let skip_value = skip[offset + i];
          let bias_value = ${v?"bias[offset1d + i]":vt+"(0.0)"};
          let input_value = x[offset + i];
          let value = input_value + skip_value + bias_value;
          ${ce?"input_skip_bias_sum[offset + i] = value;":""}
          output[offset + i] = value;
          let f32_value = ${Gr(vt,be,"value")};
          sum_shared[ix] += f32_value;
          sum_squared_shared[ix] += f32_value * f32_value;
        }
        workgroupBarrier();

        var reduce_size : u32 = ${_e};
        for (var curr_size = reduce_size >> 1;  curr_size > 0; curr_size = reduce_size >> 1) {
          reduce_size = curr_size + (reduce_size & 1);
          if (ix < curr_size) {
            sum_shared[ix] += sum_shared[ix + reduce_size];
            sum_squared_shared[ix] += sum_squared_shared[ix + reduce_size];
          }
          workgroupBarrier();
        }

        let sum = sum_shared[0];
        let square_sum = sum_squared_shared[0];
        let mean = ${Nn("sum",be)} / f32(uniforms.hidden_size);
        let inv_std_dev = inverseSqrt(${Nn("square_sum",be)} / f32(uniforms.hidden_size) ${c?"":"- mean * mean"} + uniforms.epsilon);
        ${ne?"mean_output[global_idx] = mean;":""}
        ${re?"inv_std_output[global_idx] = inv_std_dev;":""}

        for (var i: u32 = 0; i < stride; i++) {
          output[offset + i] = (output[offset + i] ${c?"":`- ${vt}(mean)`}) *
            ${vt}(inv_std_dev) * gamma[offset1d + i]
            ${H?"+ beta[offset1d + i]":""};
        }
      }`},xe=[{dims:b,dataType:r[0].dataType}];return s>1&&xe.push({dims:q,dataType:1}),s>2&&xe.push({dims:q,dataType:1}),s>3&&xe.push({dims:p,dataType:r[0].dataType}),{name:"SkipLayerNormalization",shaderCache:{hint:`${be};${ne};${re};${ce}`,inputDependencies:r.map((Ie,ct)=>"type")},getShaderSource:Fe,getRunData:()=>({outputs:xe,dispatchGroup:{x:Math.ceil(T/E)},programUniforms:he})}},V0=(r,i)=>{j0(r.inputs);let s=[0];r.outputCount>1&&s.push(-3),r.outputCount>2&&s.push(-3),r.outputCount>3&&s.push(3),r.compute(U0(r.inputs,i,r.outputCount,!1),{outputs:s})}}),W0,rf,G0,ym,q0,H0,K0,Q0,ix=h(()=>{Xt(),Yt(),mr(),or(),W0=(r,i)=>{if(!r||r.length<1)throw new Error("too few inputs");if(i.axes.length!==0){if(i.axes.length!==i.starts.length||i.axes.length!==i.ends.length)throw new Error("axes, starts and ends must have the same length")}else if(i.starts.length!==i.ends.length)throw new Error("starts and ends must have the same length");r.slice(1).forEach((s,u)=>{if(r[u+1].dataType!==6&&r[u+1].dataType!==7)throw new Error(`Input ${u} must be an array of int32 or int64`)})},rf=(r,i)=>{let s=[];if(r.length>i)if(r[i].dataType===7)r[i].getBigInt64Array().forEach(u=>s.push(Number(u)));else if(r[i].dataType===6)r[i].getInt32Array().forEach(u=>s.push(Number(u)));else throw new Error(`Input ${i} must be an array of int32 or int64`);return s},G0=(r,i)=>{if(r.length>1){let s=rf(r,1),u=rf(r,2),c=rf(r,3);return c.length===0&&(c=[...Array(r[0].dims.length).keys()]),Gt({starts:s,ends:u,axes:c})}else return i},ym=(r,i,s,u,c)=>{let p=r;return r<0&&(p+=s[u[i]]),c[i]<0?Math.max(0,Math.min(p,s[u[i]]-1)):Math.max(0,Math.min(p,s[u[i]]))},q0=(r,i,s)=>`fn calculateInputIndices(output_indices: ${i.type.indices}) -> ${r.type.indices} {
          var input_indices: ${r.type.indices};
          var carry = 0u;
          for (var i = ${s.length}; i >= 0; i--) {
            let input_shape_i = ${Dt("uniforms.input_shape","i",s.length)};
            let steps_i = ${Dt("uniforms.steps","i",s.length)};
            let signs_i = ${Dt("uniforms.signs","i",s.length)};
            let starts_i = ${Dt("uniforms.starts","i",s.length)};
            var output_index = ${i.indicesGet("output_indices","i")};
            var input_index = output_index * steps_i + starts_i + carry;
            carry = input_index / input_shape_i;
            input_index = input_index % input_shape_i;
            if (signs_i < 0) {
              input_index = input_shape_i - input_index - 1u + starts_i;
            }
            ${r.indicesSet("input_indices","i","input_index")};
          }
          return input_indices;
      }`,H0=(r,i)=>{let s=r[0].dims,u=st.size(s),c=i.axes.length>0?st.normalizeAxes(i.axes,s.length):[...Array(s.length).keys()],p=rf(r,4);p.forEach(be=>be!==0||(()=>{throw new Error("step cannot be 0")})),p.length===0&&(p=Array(c.length).fill(1));let d=i.starts.map((be,he)=>ym(be,he,s,c,p)),b=i.ends.map((be,he)=>ym(be,he,s,c,p));if(c.length!==d.length||c.length!==b.length)throw new Error("start, ends and axes should have the same number of elements");if(c.length!==s.length)for(let be=0;be<s.length;++be)c.includes(be)||(d.splice(be,0,0),b.splice(be,0,s[be]),p.splice(be,0,1));let T=p.map(be=>Math.sign(be));p.forEach((be,he,Fe)=>{if(be<0){let xe=(b[he]-d[he])/be,Ie=d[he],ct=Ie+xe*p[he];d[he]=ct,b[he]=Ie,Fe[he]=-be}});let E=s.slice(0);c.forEach((be,he)=>{E[be]=Math.ceil((b[be]-d[be])/p[be])});let q={dims:E,dataType:r[0].dataType},H=Vt("output",r[0].dataType,E.length),v=gt("input",r[0].dataType,r[0].dims.length),ne=st.size(E),re=[{name:"outputSize",type:"u32"},{name:"starts",type:"u32",length:d.length},{name:"signs",type:"i32",length:T.length},{name:"steps",type:"u32",length:p.length}],ce=[{type:12,data:ne},{type:12,data:d},{type:6,data:T},{type:12,data:p},...Ct(r[0].dims,E)],_e=be=>`
      ${be.registerUniforms(re).declareVariables(v,H)}
        ${q0(v,H,s)}
        ${be.mainStart()}
          ${be.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}
          let output_indices = ${H.offsetToIndices("global_idx")};
          let input_indices = calculateInputIndices(output_indices);
          ${H.setByOffset("global_idx",v.getByIndices("input_indices"))}
      }`;return{name:"Slice",shaderCache:{hint:`${T.length}_${d.length}_${p.length}`,inputDependencies:["rank"]},getShaderSource:_e,getRunData:()=>({outputs:[q],dispatchGroup:{x:Math.ceil(u/64)},programUniforms:ce})}},K0=(r,i)=>{W0(r.inputs,i);let s=G0(r.inputs,i);r.compute(H0(r.inputs,s),{inputs:[0]})},Q0=r=>{let i=r.starts,s=r.ends,u=r.axes;return Gt({starts:i,ends:s,axes:u})}}),X0,Y0,Z0,J0,ox=h(()=>{Xt(),Yt(),mr(),or(),X0=r=>{if(!r||r.length!==1)throw new Error("Softmax op requires 1 input.")},Y0=(r,i)=>{let s=r.dims,u=st.size(s),c=64,p=i.axis;if(p<0&&(p=s.length+p),p<s.length-1)throw new Error("softmax only supports last axis for now.");let d=s[p],b=u/d,T=wr(d),E=d/T,q=(_e,be)=>be===4?`max(max(${_e}.x, ${_e}.y), max(${_e}.z, ${_e}.w))`:be===2?`max(${_e}.x, ${_e}.y)`:be===3?`max(max(${_e}.x, ${_e}.y), ${_e}.z)`:_e,H=gt("x",r.dataType,r.dims,T),v=Vt("result",r.dataType,r.dims,T),ne=H.type.value,re=Tr(r.dataType)==="f32"?`var threadMax = ${ne}(-3.402823e+38f);`:`var threadMax = ${ne}(-65504.0h);`,ce=_e=>`
      var<workgroup> rowMaxShared : ${ne};
      var<workgroup> rowSumShared : ${ne};
      var<workgroup> threadShared : array<${ne}, ${c}>;

      fn getValue(row: i32, col: i32, row_stride: i32) -> ${ne} {
        let index = row * row_stride + col;
        return x[index];
      }

      fn setValue(row: i32, col: i32, row_stride: i32, value: ${ne}) {
        let index = row * row_stride + col;
        result[index] = value;
      }
      ${_e.registerUniform("packedCols","i32").declareVariables(H,v)}
      ${_e.mainStart()}
        let gindex = i32(global_idx);
        let lindex = i32(local_idx);
        const wg = ${c};
        let row = gindex / wg;
        let cols = uniforms.packedCols;
        let row_stride : i32 = uniforms.packedCols;

        // find the rows max
        ${re}
        for (var col = lindex; col < cols; col += wg) {
          let value = getValue(row, col, row_stride);
          threadMax = max(threadMax, value);
        }
        if (lindex < cols) {
          threadShared[lindex] = threadMax;
        }
        workgroupBarrier();

        var reduceSize = min(cols, wg);
        for (var currSize = reduceSize >> 1;  currSize > 0; currSize = reduceSize >> 1) {
          reduceSize = currSize + (reduceSize & 1);
          if (lindex < currSize) {
            threadShared[lindex] = max(threadShared[lindex], threadShared[lindex + reduceSize]);
          }
          workgroupBarrier();
        }
        if (lindex == 0) {
          rowMaxShared = ${ne}(${q("threadShared[0]",T)});
        }
        workgroupBarrier();

        // find the rows sum
        var threadSum = ${ne}(0.0);
        for (var col = lindex; col < cols; col += wg) {
          let subExp = exp(getValue(row, col, row_stride) - rowMaxShared);
          threadSum += subExp;
        }
        threadShared[lindex] = threadSum;
        workgroupBarrier();

        for (var currSize = wg >> 1;  currSize > 0; currSize = currSize >> 1) {
          if (lindex < currSize) {
            threadShared[lindex] = threadShared[lindex] + threadShared[lindex + currSize];
          }
          workgroupBarrier();
        }
        if (lindex == 0) {
          rowSumShared = ${ne}(${Nn("threadShared[0]",T)});
        }
        workgroupBarrier();

        // calculate final value for each element in the row
        for (var col = lindex; col < cols; col += wg) {
          let value = exp(getValue(row, col, row_stride) - rowMaxShared) / rowSumShared;
          setValue(row, col, row_stride, value);
        }
      }`;return{name:"Softmax",shaderCache:{hint:`${T}`,inputDependencies:["type"]},getRunData:()=>({outputs:[{dims:s,dataType:r.dataType}],dispatchGroup:{x:b},programUniforms:[{type:6,data:E}]}),getShaderSource:ce}},Z0=(r,i)=>{X0(r.inputs),r.compute(Y0(r.inputs[0],i))},J0=r=>Gt({axis:r.axis})}),ey,ty,ry,ny,iy,oy,sy,sx=h(()=>{Xt(),Yt(),mr(),or(),ey=r=>{if(!r||r.length<1)throw new Error("too few inputs")},ty=(r,i)=>{let s=[],u=i.numOutputs;return r[1].dims[0]>0&&(r[1].getBigInt64Array().forEach(c=>s.push(Number(c))),u=s.length),Gt({numOutputs:u,axis:i.axis,splitSizes:s})},ry=r=>`
fn calculateOutputIndex(index: u32) -> u32 {
    for (var i: u32 = 0u; i < ${r}u; i += 1u ) {
    if (index < ${Dt("uniforms.size_in_split_axis","i",r)}) {
        return i;
    }
    }
    return ${r}u;
}`,ny=r=>{let i=r.length,s=[];for(let u=0;u<i;++u){let c=r[u].setByIndices("indices","input[global_idx]");i===1?s.push(c):u===0?s.push(`if (output_number == ${u}u) { ${c} }`):u===i-1?s.push(`else { ${c} }`):s.push(`else if (output_number == ${u}) { ${c} }`)}return`
      fn writeBufferData(output_number: u32, indices: ${r[0].type.indices}, global_idx: u32) {
        ${s.join(`
`)}
      }`},iy=(r,i)=>{let s=r[0].dims,u=st.size(s),c=r[0].dataType,p=st.normalizeAxis(i.axis,s.length),d=new Array(i.numOutputs),b=gt("input",c,s.length),T=new Array(i.numOutputs),E=[],q=[],H=0,v=[{type:12,data:u}];for(let re=0;re<i.numOutputs;re++){H+=i.splitSizes[re],T[re]=H;let ce=s.slice();ce[p]=i.splitSizes[re],q.push(ce),d[re]=Vt(`output${re}`,c,ce.length),E.push({dims:q[re],dataType:r[0].dataType})}v.push({type:12,data:T},...Ct(s,...q));let ne=re=>`
  ${re.registerUniform("input_size","u32").registerUniform("size_in_split_axis","u32",T.length).declareVariables(b,...d)}
  ${ry(T.length)}
  ${ny(d)}

  ${re.mainStart()}
    ${re.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.input_size")}

    var indices = ${b.offsetToIndices("global_idx")};
    var index = ${b.indicesGet("indices",p)};
    let output_number = calculateOutputIndex(index);
    if (output_number != 0) {
      index -= ${Dt("uniforms.size_in_split_axis","output_number - 1u",T.length)};
      ${b.indicesSet("indices",p,"index")};
    }
    writeBufferData(output_number, indices, global_idx);
  }`;return{name:"Split",shaderCache:{hint:i.cacheKey,inputDependencies:["rank"]},getShaderSource:ne,getRunData:()=>({outputs:E,dispatchGroup:{x:Math.ceil(u/64)},programUniforms:v})}},oy=(r,i)=>{ey(r.inputs);let s=r.inputs.length===1?i:ty(r.inputs,i);r.compute(iy(r.inputs,s),{inputs:[0]})},sy=r=>{let i=r.axis,s=r.splitSizes,u=r.numOutputs<0?s.length:r.numOutputs;if(u!==s.length)throw new Error("numOutputs and splitSizes lengh must be equal");return Gt({axis:i,numOutputs:u,splitSizes:s})}}),ay,ly,uy,ax=h(()=>{Xt(),Yt(),or(),ay=(r,i,s,u,c)=>{let p=Vt("output_data",c,s.length,4),d=gt("a_data",i[1].dataType,i[1].dims.length,4),b=gt("b_data",i[2].dataType,i[2].dims.length,4),T=gt("c_data",i[0].dataType,i[0].dims.length,4),E,q=(H,v,ne)=>`select(${v}, ${H}, ${ne})`;if(!u)E=p.setByOffset("global_idx",q(d.getByOffset("global_idx"),b.getByOffset("global_idx"),T.getByOffset("global_idx")));else{let H=(v,ne,re="")=>{let ce=`a_data[index_a${ne}][component_a${ne}]`,_e=`b_data[index_b${ne}][component_b${ne}]`,be=`bool(c_data[index_c${ne}] & (0xffu << (component_c${ne} * 8)))`;return`
            let output_indices${ne} = ${p.offsetToIndices(`global_idx * 4u + ${ne}u`)};
            let offset_a${ne} = ${d.broadcastedIndicesToOffset(`output_indices${ne}`,p)};
            let offset_b${ne} = ${b.broadcastedIndicesToOffset(`output_indices${ne}`,p)};
            let offset_c${ne} = ${T.broadcastedIndicesToOffset(`output_indices${ne}`,p)};
            let index_a${ne} = offset_a${ne} / 4u;
            let index_b${ne} = offset_b${ne} / 4u;
            let index_c${ne} = offset_c${ne} / 4u;
            let component_a${ne} = offset_a${ne} % 4u;
            let component_b${ne} = offset_b${ne} % 4u;
            let component_c${ne} = offset_c${ne} % 4u;
            ${v}[${ne}] = ${re}(${q(ce,_e,be)});
          `};c===9?E=`
            var data = vec4<u32>(0);
            ${H("data",0,"u32")}
            ${H("data",1,"u32")}
            ${H("data",2,"u32")}
            ${H("data",3,"u32")}
            output_data[global_idx] = dot(vec4<u32>(0x1, 0x100, 0x10000, 0x1000000), vec4<u32>(data));`:E=`
            ${H("output_data[global_idx]",0)}
            ${H("output_data[global_idx]",1)}
            ${H("output_data[global_idx]",2)}
            ${H("output_data[global_idx]",3)}
          `}return`
        ${r.registerUniform("vec_size","u32").declareVariables(T,d,b,p)}
        ${r.mainStart()}
        ${r.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.vec_size")}
        ${E}
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c=this.sessionExternalDataMapping.get(r);c||(c=new Map,this.sessionExternalDataMapping.set(r,c));let p=c.get(i),d=this.gpuDataManager.registerExternalBuffer(s,u,p==null?void 0:p[1]);return c.set(i,[d,s]),d}unregisterBuffers(r){let i=this.sessionExternalDataMapping.get(r);i&&(i.forEach(s=>this.gpuDataManager.unregisterExternalBuffer(s[1])),this.sessionExternalDataMapping.delete(r))}getBuffer(r){let i=this.gpuDataManager.get(r);if(!i)throw new Error(`no GPU data for buffer: ${r}`);return i.buffer}createDownloader(r,i,s){return async()=>{let u=await Tt(this,r,i);return Ue(u.buffer,s)}}writeTimestamp(r){this.queryType==="inside-passes"&&this.computePassEncoder.writeTimestamp(this.querySet,r)}setQueryType(){var r;this.queryType="none",(((r=this.env.webgpu.profiling)==null?void 0:r.mode)==="default"||(typeof 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D.wasm.trace!="boolean"&&(D.wasm.trace=!1),typeof D.wasm.numThreads!="number"||!Number.isInteger(D.wasm.numThreads)||D.wasm.numThreads<=0)if(typeof self<"u"&&!self.crossOriginIsolated)D.wasm.numThreads=1;else{let r=typeof navigator>"u"?_("node:os").cpus().length:navigator.hardwareConcurrency;D.wasm.numThreads=Math.min(4,Math.ceil((r||1)/2))}},zy=class{async init(r){Fy(),await My(),await Ty(r)}async createInferenceSessionHandler(r,i){let s=new Iy;return await s.loadModel(r,i),Promise.resolve(s)}}}),Oy={};g(Oy,{wasmBackend:()=>Dy});var Dy,hx=h(()=>{px(),Dy=new zy});Z(),Z(),Z();var mx="1.20.0-dev.20240821-009209e016",gx=Ve;{let r=(hx(),w(Oy)).wasmBackend;z("webgpu",r,5),z("webnn",r,5),z("cpu",r,10),z("wasm",r,10)}Object.defineProperty(D.versions,"web",{value:mx,enumerable:!0});/**
 * @license
 * Copyright 2021 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 *//**
 * @license
 * Copyright 2020 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 *//**
 * @license
 * Copyright 2019 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */},"./src/backends/onnx.js":(e,t,n)=>{var o;n.r(t),n.d(t,{Tensor:()=>_.Tensor,createInferenceSession:()=>S,deviceToExecutionProviders:()=>k,isONNXProxy:()=>x,isONNXTensor:()=>P});var a=n("./src/env.js"),l=n("?2ce3"),f=n("./node_modules/onnxruntime-web/dist/ort.webgpu.bundle.min.mjs"),_=n("./node_modules/onnxruntime-common/dist/esm/index.js");const h=Object.freeze({auto:null,gpu:null,cpu:"cpu",wasm:"wasm",webgpu:"webgpu",cuda:"cuda",dml:"dml",webnn:{name:"webnn",deviceType:"cpu"},"webnn-npu":{name:"webnn",deviceType:"npu"},"webnn-gpu":{name:"webnn",deviceType:"gpu"},"webnn-cpu":{name:"webnn",deviceType:"cpu"}}),g=[];let M,w;if(a.apis.IS_NODE_ENV){switch(w=l??(o||(o=n.t(l,2))),process.platform){case"win32":g.push("dml");break;case"linux":process.arch==="x64"&&g.push("cuda");break}g.push("cpu"),M=["cpu"]}else w=f,a.apis.IS_WEBNN_AVAILABLE&&g.push("webnn-npu","webnn-gpu","webnn-cpu","webnn"),a.apis.IS_WEBGPU_AVAILABLE&&g.push("webgpu"),g.push("wasm"),M=["wasm"];const C=w.InferenceSession;function k(I=null){if(!I)return M;switch(I){case"auto":return g;case"gpu":return g.filter(U=>["webgpu","cuda","dml","webnn-gpu"].includes(U))}if(g.includes(I))return[h[I]??I];throw new Error(`Unsupported device: "${I}". 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o=n("./src/utils/generic.js");n("./src/utils/tensor.js");var a=n("./src/utils/maths.js");class l extends o.Callable{_call(N,j){throw Error("`_call` should be implemented in a subclass")}}class f extends o.Callable{_call(N,j){throw Error("`_call` should be implemented in a subclass")}}class _ extends o.Callable{constructor(){super(),this.processors=[]}push(N){this.processors.push(N)}extend(N){this.processors.push(...N)}_call(N,j){let D=j;for(const Y of this.processors)D=Y(N,D);return D}[Symbol.iterator](){return this.processors.values()}}class h extends l{constructor(N){super(),this.bos_token_id=N}_call(N,j){for(let D=0;D<N.length;++D)if(N[D].length===1){const Y=j[D];Y.data.fill(-1/0),Y.data[this.bos_token_id]=0}return j}}class g extends l{constructor(N,j){super(),this.max_length=N,this.eos_token_id=Array.isArray(j)?j:[j]}_call(N,j){for(let D=0;D<N.length;++D)if(N[D].length===this.max_length-1){const Y=j[D];Y.data.fill(-1/0);for(const de of this.eos_token_id)Y.data[de]=0}return j}}class M extends l{constructor(N,j){super(),this.begin_suppress_tokens=N,this.begin_index=j}_call(N,j){for(let D=0;D<N.length;++D)if(N[D].length===this.begin_index){const Y=j[D];for(const de of this.begin_suppress_tokens)Y.data[de]=-1/0}return j}}class w extends l{constructor(N,j){super(),this.eos_token_id=Array.isArray(N.eos_token_id)?N.eos_token_id[0]:N.eos_token_id,this.no_timestamps_token_id=N.no_timestamps_token_id,this.timestamp_begin=this.no_timestamps_token_id+1,this.begin_index=j.length,j.at(-1)===this.no_timestamps_token_id&&(this.begin_index-=1),this.max_initial_timestamp_index=N.max_initial_timestamp_index}_call(N,j){for(let D=0;D<N.length;++D){const de=j[D].data;if(de[this.no_timestamps_token_id]=-1/0,N[D].length===this.begin_index-1){de.fill(-1/0),de[this.timestamp_begin]=0;continue}const Ce=N[D].slice(this.begin_index),ee=Ce.length>=1&&Ce[Ce.length-1]>=this.timestamp_begin,ye=Ce.length<2||Ce[Ce.length-2]>=this.timestamp_begin;if(ee&&(ye?de.subarray(this.timestamp_begin).fill(-1/0):de.subarray(0,this.eos_token_id).fill(-1/0)),N[D].length===this.begin_index&&this.max_initial_timestamp_index!==null){const ge=this.timestamp_begin+this.max_initial_timestamp_index;de.subarray(ge+1).fill(-1/0)}const R=(0,a.log_softmax)(de),Me=Math.log(R.subarray(this.timestamp_begin).map(Math.exp).reduce((ge,Q)=>ge+Q)),Qe=(0,a.max)(R.subarray(0,this.timestamp_begin))[0];Me>Qe&&de.subarray(0,this.timestamp_begin).fill(-1/0)}return j}}class C extends l{constructor(N){super(),this.no_repeat_ngram_size=N}getNgrams(N){const j=N.length,D=[];for(let de=0;de<j+1-this.no_repeat_ngram_size;++de){const Ce=[];for(let ee=0;ee<this.no_repeat_ngram_size;++ee)Ce.push(N[de+ee]);D.push(Ce.map(Number))}const Y=new Map;for(const de of D){const Ce=de.slice(0,de.length-1),ee=JSON.stringify(Ce),ye=Y.get(ee)??[];ye.push(de[de.length-1]),Y.set(ee,ye)}return Y}getGeneratedNgrams(N,j){const D=j.slice(j.length+1-this.no_repeat_ngram_size,j.length);return N.get(JSON.stringify(D.map(Number)))??[]}calcBannedNgramTokens(N){const j=[];if(N.length+1<this.no_repeat_ngram_size)return j;{const D=this.getNgrams(N);return this.getGeneratedNgrams(D,N)}}_call(N,j){for(let D=0;D<N.length;++D){const Y=j[D],de=this.calcBannedNgramTokens(N[D]);for(const Ce of de)Y.data[Ce]=-1/0}return j}}class k extends l{constructor(N){super(),this.penalty=N}_call(N,j){for(let D=0;D<N.length;++D){const Y=j[D];for(const de of N[D])Y.data[de]<0?Y.data[de]*=this.penalty:Y.data[de]/=this.penalty}return j}}class z extends l{constructor(N,j){super(),this.min_length=N,this.eos_token_id=Array.isArray(j)?j:[j]}_call(N,j){for(let D=0;D<N.length;++D)if(N[D].length<this.min_length){const Y=j[D];for(const de of this.eos_token_id)Y.data[de]=-1/0}return j}}class S extends l{constructor(N,j,D){super(),this.prompt_length_to_skip=N,this.min_new_tokens=j,this.eos_token_id=Array.isArray(D)?D:[D]}_call(N,j){for(let D=0;D<N.length;++D)if(N[D].length-this.prompt_length_to_skip<this.min_new_tokens){const de=j[D];for(const Ce of this.eos_token_id)de[Ce]=-1/0}return j}}class P extends l{constructor(N,j){super(),this.bad_words_ids=N,this.eos_token_id=Array.isArray(j)?j:[j]}_call(N,j){for(let D=0;D<N.length;++D){const Y=j[D];for(const de of this.bad_words_ids){let Ce=!0;for(let ee=1;ee<=de.length-1&&de.length<N[ee].length;++ee)if(de.at(-ee-1)!==Number(N[ee].at(-ee))){Ce=!1;break}Ce&&(Y[de.at(-1)]=-1/0)}}return j}}class y extends l{constructor(N){if(super(),N<=1)throw new Error(`Require guidance scale >1 to use the classifier free guidance processor, got guidance scale ${N}.`);this.guidance_scale=N}_call(N,j){if(j.dims[0]!==2*N.length)throw new Error(`Logits should have twice the batch size of the input ids, the first half of batches corresponding to the conditional inputs, and the second half of batches corresponding to the unconditional inputs. Got batch size ${j.dims[0]} for the logits and ${N.length} for the input ids.`);const D=N.length,Y=j.slice([0,D],null),de=j.slice([D,j.dims[0]],null);for(let Ce=0;Ce<de.data.length;++Ce)de.data[Ce]+=(Y.data[Ce]-de.data[Ce])*this.guidance_scale;return de}}class x extends f{constructor(N){super(),this.temperature=N}_call(N,j){const D=j.data;for(let Y=0;Y<D.length;++Y)D[Y]/=this.temperature;return j}}class I extends f{constructor(N,{filter_value:j=-1/0,min_tokens_to_keep:D=1}={}){if(super(),N<0||N>1)throw new Error(`\`top_p\` must be a float > 0 and < 1, but is ${N}`);if(!Number.isInteger(D)||D<1)throw new Error(`\`min_tokens_to_keep\` must be a positive integer, but is ${D}`);this.top_p=N,this.filter_value=j,this.min_tokens_to_keep=D}}class U extends f{constructor(N,{filter_value:j=-1/0,min_tokens_to_keep:D=1}={}){if(super(),!Number.isInteger(N)||N<0)throw new Error(`\`top_k\` must be a positive integer, but is ${N}`);this.top_k=Math.max(N,D),this.filter_value=j}}},"./src/generation/logits_sampler.js":(e,t,n)=>{n.r(t),n.d(t,{LogitsSampler:()=>f});var o=n("./src/utils/generic.js"),a=n("./src/utils/tensor.js"),l=n("./src/utils/maths.js");n("./src/generation/configuration_utils.js");class f extends o.Callable{constructor(w){super(),this.generation_config=w}async _call(w){return this.sample(w)}async sample(w){throw Error("sample should be implemented in subclasses.")}getLogits(w,C){let k=w.dims.at(-1),z=w.data;if(C===-1)z=z.slice(-k);else{let S=C*k;z=z.slice(S,S+k)}return z}randomSelect(w){let C=0;for(let z=0;z<w.length;++z)C+=w[z];let k=Math.random()*C;for(let z=0;z<w.length;++z)if(k-=w[z],k<=0)return z;return 0}static getSampler(w){if(w.do_sample)return new h(w);if(w.num_beams>1)return new g(w);if(w.num_return_sequences>1)throw Error(`num_return_sequences has to be 1 when doing greedy search, but is ${w.num_return_sequences}.`);return new _(w)}}class _ extends f{async sample(w){const C=(0,l.max)(w.data)[1];return[[BigInt(C),0]]}}class h extends f{async sample(w){let C=w.dims.at(-1);this.generation_config.top_k>0&&(C=Math.min(this.generation_config.top_k,C));const[k,z]=await(0,a.topk)(w,C),S=(0,l.softmax)(k.data);return Array.from({length:this.generation_config.num_beams},()=>{const P=this.randomSelect(S);return[z.data[P],Math.log(S[P])]})}}class g extends f{async sample(w){let C=w.dims.at(-1);this.generation_config.top_k>0&&(C=Math.min(this.generation_config.top_k,C));const[k,z]=await(0,a.topk)(w,C),S=(0,l.softmax)(k.data);return Array.from({length:this.generation_config.num_beams},(P,y)=>[z.data[y],Math.log(S[y])])}}},"./src/generation/stopping_criteria.js":(e,t,n)=>{n.r(t),n.d(t,{EosTokenCriteria:()=>_,InterruptableStoppingCriteria:()=>h,MaxLengthCriteria:()=>f,StoppingCriteria:()=>a,StoppingCriteriaList:()=>l});var o=n("./src/utils/generic.js");class a extends o.Callable{_call(M,w){throw Error("StoppingCriteria needs to be subclassed")}}class l extends o.Callable{constructor(){super(),this.criteria=[]}push(M){this.criteria.push(M)}extend(M){M instanceof l?M=M.criteria:M instanceof a&&(M=[M]),this.criteria.push(...M)}_call(M,w){const C=new Array(M.length).fill(!1);for(const k of this.criteria){const z=k(M,w);for(let S=0;S<C.length;++S)C[S]||(C[S]=z[S])}return C}[Symbol.iterator](){return this.criteria.values()}}class f extends a{constructor(M,w=null){super(),this.max_length=M,this.max_position_embeddings=w}_call(M){return M.map(w=>w.length>=this.max_length)}}class _ extends a{constructor(M){super(),Array.isArray(M)||(M=[M]),this.eos_token_id=M}_call(M,w){return M.map(C=>{const k=C.at(-1);return this.eos_token_id.some(z=>k==z)})}}class h extends a{constructor(){super(),this.interrupted=!1}interrupt(){this.interrupted=!0}reset(){this.interrupted=!1}_call(M,w){return new Array(M.length).fill(this.interrupted)}}},"./src/generation/streamers.js":(e,t,n)=>{n.r(t),n.d(t,{BaseStreamer:()=>f,TextStreamer:()=>h,WhisperTextStreamer:()=>g});var o=n("./src/utils/core.js"),a=n("./src/tokenizers.js"),l=n("./src/env.js");class f{put(w){throw Error("Not implemented")}end(){throw Error("Not implemented")}}const _=l.apis.IS_PROCESS_AVAILABLE?M=>process.stdout.write(M):M=>console.log(M);class h extends f{constructor(w,{skip_prompt:C=!1,callback_function:k=null,token_callback_function:z=null,decode_kwargs:S={},...P}={}){super(),this.tokenizer=w,this.skip_prompt=C,this.callback_function=k??_,this.token_callback_function=z,this.decode_kwargs={...S,...P},this.token_cache=[],this.print_len=0,this.next_tokens_are_prompt=!0}put(w){var S;if(w.length>1)throw Error("TextStreamer only supports batch size of 1");if(this.skip_prompt&&this.next_tokens_are_prompt){this.next_tokens_are_prompt=!1;return}const C=w[0];(S=this.token_callback_function)==null||S.call(this,C),this.token_cache=(0,o.mergeArrays)(this.token_cache,C);const k=this.tokenizer.decode(this.token_cache,this.decode_kwargs);let z;k.endsWith(`
`)?(z=k.slice(this.print_len),this.token_cache=[],this.print_len=0):k.length>0&&(0,a.is_chinese_char)(k.charCodeAt(k.length-1))?(z=k.slice(this.print_len),this.print_len+=z.length):(z=k.slice(this.print_len,k.lastIndexOf(" ")+1),this.print_len+=z.length),this.on_finalized_text(z,!1)}end(){let w;this.token_cache.length>0?(w=this.tokenizer.decode(this.token_cache,this.decode_kwargs).slice(this.print_len),this.token_cache=[],this.print_len=0):w="",this.next_tokens_are_prompt=!0,this.on_finalized_text(w,!0)}on_finalized_text(w,C){var k,z;w.length>0&&((k=this.callback_function)==null||k.call(this,w)),C&&this.callback_function===_&&l.apis.IS_PROCESS_AVAILABLE&&((z=this.callback_function)==null||z.call(this,`
`))}}class g extends h{constructor(w,{skip_prompt:C=!1,callback_function:k=null,token_callback_function:z=null,on_chunk_start:S=null,on_chunk_end:P=null,on_finalize:y=null,time_precision:x=.02,skip_special_tokens:I=!0,decode_kwargs:U={}}={}){super(w,{skip_prompt:C,callback_function:k,token_callback_function:z,decode_kwargs:{skip_special_tokens:I,...U}}),this.timestamp_begin=w.timestamp_begin,this.on_chunk_start=S,this.on_chunk_end=P,this.on_finalize=y,this.time_precision=x,this.waiting_for_timestamp=!1}put(w){var k,z;if(w.length>1)throw Error("WhisperTextStreamer only supports batch size of 1");const C=w[0];if(C.length===1){const S=Number(C[0])-this.timestamp_begin;if(S>=0){const P=S*this.time_precision;this.waiting_for_timestamp?(k=this.on_chunk_end)==null||k.call(this,P):(z=this.on_chunk_start)==null||z.call(this,P),this.waiting_for_timestamp=!this.waiting_for_timestamp,w=[[]]}}return super.put(w)}end(){var w;super.end(),(w=this.on_finalize)==null||w.call(this)}}},"./src/models.js":(e,t,n)=>{n.r(t),n.d(t,{ASTForAudioClassification:()=>Es,ASTModel:()=>Dt,ASTPreTrainedModel:()=>Nn,AlbertForMaskedLM:()=>Xt,AlbertForQuestionAnswering:()=>po,AlbertForSequenceClassification:()=>fo,AlbertModel:()=>Yi,AlbertPreTrainedModel:()=>Ti,AutoModel:()=>Od,AutoModelForAudioClassification:()=>Hd,AutoModelForAudioFrameClassification:()=>Kd,AutoModelForCTC:()=>qd,AutoModelForCausalLM:()=>Bd,AutoModelForDepthEstimation:()=>Yd,AutoModelForDocumentQuestionAnswering:()=>bp,AutoModelForImageClassification:()=>Ud,AutoModelForImageFeatureExtraction:()=>Zd,AutoModelForImageMatting:()=>Qd,AutoModelForImageSegmentation:()=>vl,AutoModelForImageToImage:()=>Xd,AutoModelForMaskGeneration:()=>bl,AutoModelForMaskedLM:()=>Nd,AutoModelForObjectDetection:()=>Wd,AutoModelForQuestionAnswering:()=>wl,AutoModelForSemanticSegmentation:()=>Vd,AutoModelForSeq2SeqLM:()=>Ld,AutoModelForSequenceClassification:()=>Sn,AutoModelForSpeechSeq2Seq:()=>yl,AutoModelForTextToSpectrogram:()=>Rd,AutoModelForTextToWaveform:()=>Xo,AutoModelForTokenClassification:()=>Dd,AutoModelForVision2Seq:()=>jd,AutoModelForXVector:()=>xl,AutoModelForZeroShotObjectDetection:()=>Gd,BartForConditionalGeneration:()=>W,BartForSequenceClassification:()=>fe,BartModel:()=>Ue,BartPretrainedModel:()=>Rn,BaseModelOutput:()=>Ke,BeitForImageClassification:()=>sc,BeitModel:()=>oc,BeitPreTrainedModel:()=>$a,BertForMaskedLM:()=>We,BertForQuestionAnswering:()=>Ge,BertForSequenceClassification:()=>ot,BertForTokenClassification:()=>dt,BertModel:()=>Be,BertPreTrainedModel:()=>De,BlenderbotForConditionalGeneration:()=>At,BlenderbotModel:()=>Tt,BlenderbotPreTrainedModel:()=>kt,BlenderbotSmallForConditionalGeneration:()=>rr,BlenderbotSmallModel:()=>Pr,BlenderbotSmallPreTrainedModel:()=>Zt,BloomForCausalLM:()=>ju,BloomModel:()=>Nu,BloomPreTrainedModel:()=>$s,CLIPModel:()=>lu,CLIPPreTrainedModel:()=>Wo,CLIPSegForImageSegmentation:()=>mu,CLIPSegModel:()=>hu,CLIPSegPreTrainedModel:()=>ma,CLIPTextModelWithProjection:()=>fi,CLIPVisionModelWithProjection:()=>uu,CamembertForMaskedLM:()=>Re,CamembertForQuestionAnswering:()=>rt,CamembertForSequenceClassification:()=>He,CamembertForTokenClassification:()=>Xe,CamembertModel:()=>ve,CamembertPreTrainedModel:()=>Z,CausalLMOutput:()=>Ji,CausalLMOutputWithPast:()=>xp,ChineseCLIPModel:()=>pu,ChineseCLIPPreTrainedModel:()=>fu,ClapAudioModelWithProjection:()=>ld,ClapModel:()=>sd,ClapPreTrainedModel:()=>qo,ClapTextModelWithProjection:()=>ad,CodeGenForCausalLM:()=>Cs,CodeGenModel:()=>ku,CodeGenPreTrainedModel:()=>Kn,CohereForCausalLM:()=>Cu,CohereModel:()=>Eu,CoherePreTrainedModel:()=>va,ConvBertForMaskedLM:()=>B,ConvBertForQuestionAnswering:()=>ue,ConvBertForSequenceClassification:()=>J,ConvBertForTokenClassification:()=>L,ConvBertModel:()=>we,ConvBertPreTrainedModel:()=>te,ConvNextForImageClassification:()=>Pc,ConvNextModel:()=>Cc,ConvNextPreTrainedModel:()=>Va,ConvNextV2ForImageClassification:()=>Ic,ConvNextV2Model:()=>Ac,ConvNextV2PreTrainedModel:()=>$c,DPTForDepthEstimation:()=>Na,DPTModel:()=>Ba,DPTPreTrainedModel:()=>Ra,DebertaForMaskedLM:()=>Mt,DebertaForQuestionAnswering:()=>Rt,DebertaForSequenceClassification:()=>wt,DebertaForTokenClassification:()=>St,DebertaModel:()=>ht,DebertaPreTrainedModel:()=>ft,DebertaV2ForMaskedLM:()=>Ut,DebertaV2ForQuestionAnswering:()=>Jt,DebertaV2ForSequenceClassification:()=>Kt,DebertaV2ForTokenClassification:()=>Qt,DebertaV2Model:()=>Ot,DebertaV2PreTrainedModel:()=>at,DeiTForImageClassification:()=>_c,DeiTModel:()=>gc,DeiTPreTrainedModel:()=>Fa,DepthAnythingForDepthEstimation:()=>Tc,DepthAnythingPreTrainedModel:()=>Mc,DetrForObjectDetection:()=>lc,DetrForSegmentation:()=>uc,DetrModel:()=>ac,DetrObjectDetectionOutput:()=>Aa,DetrPreTrainedModel:()=>Fs,DetrSegmentationOutput:()=>cc,Dinov2ForImageClassification:()=>zc,Dinov2Model:()=>Fc,Dinov2PreTrainedModel:()=>Xn,DistilBertForMaskedLM:()=>Pt,DistilBertForQuestionAnswering:()=>mt,DistilBertForSequenceClassification:()=>Qr,DistilBertForTokenClassification:()=>Cr,DistilBertModel:()=>Er,DistilBertPreTrainedModel:()=>qt,DonutSwinModel:()=>Ua,DonutSwinPreTrainedModel:()=>Ec,EfficientNetForImageClassification:()=>pd,EfficientNetModel:()=>fd,EfficientNetPreTrainedModel:()=>ul,ElectraForMaskedLM:()=>Ne,ElectraForQuestionAnswering:()=>Ve,ElectraForSequenceClassification:()=>ut,ElectraForTokenClassification:()=>Je,ElectraModel:()=>ke,ElectraPreTrainedModel:()=>le,EsmForMaskedLM:()=>Li,EsmForSequenceClassification:()=>bi,EsmForTokenClassification:()=>Nr,EsmModel:()=>sn,EsmPreTrainedModel:()=>Bt,FalconForCausalLM:()=>od,FalconModel:()=>id,FalconPreTrainedModel:()=>ol,FastViTForImageClassification:()=>Ku,FastViTModel:()=>Hu,FastViTPreTrainedModel:()=>Is,Florence2ForConditionalGeneration:()=>pa,Florence2PreTrainedModel:()=>au,GLPNForDepthEstimation:()=>Sc,GLPNModel:()=>kc,GLPNPreTrainedModel:()=>ja,GPT2LMHeadModel:()=>_u,GPT2Model:()=>gu,GPT2PreTrainedModel:()=>ga,GPTBigCodeForCausalLM:()=>ep,GPTBigCodeMod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o=n("./src/configs.js"),a=n("./src/backends/onnx.js"),l=n("./src/utils/dtypes.js"),f=n("./src/utils/generic.js"),_=n("./src/utils/core.js"),h=n("./src/utils/hub.js"),g=n("./src/generation/logits_process.js"),M=n("./src/generation/configuration_utils.js"),w=n("./src/utils/tensor.js"),C=n("./src/utils/maths.js"),k=n("./src/generation/stopping_criteria.js"),z=n("./src/generation/logits_sampler.js"),S=n("./src/env.js"),P=n("./src/models/whisper/generation_whisper.js"),y=n("./src/models/whisper/common_whisper.js");const x={EncoderOnly:0,EncoderDecoder:1,Seq2Seq:2,Vision2Seq:3,DecoderOnly:4,MaskGeneration:5,ImageTextToText:6,Musicgen:7},I=new Map,U=new Map,O=new Map;async function N(V,G,ie){let Ee=ie.device;Ee&&typeof Ee!="string"&&(Ee.hasOwnProperty(G)?Ee=Ee[G]:(console.warn(`device not specified for "${G}". Using the default device.`),Ee=null));const Ze=Ee??(S.apis.IS_NODE_ENV?"cpu":"wasm"),it=(0,a.deviceToExecutionProviders)(Ze);let _t=ie.dtype;typeof _t!="string"&&(_t&&_t.hasOwnProperty(G)?_t=_t[G]:(_t=l.DEFAULT_DEVICE_DTYPE_MAPPING[Ze]??l.DATA_TYPES.fp32,console.warn(`dtype not specified for "${G}". Using the default dtype (${_t}) for this device (${Ze}).`)));const Et=_t;if(l.DEFAULT_DTYPE_SUFFIX_MAPPING.hasOwnProperty(Et)){if(Et===l.DATA_TYPES.fp16&&Ze==="webgpu"&&!await(0,l.isWebGpuFp16Supported)())throw new Error(`The device (${Ze}) does not support fp16.`)}else throw new Error(`Invalid dtype: ${Et}. Should be one of: ${Object.keys(l.DATA_TYPES).join(", ")}`);const Wt=l.DEFAULT_DTYPE_SUFFIX_MAPPING[Et],cr=`${ie.subfolder??""}/${G}${Wt}.onnx`,sr={...ie.session_options};sr.executionProviders??(sr.executionProviders=it);const $r=(0,h.getModelFile)(V,cr,!0,ie);let dr=[];if(ie.use_external_data_format&&(ie.use_external_data_format===!0||typeof ie.use_external_data_format=="object"&&ie.use_external_data_format.hasOwnProperty(G)&&ie.use_external_data_format[G]===!0)){if(S.apis.IS_NODE_ENV)throw new Error("External data format is not yet supported in Node.js");const fr=`${G}${Wt}.onnx_data`,gr=`${ie.subfolder??""}/${fr}`;dr.push(new Promise(async(br,Dr)=>{const En=await(0,h.getModelFile)(V,gr,!0,ie);br({path:fr,data:En})}))}else sr.externalData!==void 0&&(dr=sr.externalData.map(async fr=>{if(typeof fr.data=="string"){const gr=await(0,h.getModelFile)(V,fr.data,!0,ie);return{...fr,data:gr}}return fr}));if(dr.length>0&&(sr.externalData=await Promise.all(dr)),Ze==="webgpu"){const fr=(0,o.getKeyValueShapes)(ie.config,{prefix:"present"});if(Object.keys(fr).length>0&&!(0,a.isONNXProxy)()){const gr={};for(const br in fr)gr[br]="gpu-buffer";sr.preferredOutputLocation=gr}}return{buffer:await $r,session_options:sr}}async function j(V,G,ie){return Object.fromEntries(await Promise.all(Object.keys(G).map(async Ee=>{const{buffer:Ze,session_options:it}=await N(V,G[Ee],ie),_t=await(0,a.createInferenceSession)(Ze,it);return[Ee,_t]})))}function D(V,G){const ie=Object.create(null),Ee=[];for(const _t of V.inputNames){const Et=G[_t];if(!(Et instanceof w.Tensor)){Ee.push(_t);continue}ie[_t]=(0,a.isONNXProxy)()?Et.clone():Et}if(Ee.length>0)throw new Error(`An error occurred during model execution: "Missing the following inputs: ${Ee.join(", ")}.`);const Ze=Object.keys(G).length,it=V.inputNames.length;if(Ze>it){let _t=Object.keys(G).filter(Et=>!V.inputNames.includes(Et));console.warn(`WARNING: Too many inputs were provided (${Ze} > ${it}). The following inputs will be ignored: "${_t.join(", ")}".`)}return ie}async function Y(V,G){const ie=D(V,G);try{const Ee=Object.fromEntries(Object.entries(ie).map(([it,_t])=>[it,_t.ort_tensor]));let Ze=await V.run(Ee);return Ze=de(Ze),Ze}catch(Ee){throw console.error(`An error occurred during model execution: "${Ee}".`),console.error("Inputs given to model:",ie),Ee}}function de(V){for(let G in V)(0,a.isONNXTensor)(V[G])?V[G]=new w.Tensor(V[G]):typeof V[G]=="object"&&de(V[G]);return V}function Ce(V){if(V instanceof w.Tensor)return V;if(V.length===0)throw Error("items must be non-empty");if(Array.isArray(V[0])){if(V.some(G=>G.length!==V[0].length))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' and/or 'truncation=True' to have batched tensors with the same length.");return new w.Tensor("int64",BigInt64Array.from(V.flat().map(G=>BigInt(G))),[V.length,V[0].length])}else return new w.Tensor("int64",BigInt64Array.from(V.map(G=>BigInt(G))),[1,V.length])}function ee(V){return new w.Tensor("bool",[V],[1])}async function ye(V,G){let{encoder_outputs:ie,input_ids:Ee,decoder_input_ids:Ze,...it}=G;if(!ie){const Et=(0,_.pick)(G,V.sessions.model.inputNames);ie=(await R(V,Et)).last_hidden_state}return it.input_ids=Ze,it.encoder_hidden_states=ie,V.sessions.decoder_model_merged.inputNames.includes("encoder_attention_mask")&&(it.encoder_attention_mask=G.attention_mask),await Me(V,it,!0)}async function R(V,G){const ie=V.sessions.model,Ee=(0,_.pick)(G,ie.inputNames);if(ie.inputNames.includes("inputs_embeds")&&!Ee.inputs_embeds){if(!G.input_ids)throw new Error("Both `input_ids` and `inputs_embeds` are missing in the model inputs.");Ee.inputs_embeds=await V.encode_text({input_ids:G.input_ids})}return ie.inputNames.includes("token_type_ids")&&!Ee.token_type_ids&&(Ee.token_type_ids=new w.Tensor("int64",new BigInt64Array(Ee.input_ids.data.length),Ee.input_ids.dims)),await Y(ie,Ee)}async function Me(V,G,ie=!1){const Ee=V.sessions[ie?"decoder_model_merged":"model"],{past_key_values:Ze,...it}=G;Ee.inputNames.includes("use_cache_branch")&&(it.use_cache_branch=ee(!!Ze)),Ee.inputNames.includes("position_ids")&&it.attention_mask&&!it.position_ids&&(it.position_ids=ge(it,Ze)),V.addPastKeyValues(it,Ze);const _t=(0,_.pick)(it,Ee.inputNames);return await Y(Ee,_t)}async function Qe(V,{input_ids:G=null,attention_mask:ie=null,pixel_values:Ee=null,position_ids:Ze=null,inputs_embeds:it=null,past_key_values:_t=null,generation_config:Et=null,logits_processor:Wt=null,...cr}){if(!it){if(it=await V.encode_text({input_ids:G}),Ee&&G.dims[1]!==1){const $r=await V.encode_image({pixel_values:Ee});({inputs_embeds:it,attention_mask:ie}=V._merge_input_ids_with_image_features({image_features:$r,inputs_embeds:it,input_ids:G,attention_mask:ie}))}else if(_t&&Ee&&G.dims[1]===1){const $r=G.dims[1],dr=Object.values(_t)[0].dims.at(-2);ie=(0,w.cat)([(0,w.ones)([G.dims[0],dr]),ie.slice(null,[ie.dims[1]-$r,ie.dims[1]])],1)}}return await Me(V,{inputs_embeds:it,past_key_values:_t,attention_mask:ie,position_ids:Ze,generation_config:Et,logits_processor:Wt},!0)}function ge(V,G=null){const{input_ids:ie,inputs_embeds:Ee,attention_mask:Ze}=V,[it,_t]=Ze.dims,Et=new BigInt64Array(Ze.data.length);for(let cr=0;cr<it;++cr){const sr=cr*_t;let $r=BigInt(0);for(let dr=0;dr<_t;++dr){const _r=sr+dr;Ze.data[_r]===0n?Et[_r]=BigInt(1):(Et[_r]=$r,$r+=Ze.data[_r])}}let Wt=new w.Tensor("int64",Et,Ze.dims);if(G){const cr=-(ie??Ee).dims.at(1);Wt=Wt.slice(null,[cr,null])}return Wt}function Q(V,G,ie,Ee){if(ie.past_key_values){const Ze=Object.values(ie.past_key_values)[0].dims.at(-2),{input_ids:it,attention_mask:_t}=ie;if(!(_t&&_t.dims[1]>it.dims[1])){if(Ze<it.dims[1])ie.input_ids=it.slice(null,[Ze,null]);else if(V.config.image_token_index!=null&&it.data.some(Et=>Et==V.config.image_token_index)){const Et=V.config.num_image_tokens;if(!Et)throw new Error("`num_image_tokens` is missing in the model configuration.");const Wt=it.dims[1]-(Ze-Et);ie.input_ids=it.slice(null,[-Wt,null]),ie.attention_mask=(0,w.ones)([1,Ze+Wt])}}}return ie}function ae(V,G,ie,Ee){return ie.past_key_values&&(G=G.map(Ze=>[Ze.at(-1)])),{...ie,decoder_input_ids:Ce(G)}}function Se(V,...G){return V.config.is_encoder_decoder?ae(V,...G):Q(V,...G)}class X extends f.Callable{constructor(ie,Ee){super();qe(this,"main_input_name","input_ids");qe(this,"forward_params",["input_ids","attention_mask"]);this.config=ie,this.sessions=Ee;const Ze=O.get(this.constructor),it=I.get(Ze);switch(this.can_generate=!1,this._forward=null,this._prepare_inputs_for_generation=null,it){case x.DecoderOnly:this.can_generate=!0,this._forward=Me,this._prepare_inputs_for_generation=Q;break;case x.Seq2Seq:case x.Vision2Seq:case x.Musicgen:this.can_generate=!0,this._forward=ye,this._prepare_inputs_for_generation=ae;break;case x.EncoderDecoder:this._forward=ye;break;case x.ImageTextToText:this.can_generate=!0,this._forward=Qe,this._prepare_inputs_for_generation=Se;break;default:this._forward=R;break}this.can_generate&&this.forward_params.push("past_key_values"),this.custom_config=this.config["transformers.js_config"]??{}}async dispose(){var Ee;const ie=[];for(const Ze of Object.values(this.sessions))(Ee=Ze==null?void 0:Ze.handler)!=null&&Ee.dispose&&ie.push(Ze.handler.dispose());return await Promise.all(ie)}static async from_pretrained(ie,{progress_callback:Ee=null,config:Ze=null,cache_dir:it=null,local_files_only:_t=!1,revision:Et="main",model_file_name:Wt=null,subfolder:cr="onnx",device:sr=null,dtype:$r=null,use_external_data_format:dr=null,session_options:_r={}}={}){let fr={progress_callback:Ee,config:Ze,cache_dir:it,local_files_only:_t,revision:Et,model_file_name:Wt,subfolder:cr,device:sr,dtype:$r,use_external_data_format:dr,session_options:_r};const gr=O.get(this),br=I.get(gr);Ze=fr.config=await o.AutoConfig.from_pretrained(ie,fr);let Dr;if(br===x.DecoderOnly)Dr=await Promise.all([j(ie,{model:fr.model_file_name??"model"},fr),(0,h.getModelJSON)(ie,"generation_config.json",!1,fr)]);else if(br===x.Seq2Seq||br===x.Vision2Seq)Dr=await Promise.all([j(ie,{model:"encoder_model",decoder_model_merged:"decoder_model_merged"},fr),(0,h.getModelJSON)(ie,"generation_config.json",!1,fr)]);else if(br===x.MaskGeneration)Dr=await Promise.all([j(ie,{model:"vision_encoder",prompt_encoder_mask_decoder:"prompt_encoder_mask_decoder"},fr)]);else if(br===x.EncoderDecoder)Dr=await Promise.all([j(ie,{model:"encoder_model",decoder_model_merged:"decoder_model_merged"},fr)]);else if(br===x.ImageTextToText){const En={embed_tokens:"embed_tokens",vision_encoder:"vision_encoder",decoder_model_merged:"decoder_model_merged"};Ze.is_encoder_decoder&&(En.model="encoder_model"),Dr=await Promise.all([j(ie,En,fr),(0,h.getModelJSON)(ie,"generation_config.json",!1,fr)])}else br===x.Musicgen?Dr=await Promise.all([j(ie,{model:"text_encoder",decoder_model_merged:"decoder_model_merged",encodec_decode:"encodec_decode"},fr),(0,h.getModelJSON)(ie,"generation_config.json",!1,fr)]):(br!==x.EncoderOnly&&console.warn(`Model type for '${gr??(Ze==null?void 0:Ze.model_type)}' not found, assuming encoder-only architecture. Please report this at https://github.com/xenova/transformers.js/issues/new/choose.`),Dr=await Promise.all([j(ie,{model:fr.model_file_name??"model"},fr)]));return new this(Ze,...Dr)}async _call(ie){return await this.forward(ie)}async forward(ie){return await this._forward(this,ie)}_get_logits_warper(ie){const Ee=new g.LogitsProcessorList;return ie.temperature!==null&&ie.temperature!==1&&Ee.push(new g.TemperatureLogitsWarper(ie.temperature)),ie.top_k!==null&&ie.top_k!==0&&Ee.push(new g.TopKLogitsWarper(ie.top_k)),ie.top_p!==null&&ie.top_p<1&&Ee.push(new g.TopPLogitsWarper(ie.top_p)),Ee}_get_logits_processor(ie,Ee,Ze=null){const it=new g.LogitsProcessorList;if(ie.repetition_penalty!==null&&ie.repetition_penalty!==1&&it.push(new g.RepetitionPenaltyLogitsProcessor(ie.repetition_penalty)),ie.no_repeat_ngram_size!==null&&ie.no_repeat_ngram_size>0&&it.push(new g.NoRepeatNGramLogitsProcessor(ie.no_repeat_ngram_size)),ie.bad_words_ids!==null&&it.push(new g.NoBadWordsLogitsProcessor(ie.bad_words_ids,ie.eos_token_id)),ie.min_length!==null&&ie.eos_token_id!==null&&ie.min_length>0&&it.push(new g.MinLengthLogitsProcessor(ie.min_length,ie.eos_token_id)),ie.min_new_tokens!==null&&ie.eos_token_id!==null&&ie.min_new_tokens>0&&it.push(new g.MinNewTokensLengthLogitsProcessor(Ee,ie.min_new_tokens,ie.eos_token_id)),ie.forced_bos_token_id!==null&&it.push(new g.ForcedBOSTokenLogitsProcessor(ie.forced_bos_token_id)),ie.forced_eos_token_id!==null&&it.push(new g.ForcedEOSTokenLogitsProcessor(ie.max_length,ie.forced_eos_token_id)),ie.begin_suppress_tokens!==null){const _t=Ee>1||ie.forced_bos_token_id===null?Ee:Ee+1;it.push(new g.SuppressTokensAtBeginLogitsProcessor(ie.begin_suppress_tokens,_t))}return ie.guidance_scale!==null&&ie.guidance_scale>1&&it.push(new g.ClassifierFreeGuidanceLogitsProcessor(ie.guidance_scale)),Ze!==null&&it.extend(Ze),it}_prepare_generation_config(ie,Ee,Ze=M.GenerationConfig){const it={...this.config};for(const Et of["decoder","generator","text_config"])Et in it&&Object.assign(it,it[Et]);const _t=new Ze(it);return"generation_config"in this&&Object.assign(_t,this.generation_config),ie&&Object.assign(_t,ie),Ee&&Object.assign(_t,(0,_.pick)(Ee,Object.getOwnPropertyNames(_t))),_t}_get_stopping_criteria(ie,Ee=null){const Ze=new k.StoppingCriteriaList;return ie.max_length!==null&&Ze.push(new k.MaxLengthCriteria(ie.max_length,this.config.max_position_embeddings??null)),ie.eos_token_id!==null&&Ze.push(new k.EosTokenCriteria(ie.eos_token_id)),Ee&&Ze.extend(Ee),Ze}_validate_model_class(){if(!this.can_generate){const ie=[Vs,_l,gl,Us],Ee=O.get(this.constructor),Ze=new Set,it=this.config.model_type;for(const Et of ie){const Wt=Et.get(it);Wt&&Ze.add(Wt[0])}let _t=`The current model class (${Ee}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;throw Ze.size>0&&(_t+=` Please use the following class instead: ${[...Ze].join(", ")}`),Error(_t)}}prepare_inputs_for_generation(...ie){return this._prepare_inputs_for_generation(this,...ie)}_update_model_kwargs_for_generation({generated_input_ids:ie,outputs:Ee,model_inputs:Ze,is_encoder_decoder:it}){return Ze.past_key_values=this.getPastKeyValues(Ee,Ze.past_key_values),Ze.input_ids=new w.Tensor("int64",ie.flat(),[ie.length,1]),it||(Ze.attention_mask=(0,w.cat)([Ze.attention_mask,(0,w.ones)([Ze.attention_mask.dims[0],1])],1)),Ze.position_ids=null,Ze}_prepare_model_inputs({inputs:ie,bos_token_id:Ee,model_kwargs:Ze}){const it=(0,_.pick)(Ze,this.forward_params),_t=this.main_input_name;if(_t in it){if(ie)throw new Error("`inputs`: {inputs}` were passed alongside {input_name} which is not allowed. Make sure to either pass {inputs} or {input_name}=...")}else it[_t]=ie;return{inputs_tensor:it[_t],model_inputs:it,model_input_name:_t}}async _prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:ie,model_inputs:Ee,model_input_name:Ze,generation_config:it}){if(this.sessions.model.inputNames.includes("inputs_embeds")&&!Ee.inputs_embeds&&"_prepare_inputs_embeds"in this){const{input_ids:Et,pixel_values:Wt,attention_mask:cr,...sr}=Ee,$r=await this._prepare_inputs_embeds(Ee);Ee={...sr,...(0,_.pick)($r,["inputs_embeds","attention_mask"])}}let{last_hidden_state:_t}=await R(this,Ee);if(it.guidance_scale!==null&&it.guidance_scale>1)_t=(0,w.cat)([_t,(0,w.full_like)(_t,0)],0),"attention_mask"in Ee&&(Ee.attention_mask=(0,w.cat)([Ee.attention_mask,(0,w.zeros_like)(Ee.attention_mask)],0));else if(Ee.decoder_input_ids){const Et=Ce(Ee.decoder_input_ids).dims[0];if(Et!==_t.dims[0]){if(_t.dims[0]!==1)throw new Error(`The encoder outputs have a different batch size (${_t.dims[0]}) than the decoder inputs (${Et}).`);_t=(0,w.cat)(Array.from({length:Et},()=>_t),0)}}return Ee.encoder_outputs=_t,Ee}_prepare_decoder_input_ids_for_generation({batch_size:ie,model_input_name:Ee,model_kwargs:Ze,decoder_start_token_id:it,bos_token_id:_t,generation_config:Et}){let{decoder_input_ids:Wt,...cr}=Ze;if(Wt)Array.isArray(Wt[0])||(Wt=Array.from({length:ie},()=>Wt));else if(it??(it=_t),this.config.model_type==="musicgen")Wt=Array.from({length:ie*this.config.decoder.num_codebooks},()=>[it]);else if(Array.isArray(it)){if(it.length!==ie)throw new Error(`\`decoder_start_token_id\` expcted to have length ${ie} but got ${it.length}`);Wt=it}else Wt=Array.from({length:ie},()=>[it]);return Wt=Ce(Wt),Ze.decoder_attention_mask=(0,w.ones_like)(Wt),{input_ids:Wt,model_inputs:cr}}async generate({inputs:ie=null,generation_config:Ee=null,logits_processor:Ze=null,stopping_criteria:it=null,streamer:_t=null,...Et}){this._validate_model_class(),Ee=this._prepare_generation_config(Ee,Et);let{inputs_tensor:Wt,model_inputs:cr,model_input_name:sr}=this._prepare_model_inputs({inputs:ie,model_kwargs:Et});const $r=this.config.is_encoder_decoder;$r&&("encoder_outputs"in cr||(cr=await this._prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:Wt,model_inputs:cr,model_input_name:sr,generation_config:Ee})));let dr;$r?{input_ids:dr,model_inputs:cr}=this._prepare_decoder_input_ids_for_generation({batch_size:cr[sr].dims.at(0),model_input_name:sr,model_kwargs:cr,decoder_start_token_id:Ee.decoder_start_token_id,bos_token_id:Ee.bos_token_id,generation_config:Ee}):dr=cr[sr];let _r=dr.dims.at(-1);Ee.max_new_tokens!==null&&(Ee.max_length=_r+Ee.max_new_tokens);const fr=this._get_logits_processor(Ee,_r,Ze),gr=this._get_stopping_criteria(Ee,it),br=cr[sr].dims.at(0),Dr=z.LogitsSampler.getSampler(Ee),En=new Array(br).fill(0),An=dr.tolist();_t&&_t.put(An);let Ei=null,vn={};for(;;){cr=this.prepare_inputs_for_generation(An,cr,Ee);const bn=await this.forward(cr);if(Ee.output_attentions&&Ee.return_dict_in_generate){const pi=this.getAttentions(bn);for(const Yo in pi)Yo in vn||(vn[Yo]=[]),vn[Yo].push(pi[Yo])}const Ws=bn.logits.slice(null,-1,null),Gs=fr(An,Ws),Ml=[];for(let pi=0;pi<Gs.dims.at(0);++pi){const Yo=Gs[pi],Tp=await Dr(Yo);for(const[kp,Sp]of Tp){const tf=BigInt(kp);En[pi]+=Sp,An[pi].push(tf),Ml.push([tf]);break}}if(_t&&_t.put(Ml),gr(An).every(pi=>pi)){Ee.return_dict_in_generate&&(Ei=this.getPastKeyValues(bn,cr.past_key_values,!1));break}cr=this._update_model_kwargs_for_generation({generated_input_ids:Ml,outputs:bn,model_inputs:cr,is_encoder_decoder:$r})}_t&&_t.end();const ln=new w.Tensor("int64",An.flat(),[An.length,An[0].length]);return Ee.return_dict_in_generate?{sequences:ln,past_key_values:Ei,...vn}:ln}getPastKeyValues(ie,Ee,Ze=!0){const it=Object.create(null);for(const _t in ie)if(_t.startsWith("present")){const Et=_t.replace("present","past_key_values");if(Ee&&_t.includes("encoder"))it[Et]=Ee[Et];else{if(Ze&&Ee){const Wt=Ee[Et];Wt.location==="gpu-buffer"&&Wt.dispose()}it[Et]=ie[_t]}}return it}getAttentions(ie){const Ee={};for(const Ze of["cross_attentions","encoder_attentions","decoder_attentions"])for(const it in ie)it.startsWith(Ze)&&(Ze in Ee||(Ee[Ze]=[]),Ee[Ze].push(ie[it]));return Ee}addPastKeyValues(ie,Ee){if(Ee)Object.assign(ie,Ee);else{const Ze=this.custom_config.kv_cache_dtype??"float32",it=Ze==="float16"?new Uint16Array:[],_t=(0,o.getKeyValueShapes)(this.config);for(const Et in _t)ie[Et]=new w.Tensor(Ze,it,_t[Et])}}async encode_image({pixel_values:ie}){const Ee=(await Y(this.sessions.vision_encoder,{pixel_values:ie})).image_features;return this.config.num_image_tokens||(console.warn(`The number of image tokens was not set in the model configuration. Setting it to the number of features detected by the vision encoder (${Ee.dims[1]}).`),this.config.num_image_tokens=Ee.dims[1]),Ee}async encode_text({input_ids:ie}){return(await Y(this.sessions.embed_tokens,{input_ids:ie})).inputs_embeds}}class me{}class Ke extends me{constructor({last_hidden_state:G,hidden_states:ie=null,attentions:Ee=null}){super(),this.last_hidden_state=G,this.hidden_states=ie,this.attentions=Ee}}class De extends X{}class Be extends De{}class We extends De{async _call(G){return new yn(await super._call(G))}}class ot extends De{async _call(G){return new ur(await super._call(G))}}class dt extends De{async _call(G){return new dn(await super._call(G))}}class Ge extends De{async _call(G){return new wn(await super._call(G))}}class Te extends X{}class je extends Te{}class Ye extends X{}class tt extends Ye{}class A extends Ye{async _call(G){return new yn(await super._call(G))}}class Ae extends Ye{async _call(G){return new ur(await super._call(G))}}class $e extends Ye{async _call(G){return new dn(await super._call(G))}}class se extends Ye{async _call(G){return new wn(await super._call(G))}}class te extends X{}class we extends te{}class B extends te{async _call(G){return new yn(await super._call(G))}}class J extends te{async _call(G){return new ur(await super._call(G))}}class L extends te{async _call(G){return new dn(await super._call(G))}}class ue extends te{async _call(G){return new wn(await super._call(G))}}class le extends X{}class ke extends le{}class Ne extends le{async _call(G){return new yn(await super._call(G))}}class ut extends le{async _call(G){return new ur(await super._call(G))}}class Je extends le{async _call(G){return new dn(await super._call(G))}}class Ve extends le{async _call(G){return new wn(await super._call(G))}}class Z extends X{}class ve extends Z{}class Re extends Z{async _call(G){return new yn(await super._call(G))}}class He extends Z{async _call(G){return new ur(await super._call(G))}}class Xe extends Z{async _call(G){return new dn(await super._call(G))}}class rt extends Z{async _call(G){return new wn(await super._call(G))}}class ft extends X{}class ht extends ft{}class Mt extends ft{async _call(G){return new yn(await super._call(G))}}class wt extends ft{async _call(G){return new ur(await super._call(G))}}class St extends ft{async _call(G){return new dn(await super._call(G))}}class Rt extends ft{async _call(G){return new wn(await super._call(G))}}class at extends X{}class Ot extends at{}class Ut extends at{async _call(G){return new yn(await super._call(G))}}class Kt extends at{async _call(G){return new ur(await super._call(G))}}class Qt extends at{async _call(G){return new dn(await super._call(G))}}class Jt extends at{async _call(G){return new wn(await super._call(G))}}class qt extends X{}class Er extends qt{}class Qr extends qt{async _call(G){return new ur(await super._call(G))}}class Cr extends qt{async _call(G){return new dn(await super._call(G))}}class mt extends qt{async _call(G){return new wn(await super._call(G))}}class Pt extends qt{async _call(G){return new yn(await super._call(G))}}class Bt extends X{}class sn extends Bt{}class Li extends Bt{async _call(G){return new yn(await super._call(G))}}class bi extends Bt{async _call(G){return new ur(await super._call(G))}}class Nr extends Bt{async _call(G){return new dn(await super._call(G))}}class mn extends X{}class Wr extends mn{}class ci extends mn{async _call(G){return new yn(await super._call(G))}}class Fr extends mn{async _call(G){return new ur(await super._call(G))}}class Ri extends mn{async _call(G){return new wn(await super._call(G))}}class xi extends X{}class ks extends xi{}class Oo extends xi{async _call(G){return new yn(await super._call(G))}}class Do extends xi{async _call(G){return new ur(await super._call(G))}}class Lo extends xi{async _call(G){return new dn(await super._call(G))}}class Ro extends xi{async _call(G){return new wn(await super._call(G))}}class Bi extends X{}class Ss extends Bi{}class co extends Bi{async _call(G){return new yn(await super._call(G))}}class di extends Bi{async _call(G){return new ur(await super._call(G))}}class Mi extends Bi{async _call(G){return new wn(await super._call(G))}}class Ti extends X{}class Yi extends Ti{}class fo extends Ti{async _call(G){return new ur(await super._call(G))}}class po extends Ti{async _call(G){return new wn(await super._call(G))}}class Xt extends Ti{async _call(G){return new yn(await super._call(G))}}class Zi extends X{constructor(ie,Ee,Ze){super(ie,Ee);qe(this,"forward_params",["input_ids","attention_mask","encoder_outputs","decoder_input_ids","decoder_attention_mask","past_key_values"]);this.generation_config=Ze}}class Bo extends Zi{}class No extends Zi{}class ho extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class jo extends ho{}class Uo extends ho{}class mo extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Vo extends mo{}class Br extends mo{}class Rn extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Ue extends Rn{}class W extends Rn{}class fe extends Rn{async _call(G){return new ur(await super._call(G))}}class Pe extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class ze extends Pe{}class Oe extends Pe{}class nt extends Pe{async _call(G){return new ur(await super._call(G))}}class xt extends Pe{}class kt extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Tt extends kt{}class At extends kt{}class Zt extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Pr extends Zt{}class rr extends Zt{}class Gt extends X{}class mr extends Gt{}class kn extends Gt{async _call(G){return new yn(await super._call(G))}}class pn extends Gt{async _call(G){return new ur(await super._call(G))}}class st extends Gt{async _call(G){return new dn(await super._call(G))}}class qn extends Gt{async _call(G){return new wn(await super._call(G))}}class xr extends X{}class an extends xr{}class $n extends xr{async _call(G){return new yn(await super._call(G))}}class Yt extends xr{async _call(G){return new ur(await super._call(G))}}class Bn extends xr{async _call(G){return new dn(await super._call(G))}}class gn extends xr{async _call(G){return new wn(await super._call(G))}}class Tr extends X{}class kr extends Tr{}class Ct extends Tr{async _call(G){return new yn(await super._call(G))}}class wr extends Tr{async _call(G){return new ur(await super._call(G))}}class zr extends Tr{async _call(G){return new dn(await super._call(G))}}class Gr extends Tr{async _call(G){return new wn(await super._call(G))}}class Nn extends X{}class Dt extends Nn{}class Es extends Nn{}class gt extends X{constructor(ie,Ee,Ze){super(ie,Ee);qe(this,"requires_attention_mask",!1);qe(this,"main_input_name","input_features");qe(this,"forward_params",["input_features","attention_mask","decoder_input_ids","decoder_attention_mask","past_key_values"]);this.generation_config=Ze}}class Vt extends gt{}class da extends gt{_prepare_generation_config(G,ie){return super._prepare_generation_config(G,ie,P.WhisperGenerationConfig)}_retrieve_init_tokens(G){const ie=[G.decoder_start_token_id];let Ee=G.language;const Ze=G.task;if(G.is_multilingual){Ee||(console.warn("No language specified - defaulting to English (en)."),Ee="en");const _t=`<|${(0,y.whisper_language_to_code)(Ee)}|>`;ie.push(G.lang_to_id[_t]),ie.push(G.task_to_id[Ze??"transcribe"])}else if(Ee||Ze)throw new Error("Cannot specify `task` or `language` for an English-only model. If the model is intended to be multilingual, pass `is_multilingual=true` to generate, or update the generation config.");return!G.return_timestamps&&G.no_timestamps_token_id&&ie.at(-1)!==G.no_timestamps_token_id?ie.push(G.no_timestamps_token_id):G.return_timestamps&&ie.at(-1)===G.no_timestamps_token_id&&(console.warn("<|notimestamps|> prompt token is removed from generation_config since `return_timestamps` is set to `true`."),ie.pop()),ie.filter(it=>it!=null)}async generate({inputs:G=null,generation_config:ie=null,logits_processor:Ee=null,stopping_criteria:Ze=null,...it}){ie=this._prepare_generation_config(ie,it);const _t=it.decoder_input_ids??this._retrieve_init_tokens(ie);if(ie.return_timestamps&&(Ee??(Ee=new g.LogitsProcessorList),Ee.push(new g.WhisperTimeStampLogitsProcessor(ie,_t))),ie.begin_suppress_tokens&&(Ee??(Ee=new g.LogitsProcessorList),Ee.push(new g.SuppressTokensAtBeginLogitsProcessor(ie.begin_suppress_tokens,_t.length))),ie.return_token_timestamps){if(!ie.alignment_heads)throw new Error("Model generation config has no `alignment_heads`, token-level timestamps not available. See https://gist.github.com/hollance/42e32852f24243b748ae6bc1f985b13a on how to add this property to the generation config.");ie.task==="translate"&&console.warn("Token-level timestamps may not be reliable for task 'translate'."),ie.output_attentions=!0,ie.return_dict_in_generate=!0}const Et=await super.generate({inputs:G,generation_config:ie,logits_processor:Ee,decoder_input_ids:_t,...it});return ie.return_token_timestamps&&(Et.token_timestamps=this._extract_token_timestamps(Et,ie.alignment_heads,ie.num_frames)),Et}_extract_token_timestamps(G,ie,Ee=null,Ze=.02){if(!G.cross_attentions)throw new Error("Model outputs must contain cross attentions to extract timestamps. This is most likely because the model was not exported with `output_attentions=True`.");Ee==null&&console.warn("`num_frames` has not been set, meaning the entire audio will be analyzed. This may lead to inaccurate token-level timestamps for short audios (< 30 seconds).");let it=this.config.median_filter_width;it===void 0&&(console.warn("Model config has no `median_filter_width`, using default value of 7."),it=7);const _t=G.cross_attentions,Et=Array.from({length:this.config.decoder_layers},(gr,br)=>(0,w.cat)(_t.map(Dr=>Dr[br]),2)),Wt=(0,w.stack)(ie.map(([gr,br])=>{if(gr>=Et.length)throw new Error(`Layer index ${gr} is out of bounds for cross attentions (length ${Et.length}).`);return Ee?Et[gr].slice(null,br,null,[0,Ee]):Et[gr].slice(null,br)})).transpose(1,0,2,3),[cr,sr]=(0,w.std_mean)(Wt,-2,0,!0),$r=Wt.clone();for(let gr=0;gr<$r.dims[0];++gr){const br=$r[gr];for(let Dr=0;Dr<br.dims[0];++Dr){const En=br[Dr],An=cr[gr][Dr][0].data,Ei=sr[gr][Dr][0].data;for(let vn=0;vn<En.dims[0];++vn){let ln=En[vn].data;for(let bn=0;bn<ln.length;++bn)ln[bn]=(ln[bn]-Ei[bn])/An[bn];ln.set((0,C.medianFilter)(ln,it))}}}const dr=[(0,w.mean)($r,1)],_r=G.sequences.dims,fr=new w.Tensor("float32",new Float32Array(_r[0]*_r[1]),_r);for(let gr=0;gr<_r[0];++gr){const br=dr[gr].neg().squeeze_(0),[Dr,En]=(0,C.dynamic_time_warping)(br.tolist()),An=Array.from({length:Dr.length-1},(ln,bn)=>Dr[bn+1]-Dr[bn]),Ei=(0,_.mergeArrays)([1],An).map(ln=>!!ln),vn=[];for(let ln=0;ln<Ei.length;++ln)Ei[ln]&&vn.push(En[ln]*Ze);fr[gr].data.set(vn,1)}return fr}}class fa extends X{constructor(ie,Ee,Ze){super(ie,Ee);qe(this,"main_input_name","pixel_values");qe(this,"forward_params",["pixel_values","input_ids","encoder_hidden_states","past_key_values"]);this.generation_config=Ze}}class su extends X{constructor(ie,Ee,Ze){super(ie,Ee);qe(this,"forward_params",["input_ids","pixel_values","attention_mask","position_ids","past_key_values"]);this.generation_config=Ze}}class go extends su{_merge_input_ids_with_image_features({inputs_embeds:G,image_features:ie,input_ids:Ee,attention_mask:Ze}){const it=this.config.image_token_index,Et=Ee.tolist().map(dr=>dr.findIndex(_r=>_r==it)),Wt=Et.every(dr=>dr===-1),cr=Et.every(dr=>dr!==-1);if(!Wt&&!cr)throw new Error("Every input should contain either 0 or 1 image token.");if(Wt)return{inputs_embeds:G,attention_mask:Ze};const sr=[],$r=[];for(let dr=0;dr<Et.length;++dr){const _r=Et[dr],fr=G[dr],gr=ie[dr],br=Ze[dr];sr.push((0,w.cat)([fr.slice([0,_r]),gr,fr.slice([_r+1,fr.dims[0]])],0)),$r.push((0,w.cat)([br.slice([0,_r]),(0,w.ones)([gr.dims[0]]),br.slice([_r+1,br.dims[0]])],0))}return{inputs_embeds:(0,w.stack)(sr,0),attention_mask:(0,w.stack)($r,0)}}}class or extends go{}class au extends X{constructor(ie,Ee,Ze){super(ie,Ee);qe(this,"forward_params",["input_ids","inputs_embeds","attention_mask","pixel_values","encoder_outputs","decoder_input_ids","decoder_inputs_embeds","decoder_attention_mask","past_key_values"]);qe(this,"main_input_name","inputs_embeds");this.generation_config=Ze}}class pa extends au{_merge_input_ids_with_image_features({inputs_embeds:G,image_features:ie,input_ids:Ee,attention_mask:Ze}){return{inputs_embeds:(0,w.cat)([ie,G],1),attention_mask:(0,w.cat)([(0,w.ones)(ie.dims.slice(0,2)),Ze],1)}}async _prepare_inputs_embeds({input_ids:G,pixel_values:ie,inputs_embeds:Ee,attention_mask:Ze}){if(!G&&!ie)throw new Error("Either `input_ids` or `pixel_values` should be provided.");let it,_t;return G&&(it=await this.encode_text({input_ids:G})),ie&&(_t=await this.encode_image({pixel_values:ie})),it&&_t?{inputs_embeds:Ee,attention_mask:Ze}=this._merge_input_ids_with_image_features({inputs_embeds:it,image_features:_t,input_ids:G,attention_mask:Ze}):Ee=it||_t,{inputs_embeds:Ee,attention_mask:Ze}}async forward({input_ids:G,pixel_values:ie,attention_mask:Ee,decoder_input_ids:Ze,decoder_attention_mask:it,encoder_outputs:_t,past_key_values:Et,inputs_embeds:Wt,decoder_inputs_embeds:cr}){if(Wt||({inputs_embeds:Wt,attention_mask:Ee}=await this._prepare_inputs_embeds({input_ids:G,pixel_values:ie,inputs_embeds:Wt,attention_mask:Ee})),!_t){let{last_hidden_state:dr}=await R(this,{inputs_embeds:Wt,attention_mask:Ee});_t=dr}if(!cr){if(!Ze)throw new Error("Either `decoder_input_ids` or `decoder_inputs_embeds` should be provided.");cr=await this.encode_text({input_ids:Ze})}return await Me(this,{inputs_embeds:cr,attention_mask:it,encoder_attention_mask:Ee,encoder_hidden_states:_t,past_key_values:Et},!0)}}class Wo extends X{}class lu extends Wo{}class fi extends Wo{static async from_pretrained(G,ie={}){return ie.model_file_name??(ie.model_file_name="text_model"),super.from_pretrained(G,ie)}}class uu extends Wo{static async from_pretrained(G,ie={}){return ie.model_file_name??(ie.model_file_name="vision_model"),super.from_pretrained(G,ie)}}class ha extends X{}class _o extends ha{}class cu extends ha{static async from_pretrained(G,ie={}){return ie.model_file_name??(ie.model_file_name="text_model"),super.from_pretrained(G,ie)}}class du extends Wo{static async from_pretrained(G,ie={}){return ie.model_file_name??(ie.model_file_name="vision_model"),super.from_pretrained(G,ie)}}class fu extends X{}class pu extends fu{}class ma extends X{}class hu extends ma{}class mu extends ma{}class ga extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class gu extends ga{}class _u extends ga{}class Hn extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class yu extends Hn{}class wu extends Hn{}class _a extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class vu extends _a{}class bu extends _a{}class ya extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class xu extends ya{}class Mu extends ya{}class wa extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Tu extends wa{}class ep extends wa{}class Kn extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class ku extends Kn{}class Cs extends Kn{}class Ps extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class ni extends Ps{}class Su extends Ps{}class va extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Eu extends va{}class Cu extends va{}class ba extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Pu extends ba{}class $u extends ba{}class xa extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Au extends xa{}class Iu extends xa{}class Qn extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Fu extends Qn{}class zu extends Qn{}class Ma extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Ou extends Ma{}class Du extends Ma{}class Ta extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Lu extends Ta{}class Ru extends Ta{}class ka extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Bu extends ka{}class Sa extends ka{}class $s extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Nu extends $s{}class ju extends $s{}class As extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class tp extends As{}class Uu extends As{}class Ea extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Vu extends Ea{}class Wu extends Ea{}class yo extends X{}class Gu extends yo{}class qu extends yo{async _call(G){return new ur(await super._call(G))}}class Is extends X{}class Hu extends Is{}class Ku extends Is{async _call(G){return new ur(await super._call(G))}}class Qu extends X{}class Xu extends Qu{async _call(G){return new ef(await super._call(G))}}class Yu extends X{}class Zu extends Yu{}class Ju extends Yu{async _call(G){return new ur(await super._call(G))}}class Ca extends X{}class rp extends Ca{}class ec extends Ca{async _call(G){return new ur(await super._call(G))}}class vr extends X{}class tc extends vr{}class rc extends vr{}class Pa extends X{}class nc extends Pa{}class ic extends Pa{}class $a extends X{}class oc extends $a{}class sc extends $a{async _call(G){return new ur(await super._call(G))}}class Fs extends X{}class ac extends Fs{}class lc extends Fs{async _call(G){return new Aa(await super._call(G))}}class uc extends Fs{async _call(G){return new cc(await super._call(G))}}class Aa extends me{constructor({logits:G,pred_boxes:ie}){super(),this.logits=G,this.pred_boxes=ie}}class cc extends me{constructor({logits:G,pred_boxes:ie,pred_masks:Ee}){super(),this.logits=G,this.pred_boxes=ie,this.pred_masks=Ee}}class wo extends X{}class dc extends wo{}class zs extends wo{async _call(G){return new fc(await super._call(G))}}class fc extends me{constructor({logits:G,pred_boxes:ie}){super(),this.logits=G,this.pred_boxes=ie}}class Ia extends X{}class pc extends Ia{}class hc extends Ia{async _call(G){return new mc(await super._call(G))}}class mc extends Aa{}class Fa extends X{}class gc extends Fa{}class _c extends Fa{async _call(G){return new ur(await super._call(G))}}class za extends X{}class yc extends za{}class wc extends za{async _call(G){return new ur(await super._call(G))}}class Oa extends X{}class vc extends Oa{}class bc extends Oa{async _call(G){return new ur(await super._call(G))}}class Da extends X{}class xc extends Da{}class La extends Da{}class Ra extends X{}class Ba extends Ra{}class Na extends Ra{}class Mc extends X{}class Tc extends Mc{}class ja extends X{}class kc extends ja{}class Sc extends ja{}class Ec extends X{}class Ua extends Ec{}class Va extends X{}class Cc extends Va{}class Pc extends Va{async _call(G){return new ur(await super._call(G))}}class $c extends X{}class Ac extends $c{}class Ic extends $c{async _call(G){return new ur(await super._call(G))}}class Xn extends X{}class Fc extends Xn{}class zc extends Xn{async _call(G){return new ur(await super._call(G))}}class Wa extends X{}class Oc extends Wa{}class Dc extends Wa{async _call(G){return new Lc(await super._call(G))}}class Lc extends me{constructor({logits:G,pred_boxes:ie}){super(),this.logits=G,this.pred_boxes=ie}}class Rc extends X{}class Bc extends Rc{async get_image_embeddings({pixel_values:G}){return await R(this,{pixel_values:G})}async forward(G){if((!G.image_embeddings||!G.image_positional_embeddings)&&(G={...G,...await this.get_image_embeddings(G)}),!G.input_labels&&G.input_points){const Ee=G.input_points.dims.slice(0,-1),Ze=Ee.reduce((it,_t)=>it*_t,1);G.input_labels=new w.Tensor("int64",new BigInt64Array(Ze).fill(1n),Ee)}const ie={image_embeddings:G.image_embeddings,image_positional_embeddings:G.image_positional_embeddings};return G.input_points&&(ie.input_points=G.input_points),G.input_labels&&(ie.input_labels=G.input_labels),G.input_boxes&&(ie.input_boxes=G.input_boxes),await Y(this.sessions.prompt_encoder_mask_decoder,ie)}async _call(G){return new Nc(await super._call(G))}}class Nc extends me{constructor({iou_scores:G,pred_masks:ie}){super(),this.iou_scores=G,this.pred_masks=ie}}class Ga extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class np extends Ga{}class jc extends Ga{}class qa extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Uc extends qa{}class Vc extends qa{}class Ni extends X{}class Wc extends Ni{}class ip extends Ni{async _call(G){return new Ji(await super._call(G))}}class ji extends Ni{async _call(G){return new ur(await super._call(G))}}class Ui extends Ni{async _call(G){return new dn(await super._call(G))}}class ki extends X{}class Ha extends ki{}class Vi extends ki{async _call(G){return new dn(await super._call(G))}}class _n extends X{}class Ka extends _n{}class vo extends X{}class Qa extends vo{}class Gc extends vo{async _call(G){return new Ji(await super._call(G))}}class qc extends vo{async _call(G){return new ur(await super._call(G))}}class Go extends X{}class Os extends Go{}class Xa extends Go{async _call(G){return new Ji(await super._call(G))}}class Hc extends Go{async _call(G){return new ur(await super._call(G))}}class Ds extends Go{async _call(G){return new dn(await super._call(G))}}class Ls extends X{}class Ya extends Ls{}class Rs extends Ls{async _call(G){return new Ji(await super._call(G))}}class Kc extends Ls{async _call(G){return new ur(await super._call(G))}}class op extends X{}class sp extends Ni{}class Qc extends Ni{async _call(G){return new Ji(await super._call(G))}}class Za extends Ni{async _call(G){return new ur(await super._call(G))}}class Si extends X{}class Xc extends Si{}class Ja extends Si{async _call(G){return new Ji(await super._call(G))}}class Yc extends Si{async _call(G){return new ur(await super._call(G))}}class Zc extends Si{async _call(G){return new Jd(await super._call(G))}}class Jc extends Si{async _call(G){return new dn(await super._call(G))}}class el extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class ed extends el{}class td extends el{}class ap extends el{async generate_speech(G,ie,{threshold:Ee=.5,minlenratio:Ze=0,maxlenratio:it=20,vocoder:_t=null}={}){const Et={input_ids:G},{encoder_outputs:Wt,encoder_attention_mask:cr}=await R(this,Et),sr=Wt.dims[1]/this.config.reduction_factor,$r=Math.floor(sr*it),dr=Math.floor(sr*Ze),_r=this.config.num_mel_bins;let fr=[],gr=null,br=null,Dr=0;for(;;){++Dr;const Ei=ee(!!br);let vn;br?vn=br.output_sequence_out:vn=new w.Tensor("float32",new Float32Array(_r),[1,1,_r]);let ln={use_cache_branch:Ei,output_sequence:vn,encoder_attention_mask:cr,speaker_embeddings:ie,encoder_hidden_states:Wt};this.addPastKeyValues(ln,gr),br=await Y(this.sessions.decoder_model_merged,ln),gr=this.getPastKeyValues(br,gr);const{prob:bn,spectrum:Ws}=br;if(fr.push(Ws),Dr>=dr&&(Array.from(bn.data).filter(Gs=>Gs>=Ee).length>0||Dr>=$r))break}const En=(0,w.cat)(fr),{waveform:An}=await Y(_t.sessions.model,{spectrogram:En});return{spectrogram:En,waveform:An}}}class tl extends X{constructor(){super(...arguments);qe(this,"main_input_name","spectrogram")}}class rd extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class nd extends rd{}class rl extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class Bs extends rl{}class Ns extends rl{}class nl extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class js extends nl{}class il extends nl{}class ol extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class id extends ol{}class od extends ol{}class qo extends X{}class sd extends qo{}class ad extends qo{static async from_pretrained(G,ie={}){return ie.model_file_name??(ie.model_file_name="text_model"),super.from_pretrained(G,ie)}}class ld extends qo{static async from_pretrained(G,ie={}){return ie.model_file_name??(ie.model_file_name="audio_model"),super.from_pretrained(G,ie)}}class lp extends X{}class sl extends lp{async _call(G){return new Mp(await super._call(G))}}class Ho extends X{}class fm extends Ho{}class ud extends Ho{}class cd extends Ho{}class al extends X{constructor(G,ie,Ee){super(G,ie),this.generation_config=Ee}}class ll extends al{}class dd extends al{}class ul extends X{}class fd extends ul{}class pd extends ul{async _call(G){return new ur(await super._call(G))}}class cl extends X{}class up extends cl{}class pm extends cl{}class dl extends X{constructor(ie,Ee,Ze){super(ie,Ee);qe(this,"forward_params",["input_ids","attention_mask","encoder_outputs","decoder_input_ids","decoder_attention_mask","past_key_values"]);this.generation_config=Ze}_apply_and_filter_by_delay_pattern_mask(ie){const[Ee,Ze]=ie.dims,it=this.config.decoder.num_codebooks,_t=Ze-it;let Et=0;for(let sr=0;sr<ie.size;++sr){if(ie.data[sr]===this.config.decoder.pad_token_id)continue;const $r=sr%Ze,dr=Math.floor(sr/Ze)%it,_r=$r-dr;_r>0&&_r<=_t&&(ie.data[Et++]=ie.data[sr])}const Wt=Math.floor(Ee/it),cr=Et/(Wt*it);return new w.Tensor(ie.type,ie.data.slice(0,Et),[Wt,it,cr])}prepare_inputs_for_generation(ie,Ee,Ze){let it=structuredClone(ie);for(let Et=0;Et<it.length;++Et)for(let Wt=0;Wt<it[Et].length;++Wt)Et%this.config.decoder.num_codebooks>=Wt&&(it[Et][Wt]=BigInt(this.config.decoder.pad_token_id));return Ze.guidance_scale!==null&&Ze.guidance_scale>1&&(it=it.concat(it)),super.prepare_inputs_for_generation(it,Ee,Ze)}async generate(ie){const Ee=await super.generate(ie),Ze=this._apply_and_filter_by_delay_pattern_mask(Ee).unsqueeze_(0),{audio_values:it}=await Y(this.sessions.encodec_decode,{audio_codes:Ze});return it}}class fl extends X{}class hd extends fl{}class cp extends fl{async _call(G){return new ur(await super._call(G))}}class pl extends X{}class md extends pl{}class gd extends pl{async _call(G){return new ur(await super._call(G))}}class hl extends X{}class _d extends hl{}class dp extends hl{async _call(G){return new ur(await super._call(G))}}class Ko extends X{}class Qo extends Ko{}class ml extends Ko{async _call(G){return new ur(await super._call(G))}}class Or{static async from_pretrained(G,{progress_callback:ie=null,config:Ee=null,cache_dir:Ze=null,local_files_only:it=!1,revision:_t="main",model_file_name:Et=null,subfolder:Wt="onnx",device:cr=null,dtype:sr=null,use_external_data_format:$r=null,session_options:dr={}}={}){let _r={progress_callback:ie,config:Ee,cache_dir:Ze,local_files_only:it,revision:_t,model_file_name:Et,subfolder:Wt,device:cr,dtype:sr,use_external_data_format:$r,session_options:dr};if(_r.config=await o.AutoConfig.from_pretrained(G,_r),!this.MODEL_CLASS_MAPPINGS)throw new Error("`MODEL_CLASS_MAPPINGS` not implemented for this type of `AutoClass`: "+this.name);for(let fr of this.MODEL_CLASS_MAPPINGS){const gr=fr.get(_r.config.model_type);if(gr)return await gr[1].from_pretrained(G,_r)}if(this.BASE_IF_FAIL)return console.warn(`Unknown model class "${_r.config.model_type}", attempting to construct from base class.`),await X.from_pretrained(G,_r);throw Error(`Unsupported model type: ${_r.config.model_type}`)}}qe(Or,"MODEL_CLASS_MAPPINGS",null),qe(Or,"BASE_IF_FAIL",!1);const fp=new Map([["bert",["BertModel",Be]],["nomic_bert",["NomicBertModel",je]],["roformer",["RoFormerModel",tt]],["electra",["ElectraModel",ke]],["esm",["EsmModel",sn]],["convbert",["ConvBertModel",we]],["camembert",["CamembertModel",ve]],["deberta",["DebertaModel",ht]],["deberta-v2",["DebertaV2Model",Ot]],["mpnet",["MPNetModel",ks]],["albert",["AlbertModel",Yi]],["distilbert",["DistilBertModel",Er]],["roberta",["RobertaModel",mr]],["xlm",["XLMModel",an]],["xlm-roberta",["XLMRobertaModel",kr]],["clap",["ClapModel",sd]],["clip",["CLIPModel",lu]],["clipseg",["CLIPSegModel",hu]],["chinese_clip",["ChineseCLIPModel",pu]],["siglip",["SiglipModel",_o]],["mobilebert",["MobileBertModel",Wr]],["squeezebert",["SqueezeBertModel",Ss]],["wav2vec2",["Wav2Vec2Model",Wc]],["wav2vec2-bert",["Wav2Vec2BertModel",Ya]],["unispeech",["UniSpeechModel",Qa]],["unispeech-sat",["UniSpeechSatModel",Os]],["hubert",["HubertModel",sp]],["wavlm",["WavLMModel",Xc]],["audio-spectrogram-transformer",["ASTModel",Dt]],["vits",["VitsModel",sl]],["pyannote",["PyAnnoteModel",Ha]],["wespeaker-resnet",["WeSpeakerResNetModel",Ka]],["detr",["DetrModel",ac]],["rt_detr",["RTDetrModel",dc]],["table-transformer",["TableTransformerModel",pc]],["vit",["ViTModel",Gu]],["fastvit",["FastViTModel",Hu]],["mobilevit",["MobileViTModel",Zu]],["mobilevitv2",["MobileViTV2Model",rp]],["owlvit",["OwlViTModel",tc]],["owlv2",["Owlv2Model",nc]],["beit",["BeitModel",oc]],["deit",["DeiTModel",gc]],["convnext",["ConvNextModel",Cc]],["convnextv2",["ConvNextV2Model",Ac]],["dinov2",["Dinov2Model",Fc]],["resnet",["ResNetModel",yc]],["swin",["SwinModel",vc]],["swin2sr",["Swin2SRModel",xc]],["donut-swin",["DonutSwinModel",Ua]],["yolos",["YolosModel",Oc]],["dpt",["DPTModel",Ba]],["glpn",["GLPNModel",kc]],["hifigan",["SpeechT5HifiGan",tl]],["efficientnet",["EfficientNetModel",fd]],["mobilenet_v1",["MobileNetV1Model",hd]],["mobilenet_v2",["MobileNetV2Model",md]],["mobilenet_v3",["MobileNetV3Model",_d]],["mobilenet_v4",["MobileNetV4Model",Qo]]]),pp=new Map([["t5",["T5Model",Bo]],["longt5",["LongT5Model",jo]],["mt5",["MT5Model",Vo]],["bart",["BartModel",Ue]],["mbart",["MBartModel",ze]],["marian",["MarianModel",np]],["whisper",["WhisperModel",Vt]],["m2m_100",["M2M100Model",Uc]],["blenderbot",["BlenderbotModel",Tt]],["blenderbot-small",["BlenderbotSmallModel",Pr]]]),hp=new Map([["bloom",["BloomModel",Nu]],["gpt2",["GPT2Model",gu]],["gptj",["GPTJModel",xu]],["gpt_bigcode",["GPTBigCodeModel",Tu]],["gpt_neo",["GPTNeoModel",yu]],["gpt_neox",["GPTNeoXModel",vu]],["codegen",["CodeGenModel",ku]],["llama",["LlamaModel",ni]],["cohere",["CohereModel",Eu]],["gemma",["GemmaModel",Pu]],["gemma2",["Gemma2Model",Au]],["openelm",["OpenELMModel",Fu]],["qwen2",["Qwen2Model",Ou]],["phi",["PhiModel",Lu]],["phi3",["Phi3Model",Bu]],["mpt",["MptModel",tp]],["opt",["OPTModel",Vu]],["mistral",["MistralModel",Bs]],["starcoder2",["Starcoder2Model",js]],["falcon",["FalconModel",id]],["stablelm",["StableLmModel",ll]]]),Us=new Map([["speecht5",["SpeechT5ForSpeechToText",td]],["whisper",["WhisperForConditionalGeneration",da]]]),yd=new Map([["speecht5",["SpeechT5ForTextToSpeech",ap]]]),wd=new Map([["vits",["VitsModel",sl]],["musicgen",["MusicgenForConditionalGeneration",dl]]]),vd=new Map([["bert",["BertForSequenceClassification",ot]],["roformer",["RoFormerForSequenceClassification",Ae]],["electra",["ElectraForSequenceClassification",ut]],["esm",["EsmForSequenceClassification",bi]],["convbert",["ConvBertForSequenceClassification",J]],["camembert",["CamembertForSequenceClassification",He]],["deberta",["DebertaForSequenceClassification",wt]],["deberta-v2",["DebertaV2ForSequenceClassification",Kt]],["mpnet",["MPNetForSequenceClassification",Do]],["albert",["AlbertForSequenceClassification",fo]],["distilbert",["DistilBertForSequenceClassification",Qr]],["roberta",["RobertaForSequenceClassification",pn]],["xlm",["XLMForSequenceClassification",Yt]],["xlm-roberta",["XLMRobertaForSequenceClassification",wr]],["bart",["BartForSequenceClassification",fe]],["mbart",["MBartForSequenceClassification",nt]],["mobilebert",["MobileBertForSequenceClassification",Fr]],["squeezebert",["SqueezeBertForSequenceClassification",di]]]),mp=new Map([["bert",["BertForTokenClassification",dt]],["roformer",["RoFormerForTokenClassification",$e]],["electra",["ElectraForTokenClassification",Je]],["esm",["EsmForTokenClassification",Nr]],["convbert",["ConvBertForTokenClassification",L]],["camembert",["CamembertForTokenClassification",Xe]],["deberta",["DebertaForTokenClassification",St]],["deberta-v2",["DebertaV2ForTokenClassification",Qt]],["mpnet",["MPNetForTokenClassification",Lo]],["distilbert",["DistilBertForTokenClassification",Cr]],["roberta",["RobertaForTokenClassification",st]],["xlm",["XLMForTokenClassification",Bn]],["xlm-roberta",["XLMRobertaForTokenClassification",zr]]]),gl=new Map([["t5",["T5ForConditionalGeneration",No]],["longt5",["LongT5ForConditionalGeneration",Uo]],["mt5",["MT5ForConditionalGeneration",Br]],["bart",["BartForConditionalGeneration",W]],["mbart",["MBartForConditionalGeneration",Oe]],["marian",["MarianMTModel",jc]],["m2m_100",["M2M100ForConditionalGeneration",Vc]],["blenderbot",["BlenderbotForConditionalGeneration",At]],["blenderbot-small",["BlenderbotSmallForConditionalGeneration",rr]]]),Vs=new Map([["bloom",["BloomForCausalLM",ju]],["gpt2",["GPT2LMHeadModel",_u]],["gptj",["GPTJForCausalLM",Mu]],["gpt_bigcode",["GPTBigCodeForCausalLM",ep]],["gpt_neo",["GPTNeoForCausalLM",wu]],["gpt_neox",["GPTNeoXForCausalLM",bu]],["codegen",["CodeGenForCausalLM",Cs]],["llama",["LlamaForCausalLM",Su]],["cohere",["CohereForCausalLM",Cu]],["gemma",["GemmaForCausalLM",$u]],["gemma2",["Gemma2ForCausalLM",Iu]],["openelm",["OpenELMForCausalLM",zu]],["qwen2",["Qwen2ForCausalLM",Du]],["phi",["PhiForCausalLM",Ru]],["phi3",["Phi3ForCausalLM",Sa]],["mpt",["MptForCausalLM",Uu]],["opt",["OPTForCausalLM",Wu]],["mbart",["MBartForCausalLM",xt]],["mistral",["MistralForCausalLM",Ns]],["starcoder2",["Starcoder2ForCausalLM",il]],["falcon",["FalconForCausalLM",od]],["trocr",["TrOCRForCausalLM",nd]],["stablelm",["StableLmForCausalLM",dd]]]),bd=new Map([["bert",["BertForMaskedLM",We]],["roformer",["RoFormerForMaskedLM",A]],["electra",["ElectraForMaskedLM",Ne]],["esm",["EsmForMaskedLM",Li]],["convbert",["ConvBertForMaskedLM",B]],["camembert",["CamembertForMaskedLM",Re]],["deberta",["DebertaForMaskedLM",Mt]],["deberta-v2",["DebertaV2ForMaskedLM",Ut]],["mpnet",["MPNetForMaskedLM",Oo]],["albert",["AlbertForMaskedLM",Xt]],["distilbert",["DistilBertForMaskedLM",Pt]],["roberta",["RobertaForMaskedLM",kn]],["xlm",["XLMWithLMHeadModel",$n]],["xlm-roberta",["XLMRobertaForMaskedLM",Ct]],["mobilebert",["MobileBertForMaskedLM",ci]],["squeezebert",["SqueezeBertForMaskedLM",co]]]),xd=new Map([["bert",["BertForQuestionAnswering",Ge]],["roformer",["RoFormerForQuestionAnswering",se]],["electra",["ElectraForQuestionAnswering",Ve]],["convbert",["ConvBertForQuestionAnswering",ue]],["camembert",["CamembertForQuestionAnswering",rt]],["deberta",["DebertaForQuestionAnswering",Rt]],["deberta-v2",["DebertaV2ForQuestionAnswering",Jt]],["mpnet",["MPNetForQuestionAnswering",Ro]],["albert",["AlbertForQuestionAnswering",po]],["distilbert",["DistilBertForQuestionAnswering",mt]],["roberta",["RobertaForQuestionAnswering",qn]],["xlm",["XLMForQuestionAnswering",gn]],["xlm-roberta",["XLMRobertaForQuestionAnswering",Gr]],["mobilebert",["MobileBertForQuestionAnswering",Ri]],["squeezebert",["SqueezeBertForQuestionAnswering",Mi]]]),_l=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",fa]]]),hm=new Map([["llava",["LlavaForConditionalGeneration",go]],["moondream1",["Moondream1ForConditionalGeneration",or]],["florence2",["Florence2ForConditionalGeneration",pa]]]),gp=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",fa]]]),Md=new Map([["vit",["ViTForImageClassification",qu]],["fastvit",["FastViTForImageClassification",Ku]],["mobilevit",["MobileViTForImageClassification",Ju]],["mobilevitv2",["MobileViTV2ForImageClassification",ec]],["beit",["BeitForImageClassification",sc]],["deit",["DeiTForImageClassification",_c]],["convnext",["ConvNextForImageClassification",Pc]],["convnextv2",["ConvNextV2ForImageClassification",Ic]],["dinov2",["Dinov2ForImageClassification",zc]],["resnet",["ResNetForImageClassification",wc]],["swin",["SwinForImageClassification",bc]],["segformer",["SegformerForImageClassification",ud]],["efficientnet",["EfficientNetForImageClassification",pd]],["mobilenet_v1",["MobileNetV1ForImageClassification",cp]],["mobilenet_v2",["MobileNetV2ForImageClassification",gd]],["mobilenet_v3",["MobileNetV3ForImageClassification",dp]],["mobilenet_v4",["MobileNetV4ForImageClassification",ml]]]),_p=new Map([["detr",["DetrForObjectDetection",lc]],["rt_detr",["RTDetrForObjectDetection",zs]],["table-transformer",["TableTransformerForObjectDetection",hc]],["yolos",["YolosForObjectDetection",Dc]]]),Td=new Map([["owlvit",["OwlViTForObjectDetection",rc]],["owlv2",["Owlv2ForObjectDetection",ic]]]),kd=new Map([["detr",["DetrForSegmentation",uc]],["clipseg",["CLIPSegForImageSegmentation",mu]]]),Sd=new Map([["segformer",["SegformerForSemanticSegmentation",cd]]]),Ed=new Map([["sam",["SamModel",Bc]]]),yp=new Map([["wav2vec2",["Wav2Vec2ForCTC",ip]],["wav2vec2-bert",["Wav2Vec2BertForCTC",Rs]],["unispeech",["UniSpeechForCTC",Gc]],["unispeech-sat",["UniSpeechSatForCTC",Xa]],["wavlm",["WavLMForCTC",Ja]],["hubert",["HubertForCTC",Qc]]]),Cd=new Map([["wav2vec2",["Wav2Vec2ForSequenceClassification",ji]],["wav2vec2-bert",["Wav2Vec2BertForSequenceClassification",Kc]],["unispeech",["UniSpeechForSequenceClassification",qc]],["unispeech-sat",["UniSpeechSatForSequenceClassification",Hc]],["wavlm",["WavLMForSequenceClassification",Yc]],["hubert",["HubertForSequenceClassification",Za]],["audio-spectrogram-transformer",["ASTForAudioClassification",Es]]]),Pd=new Map([["wavlm",["WavLMForXVector",Zc]]]),$d=new Map([["unispeech-sat",["UniSpeechSatForAudioFrameClassification",Ds]],["wavlm",["WavLMForAudioFrameClassification",Jc]],["wav2vec2",["Wav2Vec2ForAudioFrameClassification",Ui]],["pyannote",["PyAnnoteForAudioFrameClassification",Vi]]]),Ad=new Map([["vitmatte",["VitMatteForImageMatting",Xu]]]),wp=new Map([["swin2sr",["Swin2SRForImageSuperResolution",La]]]),Id=new Map([["dpt",["DPTForDepthEstimation",Na]],["depth_anything",["DepthAnythingForDepthEstimation",Tc]],["glpn",["GLPNForDepthEstimation",Sc]]]),Fd=new Map([["clip",["CLIPVisionModelWithProjection",uu]],["siglip",["SiglipVisionModel",du]]]),zd=[[fp,x.EncoderOnly],[pp,x.EncoderDecoder],[hp,x.DecoderOnly],[vd,x.EncoderOnly],[mp,x.EncoderOnly],[gl,x.Seq2Seq],[Us,x.Seq2Seq],[Vs,x.DecoderOnly],[bd,x.EncoderOnly],[xd,x.EncoderOnly],[_l,x.Vision2Seq],[hm,x.ImageTextToText],[Md,x.EncoderOnly],[kd,x.EncoderOnly],[Sd,x.EncoderOnly],[Ad,x.EncoderOnly],[wp,x.EncoderOnly],[Id,x.EncoderOnly],[_p,x.EncoderOnly],[Td,x.EncoderOnly],[Ed,x.MaskGeneration],[yp,x.EncoderOnly],[Cd,x.EncoderOnly],[yd,x.Seq2Seq],[wd,x.EncoderOnly],[Pd,x.EncoderOnly],[$d,x.EncoderOnly],[Fd,x.EncoderOnly]];for(const[V,G]of zd)for(const[ie,Ee]of V.values())I.set(ie,G),O.set(Ee,ie),U.set(ie,Ee);const vp=[["MusicgenForConditionalGeneration",dl,x.Musicgen],["CLIPTextModelWithProjection",fi,x.EncoderOnly],["SiglipTextModel",cu,x.EncoderOnly],["ClapTextModelWithProjection",ad,x.EncoderOnly],["ClapAudioModelWithProjection",ld,x.EncoderOnly]];for(const[V,G,ie]of vp)I.set(V,ie),O.set(G,V),U.set(V,G);class Od extends Or{}qe(Od,"MODEL_CLASS_MAPPINGS",zd.map(G=>G[0])),qe(Od,"BASE_IF_FAIL",!0);class Sn extends Or{}qe(Sn,"MODEL_CLASS_MAPPINGS",[vd]);class Dd extends Or{}qe(Dd,"MODEL_CLASS_MAPPINGS",[mp]);class Ld extends Or{}qe(Ld,"MODEL_CLASS_MAPPINGS",[gl]);class yl extends Or{}qe(yl,"MODEL_CLASS_MAPPINGS",[Us]);class Rd extends Or{}qe(Rd,"MODEL_CLASS_MAPPINGS",[yd]);class Xo extends Or{}qe(Xo,"MODEL_CLASS_MAPPINGS",[wd]);class Bd extends Or{}qe(Bd,"MODEL_CLASS_MAPPINGS",[Vs]);class Nd extends Or{}qe(Nd,"MODEL_CLASS_MAPPINGS",[bd]);class wl extends Or{}qe(wl,"MODEL_CLASS_MAPPINGS",[xd]);class jd extends Or{}qe(jd,"MODEL_CLASS_MAPPINGS",[_l]);class Ud extends Or{}qe(Ud,"MODEL_CLASS_MAPPINGS",[Md]);class vl extends Or{}qe(vl,"MODEL_CLASS_MAPPINGS",[kd]);class Vd extends Or{}qe(Vd,"MODEL_CLASS_MAPPINGS",[Sd]);class Wd extends Or{}qe(Wd,"MODEL_CLASS_MAPPINGS",[_p]);class Gd extends Or{}qe(Gd,"MODEL_CLASS_MAPPINGS",[Td]);class bl extends Or{}qe(bl,"MODEL_CLASS_MAPPINGS",[Ed]);class qd extends Or{}qe(qd,"MODEL_CLASS_MAPPINGS",[yp]);class Hd extends Or{}qe(Hd,"MODEL_CLASS_MAPPINGS",[Cd]);class xl extends Or{}qe(xl,"MODEL_CLASS_MAPPINGS",[Pd]);class Kd extends Or{}qe(Kd,"MODEL_CLASS_MAPPINGS",[$d]);class bp extends Or{}qe(bp,"MODEL_CLASS_MAPPINGS",[gp]);class Qd extends Or{}qe(Qd,"MODEL_CLASS_MAPPINGS",[Ad]);class Xd extends Or{}qe(Xd,"MODEL_CLASS_MAPPINGS",[wp]);class Yd extends Or{}qe(Yd,"MODEL_CLASS_MAPPINGS",[Id]);class Zd extends Or{}qe(Zd,"MODEL_CLASS_MAPPINGS",[Fd]);class mm extends me{constructor({logits:G,past_key_values:ie,encoder_outputs:Ee,decoder_attentions:Ze=null,cross_attentions:it=null}){super(),this.logits=G,this.past_key_values=ie,this.encoder_outputs=Ee,this.decoder_attentions=Ze,this.cross_attentions=it}}class ur extends me{constructor({logits:G}){super(),this.logits=G}}class Jd extends me{constructor({logits:G,embeddings:ie}){super(),this.logits=G,this.embeddings=ie}}class dn extends me{constructor({logits:G}){super(),this.logits=G}}class yn extends me{constructor({logits:G}){super(),this.logits=G}}class wn extends me{constructor({start_logits:G,end_logits:ie}){super(),this.start_logits=G,this.end_logits=ie}}class Ji extends me{constructor({logits:G}){super(),this.logits=G}}class xp extends me{constructor({logits:G,past_key_values:ie}){super(),this.logits=G,this.past_key_values=ie}}class ef extends me{constructor({alphas:G}){super(),this.alphas=G}}class Mp extends me{constructor({waveform:G,spectrogram:ie}){super(),this.waveform=G,this.spectrogram=ie}}},"./src/models/whisper/common_whisper.js":(e,t,n)=>{n.r(t),n.d(t,{WHISPER_LANGUAGE_MAPPING:()=>a,WHISPER_TO_LANGUAGE_CODE_MAPPING:()=>l,whisper_language_to_code:()=>f});const o=[["en","english"],["zh","chinese"],["de","german"],["es","spanish"],["ru","russian"],["ko","korean"],["fr","french"],["ja","japanese"],["pt","portuguese"],["tr","turkish"],["pl","polish"],["ca","catalan"],["nl","dutch"],["ar","arabic"],["sv","swedish"],["it","italian"],["id","indonesian"],["hi","hindi"],["fi","finnish"],["vi","vietnamese"],["he","hebrew"],["uk","ukrainian"],["el","greek"],["ms","malay"],["cs","czech"],["ro","romanian"],["da","danish"],["hu","hungarian"],["ta","tamil"],["no","norwegian"],["th","thai"],["ur","urdu"],["hr","croatian"],["bg","bulgarian"],["lt","lithuanian"],["la","latin"],["mi","maori"],["ml","malayalam"],["cy","welsh"],["sk","slovak"],["te","telugu"],["fa","persian"],["lv","latvian"],["bn","bengali"],["sr","serbian"],["az","azerbaijani"],["sl","slovenian"],["kn","kannada"],["et","estonian"],["mk","macedonian"],["br","breton"],["eu","basque"],["is","icelandic"],["hy","armenian"],["ne","nepali"],["mn","mongolian"],["bs","bosnian"],["kk","kazakh"],["sq","albanian"],["sw","swahili"],["gl","galician"],["mr","marathi"],["pa","punjabi"],["si","sinhala"],["km","khmer"],["sn","shona"],["yo","yoruba"],["so","somali"],["af","afrikaans"],["oc","occitan"],["ka","georgian"],["be","belarusian"],["tg","tajik"],["sd","sindhi"],["gu","gujarati"],["am","amharic"],["yi","yiddish"],["lo","lao"],["uz","uzbek"],["fo","faroese"],["ht","haitian creole"],["ps","pashto"],["tk","turkmen"],["nn","nynorsk"],["mt","maltese"],["sa","sanskrit"],["lb","luxembourgish"],["my","myanmar"],["bo","tibetan"],["tl","tagalog"],["mg","malagasy"],["as","assamese"],["tt","tatar"],["haw","hawaiian"],["ln","lingala"],["ha","hausa"],["ba","bashkir"],["jw","javanese"],["su","sundanese"]],a=new Map(o),l=new Map([...o.map(([_,h])=>[h,_]),["burmese","my"],["valencian","ca"],["flemish","nl"],["haitian","ht"],["letzeburgesch","lb"],["pushto","ps"],["panjabi","pa"],["moldavian","ro"],["moldovan","ro"],["sinhalese","si"],["castilian","es"]]);function f(_){_=_.toLowerCase();let h=l.get(_);if(h===void 0)if(a.has(_))h=_;else{const M=_.length===2?a.keys():a.values();throw new Error(`Language "${_}" is not supported. Must be one of: ${JSON.stringify(M)}`)}return h}},"./src/models/whisper/generation_whisper.js":(e,t,n)=>{n.r(t),n.d(t,{WhisperGenerationConfig:()=>a});var o=n("./src/generation/configuration_utils.js");class a extends o.GenerationConfig{constructor(){super(...arguments);qe(this,"return_timestamps",null);qe(this,"return_token_timestamps",null);qe(this,"num_frames",null);qe(this,"alignment_heads",null);qe(this,"task",null);qe(this,"language",null);qe(this,"no_timestamps_token_id",null);qe(this,"prompt_ids",null);qe(this,"is_multilingual",null);qe(this,"lang_to_id",null);qe(this,"task_to_id",null);qe(this,"max_initial_timestamp_index",1)}}},"./src/ops/registry.js":(e,t,n)=>{n.r(t),n.d(t,{TensorOpRegistry:()=>f});var o=n("./src/backends/onnx.js"),a=n("./src/utils/tensor.js");const l=async(_,h,g)=>{const M=await(0,o.createInferenceSession)(new Uint8Array(_),h);return async w=>{const C=Object.fromEntries(Object.entries(w).map(([z,S])=>[z,S.ort_tensor])),k=await M.run(C);return Array.isArray(g)?g.map(z=>new a.Tensor(k[z])):new a.Tensor(k[g])}};class f{static get bilinear_interpolate_4d(){return this._bilinear_interpolate_4d||(this._bilinear_interpolate_4d=l([8,9,18,0,58,128,1,10,40,10,1,120,10,0,10,0,10,1,115,18,1,121,34,6,82,101,115,105,122,101,42,17,10,4,109,111,100,101,34,6,108,105,110,101,97,114,160,1,3,18,1,114,90,31,10,1,120,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,90,15,10,1,115,18,10,10,8,8,7,18,4,10,2,8,4,98,31,10,1,121,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,66,2,16,20],this.session_options,"y")),this._bilinear_interpolate_4d}static get bicubic_interpolate_4d(){return this._bicubic_interpolate_4d||(this._bicubic_interpolate_4d=l([8,9,18,0,58,127,10,39,10,1,120,10,0,10,0,10,1,115,18,1,121,34,6,82,101,115,105,122,101,42,16,10,4,109,111,100,101,34,5,99,117,98,105,99,160,1,3,18,1,114,90,31,10,1,120,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,90,15,10,1,115,18,10,10,8,8,7,18,4,10,2,8,4,98,31,10,1,121,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,66,2,16,20],this.session_options,"y")),this._bicubic_interpolate_4d}static get matmul(){return this._matmul||(this._matmul=l([8,9,18,0,58,55,10,17,10,1,97,10,1,98,18,1,99,34,6,77,97,116,77,117,108,18,1,114,90,9,10,1,97,18,4,10,2,8,1,90,9,10,1,98,18,4,10,2,8,1,98,9,10,1,99,18,4,10,2,8,1,66,2,16,20],this.session_options,"c")),this._matmul}static get stft(){return this._stft||(this._stft=l([8,7,18,0,58,148,1,10,38,10,1,115,10,1,106,10,1,119,10,1,108,18,1,111,34,4,83,84,70,84,42,15,10,8,111,110,101,115,105,100,101,100,24,1,160,1,2,18,1,115,90,26,10,1,115,18,21,10,19,8,1,18,15,10,3,18,1,98,10,3,18,1,115,10,3,18,1,99,90,11,10,1,106,18,6,10,4,8,7,18,0,90,16,10,1,119,18,11,10,9,8,1,18,5,10,3,18,1,119,90,11,10,1,108,18,6,10,4,8,7,18,0,98,31,10,1,111,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,102,10,3,18,1,100,10,3,18,1,99,66,2,16,17],this.session_options,"o")),this._stft}static get rfft(){return this._rfft||(this._rfft=l([8,9,18,0,58,97,10,33,10,1,120,10,0,10,1,97,18,1,121,34,3,68,70,84,42,15,10,8,111,110,101,115,105,100,101,100,24,1,160,1,2,18,1,100,90,21,10,1,120,18,16,10,14,8,1,18,10,10,3,18,1,115,10,3,18,1,99,90,11,10,1,97,18,6,10,4,8,7,18,0,98,21,10,1,121,18,16,10,14,8,1,18,10,10,3,18,1,115,10,3,18,1,99,66,2,16,20],this.session_options,"y")),this._rfft}static get top_k(){return this._top_k||(this._top_k=l([8,10,18,0,58,73,10,18,10,1,120,10,1,107,18,1,118,18,1,105,34,4,84,111,112,75,18,1,116,90,9,10,1,120,18,4,10,2,8,1,90,15,10,1,107,18,10,10,8,8,7,18,4,10,2,8,1,98,9,10,1,118,18,4,10,2,8,1,98,9,10,1,105,18,4,10,2,8,7,66,2,16,21],this.session_options,["v","i"])),this._top_k}}qe(f,"session_options",{})},"./src/pipelines.js":(e,t,n)=>{n.r(t),n.d(t,{AudioClassificationPipeline:()=>ee,AutomaticSpeechRecognitionPipeline:()=>R,DepthEstimationPipeline:()=>De,DocumentQuestionAnsweringPipeline:()=>X,FeatureExtractionPipeline:()=>de,FillMaskPipeline:()=>I,ImageClassificationPipeline:()=>Qe,ImageFeatureExtractionPipeline:()=>Ce,ImageSegmentationPipeline:()=>ge,ImageToImagePipeline:()=>Ke,ImageToTextPipeline:()=>Me,ObjectDetectionPipeline:()=>ae,Pipeline:()=>S,QuestionAnsweringPipeline:()=>x,SummarizationPipeline:()=>O,Text2TextGenerationPipeline:()=>U,TextClassificationPipeline:()=>P,TextGenerationPipeline:()=>D,TextToAudioPipeline:()=>me,TokenClassificationPipeline:()=>y,TranslationPipeline:()=>N,ZeroShotAudioClassificationPipeline:()=>ye,ZeroShotClassificationPipeline:()=>Y,ZeroShotImageClassificationPipeline:()=>Q,ZeroShotObjectDetectionPipeline:()=>Se,pipeline:()=>ot});var o=n("./src/tokenizers.js"),a=n("./src/models.js"),l=n("./src/processors.js"),f=n("./src/utils/generic.js"),_=n("./src/utils/core.js"),h=n("./src/utils/maths.js"),g=n("./src/utils/audio.js"),M=n("./src/utils/tensor.js"),w=n("./src/utils/image.js");async function C(Ge){return Array.isArray(Ge)||(Ge=[Ge]),await Promise.all(Ge.map(Te=>w.RawImage.read(Te)))}async function k(Ge,Te){return Array.isArray(Ge)||(Ge=[Ge]),await Promise.all(Ge.map(je=>typeof je=="string"||je instanceof URL?(0,g.read_audio)(je,Te):je instanceof Float64Array?new Float32Array(je):je))}function z(Ge,Te){Te&&(Ge=Ge.map(Ae=>Ae|0));const[je,Ye,tt,A]=Ge;return{xmin:je,ymin:Ye,xmax:tt,ymax:A}}class S extends f.Callable{constructor({task:Te,model:je,tokenizer:Ye=null,processor:tt=null}){super(),this.task=Te,this.model=je,this.tokenizer=Ye,this.processor=tt}async dispose(){await this.model.dispose()}}class P extends S{constructor(Te){super(Te)}async _call(Te,{top_k:je=1}={}){const Ye=this.tokenizer(Te,{padding:!0,truncation:!0}),tt=await this.model(Ye),A=this.model.config.problem_type==="multi_label_classification"?se=>se.sigmoid():se=>new M.Tensor("float32",(0,h.softmax)(se.data),se.dims),Ae=this.model.config.id2label,$e=[];for(const se of tt.logits){const te=A(se),we=await(0,M.topk)(te,je),B=we[0].tolist(),L=we[1].tolist().map((ue,le)=>({label:Ae?Ae[ue]:`LABEL_${ue}`,score:B[le]}));je===1?$e.push(...L):$e.push(L)}return Array.isArray(Te)||je===1?$e:$e[0]}}class y extends S{constructor(Te){super(Te)}async _call(Te,{ignore_labels:je=["O"]}={}){const Ye=Array.isArray(Te),tt=this.tokenizer(Ye?Te:[Te],{padding:!0,truncation:!0}),Ae=(await this.model(tt)).logits,$e=this.model.config.id2label,se=[];for(let te=0;te<Ae.dims[0];++te){const we=tt.input_ids[te],B=Ae[te],J=[];for(let L=0;L<B.dims[0];++L){const ue=B[L],le=(0,h.max)(ue.data)[1],ke=$e?$e[le]:`LABEL_${le}`;if(je.includes(ke))continue;const Ne=this.tokenizer.decode([we[L].item()],{skip_special_tokens:!0});if(Ne==="")continue;const ut=(0,h.softmax)(ue.data);J.push({entity:ke,score:ut[le],index:L,word:Ne})}se.push(J)}return Ye?se:se[0]}}class x extends S{constructor(Te){super(Te)}async _call(Te,je,{top_k:Ye=1}={}){const tt=this.tokenizer(Te,{text_pair:je,padding:!0,truncation:!0}),{start_logits:A,end_logits:Ae}=await this.model(tt),$e=tt.input_ids.tolist(),se=tt.attention_mask.tolist(),te=this.tokenizer.all_special_ids,we=[];for(let B=0;B<A.dims[0];++B){const J=$e[B],L=J.findIndex(Je=>Je==this.tokenizer.sep_token_id);se[B].map((Je,Ve)=>Je==1&&(Ve===0||Ve>L&&te.findIndex(Z=>Z==J[Ve])===-1));const ue=A[B].tolist(),le=Ae[B].tolist();for(let Je=1;Je<ue.length;++Je)(se[B]==0||Je<=L||te.findIndex(Ve=>Ve==J[Je])!==-1)&&(ue[Je]=-1/0,le[Je]=-1/0);const ke=(0,h.softmax)(ue).map((Je,Ve)=>[Je,Ve]),Ne=(0,h.softmax)(le).map((Je,Ve)=>[Je,Ve]);ke[0][0]=0,Ne[0][0]=0;const ut=(0,_.product)(ke,Ne).filter(Je=>Je[0][1]<=Je[1][1]).map(Je=>[Je[0][1],Je[1][1],Je[0][0]*Je[1][0]]).sort((Je,Ve)=>Ve[2]-Je[2]);for(let Je=0;Je<Math.min(ut.length,Ye);++Je){const[Ve,Z,ve]=ut[Je],Re=J.slice(Ve,Z+1),He=this.tokenizer.decode(Re,{skip_special_tokens:!0});we.push({answer:He,score:ve})}}return Ye===1?we[0]:we}}class I extends S{constructor(Te){super(Te)}async _call(Te,{top_k:je=5}={}){const Ye=this.tokenizer(Te,{padding:!0,truncation:!0}),{logits:tt}=await this.model(Ye),A=[],Ae=Ye.input_ids.tolist();for(let $e=0;$e<Ae.length;++$e){const se=Ae[$e],te=se.findIndex(ue=>ue==this.tokenizer.mask_token_id);if(te===-1)throw Error(`Mask token (${this.tokenizer.mask_token}) not found in text.`);const we=tt[$e][te],B=await(0,M.topk)(new M.Tensor("float32",(0,h.softmax)(we.data),we.dims),je),J=B[0].tolist(),L=B[1].tolist();A.push(L.map((ue,le)=>{const ke=se.slice();return ke[te]=ue,{score:J[le],token:Number(ue),token_str:this.tokenizer.model.vocab[ue],sequence:this.tokenizer.decode(ke,{skip_special_tokens:!0})}}))}return Array.isArray(Te)?A:A[0]}}class U extends S{constructor(je){super(je);qe(this,"_key","generated_text")}async _call(je,Ye={}){Array.isArray(je)||(je=[je]),this.model.config.prefix&&(je=je.map(te=>this.model.config.prefix+te));const tt=this.model.config.task_specific_params;tt&&tt[this.task]&&tt[this.task].prefix&&(je=je.map(te=>tt[this.task].prefix+te));const A=this.tokenizer,Ae={padding:!0,truncation:!0};let $e;this instanceof N&&"_build_translation_inputs"in A?$e=A._build_translation_inputs(je,Ae,Ye):$e=A(je,Ae);const se=await this.model.generate({...$e,...Ye});return A.batch_decode(se,{skip_special_tokens:!0}).map(te=>({[this._key]:te}))}}class O extends U{constructor(je){super(je);qe(this,"_key","summary_text")}}class N extends U{constructor(je){super(je);qe(this,"_key","translation_text")}}function j(Ge){return Array.isArray(Ge)&&Ge.every(Te=>"role"in Te&&"content"in Te)}class D extends S{constructor(Te){super(Te)}async _call(Te,je={}){let Ye=!1,tt=!1,A;if(typeof Te=="string")A=Te=[Te];else if(Array.isArray(Te)&&Te.every(L=>typeof L=="string"))Ye=!0,A=Te;else{if(j(Te))Te=[Te];else if(Array.isArray(Te)&&Te.every(j))Ye=!0;else throw new Error("Input must be a string, an array of strings, a Chat, or an array of Chats");tt=!0,A=Te.map(L=>this.tokenizer.apply_chat_template(L,{tokenize:!1,add_generation_prompt:!0}))}const Ae=je.add_special_tokens??!1,$e=tt?!1:je.return_full_text??!0;this.tokenizer.padding_side="left";const se=this.tokenizer(A,{add_special_tokens:Ae,padding:!0,truncation:!0}),te=await this.model.generate({...se,...je}),we=this.tokenizer.batch_decode(te,{skip_special_tokens:!0});let B;!$e&&se.input_ids.dims.at(-1)>0&&(B=this.tokenizer.batch_decode(se.input_ids,{skip_special_tokens:!0}).map(L=>L.length));const J=Array.from({length:Te.length},L=>[]);for(let L=0;L<we.length;++L){const ue=Math.floor(L/te.dims[0]*Te.length);B&&(we[L]=we[L].slice(B[ue])),J[ue].push({generated_text:tt?[...Te[ue],{role:"assistant",content:we[L]}]:we[L]})}return!Ye&&J.length===1?J[0]:J}}class Y extends S{constructor(Te){super(Te),this.label2id=Object.fromEntries(Object.entries(this.model.config.label2id).map(([je,Ye])=>[je.toLowerCase(),Ye])),this.entailment_id=this.label2id.entailment,this.entailment_id===void 0&&(console.warn("Could not find 'entailment' in label2id mapping. Using 2 as entailment_id."),this.entailment_id=2),this.contradiction_id=this.label2id.contradiction??this.label2id.not_entailment,this.contradiction_id===void 0&&(console.warn("Could not find 'contradiction' in label2id mapping. Using 0 as contradiction_id."),this.contradiction_id=0)}async _call(Te,je,{hypothesis_template:Ye="This example is {}.",multi_label:tt=!1}={}){const A=Array.isArray(Te);A||(Te=[Te]),Array.isArray(je)||(je=[je]);const Ae=je.map(te=>Ye.replace("{}",te)),$e=tt||je.length===1,se=[];for(const te of Te){const we=[];for(const L of Ae){const ue=this.tokenizer(te,{text_pair:L,padding:!0,truncation:!0}),le=await this.model(ue);$e?we.push([le.logits.data[this.contradiction_id],le.logits.data[this.entailment_id]]):we.push(le.logits.data[this.entailment_id])}const J=($e?we.map(L=>(0,h.softmax)(L)[1]):(0,h.softmax)(we)).map((L,ue)=>[L,ue]).sort((L,ue)=>ue[0]-L[0]);se.push({sequence:te,labels:J.map(L=>je[L[1]]),scores:J.map(L=>L[0])})}return A?se:se[0]}}class de extends S{constructor(Te){super(Te)}async _call(Te,{pooling:je="none",normalize:Ye=!1,quantize:tt=!1,precision:A="binary"}={}){const Ae=this.tokenizer(Te,{padding:!0,truncation:!0}),$e=await this.model(Ae);let se=$e.last_hidden_state??$e.logits??$e.token_embeddings;if(je!=="none")if(je==="mean")se=(0,M.mean_pooling)(se,Ae.attention_mask);else if(je==="cls")se=se.slice(null,0);else throw Error(`Pooling method '${je}' not supported.`);return Ye&&(se=se.normalize(2,-1)),tt&&(se=(0,M.quantize_embeddings)(se,A)),se}}class Ce extends S{constructor(Te){super(Te)}async _call(Te,{pool:je=null}={}){const Ye=await C(Te),{pixel_values:tt}=await this.processor(Ye),A=await this.model({pixel_values:tt});let Ae;if(je){if(!("pooler_output"in A))throw Error("No pooled output was returned. Make sure the model has a 'pooler' layer when using the 'pool' option.");Ae=A.pooler_output}else Ae=A.last_hidden_state??A.logits??A.image_embeds;return Ae}}class ee extends S{constructor(Te){super(Te)}async _call(Te,{top_k:je=5}={}){const Ye=this.processor.feature_extractor.config.sampling_rate,tt=await k(Te,Ye),A=this.model.config.id2label,Ae=[];for(const $e of tt){const se=await this.processor($e),we=(await this.model(se)).logits[0],B=await(0,M.topk)(new M.Tensor("float32",(0,h.softmax)(we.data),we.dims),je),J=B[0].tolist(),ue=B[1].tolist().map((le,ke)=>({label:A?A[le]:`LABEL_${le}`,score:J[ke]}));Ae.push(ue)}return Array.isArray(Te)?Ae:Ae[0]}}class ye extends S{constructor(Te){super(Te)}async _call(Te,je,{hypothesis_template:Ye="This is a sound of {}."}={}){const tt=!Array.isArray(Te);tt&&(Te=[Te]);const A=je.map(we=>Ye.replace("{}",we)),Ae=this.tokenizer(A,{padding:!0,truncation:!0}),$e=this.processor.feature_extractor.config.sampling_rate,se=await k(Te,$e),te=[];for(const we of se){const B=await this.processor(we),J=await this.model({...Ae,...B}),L=(0,h.softmax)(J.logits_per_audio.data);te.push([...L].map((ue,le)=>({score:ue,label:je[le]})))}return tt?te[0]:te}}class R extends S{constructor(Te){super(Te)}async _call(Te,je={}){switch(this.model.config.model_type){case"whisper":return this._call_whisper(Te,je);case"wav2vec2":case"wav2vec2-bert":case"unispeech":case"unispeech-sat":case"hubert":return this._call_wav2vec2(Te,je);default:throw new Error(`AutomaticSpeechRecognitionPipeline does not support model type '${this.model.config.model_type}'.`)}}async _call_wav2vec2(Te,je){je.language&&console.warn('`language` parameter is not yet supported for `wav2vec2` models, defaulting to "English".'),je.task&&console.warn('`task` parameter is not yet supported for `wav2vec2` models, defaulting to "transcribe".');const Ye=!Array.isArray(Te);Ye&&(Te=[Te]);const tt=this.processor.feature_extractor.config.sampling_rate,A=await k(Te,tt),Ae=[];for(const $e of A){const se=await this.processor($e),we=(await this.model(se)).logits[0],B=[];for(const L of we)B.push((0,h.max)(L.data)[1]);const J=this.tokenizer.decode(B);Ae.push({text:J})}return Ye?Ae[0]:Ae}async _call_whisper(Te,je){const Ye=je.return_timestamps??!1,tt=je.chunk_length_s??0,A=je.force_full_sequences??!1;let Ae=je.stride_length_s??null;const $e={...je};Ye==="word"&&($e.return_token_timestamps=!0,$e.return_timestamps=!1);const se=!Array.isArray(Te);se&&(Te=[Te]);const te=this.processor.feature_extractor.config.chunk_length/this.model.config.max_source_positions,we=this.processor.feature_extractor.config.hop_length,B=this.processor.feature_extractor.config.sampling_rate,J=await k(Te,B),L=[];for(const ue of J){let le=[];if(tt>0){if(Ae===null)Ae=tt/6;else if(tt<=Ae)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");const ut=B*tt,Je=B*Ae,Ve=ut-2*Je;let Z=0;for(;;){const ve=Z+ut,Re=ue.subarray(Z,ve),He=await this.processor(Re),Xe=Z===0,rt=ve>=ue.length;if(le.push({stride:[Re.length,Xe?0:Je,rt?0:Je],input_features:He.input_features,is_last:rt}),rt)break;Z+=Ve}}else le=[{stride:[ue.length,0,0],input_features:(await this.processor(ue)).input_features,is_last:!0}];for(const ut of le){$e.num_frames=Math.floor(ut.stride[0]/we);const Je=await this.model.generate({inputs:ut.input_features,...$e});Ye==="word"?(ut.tokens=Je.sequences.tolist()[0],ut.token_timestamps=Je.token_timestamps.tolist()[0].map(Ve=>(0,h.round)(Ve,2))):ut.tokens=Je[0].tolist(),ut.stride=ut.stride.map(Ve=>Ve/B)}const[ke,Ne]=this.tokenizer._decode_asr(le,{time_precision:te,return_timestamps:Ye,force_full_sequences:A});L.push({text:ke,...Ne})}return se?L[0]:L}}class Me extends S{constructor(Te){super(Te)}async _call(Te,je={}){const Ye=Array.isArray(Te),tt=await C(Te),{pixel_values:A}=await this.processor(tt),Ae=[];for(const $e of A){$e.dims=[1,...$e.dims];const se=await this.model.generate({inputs:$e,...je}),te=this.tokenizer.batch_decode(se,{skip_special_tokens:!0}).map(we=>({generated_text:we.trim()}));Ae.push(te)}return Ye?Ae:Ae[0]}}class Qe extends S{constructor(Te){super(Te)}async _call(Te,{top_k:je=5}={}){const Ye=await C(Te),{pixel_values:tt}=await this.processor(Ye),A=await this.model({pixel_values:tt}),Ae=this.model.config.id2label,$e=[];for(const se of A.logits){const te=await(0,M.topk)(new M.Tensor("float32",(0,h.softmax)(se.data),se.dims),je),we=te[0].tolist(),J=te[1].tolist().map((L,ue)=>({label:Ae?Ae[L]:`LABEL_${L}`,score:we[ue]}));$e.push(J)}return Array.isArray(Te)?$e:$e[0]}}class ge extends S{constructor(Te){super(Te),this.subtasks_mapping={panoptic:"post_process_panoptic_segmentation",instance:"post_process_instance_segmentation",semantic:"post_process_semantic_segmentation"}}async _call(Te,{threshold:je=.5,mask_threshold:Ye=.5,overlap_mask_area_threshold:tt=.8,label_ids_to_fuse:A=null,target_sizes:Ae=null,subtask:$e=null}={}){if(Array.isArray(Te)&&Te.length!==1)throw Error("Image segmentation pipeline currently only supports a batch size of 1.");const te=await C(Te),we=te.map(Ne=>[Ne.height,Ne.width]),{pixel_values:B,pixel_mask:J}=await this.processor(te),L=await this.model({pixel_values:B,pixel_mask:J});let ue=null;if($e!==null)ue=this.subtasks_mapping[$e];else for(let[Ne,ut]of Object.entries(this.subtasks_mapping))if(ut in this.processor.feature_extractor){ue=this.processor.feature_extractor[ut].bind(this.processor.feature_extractor),$e=Ne;break}const le=this.model.config.id2label,ke=[];if($e==="panoptic"||$e==="instance"){const Ne=ue(L,je,Ye,tt,A,Ae??we)[0],ut=Ne.segmentation;for(const Je of Ne.segments_info){const Ve=new Uint8ClampedArray(ut.data.length);for(let ve=0;ve<ut.data.length;++ve)ut.data[ve]===Je.id&&(Ve[ve]=255);const Z=new w.RawImage(Ve,ut.dims[1],ut.dims[0],1);ke.push({score:Je.score,label:le[Je.label_id],mask:Z})}}else if($e==="semantic"){const{segmentation:Ne,labels:ut}=ue(L,Ae??we)[0];for(const Je of ut){const Ve=new Uint8ClampedArray(Ne.data.length);for(let ve=0;ve<Ne.data.length;++ve)Ne.data[ve]===Je&&(Ve[ve]=255);const Z=new w.RawImage(Ve,Ne.dims[1],Ne.dims[0],1);ke.push({score:null,label:le[Je],mask:Z})}}else throw Error(`Subtask ${$e} not supported.`);return ke}}class Q extends S{constructor(Te){super(Te)}async _call(Te,je,{hypothesis_template:Ye="This is a photo of {}"}={}){const tt=Array.isArray(Te),A=await C(Te),Ae=je.map(J=>Ye.replace("{}",J)),$e=this.tokenizer(Ae,{padding:this.model.config.model_type==="siglip"?"max_length":!0,truncation:!0}),{pixel_values:se}=await this.processor(A),te=await this.model({...$e,pixel_values:se}),we=this.model.config.model_type==="siglip"?J=>J.sigmoid().data:J=>(0,h.softmax)(J.data),B=[];for(const J of te.logits_per_image){const ue=[...we(J)].map((le,ke)=>({score:le,label:je[ke]}));ue.sort((le,ke)=>ke.score-le.score),B.push(ue)}return tt?B:B[0]}}class ae extends S{constructor(Te){super(Te)}async _call(Te,{threshold:je=.9,percentage:Ye=!1}={}){const tt=Array.isArray(Te);if(tt&&Te.length!==1)throw Error("Object detection pipeline currently only supports a batch size of 1.");const A=await C(Te),Ae=Ye?null:A.map(L=>[L.height,L.width]),{pixel_values:$e,pixel_mask:se}=await this.processor(A),te=await this.model({pixel_values:$e,pixel_mask:se}),we=this.processor.feature_extractor.post_process_object_detection(te,je,Ae),B=this.model.config.id2label,J=we.map(L=>L.boxes.map((ue,le)=>({score:L.scores[le],label:B[L.classes[le]],box:z(ue,!Ye)})));return tt?J:J[0]}}class Se extends S{constructor(Te){super(Te)}async _call(Te,je,{threshold:Ye=.1,top_k:tt=null,percentage:A=!1}={}){const Ae=Array.isArray(Te),$e=await C(Te),se=this.tokenizer(je,{padding:!0,truncation:!0}),te=await this.processor($e),we=[];for(let B=0;B<$e.length;++B){const J=$e[B],L=A?null:[[J.height,J.width]],ue=te.pixel_values[B].unsqueeze_(0),le=await this.model({...se,pixel_values:ue}),ke=this.processor.feature_extractor.post_process_object_detection(le,Ye,L,!0)[0];let Ne=ke.boxes.map((ut,Je)=>({score:ke.scores[Je],label:je[ke.classes[Je]],box:z(ut,!A)})).sort((ut,Je)=>Je.score-ut.score);tt!==null&&(Ne=Ne.slice(0,tt)),we.push(Ne)}return Ae?we:we[0]}}class X extends S{constructor(Te){super(Te)}async _call(Te,je,Ye={}){throw new Error("This pipeline is not yet supported in Transformers.js v3.")}}class me extends S{constructor(je){super(je);qe(this,"DEFAULT_VOCODER_ID","Xenova/speecht5_hifigan");this.vocoder=je.vocoder??null}async _call(je,{speaker_embeddings:Ye=null}={}){return this.processor?this._call_text_to_spectrogram(je,{speaker_embeddings:Ye}):this._call_text_to_waveform(je)}async _call_text_to_waveform(je){const Ye=this.tokenizer(je,{padding:!0,truncation:!0}),{waveform:tt}=await this.model(Ye),A=this.model.config.sampling_rate;return{audio:tt.data,sampling_rate:A}}async _call_text_to_spectrogram(je,{speaker_embeddings:Ye}){if(this.vocoder||(console.log("No vocoder specified, using default HifiGan vocoder."),this.vocoder=await a.AutoModel.from_pretrained(this.DEFAULT_VOCODER_ID,{dtype:"fp32"})),(typeof Ye=="string"||Ye instanceof URL)&&(Ye=new Float32Array(await(await fetch(Ye)).arrayBuffer())),Ye instanceof Float32Array)Ye=new M.Tensor("float32",Ye,[1,Ye.length]);else if(!(Ye instanceof M.Tensor))throw new Error("Speaker embeddings must be a `Tensor`, `Float32Array`, `string`, or `URL`.");const{input_ids:tt}=this.tokenizer(je,{padding:!0,truncation:!0}),{waveform:A}=await this.model.generate_speech(tt,Ye,{vocoder:this.vocoder}),Ae=this.processor.feature_extractor.config.sampling_rate;return{audio:A.data,sampling_rate:Ae}}}class Ke extends S{constructor(Te){super(Te)}async _call(Te){const je=await C(Te),Ye=await this.processor(je),tt=await this.model(Ye),A=[];for(const Ae of tt.reconstruction){const $e=Ae.squeeze().clamp_(0,1).mul_(255).round_().to("uint8");A.push(w.RawImage.fromTensor($e))}return A.length>1?A:A[0]}}class De extends S{constructor(Te){super(Te)}async _call(Te){const je=await C(Te),Ye=await this.processor(je),{predicted_depth:tt}=await this.model(Ye),A=[];for(let Ae=0;Ae<je.length;++Ae){const $e=(0,M.interpolate)(tt[Ae],je[Ae].size.reverse(),"bilinear",!1),se=$e.mul_(255/(0,h.max)($e.data)[0]).to("uint8");A.push({predicted_depth:tt[Ae],depth:w.RawImage.fromTensor(se)})}return A.length>1?A:A[0]}}const Be=Object.freeze({"text-classification":{tokenizer:o.AutoTokenizer,pipeline:P,model:a.AutoModelForSequenceClassification,default:{model:"Xenova/distilbert-base-uncased-finetuned-sst-2-english"},type:"text"},"token-classification":{tokenizer:o.AutoTokenizer,pipeline:y,model:a.AutoModelForTokenClassification,default:{model:"Xenova/bert-base-multilingual-cased-ner-hrl"},type:"text"},"question-answering":{tokenizer:o.AutoTokenizer,pipeline:x,model:a.AutoModelForQuestionAnswering,default:{model:"Xenova/distilbert-base-cased-distilled-squad"},type:"text"},"fill-mask":{tokenizer:o.AutoTokenizer,pipeline:I,model:a.AutoModelForMaskedLM,default:{model:"Xenova/bert-base-uncased"},type:"text"},summarization:{tokenizer:o.AutoTokenizer,pipeline:O,model:a.AutoModelForSeq2SeqLM,default:{model:"Xenova/distilbart-cnn-6-6"},type:"text"},translation:{tokenizer:o.AutoTokenizer,pipeline:N,model:a.AutoModelForSeq2SeqLM,default:{model:"Xenova/t5-small"},type:"text"},"text2text-generation":{tokenizer:o.AutoTokenizer,pipeline:U,model:a.AutoModelForSeq2SeqLM,default:{model:"Xenova/flan-t5-small"},type:"text"},"text-generation":{tokenizer:o.AutoTokenizer,pipeline:D,model:a.AutoModelForCausalLM,default:{model:"Xenova/gpt2"},type:"text"},"zero-shot-classification":{tokenizer:o.AutoTokenizer,pipeline:Y,model:a.AutoModelForSequenceClassification,default:{model:"Xenova/distilbert-base-uncased-mnli"},type:"text"},"audio-classification":{pipeline:ee,model:a.AutoModelForAudioClassification,processor:l.AutoProcessor,default:{model:"Xenova/wav2vec2-base-superb-ks"},type:"audio"},"zero-shot-audio-classification":{tokenizer:o.AutoTokenizer,pipeline:ye,model:a.AutoModel,processor:l.AutoProcessor,default:{model:"Xenova/clap-htsat-unfused"},type:"multimodal"},"automatic-speech-recognition":{tokenizer:o.AutoTokenizer,pipeline:R,model:[a.AutoModelForSpeechSeq2Seq,a.AutoModelForCTC],processor:l.AutoProcessor,default:{model:"Xenova/whisper-tiny.en"},type:"multimodal"},"text-to-audio":{tokenizer:o.AutoTokenizer,pipeline:me,model:[a.AutoModelForTextToWaveform,a.AutoModelForTextToSpectrogram],processor:[l.AutoProcessor,null],default:{model:"Xenova/speecht5_tts"},type:"text"},"image-to-text":{tokenizer:o.AutoTokenizer,pipeline:Me,model:a.AutoModelForVision2Seq,processor:l.AutoProcessor,default:{model:"Xenova/vit-gpt2-image-captioning"},type:"multimodal"},"image-classification":{pipeline:Qe,model:a.AutoModelForImageClassification,processor:l.AutoProcessor,default:{model:"Xenova/vit-base-patch16-224"},type:"multimodal"},"image-segmentation":{pipeline:ge,model:[a.AutoModelForImageSegmentation,a.AutoModelForSemanticSegmentation],processor:l.AutoProcessor,default:{model:"Xenova/detr-resnet-50-panoptic"},type:"multimodal"},"zero-shot-image-classification":{tokenizer:o.AutoTokenizer,pipeline:Q,model:a.AutoModel,processor:l.AutoProcessor,default:{model:"Xenova/clip-vit-base-patch32"},type:"multimodal"},"object-detection":{pipeline:ae,model:a.AutoModelForObjectDetection,processor:l.AutoProcessor,default:{model:"Xenova/detr-resnet-50"},type:"multimodal"},"zero-shot-object-detection":{tokenizer:o.AutoTokenizer,pipeline:Se,model:a.AutoModelForZeroShotObjectDetection,processor:l.AutoProcessor,default:{model:"Xenova/owlvit-base-patch32"},type:"multimodal"},"document-question-answering":{tokenizer:o.AutoTokenizer,pipeline:X,model:a.AutoModelForDocumentQuestionAnswering,processor:l.AutoProcessor,default:{model:"Xenova/donut-base-finetuned-docvqa"},type:"multimodal"},"image-to-image":{pipeline:Ke,model:a.AutoModelForImageToImage,processor:l.AutoProcessor,default:{model:"Xenova/swin2SR-classical-sr-x2-64"},type:"image"},"depth-estimation":{pipeline:De,model:a.AutoModelForDepthEstimation,processor:l.AutoProcessor,default:{model:"Xenova/dpt-large"},type:"image"},"feature-extraction":{tokenizer:o.AutoTokenizer,pipeline:de,model:a.AutoModel,default:{model:"Xenova/all-MiniLM-L6-v2"},type:"text"},"image-feature-extraction":{processor:l.AutoProcessor,pipeline:Ce,model:[a.AutoModelForImageFeatureExtraction,a.AutoModel],default:{model:"Xenova/vit-base-patch16-224-in21k"},type:"image"}}),We=Object.freeze({"sentiment-analysis":"text-classification",ner:"token-classification",asr:"automatic-speech-recognition","text-to-speech":"text-to-audio",embeddings:"feature-extraction"});async function ot(Ge,Te=null,{progress_callback:je=null,config:Ye=null,cache_dir:tt=null,local_files_only:A=!1,revision:Ae="main",device:$e=null,dtype:se=null,model_file_name:te=null,session_options:we={}}={}){Ge=We[Ge]??Ge;const B=Be[Ge.split("_",1)[0]];if(!B)throw Error(`Unsupported pipeline: ${Ge}. Must be one of [${Object.keys(Be)}]`);Te||(Te=B.default.model,console.log(`No model specified. Using default model: "${Te}".`));const J={progress_callback:je,config:Ye,cache_dir:tt,local_files_only:A,revision:Ae,device:$e,dtype:se,model_file_name:te,session_options:we},L=new Map([["tokenizer",B.tokenizer],["model",B.model],["processor",B.processor]]),ue=await dt(L,Te,J);ue.task=Ge,(0,_.dispatchCallback)(je,{status:"ready",task:Ge,model:Te});const le=B.pipeline;return new le(ue)}async function dt(Ge,Te,je){const Ye=Object.create(null),tt=[];for(let[A,Ae]of Ge.entries()){if(!Ae)continue;let $e;Array.isArray(Ae)?$e=new Promise(async(se,te)=>{var B,J;let we;for(let L of Ae){if(L===null){se(null);return}try{se(await L.from_pretrained(Te,je));return}catch(ue){if((B=ue.message)!=null&&B.includes("Unsupported model type"))we=ue;else if((J=ue.message)!=null&&J.includes("Could not locate file"))we=ue;else{te(ue);return}}}te(we)}):$e=Ae.from_pretrained(Te,je),Ye[A]=$e,tt.push($e)}await Promise.all(tt);for(let[A,Ae]of Object.entries(Ye))Ye[A]=await Ae;return Ye}},"./src/processors.js":(e,t,n)=>{n.r(t),n.d(t,{ASTFeatureExtractor:()=>Ae,AutoProcessor:()=>Je,BeitFeatureExtractor:()=>De,BitImageProcessor:()=>I,CLIPFeatureExtractor:()=>O,CLIPImageProcessor:()=>N,ChineseCLIPFeatureExtractor:()=>j,ClapFeatureExtractor:()=>$e,ConvNextFeatureExtractor:()=>Y,ConvNextImageProcessor:()=>de,DPTFeatureExtractor:()=>y,DPTImageProcessor:()=>x,DeiTFeatureExtractor:()=>Ke,DetrFeatureExtractor:()=>ot,DonutFeatureExtractor:()=>Be,EfficientNetImageProcessor:()=>ye,FeatureExtractor:()=>z,Florence2Processor:()=>ut,GLPNFeatureExtractor:()=>U,ImageFeatureExtractor:()=>S,MobileNetV1FeatureExtractor:()=>R,MobileNetV2FeatureExtractor:()=>Me,MobileNetV3FeatureExtractor:()=>Qe,MobileNetV4FeatureExtractor:()=>ge,MobileViTFeatureExtractor:()=>Q,MobileViTImageProcessor:()=>ae,NougatImageProcessor:()=>We,OwlViTFeatureExtractor:()=>Se,OwlViTProcessor:()=>Ne,Owlv2ImageProcessor:()=>X,Processor:()=>B,PyAnnoteFeatureExtractor:()=>se,PyAnnoteProcessor:()=>le,RTDetrImageProcessor:()=>me,SamImageProcessor:()=>Ge,SamProcessor:()=>J,SeamlessM4TFeatureExtractor:()=>A,SegformerFeatureExtractor:()=>P,SiglipImageProcessor:()=>D,SpeechT5FeatureExtractor:()=>we,SpeechT5Processor:()=>ke,Swin2SRImageProcessor:()=>Te,ViTFeatureExtractor:()=>Ce,ViTImageProcessor:()=>ee,VitMatteImageProcessor:()=>je,Wav2Vec2FeatureExtractor:()=>tt,Wav2Vec2ProcessorWithLM:()=>ue,WeSpeakerFeatureExtractor:()=>te,WhisperFeatureExtractor:()=>Ye,WhisperProcessor:()=>L,YolosFeatureExtractor:()=>dt});var o=n("./src/utils/generic.js"),a=n("./src/utils/core.js"),l=n("./src/utils/hub.js"),f=n("./src/utils/maths.js"),_=n("./src/utils/tensor.js");n("./src/utils/image.js");var h=n("./src/utils/audio.js");function g([Ve,Z,ve,Re]){return[Ve-ve/2,Z-Re/2,Ve+ve/2,Z+Re/2]}function M(Ve,Z=.5,ve=null,Re=!1){const He=Ve.logits,Xe=Ve.pred_boxes,[rt,ft,ht]=He.dims;if(ve!==null&&ve.length!==rt)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let Mt=[];for(let wt=0;wt<rt;++wt){let St=ve!==null?ve[wt]:null,Rt={boxes:[],classes:[],scores:[]},at=He[wt],Ot=Xe[wt];for(let Ut=0;Ut<ft;++Ut){let Kt=at[Ut],Qt=[],Jt;if(Re){Jt=Kt.sigmoid().data;for(let qt=0;qt<Jt.length;++qt)Jt[qt]>Z&&Qt.push(qt)}else{let qt=(0,f.max)(Kt.data)[1];if(qt===ht-1||(Jt=(0,f.softmax)(Kt.data),Jt[qt]<Z))continue;Qt.push(qt)}for(const qt of Qt){let Er=Ot[Ut].data;Er=g(Er),St!==null&&(Er=Er.map((Qr,Cr)=>Qr*St[(Cr+1)%2])),Rt.boxes.push(Er),Rt.classes.push(qt),Rt.scores.push(Jt[qt])}}Mt.push(Rt)}return Mt}function w(Ve,Z){var ve;if(!(Ve instanceof Float32Array||Ve instanceof Float64Array))throw new Error(`${Z} expects input to be a Float32Array or a Float64Array, but got ${((ve=Ve==null?void 0:Ve.constructor)==null?void 0:ve.name)??typeof Ve} instead. If using the feature extractor directly, remember to use \`read_audio(url, sampling_rate)\` to obtain the raw audio data of the file/url.`)}function C(Ve,Z,ve=0,Re=null){const He=Ve/Z;let Xe=(0,f.bankers_round)(He)*Z;return Re!==null&&Xe>Re&&(Xe=Math.floor(He)*Z),Xe<ve&&(Xe=Math.ceil(He)*Z),Xe}function k([Ve,Z],ve){return[Math.max(Math.floor(Ve/ve),1)*ve,Math.max(Math.floor(Z/ve),1)*ve]}class z extends o.Callable{constructor(Z){super(),this.config=Z}}class S extends z{constructor(Z){super(Z),this.image_mean=this.config.image_mean??this.config.mean,this.image_std=this.config.image_std??this.config.std,this.resample=this.config.resample??2,this.do_rescale=this.config.do_rescale??!0,this.rescale_factor=this.config.rescale_factor??1/255,this.do_normalize=this.config.do_normalize,this.do_resize=this.config.do_resize,this.do_thumbnail=this.config.do_thumbnail,this.size=this.config.size,this.size_divisibility=this.config.size_divisibility??this.config.size_divisor,this.do_center_crop=this.config.do_center_crop,this.crop_size=this.config.crop_size,this.do_convert_rgb=this.config.do_convert_rgb??!0,this.do_crop_margin=this.config.do_crop_margin,this.pad_size=this.config.pad_size,this.do_pad=this.config.do_pad,this.do_pad&&!this.pad_size&&this.size&&this.size.width!==void 0&&this.size.height!==void 0&&(this.pad_size=this.size),this.do_flip_channel_order=this.config.do_flip_channel_order??!1}async thumbnail(Z,ve,Re=2){const He=Z.height,Xe=Z.width,rt=ve.height,ft=ve.width;let ht=Math.min(He,rt),Mt=Math.min(Xe,ft);return ht===He&&Mt===Xe?Z:(He>Xe?Mt=Math.floor(Xe*ht/He):Xe>He&&(ht=Math.floor(He*Mt/Xe)),await Z.resize(Mt,ht,{resample:Re}))}async crop_margin(Z,ve=200){const Re=Z.clone().grayscale(),He=(0,f.min)(Re.data)[0],rt=(0,f.max)(Re.data)[0]-He;if(rt===0)return Z;const ft=ve/255;let ht=Re.width,Mt=Re.height,wt=0,St=0;const Rt=Re.data;for(let at=0;at<Re.height;++at){const Ot=at*Re.width;for(let Ut=0;Ut<Re.width;++Ut)(Rt[Ot+Ut]-He)/rt<ft&&(ht=Math.min(ht,Ut),Mt=Math.min(Mt,at),wt=Math.max(wt,Ut),St=Math.max(St,at))}return Z=await Z.crop([ht,Mt,wt,St]),Z}pad_image(Z,ve,Re,{mode:He="constant",center:Xe=!1,constant_values:rt=0}={}){const[ft,ht,Mt]=ve;let wt,St;if(typeof Re=="number"?(wt=Re,St=Re):(wt=Re.width,St=Re.height),wt!==ht||St!==ft){const Rt=new Float32Array(wt*St*Mt);if(Array.isArray(rt))for(let Ut=0;Ut<Rt.length;++Ut)Rt[Ut]=rt[Ut%Mt];else rt!==0&&Rt.fill(rt);const[at,Ot]=Xe?[Math.floor((wt-ht)/2),Math.floor((St-ft)/2)]:[0,0];for(let Ut=0;Ut<ft;++Ut){const Kt=(Ut+Ot)*wt,Qt=Ut*ht;for(let Jt=0;Jt<ht;++Jt){const qt=(Kt+Jt+at)*Mt,Er=(Qt+Jt)*Mt;for(let Qr=0;Qr<Mt;++Qr)Rt[qt+Qr]=Z[Er+Qr]}}if(He==="symmetric"){if(Xe)throw new Error("`center` padding is not supported when `mode` is set to `symmetric`.");const Ut=ft-1,Kt=ht-1;for(let Qt=0;Qt<St;++Qt){const Jt=Qt*wt,qt=(0,a.calculateReflectOffset)(Qt,Ut)*ht;for(let Er=0;Er<wt;++Er){if(Qt<ft&&Er<ht)continue;const Qr=(Jt+Er)*Mt,Cr=(qt+(0,a.calculateReflectOffset)(Er,Kt))*Mt;for(let mt=0;mt<Mt;++mt)Rt[Qr+mt]=Z[Cr+mt]}}}Z=Rt,ve=[St,wt,Mt]}return[Z,ve]}rescale(Z){for(let ve=0;ve<Z.length;++ve)Z[ve]=this.rescale_factor*Z[ve]}get_resize_output_image_size(Z,ve){const[Re,He]=Z.size;let Xe,rt;if(this.do_thumbnail){const{height:ft,width:ht}=ve;Xe=Math.min(ft,ht)}else Number.isInteger(ve)?(Xe=ve,rt=this.config.max_size??Xe):ve!==void 0&&(Xe=ve.shortest_edge,rt=ve.longest_edge);if(Xe!==void 0||rt!==void 0){const ft=Xe===void 0?1:Math.max(Xe/Re,Xe/He),ht=Re*ft,Mt=He*ft,wt=rt===void 0?1:Math.min(rt/ht,rt/Mt);let St=Math.floor(Number((ht*wt).toFixed(2))),Rt=Math.floor(Number((Mt*wt).toFixed(2)));return this.size_divisibility!==void 0&&([St,Rt]=k([St,Rt],this.size_divisibility)),[St,Rt]}else if(ve!==void 0&&ve.width!==void 0&&ve.height!==void 0){let ft=ve.width,ht=ve.height;if(this.config.keep_aspect_ratio&&this.config.ensure_multiple_of){let Mt=ht/He,wt=ft/Re;Math.abs(1-wt)<Math.abs(1-Mt)?Mt=wt:wt=Mt,ht=C(Mt*He,this.config.ensure_multiple_of),ft=C(wt*Re,this.config.ensure_multiple_of)}return[ft,ht]}else{if(this.size_divisibility!==void 0)return k([Re,He],this.size_divisibility);throw new Error(`Could not resize image due to unsupported \`this.size\` option in config: ${JSON.stringify(ve)}`)}}async resize(Z){const[ve,Re]=this.get_resize_output_image_size(Z,this.size);return await Z.resize(ve,Re,{resample:this.resample})}async preprocess(Z,{do_normalize:ve=null,do_pad:Re=null,do_convert_rgb:He=null,do_convert_grayscale:Xe=null,do_flip_channel_order:rt=null}={}){this.do_crop_margin&&(Z=await this.crop_margin(Z));const[ft,ht]=Z.size;if(He??this.do_convert_rgb?Z=Z.rgb():Xe&&(Z=Z.grayscale()),this.do_resize&&(Z=await this.resize(Z)),this.do_thumbnail&&(Z=await this.thumbnail(Z,this.size,this.resample)),this.do_center_crop){let at,Ot;Number.isInteger(this.crop_size)?(at=this.crop_size,Ot=this.crop_size):(at=this.crop_size.width,Ot=this.crop_size.height),Z=await Z.center_crop(at,Ot)}const Mt=[Z.height,Z.width];let wt=Float32Array.from(Z.data),St=[Z.height,Z.width,Z.channels];if(this.do_rescale&&this.rescale(wt),ve??this.do_normalize){let at=this.image_mean;Array.isArray(this.image_mean)||(at=new Array(Z.channels).fill(at));let Ot=this.image_std;if(Array.isArray(this.image_std)||(Ot=new Array(Z.channels).fill(at)),at.length!==Z.channels||Ot.length!==Z.channels)throw new Error(`When set to arrays, the length of \`image_mean\` (${at.length}) and \`image_std\` (${Ot.length}) must match the number of channels in the image (${Z.channels}).`);for(let Ut=0;Ut<wt.length;Ut+=Z.channels)for(let Kt=0;Kt<Z.channels;++Kt)wt[Ut+Kt]=(wt[Ut+Kt]-at[Kt])/Ot[Kt]}if(Re??this.do_pad){if(this.pad_size)[wt,St]=this.pad_image(wt,[Z.height,Z.width,Z.channels],this.pad_size);else if(this.size_divisibility){const[at,Ot]=k([St[1],St[0]],this.size_divisibility);[wt,St]=this.pad_image(wt,St,{width:at,height:Ot})}}if(rt??this.do_flip_channel_order){if(St[2]!==3)throw new Error("Flipping channel order is only supported for RGB images.");for(let at=0;at<wt.length;at+=3){const Ot=wt[at];wt[at]=wt[at+2],wt[at+2]=Ot}}const Rt=new _.Tensor("float32",wt,St).permute(2,0,1);return{original_size:[ht,ft],reshaped_input_size:Mt,pixel_values:Rt}}async _call(Z,...ve){Array.isArray(Z)||(Z=[Z]);const Re=await Promise.all(Z.map(Xe=>this.preprocess(Xe)));return{pixel_values:(0,_.stack)(Re.map(Xe=>Xe.pixel_values),0),original_sizes:Re.map(Xe=>Xe.original_size),reshaped_input_sizes:Re.map(Xe=>Xe.reshaped_input_size)}}}class P extends S{post_process_semantic_segmentation(Z,ve=null){const Re=Z.logits,He=Re.dims[0];if(ve!==null&&ve.length!==He)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");const Xe=[];for(let rt=0;rt<He;++rt){const ft=ve!==null?ve[rt]:null;let ht=Re[rt];ft!==null&&(ht=(0,_.interpolate)(ht,ft,"bilinear",!1));const[Mt,wt]=ft??ht.dims.slice(-2),St=new _.Tensor("int32",new Int32Array(Mt*wt),[Mt,wt]),Rt=ht[0].data,at=St.data;for(let Qt=1;Qt<ht.dims[0];++Qt){const Jt=ht[Qt].data;for(let qt=0;qt<Jt.length;++qt)Jt[qt]>Rt[qt]&&(Rt[qt]=Jt[qt],at[qt]=Qt)}const Ot=new Array(ht.dims[0]),Ut=St.data;for(let Qt=0;Qt<Ut.length;++Qt){const Jt=Ut[Qt];Ot[Jt]=Jt}const Kt=Ot.filter(Qt=>Qt!==void 0);Xe.push({segmentation:St,labels:Kt})}return Xe}}class y extends S{}class x extends y{}class I extends S{}class U extends S{}class O extends S{}class N extends O{}class j extends S{}class D extends S{}class Y extends S{constructor(Z){super(Z),this.crop_pct=this.config.crop_pct??224/256}async resize(Z){var Re;const ve=(Re=this.size)==null?void 0:Re.shortest_edge;if(ve===void 0)throw new Error("Size dictionary must contain 'shortest_edge' key.");if(ve<384){const He=Math.floor(ve/this.crop_pct),[Xe,rt]=this.get_resize_output_image_size(Z,{shortest_edge:He});Z=await Z.resize(Xe,rt,{resample:this.resample}),Z=await Z.center_crop(ve,ve)}else Z=await Z.resize(ve,ve,{resample:this.resample});return Z}}class de extends Y{}class Ce extends S{}class ee extends S{}class ye extends S{constructor(Z){super(Z),this.include_top=this.config.include_top??!0,this.include_top&&(this.image_std=this.image_std.map(ve=>ve*ve))}}class R extends S{}class Me extends S{}class Qe extends S{}class ge extends S{}class Q extends S{}class ae extends Q{}class Se extends S{post_process_object_detection(...Z){return M(...Z)}}class X extends Se{}class me extends S{post_process_object_detection(...Z){return M(...Z)}}class Ke extends S{}class De extends S{}class Be extends S{pad_image(Z,ve,Re,He={}){const[Xe,rt,ft]=ve;let ht=this.image_mean;Array.isArray(this.image_mean)||(ht=new Array(ft).fill(ht));let Mt=this.image_std;Array.isArray(Mt)||(Mt=new Array(ft).fill(ht));const wt=ht.map((St,Rt)=>-St/Mt[Rt]);return super.pad_image(Z,ve,Re,{center:!0,constant_values:wt,...He})}}class We extends Be{}class ot extends S{async _call(Z){const ve=await super._call(Z),Re=[ve.pixel_values.dims[0],64,64],He=new _.Tensor("int64",new BigInt64Array(Re.reduce((Xe,rt)=>Xe*rt)).fill(1n),Re);return{...ve,pixel_mask:He}}post_process_object_detection(...Z){return M(...Z)}remove_low_and_no_objects(Z,ve,Re,He){let Xe=[],rt=[],ft=[];for(let ht=0;ht<Z.dims[0];++ht){let Mt=Z[ht],wt=ve[ht],St=(0,f.max)(Mt.data)[1];if(St===He)continue;let at=(0,f.softmax)(Mt.data)[St];at>Re&&(Xe.push(wt),rt.push(at),ft.push(St))}return[Xe,rt,ft]}check_segment_validity(Z,ve,Re,He=.5,Xe=.8){let rt=[],ft=0,ht=0;const Mt=ve[Re].data;for(let St=0;St<Z.length;++St)Z[St]===Re&&(rt.push(St),++ft),Mt[St]>=He&&++ht;let wt=ft>0&&ht>0;return wt&&(wt=ft/ht>Xe),[wt,rt]}compute_segments(Z,ve,Re,He,Xe,rt=null,ft=null){let[ht,Mt]=ft??Z[0].dims,wt=new _.Tensor("int32",new Int32Array(ht*Mt),[ht,Mt]),St=[];if(ft!==null)for(let Kt=0;Kt<Z.length;++Kt)Z[Kt]=(0,_.interpolate)(Z[Kt],ft,"bilinear",!1);let Rt=new Int32Array(Z[0].data.length),at=new Float32Array(Z[0].data.length);for(let Kt=0;Kt<Z.length;++Kt){let Qt=ve[Kt];const Jt=Z[Kt].data;for(let qt=0;qt<Jt.length;++qt)Jt[qt]*=Qt,Jt[qt]>at[qt]&&(Rt[qt]=Kt,at[qt]=Jt[qt])}let Ot=0;const Ut=wt.data;for(let Kt=0;Kt<Re.length;++Kt){let Qt=Re[Kt],[Jt,qt]=this.check_segment_validity(Rt,Z,Kt,He,Xe);if(Jt){++Ot;for(let Er of qt)Ut[Er]=Ot;St.push({id:Ot,label_id:Qt,score:ve[Kt]})}}return[wt,St]}post_process_panoptic_segmentation(Z,ve=.5,Re=.5,He=.8,Xe=null,rt=null){Xe===null&&(console.warn("`label_ids_to_fuse` unset. No instance will be fused."),Xe=new Set);const ft=Z.logits,Mt=Z.pred_masks.sigmoid();let[wt,St,Rt]=ft.dims;if(Rt-=1,rt!==null&&rt.length!==wt)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let at=[];for(let Ot=0;Ot<wt;++Ot){let Ut=rt!==null?rt[Ot]:null,Kt=ft[Ot],Qt=Mt[Ot],[Jt,qt,Er]=this.remove_low_and_no_objects(Kt,Qt,ve,Rt);if(Er.length===0){let[mt,Pt]=Ut??Qt.dims.slice(-2),Bt=new _.Tensor("int32",new Int32Array(mt*Pt).fill(-1),[mt,Pt]);at.push({segmentation:Bt,segments_info:[]});continue}let[Qr,Cr]=this.compute_segments(Jt,qt,Er,Re,He,Xe,Ut);at.push({segmentation:Qr,segments_info:Cr})}return at}post_process_instance_segmentation(){throw Error("Not implemented yet")}}class dt extends S{post_process_object_detection(...Z){return M(...Z)}}class Ge extends S{reshape_input_points(Z,ve,Re,He=!1){Z=structuredClone(Z);let Xe=(0,a.calculateDimensions)(Z);if(Xe.length===3)He||(Xe=[1,...Xe]),Z=[Z];else if(Xe.length!==4)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");for(let rt=0;rt<Z.length;++rt){let ft=ve[rt],ht=Re[rt],Mt=[ht[0]/ft[0],ht[1]/ft[1]];for(let wt=0;wt<Z[rt].length;++wt)for(let St=0;St<Z[rt][wt].length;++St)for(let Rt=0;Rt<Z[rt][wt][St].length;++Rt)Z[rt][wt][St][Rt]*=Mt[Rt%2]}return new _.Tensor("float32",Float32Array.from(Z.flat(1/0)),Xe)}add_input_labels(Z,ve){let Re=(0,a.calculateDimensions)(Z);if(Re.length===2)Re=[1,...Re],Z=[Z];else if(Re.length!==3)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");if(Re.some((He,Xe)=>He!==ve.dims[Xe]))throw Error(`The first ${Re.length} dimensions of 'input_points' and 'input_labels' must be the same.`);return new _.Tensor("int64",Z.flat(1/0).map(BigInt),Re)}async _call(Z,{input_points:ve=null,input_labels:Re=null,input_boxes:He=null}={}){const Xe=await super._call(Z);if(ve&&(Xe.input_points=this.reshape_input_points(ve,Xe.original_sizes,Xe.reshaped_input_sizes)),Re){if(!Xe.input_points)throw Error("`input_points` must be provided if `input_labels` are provided.");Xe.input_labels=this.add_input_labels(Re,Xe.input_points)}return He&&(Xe.input_boxes=this.reshape_input_points(He,Xe.original_sizes,Xe.reshaped_input_sizes,!0)),Xe}async post_process_masks(Z,ve,Re,{mask_threshold:He=0,binarize:Xe=!0,pad_size:rt=null}={}){const ft=[];rt=rt??this.pad_size;const ht=[rt.height,rt.width];for(let Mt=0;Mt<ve.length;++Mt){const wt=ve[Mt],St=Re[Mt];let Rt=await(0,_.interpolate_4d)(Z[Mt],{mode:"bilinear",size:ht});if(Rt=Rt.slice(null,null,[0,St[0]],[0,St[1]]),Rt=await(0,_.interpolate_4d)(Rt,{mode:"bilinear",size:wt}),Xe){const at=Rt.data,Ot=new Uint8Array(at.length);for(let Ut=0;Ut<at.length;++Ut)at[Ut]>He&&(Ot[Ut]=1);Rt=new _.Tensor("bool",Ot,Rt.dims)}ft.push(Rt)}return ft}generate_crop_boxes(Z,ve,{crop_n_layers:Re=0,overlap_ratio:He=512/1500,points_per_crop:Xe=32,crop_n_points_downscale_factor:rt=1}={}){}}class Te extends S{pad_image(Z,ve,Re,He={}){const[Xe,rt,ft]=ve;return super.pad_image(Z,ve,{width:rt+(Re-rt%Re)%Re,height:Xe+(Re-Xe%Re)%Re},{mode:"symmetric",center:!1,constant_values:-1,...He})}}class je extends S{async _call(Z,ve){Array.isArray(Z)||(Z=[Z]),Array.isArray(ve)||(ve=[ve]);const Re=await Promise.all(Z.map(rt=>this.preprocess(rt))),He=await Promise.all(ve.map(rt=>this.preprocess(rt,{do_normalize:!1,do_convert_rgb:!1,do_convert_grayscale:!0})));return{pixel_values:(0,_.stack)(Re.map((rt,ft)=>(0,_.cat)([rt.pixel_values,He[ft].pixel_values],0)),0),original_sizes:Re.map(rt=>rt.original_size),reshaped_input_sizes:Re.map(rt=>rt.reshaped_input_size)}}}class Ye extends z{constructor(Z){var ve;super(Z),(ve=this.config).mel_filters??(ve.mel_filters=(0,h.mel_filter_bank)(Math.floor(1+this.config.n_fft/2),this.config.feature_size,0,8e3,this.config.sampling_rate,"slaney","slaney")),this.window=(0,h.window_function)(this.config.n_fft,"hann")}async _extract_fbank_features(Z){const ve=await(0,h.spectrogram)(Z,this.window,this.config.n_fft,this.config.hop_length,{power:2,mel_filters:this.config.mel_filters,log_mel:"log10",max_num_frames:this.config.nb_max_frames}),Re=ve.data,He=(0,f.max)(Re)[0];for(let Xe=0;Xe<Re.length;++Xe)Re[Xe]=(Math.max(Re[Xe],He-8)+4)/4;return ve}async _call(Z){w(Z,"WhisperFeatureExtractor");let ve;return Z.length>this.config.n_samples?(console.warn("Attempting to extract features for audio longer than 30 seconds. If using a pipeline to extract transcript from a long audio clip, remember to specify `chunk_length_s` and/or `stride_length_s`."),ve=Z.slice(0,this.config.n_samples)):(ve=new Float32Array(this.config.n_samples),ve.set(Z)),{input_features:(await this._extract_fbank_features(ve)).unsqueeze_(0)}}}class tt extends z{_zero_mean_unit_var_norm(Z){const Re=Z.reduce((Xe,rt)=>Xe+rt,0)/Z.length,He=Z.reduce((Xe,rt)=>Xe+(rt-Re)**2,0)/Z.length;return Z.map(Xe=>(Xe-Re)/Math.sqrt(He+1e-7))}async _call(Z){w(Z,"Wav2Vec2FeatureExtractor"),Z instanceof Float64Array&&(Z=new Float32Array(Z));let ve=Z;this.config.do_normalize&&(ve=this._zero_mean_unit_var_norm(ve));const Re=[1,ve.length];return{input_values:new _.Tensor("float32",ve,Re),attention_mask:new _.Tensor("int64",new BigInt64Array(ve.length).fill(1n),Re)}}}class A extends z{constructor(Z){super(Z);const ve=this.config.sampling_rate,Re=(0,h.mel_filter_bank)(256,this.config.num_mel_bins,20,Math.floor(ve/2),ve,null,"kaldi",!0);for(let He=0;He<Re.length;++He)Re[He].push(0);this.mel_filters=Re,this.window=(0,h.window_function)(400,"povey",{periodic:!1})}async _extract_fbank_features(Z,ve){return Z=Z.map(Re=>Re*32768),(0,h.spectrogram)(Z,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,max_num_frames:ve,transpose:!0})}async _call(Z,{padding:ve=!0,pad_to_multiple_of:Re=2,do_normalize_per_mel_bins:He=!0,return_attention_mask:Xe=!0}={}){w(Z,"SeamlessM4TFeatureExtractor");let rt=await this._extract_fbank_features(Z,this.config.max_length);if(He){const[Ot,Ut]=rt.dims,Kt=rt.data;for(let Qt=0;Qt<Ut;++Qt){let Jt=0;for(let Cr=0;Cr<Ot;++Cr)Jt+=Kt[Cr*Ut+Qt];const qt=Jt/Ot;let Er=0;for(let Cr=0;Cr<Ot;++Cr)Er+=(Kt[Cr*Ut+Qt]-qt)**2;Er/=Ot-1;const Qr=Math.sqrt(Er+1e-7);for(let Cr=0;Cr<Ot;++Cr){const mt=Cr*Ut+Qt;Kt[mt]=(Kt[mt]-qt)/Qr}}}let ft;if(ve){const[Ot,Ut]=rt.dims,Kt=rt.data,Qt=Ot%Re;if(Qt>0){const Jt=new Float32Array(Ut*(Ot+Qt));Jt.set(Kt),Jt.fill(this.config.padding_value,Kt.length);const qt=Ot+Qt;rt=new _.Tensor(rt.type,Jt,[qt,Ut]),Xe&&(ft=new _.Tensor("int64",new BigInt64Array(qt),[1,qt]),ft.data.fill(1n,0,Ot))}}const[ht,Mt]=rt.dims,wt=this.config.stride;if(ht%wt!==0)throw new Error(`The number of frames (${ht}) must be a multiple of the stride (${wt}).`);const Rt=rt.view(1,Math.floor(ht/wt),Mt*wt),at={input_features:Rt};if(Xe){const Ot=Rt.dims[1],Ut=new BigInt64Array(Ot);if(ft){const Kt=ft.data;for(let Qt=1,Jt=0;Qt<ht;Qt+=wt,++Jt)Ut[Jt]=Kt[Qt]}else Ut.fill(1n);at.attention_mask=new _.Tensor("int64",Ut,[1,Ot])}return at}}class Ae extends z{constructor(Z){super(Z);const ve=this.config.sampling_rate,Re=(0,h.mel_filter_bank)(256,this.config.num_mel_bins,20,Math.floor(ve/2),ve,null,"kaldi",!0);for(let He=0;He<Re.length;++He)Re[He].push(0);this.mel_filters=Re,this.window=(0,h.window_function)(400,"hann",{periodic:!1}),this.mean=this.config.mean,this.std=this.config.std}async _extract_fbank_features(Z,ve){return(0,h.spectrogram)(Z,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,max_num_frames:ve,transpose:!0})}async _call(Z){w(Z,"ASTFeatureExtractor");const ve=await this._extract_fbank_features(Z,this.config.max_length);if(this.config.do_normalize){const Re=this.std*2,He=ve.data;for(let Xe=0;Xe<He.length;++Xe)He[Xe]=(He[Xe]-this.mean)/Re}return{input_values:ve.unsqueeze_(0)}}}class $e extends z{constructor(Z){super(Z),this.mel_filters=(0,h.mel_filter_bank)(this.config.nb_frequency_bins,this.config.feature_size,this.config.frequency_min,this.config.frequency_max,this.config.sampling_rate,null,"htk"),this.mel_filters_slaney=(0,h.mel_filter_bank)(this.config.nb_frequency_bins,this.config.feature_size,this.config.frequency_min,this.config.frequency_max,this.config.sampling_rate,"slaney","slaney"),this.window=(0,h.window_function)(this.config.fft_window_size,"hann")}async _get_input_mel(Z,ve,Re,He){let Xe;const rt=Z.length-ve;if(rt>0)if(Re==="rand_trunc"){const ft=Math.floor(Math.random()*(rt+1));Z=Z.subarray(ft,ft+ve),Xe=await this._extract_fbank_features(Z,this.mel_filters_slaney,this.config.nb_max_samples)}else throw new Error(`Truncation strategy "${Re}" not implemented`);else{if(rt<0){let ft=new Float64Array(ve);if(ft.set(Z),He==="repeat")for(let ht=Z.length;ht<ve;ht+=Z.length)ft.set(Z.subarray(0,Math.min(Z.length,ve-ht)),ht);else if(He==="repeatpad")for(let ht=Z.length;ht<-rt;ht+=Z.length)ft.set(Z,ht);Z=ft}if(Re==="fusion")throw new Error(`Truncation strategy "${Re}" not implemented`);Xe=await this._extract_fbank_features(Z,this.mel_filters_slaney,this.config.nb_max_samples)}return Xe.unsqueeze_(0)}async _extract_fbank_features(Z,ve,Re=null){return(0,h.spectrogram)(Z,this.window,this.config.fft_window_size,this.config.hop_length,{power:2,mel_filters:ve,log_mel:"dB",max_num_frames:Re,do_pad:!1,transpose:!0})}async _call(Z,{max_length:ve=null}={}){return w(Z,"ClapFeatureExtractor"),{input_features:(await this._get_input_mel(Z,ve??this.config.nb_max_samples,this.config.truncation,this.config.padding)).unsqueeze_(0)}}}class se extends z{async _call(Z){w(Z,"PyAnnoteFeatureExtractor"),Z instanceof Float64Array&&(Z=new Float32Array(Z));const ve=[1,1,Z.length];return{input_values:new _.Tensor("float32",Z,ve)}}samples_to_frames(Z){return(Z-this.config.offset)/this.config.step}post_process_speaker_diarization(Z,ve){const Re=ve/this.samples_to_frames(ve)/this.config.sampling_rate,He=[];for(const Xe of Z.tolist()){const rt=[];let ft=-1;for(let ht=0;ht<Xe.length;++ht){const Mt=(0,f.softmax)(Xe[ht]),[wt,St]=(0,f.max)(Mt),[Rt,at]=[ht,ht+1];St!==ft?(ft=St,rt.push({id:St,start:Rt,end:at,score:wt})):(rt.at(-1).end=at,rt.at(-1).score+=wt)}He.push(rt.map(({id:ht,start:Mt,end:wt,score:St})=>({id:ht,start:Mt*Re,end:wt*Re,confidence:St/(wt-Mt)})))}return He}}class te extends z{constructor(Z){super(Z);const ve=this.config.sampling_rate,Re=(0,h.mel_filter_bank)(256,this.config.num_mel_bins,20,Math.floor(ve/2),ve,null,"kaldi",!0);for(let He=0;He<Re.length;++He)Re[He].push(0);this.mel_filters=Re,this.window=(0,h.window_function)(400,"hamming",{periodic:!1}),this.min_num_frames=this.config.min_num_frames}async _extract_fbank_features(Z){return Z=Z.map(ve=>ve*32768),(0,h.spectrogram)(Z,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,transpose:!0,min_num_frames:this.min_num_frames})}async _call(Z){w(Z,"WeSpeakerFeatureExtractor");const ve=(await this._extract_fbank_features(Z)).unsqueeze_(0);if(this.config.fbank_centering_span===null){const Re=ve.mean(1).data,He=ve.data,[Xe,rt,ft]=ve.dims;for(let ht=0;ht<Xe;++ht){const Mt=ht*rt*ft,wt=ht*ft;for(let St=0;St<rt;++St){const Rt=Mt+St*ft;for(let at=0;at<ft;++at)He[Rt+at]-=Re[wt+at]}}}return{input_features:ve}}}class we extends z{}class B extends o.Callable{constructor(Z){super(),this.feature_extractor=Z}async _call(Z,...ve){return await this.feature_extractor(Z,...ve)}}class J extends B{async _call(...Z){return await this.feature_extractor(...Z)}post_process_masks(...Z){return this.feature_extractor.post_process_masks(...Z)}reshape_input_points(...Z){return this.feature_extractor.reshape_input_points(...Z)}}class L extends B{async _call(Z){return await this.feature_extractor(Z)}}class ue extends B{async _call(Z){return await this.feature_extractor(Z)}}class le extends B{async _call(Z){return await this.feature_extractor(Z)}post_process_speaker_diarization(...Z){return this.feature_extractor.post_process_speaker_diarization(...Z)}}class ke extends B{async _call(Z){return await this.feature_extractor(Z)}}class Ne extends B{}class ut extends B{constructor(Z){super(Z);const{tasks_answer_post_processing_type:ve,task_prompts_without_inputs:Re,task_prompts_with_input:He}=Z.config;this.tasks_answer_post_processing_type=new Map(Object.entries(ve??{})),this.task_prompts_without_inputs=new Map(Object.entries(Re??{})),this.task_prompts_with_input=new Map(Object.entries(He??{})),this.regexes={quad_boxes:/(.+?)<loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)>/gm,bboxes:/([^<]+)?<loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)>/gm},this.size_per_bin=1e3}construct_prompts(Z){typeof Z=="string"&&(Z=[Z]);const ve=[];for(const Re of Z)if(this.task_prompts_without_inputs.has(Re))ve.push(this.task_prompts_without_inputs.get(Re));else{for(const[He,Xe]of this.task_prompts_with_input)if(Re.includes(He)){ve.push(Xe.replaceAll("{input}",Re).replaceAll(He,""));break}ve.length!==Z.length&&ve.push(Re)}return ve}post_process_generation(Z,ve,Re){const He=this.tasks_answer_post_processing_type.get(ve)??"pure_text";Z=Z.replaceAll("<s>","").replaceAll("</s>","");let Xe;switch(He){case"pure_text":Xe=Z;break;case"description_with_bboxes":case"bboxes":case"phrase_grounding":case"ocr":const rt=He==="ocr"?"quad_boxes":"bboxes",ft=Z.matchAll(this.regexes[rt]),ht=[],Mt=[];for(const[wt,St,...Rt]of ft)ht.push(St?St.trim():ht.at(-1)??""),Mt.push(Rt.map((at,Ot)=>(Number(at)+.5)/this.size_per_bin*Re[Ot%2]));Xe={labels:ht,[rt]:Mt};break;default:throw new Error(`Task "${ve}" (of type "${He}") not yet implemented.`)}return{[ve]:Xe}}}class Je{static async from_pretrained(Z,{progress_callback:ve=null,config:Re=null,cache_dir:He=null,local_files_only:Xe=!1,revision:rt="main"}={}){let ft=Re??await(0,l.getModelJSON)(Z,"preprocessor_config.json",!0,{progress_callback:ve,config:Re,cache_dir:He,local_files_only:Xe,revision:rt}),ht=ft.feature_extractor_type??ft.image_processor_type,Mt=this.FEATURE_EXTRACTOR_CLASS_MAPPING[ht];if(!Mt)if(ft.size!==void 0)console.warn(`Feature extractor type "${ht}" not found, assuming ImageFeatureExtractor due to size parameter in config.`),Mt=S;else throw new Error(`Unknown Feature Extractor type: ${ht}`);let wt=this.PROCESSOR_CLASS_MAPPING[ft.processor_class]??B,St=new Mt(ft);return new wt(St)}}qe(Je,"FEATURE_EXTRACTOR_CLASS_MAPPING",{ImageFeatureExtractor:S,WhisperFeatureExtractor:Ye,ViTFeatureExtractor:Ce,MobileViTFeatureExtractor:Q,MobileViTImageProcessor:ae,MobileNetV1FeatureExtractor:R,MobileNetV2FeatureExtractor:Me,MobileNetV3FeatureExtractor:Qe,MobileNetV4FeatureExtractor:ge,OwlViTFeatureExtractor:Se,Owlv2ImageProcessor:X,CLIPFeatureExtractor:O,CLIPImageProcessor:N,Florence2Processor:ut,ChineseCLIPFeatureExtractor:j,SiglipImageProcessor:D,ConvNextFeatureExtractor:Y,ConvNextImageProcessor:de,SegformerFeatureExtractor:P,BitImageProcessor:I,DPTImageProcessor:x,DPTFeatureExtractor:y,GLPNFeatureExtractor:U,BeitFeatureExtractor:De,DeiTFeatureExtractor:Ke,DetrFeatureExtractor:ot,RTDetrImageProcessor:me,YolosFeatureExtractor:dt,DonutFeatureExtractor:Be,NougatImageProcessor:We,EfficientNetImageProcessor:ye,ViTImageProcessor:ee,VitMatteImageProcessor:je,SamImageProcessor:Ge,Swin2SRImageProcessor:Te,Wav2Vec2FeatureExtractor:tt,SeamlessM4TFeatureExtractor:A,SpeechT5FeatureExtractor:we,ASTFeatureExtractor:Ae,ClapFeatureExtractor:$e,PyAnnoteFeatureExtractor:se,WeSpeakerFeatureExtractor:te}),qe(Je,"PROCESSOR_CLASS_MAPPING",{WhisperProcessor:L,Wav2Vec2ProcessorWithLM:ue,PyAnnoteProcessor:le,SamProcessor:J,SpeechT5Processor:ke,OwlViTProcessor:Ne,Florence2Processor:ut})},"./src/tokenizers.js":(e,t,n)=>{n.r(t),n.d(t,{AlbertTokenizer:()=>Ut,AutoTokenizer:()=>Rn,BartTokenizer:()=>Nr,BertTokenizer:()=>Ot,BlenderbotSmallTokenizer:()=>jo,BlenderbotTokenizer:()=>ho,BloomTokenizer:()=>Fr,CLIPTokenizer:()=>Xt,CamembertTokenizer:()=>Pt,CodeGenTokenizer:()=>po,CodeLlamaTokenizer:()=>ks,CohereTokenizer:()=>Br,ConvBertTokenizer:()=>Qr,DebertaTokenizer:()=>Jt,DebertaV2Tokenizer:()=>qt,DistilBertTokenizer:()=>mt,ElectraTokenizer:()=>sn,EsmTokenizer:()=>Bi,FalconTokenizer:()=>Lo,GPT2Tokenizer:()=>bi,GPTNeoXTokenizer:()=>Ro,GemmaTokenizer:()=>co,Grok1Tokenizer:()=>di,HerbertTokenizer:()=>Er,LlamaTokenizer:()=>xi,M2M100Tokenizer:()=>Yi,MBart50Tokenizer:()=>Wr,MBartTokenizer:()=>mn,MPNetTokenizer:()=>Do,MarianTokenizer:()=>Bo,MobileBertTokenizer:()=>Kt,NllbTokenizer:()=>Ti,NougatTokenizer:()=>mo,PreTrainedTokenizer:()=>at,Qwen2Tokenizer:()=>Ss,RoFormerTokenizer:()=>Cr,RobertaTokenizer:()=>ci,SiglipTokenizer:()=>Zi,SpeechT5Tokenizer:()=>Uo,SqueezeBertTokenizer:()=>Qt,T5Tokenizer:()=>Li,TokenizerModel:()=>Ce,VitsTokenizer:()=>Vo,Wav2Vec2CTCTokenizer:()=>No,WhisperTokenizer:()=>fo,XLMRobertaTokenizer:()=>Oo,XLMTokenizer:()=>Bt,is_chinese_char:()=>U});var o=n("./src/utils/generic.js"),a=n("./src/utils/core.js"),l=n("./src/utils/hub.js"),f=n("./src/utils/maths.js"),_=n("./src/utils/tensor.js"),h=n("./src/utils/data-structures.js"),g=n("./node_modules/@huggingface/jinja/dist/index.js"),M=n("./src/models/whisper/common_whisper.js"),w=n("./src/utils/constants.js");async function C(Ue,W){const fe=await Promise.all([(0,l.getModelJSON)(Ue,"tokenizer.json",!0,W),(0,l.getModelJSON)(Ue,"tokenizer_config.json",!0,W)]);return W.legacy!==null&&(fe[1].legacy=W.legacy),fe}function k(Ue,W){const fe=[];let Pe=0;for(const ze of Ue.matchAll(W)){const Oe=ze[0];Pe<ze.index&&fe.push(Ue.slice(Pe,ze.index)),Oe.length>0&&fe.push(Oe),Pe=ze.index+Oe.length}return Pe<Ue.length&&fe.push(Ue.slice(Pe)),fe}function z(Ue,W=!0){if(Ue.Regex!==void 0){let fe=Ue.Regex.replace(/\\([#&~])/g,"$1");for(const[Pe,ze]of Y)fe=fe.replaceAll(Pe,ze);return new RegExp(fe,"gu")}else if(Ue.String!==void 0){const fe=(0,a.escapeRegExp)(Ue.String);return new RegExp(W?fe:`(${fe})`,"gu")}else return console.warn("Unknown pattern type:",Ue),null}function S(Ue){return new Map(Object.entries(Ue))}function P(Ue){const W=Ue.dims;switch(W.length){case 1:return Ue.tolist();case 2:if(W[0]!==1)throw new Error("Unable to decode tensor with `batch size !== 1`. Use `tokenizer.batch_decode(...)` for batched inputs.");return Ue.tolist()[0];default:throw new Error(`Expected tensor to have 1-2 dimensions, got ${W.length}.`)}}function y(Ue){return Ue.replace(/ \./g,".").replace(/ \?/g,"?").replace(/ \!/g,"!").replace(/ ,/g,",").replace(/ \' /g,"'").replace(/ n\'t/g,"n't").replace(/ \'m/g,"'m").replace(/ \'s/g,"'s").replace(/ \'ve/g,"'ve").replace(/ \'re/g,"'re")}function x(Ue){return Ue.replace(/[\u0300-\u036f]/g,"")}function I(Ue){return x(Ue.toLowerCase())}function U(Ue){return Ue>=19968&&Ue<=40959||Ue>=13312&&Ue<=19903||Ue>=131072&&Ue<=173791||Ue>=173824&&Ue<=177983||Ue>=177984&&Ue<=178207||Ue>=178208&&Ue<=183983||Ue>=63744&&Ue<=64255||Ue>=194560&&Ue<=195103}function O(Ue,W,fe){const Pe=[];let ze=0;for(;ze<Ue.length;){if(Pe.push(Ue[ze]),(fe.get(Ue[ze])??W)!==W){++ze;continue}for(;ze<Ue.length&&(fe.get(Ue[ze])??W)===W;)++ze}return Pe}function N(Ue){return Ue.match(/\S+/g)||[]}const j="\\p{P}\\u0021-\\u002F\\u003A-\\u0040\\u005B-\\u0060\\u007B-\\u007E",D=new RegExp(`^[${j}]+$`,"gu"),Y=new Map([["(?i:'s|'t|'re|'ve|'m|'ll|'d)","(?:'([sS]|[tT]|[rR][eE]|[vV][eE]|[mM]|[lL][lL]|[dD]))"]]);class de{constructor(W){this.content=W.content,this.id=W.id,this.single_word=W.single_word??!1,this.lstrip=W.lstrip??!1,this.rstrip=W.rstrip??!1,this.special=W.special??!1,this.normalized=W.normalized??null}}class Ce extends o.Callable{constructor(W){super(),this.config=W,this.vocab=[],this.tokens_to_ids=new Map,this.unk_token_id=void 0,this.unk_token=void 0,this.end_of_word_suffix=void 0,this.fuse_unk=this.config.fuse_unk??!1}static fromConfig(W,...fe){switch(W.type){case"WordPiece":return new ee(W);case"Unigram":return new ye(W,...fe);case"BPE":return new Qe(W);default:if(W.vocab)return new ge(W,...fe);throw new Error(`Unknown TokenizerModel type: ${W.type}`)}}_call(W){let fe=this.encode(W);return this.fuse_unk&&(fe=O(fe,this.unk_token_id,this.tokens_to_ids)),fe}encode(W){throw Error("encode should be implemented in subclass.")}convert_tokens_to_ids(W){return W.map(fe=>this.tokens_to_ids.get(fe)??this.unk_token_id)}convert_ids_to_tokens(W){return W.map(fe=>this.vocab[fe]??this.unk_token)}}class ee extends Ce{constructor(W){super(W),this.tokens_to_ids=S(W.vocab),this.unk_token_id=this.tokens_to_ids.get(W.unk_token),this.unk_token=W.unk_token,this.max_input_chars_per_word=W.max_input_chars_per_word??100,this.vocab=new Array(this.tokens_to_ids.size);for(const[fe,Pe]of this.tokens_to_ids)this.vocab[Pe]=fe}encode(W){const fe=[];for(const Pe of W){const ze=[...Pe];if(ze.length>this.max_input_chars_per_word){fe.push(this.unk_token);continue}let Oe=!1,nt=0;const xt=[];for(;nt<ze.length;){let kt=ze.length,Tt=null;for(;nt<kt;){let At=ze.slice(nt,kt).join("");if(nt>0&&(At=this.config.continuing_subword_prefix+At),this.tokens_to_ids.has(At)){Tt=At;break}--kt}if(Tt===null){Oe=!0;break}xt.push(Tt),nt=kt}Oe?fe.push(this.unk_token):fe.push(...xt)}return fe}}class ye extends Ce{constructor(W,fe){super(W);const Pe=W.vocab.length;this.vocab=new Array(Pe),this.scores=new Array(Pe);for(let ze=0;ze<Pe;++ze){const Oe=W.vocab[ze];this.vocab[ze]=Oe[0],this.scores[ze]=Oe[1]}this.unk_token_id=W.unk_id,this.unk_token=this.vocab[W.unk_id],this.tokens_to_ids=new Map(this.vocab.map((ze,Oe)=>[ze,Oe])),this.bosToken=" ",this.bosTokenId=this.tokens_to_ids.get(this.bosToken),this.eosToken=fe.eos_token,this.eosTokenId=this.tokens_to_ids.get(this.eosToken),this.unkToken=this.vocab[this.unk_token_id],this.minScore=(0,f.min)(this.scores)[0],this.unkScore=this.minScore-10,this.scores[this.unk_token_id]=this.unkScore,this.trie=new h.CharTrie,this.trie.extend(this.vocab),this.fuse_unk=!0}populateNodes(W){const fe=W.sentence,Pe=fe.length;let ze=0;for(;ze<Pe;){let nt=!1;for(let xt of this.trie.commonPrefixSearch(fe.slice(ze))){const kt=this.tokens_to_ids.get(xt),Tt=this.scores[kt],At=xt.length;W.insert(ze,At,Tt,kt),!nt&&At===1&&(nt=!0)}nt||W.insert(ze,1,this.unkScore,this.unk_token_id),ze+=1}}tokenize(W){const fe=new h.TokenLattice(W,this.bosTokenId,this.eosTokenId);return this.populateNodes(fe),fe.tokens()}encode(W){const fe=[];for(const Pe of W){const ze=this.tokenize(Pe);fe.push(...ze)}return fe}}const R=(()=>{const Ue=[...Array.from({length:94},(ze,Oe)=>Oe+33),...Array.from({length:12},(ze,Oe)=>Oe+161),...Array.from({length:82},(ze,Oe)=>Oe+174)],W=Ue.slice();let fe=0;for(let ze=0;ze<256;++ze)Ue.includes(ze)||(Ue.push(ze),W.push(256+fe),fe+=1);const Pe=W.map(ze=>String.fromCharCode(ze));return Object.fromEntries(Ue.map((ze,Oe)=>[ze,Pe[Oe]]))})(),Me=(0,a.reverseDictionary)(R);class Qe extends Ce{constructor(W){super(W),this.BPE_SPLIT_TOKEN=" ",this.tokens_to_ids=S(W.vocab),this.unk_token_id=this.tokens_to_ids.get(W.unk_token),this.unk_token=W.unk_token,this.vocab=new Array(this.tokens_to_ids.size);for(const[fe,Pe]of this.tokens_to_ids)this.vocab[Pe]=fe;this.bpe_ranks=new Map(W.merges.map((fe,Pe)=>[fe,Pe])),this.merges=W.merges.map(fe=>fe.split(this.BPE_SPLIT_TOKEN)),this.end_of_word_suffix=W.end_of_word_suffix,this.continuing_subword_suffix=W.continuing_subword_suffix??null,this.byte_fallback=this.config.byte_fallback??!1,this.byte_fallback&&(this.text_encoder=new TextEncoder),this.ignore_merges=this.config.ignore_merges??!1,this.cache=new Map}bpe(W){if(W.length===0)return[];const fe=this.cache.get(W);if(fe!==void 0)return fe;const Pe=Array.from(W);this.end_of_word_suffix&&(Pe[Pe.length-1]+=this.end_of_word_suffix);let ze=[];if(Pe.length>1){const Oe=new h.PriorityQueue((kt,Tt)=>kt.score<Tt.score);let nt={token:Pe[0],bias:0,prev:null,next:null},xt=nt;for(let kt=1;kt<Pe.length;++kt){const Tt={bias:kt/Pe.length,token:Pe[kt],prev:xt,next:null};xt.next=Tt,this._add_node(Oe,xt),xt=Tt}for(;!Oe.isEmpty();){const kt=Oe.pop();if(kt.deleted||!kt.next||kt.next.deleted)continue;if(kt.deleted=!0,kt.next.deleted=!0,kt.prev){const At={...kt.prev};kt.prev.deleted=!0,kt.prev=At,At.prev?At.prev.next=At:nt=At}const Tt={token:kt.token+kt.next.token,bias:kt.bias,prev:kt.prev,next:kt.next.next};Tt.prev?(Tt.prev.next=Tt,this._add_node(Oe,Tt.prev)):nt=Tt,Tt.next&&(Tt.next.prev=Tt,this._add_node(Oe,Tt))}for(let kt=nt;kt!==null;kt=kt.next)ze.push(kt.token)}else ze=Pe;if(this.continuing_subword_suffix)for(let Oe=0;Oe<ze.length-1;++Oe)ze[Oe]+=this.continuing_subword_suffix;return this.cache.set(W,ze),ze}_add_node(W,fe){const Pe=this.bpe_ranks.get(fe.token+this.BPE_SPLIT_TOKEN+fe.next.token);Pe!==void 0&&(fe.score=Pe+fe.bias,W.push(fe))}encode(W){const fe=[];for(const Pe of W){if(this.ignore_merges&&this.tokens_to_ids.has(Pe)){fe.push(Pe);continue}const ze=this.bpe(Pe);for(const Oe of ze)this.tokens_to_ids.has(Oe)?fe.push(Oe):this.byte_fallback?fe.push(...Array.from(this.text_encoder.encode(Oe)).map(nt=>`<0x${nt.toString(16).toUpperCase().padStart(2,"0")}>`)):fe.push(this.unk_token)}return fe}}class ge extends Ce{constructor(W,fe){super(W),this.tokens_to_ids=S(fe.target_lang?W.vocab[fe.target_lang]:W.vocab),this.bos_token=fe.bos_token,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=fe.eos_token,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.pad_token=fe.pad_token,this.pad_token_id=this.tokens_to_ids.get(this.pad_token),this.unk_token=fe.unk_token,this.unk_token_id=this.tokens_to_ids.get(this.unk_token),this.vocab=new Array(this.tokens_to_ids.size);for(const[Pe,ze]of this.tokens_to_ids)this.vocab[ze]=Pe}encode(W){return W}}class Q extends o.Callable{constructor(W){super(),this.config=W}static fromConfig(W){if(W===null)return null;switch(W.type){case"BertNormalizer":return new dt(W);case"Precompiled":return new Xe(W);case"Sequence":return new ot(W);case"Replace":return new ae(W);case"NFC":return new Se(W);case"NFKC":return new X(W);case"NFKD":return new me(W);case"Strip":return new Ke(W);case"StripAccents":return new De(W);case"Lowercase":return new Be(W);case"Prepend":return new We(W);default:throw new Error(`Unknown Normalizer type: ${W.type}`)}}normalize(W){throw Error("normalize should be implemented in subclass.")}_call(W){return this.normalize(W)}}class ae extends Q{normalize(W){const fe=z(this.config.pattern);return fe===null?W:W.replaceAll(fe,this.config.content)}}class Se extends Q{normalize(W){return W=W.normalize("NFC"),W}}class X extends Q{normalize(W){return W=W.normalize("NFKC"),W}}class me extends Q{normalize(W){return W=W.normalize("NFKD"),W}}class Ke extends Q{normalize(W){return this.config.strip_left&&this.config.strip_right?W=W.trim():(this.config.strip_left&&(W=W.trimStart()),this.config.strip_right&&(W=W.trimEnd())),W}}class De extends Q{normalize(W){return W=x(W),W}}class Be extends Q{normalize(W){return W=W.toLowerCase(),W}}class We extends Q{normalize(W){return W=this.config.prepend+W,W}}class ot extends Q{constructor(W){super(W),this.normalizers=W.normalizers.map(fe=>Q.fromConfig(fe))}normalize(W){return this.normalizers.reduce((fe,Pe)=>Pe.normalize(fe),W)}}class dt extends Q{_tokenize_chinese_chars(W){const fe=[];for(let Pe=0;Pe<W.length;++Pe){const ze=W[Pe],Oe=ze.charCodeAt(0);U(Oe)?(fe.push(" "),fe.push(ze),fe.push(" ")):fe.push(ze)}return fe.join("")}stripAccents(W){return W.normalize("NFD").replace(/[\u0300-\u036f]/g,"")}_is_control(W){switch(W){case"	":case`
`:case"\r":return!1;default:return new RegExp("^\\p{Cc}|\\p{Cf}|\\p{Co}|\\p{Cs}$","u").test(W)}}_clean_text(W){const fe=[];for(const Pe of W){const ze=Pe.charCodeAt(0);ze===0||ze===65533||this._is_control(Pe)||(/^\s$/.test(Pe)?fe.push(" "):fe.push(Pe))}return fe.join("")}normalize(W){return this.config.clean_text&&(W=this._clean_text(W)),this.config.handle_chinese_chars&&(W=this._tokenize_chinese_chars(W)),this.config.lowercase?(W=W.toLowerCase(),this.config.strip_accents!==!1&&(W=this.stripAccents(W))):this.config.strip_accents&&(W=this.stripAccents(W)),W}}class Ge extends o.Callable{static fromConfig(W){if(W===null)return null;switch(W.type){case"BertPreTokenizer":return new Te(W);case"Sequence":return new rt(W);case"Whitespace":return new ft(W);case"WhitespaceSplit":return new ht(W);case"Metaspace":return new Re(W);case"ByteLevel":return new je(W);case"Split":return new Ye(W);case"Punctuation":return new tt(W);case"Digits":return new A(W);case"Replace":return new Mt(W);default:throw new Error(`Unknown PreTokenizer type: ${W.type}`)}}pre_tokenize_text(W,fe){throw Error("pre_tokenize_text should be implemented in subclass.")}pre_tokenize(W,fe){return(Array.isArray(W)?W.map(Pe=>this.pre_tokenize_text(Pe,fe)):this.pre_tokenize_text(W,fe)).flat()}_call(W,fe){return this.pre_tokenize(W,fe)}}class Te extends Ge{constructor(W){super(),this.pattern=new RegExp(`[^\\s${j}]+|[${j}]`,"gu")}pre_tokenize_text(W,fe){return W.trim().match(this.pattern)||[]}}class je extends Ge{constructor(W){super(),this.config=W,this.add_prefix_space=this.config.add_prefix_space,this.trim_offsets=this.config.trim_offsets,this.use_regex=this.config.use_regex??!0,this.pattern=new RegExp("'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)|\\s+","gu"),this.byte_encoder=R,this.text_encoder=new TextEncoder}pre_tokenize_text(W,fe){return this.add_prefix_space&&!W.startsWith(" ")&&(W=" "+W),(this.use_regex?W.match(this.pattern)||[]:[W]).map(ze=>Array.from(this.text_encoder.encode(ze),Oe=>this.byte_encoder[Oe]).join(""))}}class Ye extends Ge{constructor(W){super(),this.config=W,this.pattern=z(this.config.pattern,this.config.invert)}pre_tokenize_text(W,fe){return this.pattern===null?[]:this.config.invert?W.match(this.pattern)||[]:k(W,this.pattern)}}class tt extends Ge{constructor(W){super(),this.config=W,this.pattern=new RegExp(`[^${j}]+|[${j}]+`,"gu")}pre_tokenize_text(W,fe){return W.match(this.pattern)||[]}}class A extends Ge{constructor(W){super(),this.config=W;const fe=`[^\\d]+|\\d${this.config.individual_digits?"":"+"}`;this.pattern=new RegExp(fe,"gu")}pre_tokenize_text(W,fe){return W.match(this.pattern)||[]}}class Ae extends o.Callable{constructor(W){super(),this.config=W}static fromConfig(W){if(W===null)return null;switch(W.type){case"TemplateProcessing":return new te(W);case"ByteLevel":return new we(W);case"RobertaProcessing":return new se(W);case"BertProcessing":return new $e(W);case"Sequence":return new B(W);default:throw new Error(`Unknown PostProcessor type: ${W.type}`)}}post_process(W,...fe){throw Error("post_process should be implemented in subclass.")}_call(W,...fe){return this.post_process(W,...fe)}}class $e extends Ae{constructor(W){super(W),this.cls=W.cls[0],this.sep=W.sep[0]}post_process(W,fe=null,{add_special_tokens:Pe=!0}={}){Pe&&(W=(0,a.mergeArrays)([this.cls],W,[this.sep]));let ze=new Array(W.length).fill(0);if(fe!==null){const Oe=Pe&&this instanceof se?[this.sep]:[],nt=Pe?[this.sep]:[];W=(0,a.mergeArrays)(W,Oe,fe,nt),ze=(0,a.mergeArrays)(ze,new Array(fe.length+Oe.length+nt.length).fill(1))}return{tokens:W,token_type_ids:ze}}}class se extends $e{}class te extends Ae{constructor(W){super(W),this.single=W.single,this.pair=W.pair}post_process(W,fe=null,{add_special_tokens:Pe=!0}={}){const ze=fe===null?this.single:this.pair;let Oe=[],nt=[];for(const xt of ze)"SpecialToken"in xt?Pe&&(Oe.push(xt.SpecialToken.id),nt.push(xt.SpecialToken.type_id)):"Sequence"in xt&&(xt.Sequence.id==="A"?(Oe=(0,a.mergeArrays)(Oe,W),nt=(0,a.mergeArrays)(nt,new Array(W.length).fill(xt.Sequence.type_id))):xt.Sequence.id==="B"&&(Oe=(0,a.mergeArrays)(Oe,fe),nt=(0,a.mergeArrays)(nt,new Array(fe.length).fill(xt.Sequence.type_id))));return{tokens:Oe,token_type_ids:nt}}}class we extends Ae{post_process(W,fe=null){return fe&&(W=(0,a.mergeArrays)(W,fe)),{tokens:W}}}class B extends Ae{constructor(W){super(W),this.processors=W.processors.map(fe=>Ae.fromConfig(fe))}post_process(W,fe=null,Pe={}){let ze;for(const Oe of this.processors)if(Oe instanceof we)W=Oe.post_process(W).tokens,fe&&(fe=Oe.post_process(fe).tokens);else{const nt=Oe.post_process(W,fe,Pe);W=nt.tokens,ze=nt.token_type_ids}return{tokens:W,token_type_ids:ze}}}class J extends o.Callable{constructor(W){super(),this.config=W,this.added_tokens=[],this.end_of_word_suffix=null,this.trim_offsets=W.trim_offsets}static fromConfig(W){if(W===null)return null;switch(W.type){case"WordPiece":return new Ne(W);case"Metaspace":return new He(W);case"ByteLevel":return new ut(W);case"Replace":return new L(W);case"ByteFallback":return new ue(W);case"Fuse":return new le(W);case"Strip":return new ke(W);case"Sequence":return new Ve(W);case"CTC":return new Je(W);case"BPEDecoder":return new Z(W);default:throw new Error(`Unknown Decoder type: ${W.type}`)}}_call(W){return this.decode(W)}decode(W){return this.decode_chain(W).join("")}decode_chain(W){throw Error("`decode_chain` should be implemented in subclass.")}}class L extends J{decode_chain(W){const fe=z(this.config.pattern);return fe===null?W:W.map(Pe=>Pe.replaceAll(fe,this.config.content))}}class ue extends J{constructor(W){super(W),this.text_decoder=new TextDecoder}decode_chain(W){const fe=[];let Pe=[];for(const ze of W){let Oe=null;if(ze.length===6&&ze.startsWith("<0x")&&ze.endsWith(">")){const nt=parseInt(ze.slice(3,5),16);isNaN(nt)||(Oe=nt)}if(Oe!==null)Pe.push(Oe);else{if(Pe.length>0){const nt=this.text_decoder.decode(Uint8Array.from(Pe));fe.push(nt),Pe=[]}fe.push(ze)}}if(Pe.length>0){const ze=this.text_decoder.decode(Uint8Array.from(Pe));fe.push(ze),Pe=[]}return fe}}class le extends J{decode_chain(W){return[W.join("")]}}class ke extends J{constructor(W){super(W),this.content=this.config.content,this.start=this.config.start,this.stop=this.config.stop}decode_chain(W){return W.map(fe=>{let Pe=0;for(let Oe=0;Oe<this.start&&fe[Oe]===this.content;++Oe){Pe=Oe+1;continue}let ze=fe.length;for(let Oe=0;Oe<this.stop;++Oe){const nt=fe.length-Oe-1;if(fe[nt]===this.content){ze=nt;continue}else break}return fe.slice(Pe,ze)})}}class Ne extends J{constructor(W){super(W),this.cleanup=W.cleanup}decode_chain(W){return W.map((fe,Pe)=>(Pe!==0&&(fe.startsWith(this.config.prefix)?fe=fe.replace(this.config.prefix,""):fe=" "+fe),this.cleanup&&(fe=y(fe)),fe))}}class ut extends J{constructor(W){super(W),this.byte_decoder=Me,this.text_decoder=new TextDecoder("utf-8",{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(W){const fe=W.join(""),Pe=new Uint8Array([...fe].map(Oe=>this.byte_decoder[Oe]));return this.text_decoder.decode(Pe)}decode_chain(W){const fe=[];let Pe=[];for(const ze of W)this.added_tokens.find(Oe=>Oe.content===ze)!==void 0?(Pe.length>0&&(fe.push(this.convert_tokens_to_string(Pe)),Pe=[]),fe.push(ze)):Pe.push(ze);return Pe.length>0&&fe.push(this.convert_tokens_to_string(Pe)),fe}}class Je extends J{constructor(W){super(W),this.pad_token=this.config.pad_token,this.word_delimiter_token=this.config.word_delimiter_token,this.cleanup=this.config.cleanup}convert_tokens_to_string(W){if(W.length===0)return"";const fe=[W[0]];for(let Oe=1;Oe<W.length;++Oe)W[Oe]!==fe.at(-1)&&fe.push(W[Oe]);let ze=fe.filter(Oe=>Oe!==this.pad_token).join("");return this.cleanup&&(ze=y(ze).replaceAll(this.word_delimiter_token," ").trim()),ze}decode_chain(W){return[this.convert_tokens_to_string(W)]}}class Ve extends J{constructor(W){super(W),this.decoders=W.decoders.map(fe=>J.fromConfig(fe))}decode_chain(W){return this.decoders.reduce((fe,Pe)=>Pe.decode_chain(fe),W)}}class Z extends J{constructor(W){super(W),this.suffix=this.config.suffix}decode_chain(W){return W.map((fe,Pe)=>fe.replaceAll(this.suffix,Pe===W.length-1?"":" "))}}class ve extends J{decode_chain(W){let fe="";for(let Pe=1;Pe<W.length;Pe+=2)fe+=W[Pe];return[fe]}}class Re extends Ge{constructor(W){super(),this.addPrefixSpace=W.add_prefix_space,this.replacement=W.replacement,this.strRep=W.str_rep||this.replacement,this.prepend_scheme=W.prepend_scheme??"always"}pre_tokenize_text(W,{section_index:fe=void 0}={}){let Pe=W.replaceAll(" ",this.strRep);return this.addPrefixSpace&&!Pe.startsWith(this.replacement)&&(this.prepend_scheme==="always"||this.prepend_scheme==="first"&&fe===0)&&(Pe=this.strRep+Pe),[Pe]}}class He extends J{constructor(W){super(W),this.addPrefixSpace=W.add_prefix_space,this.replacement=W.replacement}decode_chain(W){const fe=[];for(let Pe=0;Pe<W.length;++Pe){let ze=W[Pe].replaceAll(this.replacement," ");this.addPrefixSpace&&Pe==0&&ze.startsWith(" ")&&(ze=ze.substring(1)),fe.push(ze)}return fe}}class Xe extends Q{constructor(W){super(W),this.charsmap=W.precompiled_charsmap}normalize(W){return W=W.replace(/[\u0001-\u0008\u000B\u000E-\u001F\u007F\u008F\u009F]/gm,""),W=W.replace(/[\u0009\u000A\u000C\u000D\u1680\u200B\u200C\u200E\u200F\u2028\u2029\u2581\uFEFF\uFFFD]/gm," "),W.includes("～")?W=W.split("～").map(Pe=>Pe.normalize("NFKC")).join("～"):W=W.normalize("NFKC"),W}}class rt extends Ge{constructor(W){super(),this.tokenizers=W.pretokenizers.map(fe=>Ge.fromConfig(fe))}pre_tokenize_text(W,fe){return this.tokenizers.reduce((Pe,ze)=>ze.pre_tokenize(Pe,fe),[W])}}class ft extends Ge{constructor(W){super()}pre_tokenize_text(W,fe){return W.match(/\w+|[^\w\s]+/g)||[]}}class ht extends Ge{constructor(W){super()}pre_tokenize_text(W,fe){return N(W)}}class Mt extends Ge{constructor(W){super(),this.config=W,this.pattern=z(this.config.pattern),this.content=this.config.content}pre_tokenize_text(W,fe){return this.pattern===null?[W]:[W.replaceAll(this.pattern,this.config.content)]}}const wt=["bos_token","eos_token","unk_token","sep_token","pad_token","cls_token","mask_token"];function St(Ue,W,fe,Pe){for(const ze of Object.keys(Ue)){const Oe=W-Ue[ze].length,nt=fe(ze),xt=new Array(Oe).fill(nt);Ue[ze]=Pe==="right"?(0,a.mergeArrays)(Ue[ze],xt):(0,a.mergeArrays)(xt,Ue[ze])}}function Rt(Ue,W){for(const fe of Object.keys(Ue))Ue[fe].length=W}class at extends o.Callable{constructor(fe,Pe){super();qe(this,"return_token_type_ids",!1);qe(this,"padding_side","right");this._tokenizer_config=Pe,this.normalizer=Q.fromConfig(fe.normalizer),this.pre_tokenizer=Ge.fromConfig(fe.pre_tokenizer),this.model=Ce.fromConfig(fe.model,Pe),this.post_processor=Ae.fromConfig(fe.post_processor),this.decoder=J.fromConfig(fe.decoder),this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];for(const ze of fe.added_tokens){const Oe=new de(ze);this.added_tokens.push(Oe),this.model.tokens_to_ids.set(Oe.content,Oe.id),this.model.vocab[Oe.id]=Oe.content,Oe.special&&(this.special_tokens.push(Oe.content),this.all_special_ids.push(Oe.id))}if(this.additional_special_tokens=Pe.additional_special_tokens??[],this.special_tokens.push(...this.additional_special_tokens),this.special_tokens=[...new Set(this.special_tokens)],this.decoder&&(this.decoder.added_tokens=this.added_tokens,this.decoder.end_of_word_suffix=this.model.end_of_word_suffix),this.added_tokens_regex=this.added_tokens.length>0?new RegExp(this.added_tokens.toSorted((ze,Oe)=>Oe.content.length-ze.content.length).map(ze=>`${ze.lstrip?"\\s*":""}(${(0,a.escapeRegExp)(ze.content)})${ze.rstrip?"\\s*":""}`).join("|")):null,this.mask_token=this.getToken("mask_token"),this.mask_token_id=this.model.tokens_to_ids.get(this.mask_token),this.pad_token=this.getToken("pad_token","eos_token"),this.pad_token_id=this.model.tokens_to_ids.get(this.pad_token),this.sep_token=this.getToken("sep_token"),this.sep_token_id=this.model.tokens_to_ids.get(this.sep_token),this.unk_token=this.getToken("unk_token"),this.unk_token_id=this.model.tokens_to_ids.get(this.unk_token),this.model_max_length=Pe.model_max_length,this.remove_space=Pe.remove_space,this.clean_up_tokenization_spaces=Pe.clean_up_tokenization_spaces??!0,this.do_lowercase_and_remove_accent=Pe.do_lowercase_and_remove_accent??!1,Pe.padding_side&&(this.padding_side=Pe.padding_side),this.legacy=!1,this.chat_template=Pe.chat_template??null,Array.isArray(this.chat_template)){const ze=Object.create(null);for(const{name:Oe,template:nt}of this.chat_template){if(typeof Oe!="string"||typeof nt!="string")throw new Error('Chat template must be a list of objects with "name" and "template" properties');ze[Oe]=nt}this.chat_template=ze}this._compiled_template_cache=new Map}getToken(...fe){for(const Pe of fe){const ze=this._tokenizer_config[Pe];if(ze)if(typeof ze=="object"){if(ze.__type==="AddedToken")return ze.content;throw Error(`Unknown token: ${ze}`)}else return ze}return null}static async from_pretrained(fe,{progress_callback:Pe=null,config:ze=null,cache_dir:Oe=null,local_files_only:nt=!1,revision:xt="main",legacy:kt=null}={}){const Tt=await C(fe,{progress_callback:Pe,config:ze,cache_dir:Oe,local_files_only:nt,revision:xt,legacy:kt});return new this(...Tt)}_call(fe,{text_pair:Pe=null,add_special_tokens:ze=!0,padding:Oe=!1,truncation:nt=null,max_length:xt=null,return_tensor:kt=!0,return_token_type_ids:Tt=null}={}){const At=Array.isArray(fe);let Zt;if(At){if(fe.length===0)throw Error("text array must be non-empty");if(Pe!==null){if(Array.isArray(Pe)){if(fe.length!==Pe.length)throw Error("text and text_pair must have the same length")}else throw Error("text_pair must also be an array");Zt=fe.map((rr,Gt)=>this._encode_plus(rr,{text_pair:Pe[Gt],add_special_tokens:ze,return_token_type_ids:Tt}))}else Zt=fe.map(rr=>this._encode_plus(rr,{add_special_tokens:ze,return_token_type_ids:Tt}))}else{if(fe==null)throw Error("text may not be null or undefined");if(Array.isArray(Pe))throw Error("When specifying `text_pair`, since `text` is a string, `text_pair` must also be a string (i.e., not an array).");Zt=[this._encode_plus(fe,{text_pair:Pe,add_special_tokens:ze,return_token_type_ids:Tt})]}if(xt===null?Oe==="max_length"?xt=this.model_max_length:xt=(0,f.max)(Zt.map(rr=>rr.input_ids.length))[0]:nt||console.warn("Truncation was not explicitly activated but `max_length` is provided a specific value, please use `truncation=true` to explicitly truncate examples to max length."),xt=Math.min(xt,this.model_max_length??1/0),Oe||nt)for(let rr=0;rr<Zt.length;++rr)Zt[rr].input_ids.length!==xt&&(Zt[rr].input_ids.length>xt?nt&&Rt(Zt[rr],xt):Oe&&St(Zt[rr],xt,Gt=>Gt==="input_ids"?this.pad_token_id:0,this.padding_side));const Pr={};if(kt){if(!(Oe&&nt)&&Zt.some(Gt=>{var mr;for(const kn of Object.keys(Gt))if(Gt[kn].length!==((mr=Zt[0][kn])==null?void 0:mr.length))return!0;return!1}))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=true' and 'truncation=true' to have batched tensors with the same length.");const rr=[Zt.length,Zt[0].input_ids.length];for(const Gt of Object.keys(Zt[0]))Pr[Gt]=new _.Tensor("int64",BigInt64Array.from(Zt.flatMap(mr=>mr[Gt]).map(BigInt)),rr)}else{for(const rr of Object.keys(Zt[0]))Pr[rr]=Zt.map(Gt=>Gt[rr]);if(!At)for(const rr of Object.keys(Pr))Pr[rr]=Pr[rr][0]}return Pr}_encode_text(fe){return fe===null?null:(this.added_tokens_regex?fe.split(this.added_tokens_regex).filter(Oe=>Oe):[fe]).map((Oe,nt)=>{if(this.added_tokens.find(kt=>kt.content===Oe)!==void 0)return Oe;{if(this.remove_space===!0&&(Oe=Oe.trim().split(/\s+/).join(" ")),this.do_lowercase_and_remove_accent&&(Oe=I(Oe)),this.normalizer!==null&&(Oe=this.normalizer(Oe)),Oe.length===0)return[];const kt=this.pre_tokenizer!==null?this.pre_tokenizer(Oe,{section_index:nt}):[Oe];return this.model(kt)}}).flat()}_encode_plus(fe,{text_pair:Pe=null,add_special_tokens:ze=!0,return_token_type_ids:Oe=null}={}){const{tokens:nt,token_type_ids:xt}=this._tokenize_helper(fe,{pair:Pe,add_special_tokens:ze}),kt=this.model.convert_tokens_to_ids(nt),Tt={input_ids:kt,attention_mask:new Array(kt.length).fill(1)};return(Oe??this.return_token_type_ids)&&xt&&(Tt.token_type_ids=xt),Tt}_tokenize_helper(fe,{pair:Pe=null,add_special_tokens:ze=!1}={}){const Oe=this._encode_text(fe),nt=this._encode_text(Pe);return this.post_processor?this.post_processor(Oe,nt,{add_special_tokens:ze}):{tokens:(0,a.mergeArrays)(Oe??[],nt??[])}}tokenize(fe,{pair:Pe=null,add_special_tokens:ze=!1}={}){return this._tokenize_helper(fe,{pair:Pe,add_special_tokens:ze}).tokens}encode(fe,{text_pair:Pe=null,add_special_tokens:ze=!0,return_token_type_ids:Oe=null}={}){return this._encode_plus(fe,{text_pair:Pe,add_special_tokens:ze,return_token_type_ids:Oe}).input_ids}batch_decode(fe,Pe={}){return fe instanceof _.Tensor&&(fe=fe.tolist()),fe.map(ze=>this.decode(ze,Pe))}decode(fe,Pe={}){if(fe instanceof _.Tensor&&(fe=P(fe)),!Array.isArray(fe)||fe.length===0||!(0,a.isIntegralNumber)(fe[0]))throw Error("token_ids must be a non-empty array of integers.");return this.decode_single(fe,Pe)}decode_single(fe,{skip_special_tokens:Pe=!1,clean_up_tokenization_spaces:ze=null}){let Oe=this.model.convert_ids_to_tokens(fe);Pe&&(Oe=Oe.filter(xt=>!this.special_tokens.includes(xt)));let nt=this.decoder?this.decoder(Oe):Oe.join(" ");return this.decoder&&this.decoder.end_of_word_suffix&&(nt=nt.replaceAll(this.decoder.end_of_word_suffix," "),Pe&&(nt=nt.trim())),(ze??this.clean_up_tokenization_spaces)&&(nt=y(nt)),nt}apply_chat_template(fe,{tools:Pe=null,documents:ze=null,chat_template:Oe=null,add_generation_prompt:nt=!1,tokenize:xt=!0,padding:kt=!1,truncation:Tt=!1,max_length:At=null,return_tensor:Zt=!0,return_dict:Pr=!1,tokenizer_kwargs:rr={},...Gt}={}){if(this.chat_template&&typeof this.chat_template=="object"||this.chat_template===null){const st=this.chat_template;if(Oe!==null&&Object.hasOwn(st,Oe))Oe=st[Oe];else if(Oe===null&&"default"in st)Oe=st.default;else if(Oe===null)throw Error(`This model has multiple chat templates with no default specified! Please either pass a chat template or the name of the template you wish to use to the 'chat_template' argument. Available template names are ${Object.keys(st).sort()}.`)}else if(this.chat_template)Oe=this.chat_template;else throw Error("Cannot use apply_chat_template() because tokenizer.chat_template is not set and no template argument was passed! For information about writing templates and setting the tokenizer.chat_template attribute, please see the documentation at https://huggingface.co/docs/transformers/main/en/chat_templating");if(typeof Oe!="string")throw Error(`chat_template must be a string, but got ${typeof Oe}`);let mr=this._compiled_template_cache.get(Oe);mr===void 0&&(mr=new g.Template(Oe),this._compiled_template_cache.set(Oe,mr));const kn=Object.create(null);for(const st of wt){const qn=this.getToken(st);qn&&(kn[st]=qn)}const pn=mr.render({messages:fe,add_generation_prompt:nt,tools:Pe,documents:ze,...kn,...Gt});if(xt){const st=this._call(pn,{add_special_tokens:!1,padding:kt,truncation:Tt,max_length:At,return_tensor:Zt,...rr});return Pr?st:st.input_ids}return pn}}class Ot extends at{constructor(){super(...arguments);qe(this,"return_token_type_ids",!0)}}class Ut extends at{constructor(){super(...arguments);qe(this,"return_token_type_ids",!0)}}class Kt extends at{constructor(){super(...arguments);qe(this,"return_token_type_ids",!0)}}class Qt extends at{constructor(){super(...arguments);qe(this,"return_token_type_ids",!0)}}class Jt extends at{constructor(){super(...arguments);qe(this,"return_token_type_ids",!0)}}class qt extends at{constructor(){super(...arguments);qe(this,"return_token_type_ids",!0)}}class Er extends at{constructor(){super(...arguments);qe(this,"return_token_type_ids",!0)}}class Qr extends at{constructor(){super(...arguments);qe(this,"return_token_type_ids",!0)}}class Cr extends at{constructor(){super(...arguments);qe(this,"return_token_type_ids",!0)}}class mt extends at{}class Pt extends at{}class Bt extends at{constructor(fe,Pe){super(fe,Pe);qe(this,"return_token_type_ids",!0);console.warn('WARNING: `XLMTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}}class sn extends at{constructor(){super(...arguments);qe(this,"return_token_type_ids",!0)}}class Li extends at{}class bi extends at{}class Nr extends at{}class mn extends at{constructor(W,fe){super(W,fe),this.languageRegex=/^[a-z]{2}_[A-Z]{2}$/,this.language_codes=this.special_tokens.filter(Pe=>this.languageRegex.test(Pe)),this.lang_to_token=Pe=>Pe}_build_translation_inputs(W,fe,Pe){return Mi(this,W,fe,Pe)}}class Wr extends mn{}class ci extends at{}class Fr extends at{constructor(W,fe){var Oe,nt;const Pe=".,!?…。，、।۔،",ze=(nt=(Oe=W.pre_tokenizer)==null?void 0:Oe.pretokenizers[0])==null?void 0:nt.pattern;ze&&ze.Regex===` ?[^(\\s|[${Pe}])]+`&&(ze.Regex=` ?[^\\s${Pe}]+`),super(W,fe)}}const Ri="▁";class xi extends at{constructor(fe,Pe){super(fe,Pe);qe(this,"padding_side","left");this.legacy=Pe.legacy??!0,this.legacy||(this.normalizer=null,this.pre_tokenizer=new Re({replacement:Ri,add_prefix_space:!0,prepend_scheme:"first"}))}_encode_text(fe){if(fe===null)return null;if(this.legacy||fe.length===0)return super._encode_text(fe);let Pe=super._encode_text(Ri+fe.replaceAll(Ri," "));return Pe.length>1&&Pe[0]===Ri&&this.special_tokens.includes(Pe[1])&&(Pe=Pe.slice(1)),Pe}}class ks extends at{}class Oo extends at{}class Do extends at{}class Lo extends at{}class Ro extends at{}class Bi extends at{}class Ss extends at{}class co extends at{}class di extends at{}function Mi(Ue,W,fe,Pe){if(!("language_codes"in Ue)||!Array.isArray(Ue.language_codes))throw new Error("Tokenizer must have `language_codes` attribute set and it should be an array of language ids.");if(!("languageRegex"in Ue)||!(Ue.languageRegex instanceof RegExp))throw new Error("Tokenizer must have `languageRegex` attribute set and it should be a regular expression.");if(!("lang_to_token"in Ue)||typeof Ue.lang_to_token!="function")throw new Error("Tokenizer must have `lang_to_token` attribute set and it should be a function.");const ze=Pe.src_lang,Oe=Pe.tgt_lang;if(!Ue.language_codes.includes(Oe))throw new Error(`Target language code "${Oe}" is not valid. Must be one of: {${Ue.language_codes.join(", ")}}`);if(ze!==void 0){if(!Ue.language_codes.includes(ze))throw new Error(`Source language code "${ze}" is not valid. Must be one of: {${Ue.language_codes.join(", ")}}`);for(const nt of Ue.post_processor.config.single)if("SpecialToken"in nt&&Ue.languageRegex.test(nt.SpecialToken.id)){nt.SpecialToken.id=Ue.lang_to_token(ze);break}}return Pe.forced_bos_token_id=Ue.model.convert_tokens_to_ids([Ue.lang_to_token(Oe)])[0],Ue._call(W,fe)}class Ti extends at{constructor(W,fe){super(W,fe),this.languageRegex=/^[a-z]{3}_[A-Z][a-z]{3}$/,this.language_codes=this.special_tokens.filter(Pe=>this.languageRegex.test(Pe)),this.lang_to_token=Pe=>Pe}_build_translation_inputs(W,fe,Pe){return Mi(this,W,fe,Pe)}}class Yi extends at{constructor(W,fe){super(W,fe),this.languageRegex=/^__[a-z]{2,3}__$/,this.language_codes=this.special_tokens.filter(Pe=>this.languageRegex.test(Pe)).map(Pe=>Pe.slice(2,-2)),this.lang_to_token=Pe=>`__${Pe}__`}_build_translation_inputs(W,fe,Pe){return Mi(this,W,fe,Pe)}}class fo extends at{get timestamp_begin(){return this.model.convert_tokens_to_ids(["<|notimestamps|>"])[0]+1}_decode_asr(W,{return_timestamps:fe=!1,return_language:Pe=!1,time_precision:ze=null,force_full_sequences:Oe=!0}={}){if(ze===null)throw Error("Must specify time_precision");let nt=null;const xt=fe==="word";function kt(){return{language:nt,timestamp:[null,null],text:""}}const Tt=[];let At=kt(),Zt=0;const Pr=this.timestamp_begin;let rr=[],Gt=[],mr=!1,kn=null;const pn=new Set(this.all_special_ids);for(const xr of W){const an=xr.tokens,$n=xt?xr.token_timestamps:null;let Yt=null,Bn=Pr;if("stride"in xr){const[kr,Ct,wr]=xr.stride;if(Zt-=Ct,kn=kr-wr,Ct&&(Bn=Ct/ze+Pr),wr)for(let zr=an.length-1;zr>=0;--zr){const Gr=Number(an[zr]);if(Gr>=Pr){if(Yt!==null&&(Gr-Pr)*ze<kn)break;Yt=Gr}}}let gn=[],Tr=[];for(let kr=0;kr<an.length;++kr){const Ct=Number(an[kr]);if(pn.has(Ct)){const wr=this.decode([Ct]),zr=M.WHISPER_LANGUAGE_MAPPING.get(wr.slice(2,-2));if(zr!==void 0){if(nt!==null&&zr!==nt&&!fe){rr.push(gn);const Gr=this.findLongestCommonSequence(rr)[0],Nn=this.decode(Gr);At.text=Nn,Tt.push(At),rr=[],gn=[],At=kt()}nt=At.language=zr}}else if(Ct>=Pr){const wr=(Ct-Pr)*ze+Zt,zr=(0,f.round)(wr,2);if(Yt!==null&&Ct>=Yt)mr=!0;else if(mr||rr.length>0&&Ct<Bn)mr=!1;else if(At.timestamp[0]===null)At.timestamp[0]=zr;else if(zr!==At.timestamp[0]){At.timestamp[1]=zr,rr.push(gn),xt&&Gt.push(Tr);const[Gr,Nn]=this.findLongestCommonSequence(rr,Gt),Dt=this.decode(Gr);At.text=Dt,xt&&(At.words=this.collateWordTimestamps(Gr,Nn,nt)),Tt.push(At),rr=[],gn=[],Gt=[],Tr=[],At=kt()}}else if(gn.push(Ct),xt){let wr=(0,f.round)($n[kr]+Zt,2),zr;if(kr+1<$n.length){zr=(0,f.round)($n[kr+1]+Zt,2);const Gr=this.decode([Ct]);D.test(Gr)&&(zr=(0,f.round)(Math.min(wr+ze,zr),2))}else zr=null;Tr.push([wr,zr])}}if("stride"in xr){const[kr,Ct,wr]=xr.stride;Zt+=kr-wr}gn.length>0?(rr.push(gn),xt&&Gt.push(Tr)):rr.every(kr=>kr.length===0)&&(At=kt(),rr=[],gn=[],Gt=[],Tr=[])}if(rr.length>0){if(Oe&&fe)throw new Error("Whisper did not predict an ending timestamp, which can happen if audio is cut off in the middle of a word. Also make sure WhisperTimeStampLogitsProcessor was used during generation.");const[xr,an]=this.findLongestCommonSequence(rr,Gt),$n=this.decode(xr);At.text=$n,xt&&(At.words=this.collateWordTimestamps(xr,an,nt)),Tt.push(At)}let st=Object.create(null);const qn=Tt.map(xr=>xr.text).join("");if(fe||Pe){for(let xr=0;xr<Tt.length;++xr){const an=Tt[xr];fe||delete an.timestamp,Pe||delete an.language}if(xt){const xr=[];for(const an of Tt)for(const $n of an.words)xr.push($n);st={chunks:xr}}else st={chunks:Tt}}return[qn,st]}findLongestCommonSequence(W,fe=null){let Pe=W[0],ze=Pe.length,Oe=[];const nt=Array.isArray(fe)&&fe.length>0;let xt=nt?[]:null,kt=nt?fe[0]:null;for(let Tt=1;Tt<W.length;++Tt){const At=W[Tt];let Zt=0,Pr=[ze,ze,0,0];const rr=At.length;for(let xr=1;xr<ze+rr;++xr){const an=Math.max(0,ze-xr),$n=Math.min(ze,ze+rr-xr),Yt=Pe.slice(an,$n),Bn=Math.max(0,xr-ze),gn=Math.min(rr,xr),Tr=At.slice(Bn,gn);if(Yt.length!==Tr.length)throw new Error("There is a bug within whisper `decode_asr` function, please report it. Dropping to prevent bad inference.");let kr;nt?kr=Yt.filter((zr,Gr)=>zr===Tr[Gr]&&kt[an+Gr]<=fe[Tt][Bn+Gr]).length:kr=Yt.filter((zr,Gr)=>zr===Tr[Gr]).length;const Ct=xr/1e4,wr=kr/xr+Ct;kr>1&&wr>Zt&&(Zt=wr,Pr=[an,$n,Bn,gn])}const[Gt,mr,kn,pn]=Pr,st=Math.floor((mr+Gt)/2),qn=Math.floor((pn+kn)/2);Oe.push(...Pe.slice(0,st)),Pe=At.slice(qn),ze=Pe.length,nt&&(xt.push(...kt.slice(0,st)),kt=fe[Tt].slice(qn))}return Oe.push(...Pe),nt?(xt.push(...kt),[Oe,xt]):[Oe,[]]}collateWordTimestamps(W,fe,Pe){const[ze,Oe,nt]=this.combineTokensIntoWords(W,Pe),xt=[];for(let kt=0;kt<ze.length;++kt){const Tt=nt[kt];xt.push({text:ze[kt],timestamp:[fe[Tt.at(0)][0],fe[Tt.at(-1)][1]]})}return xt}combineTokensIntoWords(W,fe,Pe=`"'“¡¿([{-`,ze=`"'.。,，!！?？:：”)]}、`){fe=fe??"english";let Oe,nt,xt;return["chinese","japanese","thai","lao","myanmar"].includes(fe)?[Oe,nt,xt]=this.splitTokensOnUnicode(W):[Oe,nt,xt]=this.splitTokensOnSpaces(W),this.mergePunctuations(Oe,nt,xt,Pe,ze)}decode(W,fe){let Pe;return fe!=null&&fe.decode_with_timestamps?(W instanceof _.Tensor&&(W=P(W)),Pe=this.decodeWithTimestamps(W,fe)):Pe=super.decode(W,fe),Pe}decodeWithTimestamps(W,fe){const Pe=(fe==null?void 0:fe.time_precision)??.02,ze=Array.from(this.all_special_ids).at(-1)+1;let Oe=[[]];for(let nt of W)if(nt=Number(nt),nt>=ze){const xt=((nt-ze)*Pe).toFixed(2);Oe.push(`<|${xt}|>`),Oe.push([])}else Oe[Oe.length-1].push(nt);return Oe=Oe.map(nt=>typeof nt=="string"?nt:super.decode(nt,fe)),Oe.join("")}splitTokensOnUnicode(W){const fe=this.decode(W,{decode_with_timestamps:!0}),Pe="�",ze=[],Oe=[],nt=[];let xt=[],kt=[],Tt=0;for(let At=0;At<W.length;++At){const Zt=W[At];xt.push(Zt),kt.push(At);const Pr=this.decode(xt,{decode_with_timestamps:!0});(!Pr.includes(Pe)||fe[Tt+Pr.indexOf(Pe)]===Pe)&&(ze.push(Pr),Oe.push(xt),nt.push(kt),xt=[],kt=[],Tt+=Pr.length)}return[ze,Oe,nt]}splitTokensOnSpaces(W){const[fe,Pe,ze]=this.splitTokensOnUnicode(W),Oe=[],nt=[],xt=[],kt=new RegExp(`^[${j}]$`,"gu");for(let Tt=0;Tt<fe.length;++Tt){const At=fe[Tt],Zt=Pe[Tt],Pr=ze[Tt],rr=Zt[0]>=this.model.tokens_to_ids.get("<|endoftext|>"),Gt=At.startsWith(" "),mr=At.trim(),kn=kt.test(mr);if(rr||Gt||kn||Oe.length===0)Oe.push(At),nt.push(Zt),xt.push(Pr);else{const pn=Oe.length-1;Oe[pn]+=At,nt[pn].push(...Zt),xt[pn].push(...Pr)}}return[Oe,nt,xt]}mergePunctuations(W,fe,Pe,ze,Oe){const nt=structuredClone(W),xt=structuredClone(fe),kt=structuredClone(Pe);let Tt=nt.length-2,At=nt.length-1;for(;Tt>=0;)nt[Tt].startsWith(" ")&&ze.includes(nt[Tt].trim())?(nt[At]=nt[Tt]+nt[At],xt[At]=(0,a.mergeArrays)(xt[Tt],xt[At]),kt[At]=(0,a.mergeArrays)(kt[Tt],kt[At]),nt[Tt]="",xt[Tt]=[],kt[Tt]=[]):At=Tt,--Tt;for(Tt=0,At=1;At<nt.length;)!nt[Tt].endsWith(" ")&&Oe.includes(nt[At])?(nt[Tt]+=nt[At],xt[Tt]=(0,a.mergeArrays)(xt[Tt],xt[At]),kt[Tt]=(0,a.mergeArrays)(kt[Tt],kt[At]),nt[At]="",xt[At]=[],kt[At]=[]):Tt=At,++At;return[nt.filter(Zt=>Zt),xt.filter(Zt=>Zt.length>0),kt.filter(Zt=>Zt.length>0)]}get_decoder_prompt_ids({language:W=null,task:fe=null,no_timestamps:Pe=!0}={}){const ze=[];if(W){const Oe=(0,M.whisper_language_to_code)(W),nt=this.model.tokens_to_ids.get(`<|${Oe}|>`);if(nt===void 0)throw new Error(`Unable to find language "${Oe}" in model vocabulary. Please report this issue at ${w.GITHUB_ISSUE_URL}.`);ze.push(nt)}else ze.push(null);if(fe){if(fe=fe.toLowerCase(),fe!=="transcribe"&&fe!=="translate")throw new Error(`Task "${fe}" is not supported. Must be one of: ["transcribe", "translate"]`);const Oe=this.model.tokens_to_ids.get(`<|${fe}|>`);if(Oe===void 0)throw new Error(`Unable to find task "${fe}" in model vocabulary. Please report this issue at ${w.GITHUB_ISSUE_URL}.`);ze.push(Oe)}else ze.push(null);if(Pe){const Oe=this.model.tokens_to_ids.get("<|notimestamps|>");if(Oe===void 0)throw new Error(`Unable to find "<|notimestamps|>" in model vocabulary. Please report this issue at ${w.GITHUB_ISSUE_URL}.`);ze.push(Oe)}return ze.map((Oe,nt)=>[nt+1,Oe]).filter(Oe=>Oe[1]!==null)}}class po extends at{}class Xt extends at{}class Zi extends at{}class Bo extends at{constructor(W,fe){super(W,fe),this.languageRegex=/^(>>\w+<<)\s*/g,this.supported_language_codes=this.model.vocab.filter(Pe=>this.languageRegex.test(Pe)),console.warn('WARNING: `MarianTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}_encode_text(W){if(W===null)return null;const[fe,...Pe]=W.trim().split(this.languageRegex);if(Pe.length===0)return super._encode_text(fe);if(Pe.length===2){const[ze,Oe]=Pe;return this.supported_language_codes.includes(ze)||console.warn(`Unsupported language code "${ze}" detected, which may lead to unexpected behavior. Should be one of: ${JSON.stringify(this.supported_language_codes)}`),(0,a.mergeArrays)([ze],super._encode_text(Oe))}}}class No extends at{}class ho extends at{}class jo extends at{}class Uo extends at{}class mo extends at{}class Vo extends at{constructor(W,fe){super(W,fe),this.decoder=new ve({})}}class Br extends at{}class Rn{static async from_pretrained(W,{progress_callback:fe=null,config:Pe=null,cache_dir:ze=null,local_files_only:Oe=!1,revision:nt="main",legacy:xt=null}={}){var Pr;const[kt,Tt]=await C(W,{progress_callback:fe,config:Pe,cache_dir:ze,local_files_only:Oe,revision:nt,legacy:xt}),At=((Pr=Tt.tokenizer_class)==null?void 0:Pr.replace(/Fast$/,""))??"PreTrainedTokenizer";let Zt=this.TOKENIZER_CLASS_MAPPING[At];return Zt||(console.warn(`Unknown tokenizer class "${At}", attempting to construct from base class.`),Zt=at),new Zt(kt,Tt)}}qe(Rn,"TOKENIZER_CLASS_MAPPING",{T5Tokenizer:Li,DistilBertTokenizer:mt,CamembertTokenizer:Pt,DebertaTokenizer:Jt,DebertaV2Tokenizer:qt,BertTokenizer:Ot,HerbertTokenizer:Er,ConvBertTokenizer:Qr,RoFormerTokenizer:Cr,XLMTokenizer:Bt,ElectraTokenizer:sn,MobileBertTokenizer:Kt,SqueezeBertTokenizer:Qt,AlbertTokenizer:Ut,GPT2Tokenizer:bi,BartTokenizer:Nr,MBartTokenizer:mn,MBart50Tokenizer:Wr,RobertaTokenizer:ci,WhisperTokenizer:fo,CodeGenTokenizer:po,CLIPTokenizer:Xt,SiglipTokenizer:Zi,MarianTokenizer:Bo,BloomTokenizer:Fr,NllbTokenizer:Ti,M2M100Tokenizer:Yi,LlamaTokenizer:xi,CodeLlamaTokenizer:ks,XLMRobertaTokenizer:Oo,MPNetTokenizer:Do,FalconTokenizer:Lo,GPTNeoXTokenizer:Ro,EsmTokenizer:Bi,Wav2Vec2CTCTokenizer:No,BlenderbotTokenizer:ho,BlenderbotSmallTokenizer:jo,SpeechT5Tokenizer:Uo,NougatTokenizer:mo,VitsTokenizer:Vo,Qwen2Tokenizer:Ss,GemmaTokenizer:co,Grok1Tokenizer:di,CohereTokenizer:Br,PreTrainedTokenizer:at})},"./src/utils/audio.js":(e,t,n)=>{n.r(t),n.d(t,{hamming:()=>M,hanning:()=>g,mel_filter_bank:()=>y,read_audio:()=>_,spectrogram:()=>N,window_function:()=>j});var o=n("./src/utils/hub.js"),a=n("./src/utils/maths.js"),l=n("./src/utils/core.js"),f=n("./src/utils/tensor.js");async function _(D,Y){if(typeof AudioContext>"u")throw Error("Unable to load audio from path/URL since `AudioContext` is not available in your environment. Instead, audio data should be passed directly to the pipeline/processor. 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Using bilinear instead.`),I="bilinear");case"nearest":case"bilinear":case"bicubic":U=U.affine([P/this.width,0,0,y/this.height],{interpolator:I});break;case"lanczos":U=U.resize({width:P,height:y,fit:"fill",kernel:"lanczos3"});break;default:throw new Error(`Resampling method ${I} is not supported.`)}return await w(U)}}async pad([P,y,x,I]){if(P=Math.max(P,0),y=Math.max(y,0),x=Math.max(x,0),I=Math.max(I,0),P===0&&y===0&&x===0&&I===0)return this;if(_){const U=this.channels,O=this.toCanvas(),N=this.width+P+y,j=this.height+x+I,D=g(N,j).getContext("2d");return D.drawImage(O,0,0,this.width,this.height,P,x,N,j),new z(D.getImageData(0,0,N,j).data,N,j,4).convert(U)}else{const U=this.toSharp().extend({left:P,right:y,top:x,bottom:I});return await w(U)}}async crop([P,y,x,I]){if(P=Math.max(P,0),y=Math.max(y,0),x=Math.min(x,this.width-1),I=Math.min(I,this.height-1),P===0&&y===0&&x===this.width-1&&I===this.height-1)return this;const U=x-P+1,O=I-y+1;if(_){const N=this.channels,j=this.toCanvas(),D=g(U,O).getContext("2d");return D.drawImage(j,P,y,U,O,0,0,U,O),new z(D.getImageData(0,0,U,O).data,U,O,4).convert(N)}else{const N=this.toSharp().extract({left:P,top:y,width:U,height:O});return await w(N)}}async center_crop(P,y){if(this.width===P&&this.height===y)return this;const x=(this.width-P)/2,I=(this.height-y)/2;if(_){const U=this.channels,O=this.toCanvas(),N=g(P,y).getContext("2d");let j=0,D=0,Y=0,de=0;return x>=0?j=x:Y=-x,I>=0?D=I:de=-I,N.drawImage(O,j,D,P,y,Y,de,P,y),new z(N.getImageData(0,0,P,y).data,P,y,4).convert(U)}else{let U=this.toSharp();if(x>=0&&I>=0)U=U.extract({left:Math.floor(x),top:Math.floor(I),width:P,height:y});else if(x<=0&&I<=0){const O=Math.floor(-I),N=Math.floor(-x);U=U.extend({top:O,left:N,right:P-this.width-N,bottom:y-this.height-O})}else{let O=[0,0],N=0;I<0?(O[0]=Math.floor(-I),O[1]=y-this.height-O[0]):N=Math.floor(I);let j=[0,0],D=0;x<0?(j[0]=Math.floor(-x),j[1]=P-this.width-j[0]):D=Math.floor(x),U=U.extend({top:O[0],bottom:O[1],left:j[0],right:j[1]}).extract({left:D,top:N,width:P,height:y})}return await w(U)}}async toBlob(P="image/png",y=1){if(!_)throw new Error("toBlob() is only supported in browser environments.");return await this.toCanvas().convertToBlob({type:P,quality:y})}toTensor(P="CHW"){let y=new l.Tensor("uint8",new Uint8Array(this.data),[this.height,this.width,this.channels]);if(P!=="HWC")if(P==="CHW")y=y.permute(2,0,1);else throw new Error(`Unsupported channel format: ${P}`);return y}toCanvas(){if(!_)throw new Error("toCanvas() is only supported in browser environments.");const P=this.clone().rgba(),y=g(P.width,P.height),x=new M(P.data,P.width,P.height);return y.getContext("2d").putImageData(x,0,0),y}_update(P,y,x,I=null){return this.data=P,this.width=y,this.height=x,I!==null&&(this.channels=I),this}clone(){return new z(this.data.slice(),this.width,this.height,this.channels)}convert(P){if(this.channels===P)return this;switch(P){case 1:this.grayscale();break;case 3:this.rgb();break;case 4:this.rgba();break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this}async save(P){if(_){if(h)throw new Error("Unable to save an image from a Web Worker.");const y=P.split(".").pop().toLowerCase(),x=k.get(y)??"image/png",I=await this.toBlob(x),U=URL.createObjectURL(I),O=document.createElement("a");O.href=U,O.download=P,O.click(),O.remove()}else{if(a.env.useFS)return await this.toSharp().toFile(P);throw new Error("Unable to save the image because filesystem is disabled in this environment.")}}toSharp(){if(_)throw new Error("toSharp() is only supported in server-side environments.");return f(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}})}}},"./src/utils/maths.js":(e,t,n)=>{n.r(t),n.d(t,{FFT:()=>S,bankers_round:()=>x,cos_sim:()=>h,dot:()=>_,dynamic_time_warping:()=>I,interpolate_data:()=>o,log_softmax:()=>f,magnitude:()=>g,max:()=>w,medianFilter:()=>P,min:()=>M,permute_data:()=>a,round:()=>y,softmax:()=>l});function o(U,[O,N,j],[D,Y],de="bilinear",Ce=!1){const ee=Y/j,ye=D/N,R=new U.constructor(D*Y*O),Me=N*j,Qe=D*Y;for(let ge=0;ge<D;++ge)for(let Q=0;Q<Y;++Q){const ae=ge*Y+Q,Se=(Q+.5)/ee-.5,X=(ge+.5)/ye-.5;let me=Math.floor(Se),Ke=Math.floor(X);const De=Math.min(me+1,j-1),Be=Math.min(Ke+1,N-1);me=Math.max(me,0),Ke=Math.max(Ke,0);const We=Se-me,ot=X-Ke,dt=(1-We)*(1-ot),Ge=We*(1-ot),Te=(1-We)*ot,je=We*ot,Ye=Ke*j,tt=Be*j,A=Ye+me,Ae=Ye+De,$e=tt+me,se=tt+De;for(let te=0;te<O;++te){const we=te*Me;R[te*Qe+ae]=dt*U[we+A]+Ge*U[we+Ae]+Te*U[we+$e]+je*U[we+se]}}return R}function a(U,O,N){const j=new Array(N.length),D=new Array(N.length);for(let Ce=N.length-1,ee=1;Ce>=0;--Ce)D[Ce]=ee,j[Ce]=O[N[Ce]],ee*=j[Ce];const Y=N.map((Ce,ee)=>D[N.indexOf(ee)]),de=new U.constructor(U.length);for(let Ce=0;Ce<U.length;++Ce){let ee=0;for(let ye=O.length-1,R=Ce;ye>=0;--ye)ee+=R%O[ye]*Y[ye],R=Math.floor(R/O[ye]);de[ee]=U[Ce]}return[de,j]}function l(U){const O=w(U)[0],N=U.map(Y=>Math.exp(Y-O)),j=N.reduce((Y,de)=>Y+de,0);return N.map(Y=>Y/j)}function f(U){return l(U).map(j=>Math.log(j))}function _(U,O){let N=0;for(let j=0;j<U.length;++j)N+=U[j]*O[j];return N}function h(U,O){const N=_(U,O),j=g(U),D=g(O);return N/(j*D)}function g(U){return Math.sqrt(U.reduce((O,N)=>O+N*N,0))}function M(U){if(U.length===0)throw Error("Array must not be empty");let O=U[0],N=0;for(let j=1;j<U.length;++j)U[j]<O&&(O=U[j],N=j);return[O,N]}function w(U){if(U.length===0)throw Error("Array must not be empty");let O=U[0],N=0;for(let j=1;j<U.length;++j)U[j]>O&&(O=U[j],N=j);return[Number(O),N]}function C(U){return U>0&&(U&U-1)===0}class 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Error("Input and output buffers must be different");this._realTransform4(O,N,1)}inverseTransform(O,N){if(O===N)throw new Error("Input and output buffers must be different");this._transform4(O,N,-1);for(let j=0;j<O.length;++j)O[j]/=this.size}_transform4(O,N,j){const D=this._csize;let de=1<<this._width,Ce=D/de<<1,ee,ye;const R=this._bitrev;if(Ce===4)for(ee=0,ye=0;ee<D;ee+=Ce,++ye){const Qe=R[ye];this._singleTransform2(N,O,ee,Qe,de)}else for(ee=0,ye=0;ee<D;ee+=Ce,++ye){const Qe=R[ye];this._singleTransform4(N,O,ee,Qe,de,j)}const Me=this.table;for(de>>=2;de>=2;de>>=2){Ce=D/de<<1;const Qe=Ce>>>2;for(ee=0;ee<D;ee+=Ce){const ge=ee+Qe-1;for(let Q=ee,ae=0;Q<ge;Q+=2,ae+=de){const Se=Q,X=Se+Qe,me=X+Qe,Ke=me+Qe,De=O[Se],Be=O[Se+1],We=O[X],ot=O[X+1],dt=O[me],Ge=O[me+1],Te=O[Ke],je=O[Ke+1],Ye=Me[ae],tt=j*Me[ae+1],A=We*Ye-ot*tt,Ae=We*tt+ot*Ye,$e=Me[2*ae],se=j*Me[2*ae+1],te=dt*$e-Ge*se,we=dt*se+Ge*$e,B=Me[3*ae],J=j*Me[3*ae+1],L=Te*B-je*J,ue=Te*J+je*B,le=De+te,ke=Be+we,Ne=De-te,ut=Be-we,Je=A+L,Ve=Ae+ue,Z=j*(A-L),ve=j*(Ae-ue);O[Se]=le+Je,O[Se+1]=ke+Ve,O[X]=Ne+ve,O[X+1]=ut-Z,O[me]=le-Je,O[me+1]=ke-Ve,O[Ke]=Ne-ve,O[Ke+1]=ut+Z}}}}_singleTransform2(O,N,j,D,Y){const de=O[D],Ce=O[D+1],ee=O[D+Y],ye=O[D+Y+1];N[j]=de+ee,N[j+1]=Ce+ye,N[j+2]=de-ee,N[j+3]=Ce-ye}_singleTransform4(O,N,j,D,Y,de){const Ce=Y*2,ee=Y*3,ye=O[D],R=O[D+1],Me=O[D+Y],Qe=O[D+Y+1],ge=O[D+Ce],Q=O[D+Ce+1],ae=O[D+ee],Se=O[D+ee+1],X=ye+ge,me=R+Q,Ke=ye-ge,De=R-Q,Be=Me+ae,We=Qe+Se,ot=de*(Me-ae),dt=de*(Qe-Se);N[j]=X+Be,N[j+1]=me+We,N[j+2]=Ke+dt,N[j+3]=De-ot,N[j+4]=X-Be,N[j+5]=me-We,N[j+6]=Ke-dt,N[j+7]=De+ot}_realTransform4(O,N,j){const D=this._csize;let de=1<<this._width,Ce=D/de<<1,ee,ye;const 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JSZip v3.10.1 - A JavaScript class for generating and reading zip files
<http://stuartk.com/jszip>

(c) 2009-2016 Stuart Knightley <stuart [at] stuartk.com>
Dual licenced under the MIT license or GPLv3. See https://raw.github.com/Stuk/jszip/main/LICENSE.markdown.

JSZip uses the library pako released under the MIT license :
https://github.com/nodeca/pako/blob/main/LICENSE
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z=k.meta.percent||0,S=this.entriesCount,P=this._sources.length;this.accumulate?this.contentBuffer.push(k):(this.bytesWritten+=k.data.length,h.prototype.push.call(this,{data:k.data,meta:{currentFile:this.currentFile,percent:S?(z+100*(S-P-1))/S:100}}))},C.prototype.openedSource=function(k){this.currentSourceOffset=this.bytesWritten,this.currentFile=k.file.name;var z=this.streamFiles&&!k.file.dir;if(z){var S=f(k,z,!1,this.currentSourceOffset,this.zipPlatform,this.encodeFileName);this.push({data:S.fileRecord,meta:{percent:0}})}else this.accumulate=!0},C.prototype.closedSource=function(k){this.accumulate=!1;var z=this.streamFiles&&!k.file.dir,S=f(k,z,!0,this.currentSourceOffset,this.zipPlatform,this.encodeFileName);if(this.dirRecords.push(S.dirRecord),z)this.push({data:function(P){return w.DATA_DESCRIPTOR+l(P.crc32,4)+l(P.compressedSize,4)+l(P.uncompressedSize,4)}(k),meta:{percent:100}});else for(this.push({data:S.fileRecord,meta:{percent:0}});this.contentBuffer.length;)this.push(this.contentBuffer.shift());this.currentFile=null},C.prototype.flush=function(){for(var k=this.bytesWritten,z=0;z<this.dirRecords.length;z++)this.push({data:this.dirRecords[z],meta:{percent:100}});var S=this.bytesWritten-k,P=function(y,x,I,U,O){var N=_.transformTo("string",O(U));return w.CENTRAL_DIRECTORY_END+"\0\0\0\0"+l(y,2)+l(y,2)+l(x,4)+l(I,4)+l(N.length,2)+N}(this.dirRecords.length,S,k,this.zipComment,this.encodeFileName);this.push({data:P,meta:{percent:100}})},C.prototype.prepareNextSource=function(){this.previous=this._sources.shift(),this.openedSource(this.previous.streamInfo),this.isPaused?this.previous.pause():this.previous.resume()},C.prototype.registerPrevious=function(k){this._sources.push(k);var z=this;return k.on("data",function(S){z.processChunk(S)}),k.on("end",function(){z.closedSource(z.previous.streamInfo),z._sources.length?z.prepareNextSource():z.end()}),k.on("error",function(S){z.error(S)}),this},C.prototype.resume=function(){return!!h.prototype.resume.call(this)&&(!this.previous&&this._sources.length?(this.prepareNextSource(),!0):this.previous||this._sources.length||this.generatedError?void 0:(this.end(),!0))},C.prototype.error=function(k){var z=this._sources;if(!h.prototype.error.call(this,k))return!1;for(var S=0;S<z.length;S++)try{z[S].error(k)}catch{}return!0},C.prototype.lock=function(){h.prototype.lock.call(this);for(var k=this._sources,z=0;z<k.length;z++)k[z].lock()},o.exports=C},{"../crc32":4,"../signature":23,"../stream/GenericWorker":28,"../utf8":31,"../utils":32}],9:[function(n,o,a){var l=n("../compressions"),f=n("./ZipFileWorker");a.generateWorker=function(_,h,g){var M=new f(h.streamFiles,g,h.platform,h.encodeFileName),w=0;try{_.forEach(function(C,k){w++;var z=function(x,I){var U=x||I,O=l[U];if(!O)throw new Error(U+" is not a valid compression method !");return O}(k.options.compression,h.compression),S=k.options.compressionOptions||h.compressionOptions||{},P=k.dir,y=k.date;k._compressWorker(z,S).withStreamInfo("file",{name:C,dir:P,date:y,comment:k.comment||"",unixPermissions:k.unixPermissions,dosPermissions:k.dosPermissions}).pipe(M)}),M.entriesCount=w}catch(C){M.error(C)}return M}},{"../compressions":3,"./ZipFileWorker":8}],10:[function(n,o,a){function l(){if(!(this instanceof l))return new l;if(arguments.length)throw new Error("The constructor with parameters has been removed in JSZip 3.0, please check the upgrade guide.");this.files=Object.create(null),this.comment=null,this.root="",this.clone=function(){var f=new l;for(var _ in this)typeof this[_]!="function"&&(f[_]=this[_]);return f}}(l.prototype=n("./object")).loadAsync=n("./load"),l.support=n("./support"),l.defaults=n("./defaults"),l.version="3.10.1",l.loadAsync=function(f,_){return new l().loadAsync(f,_)},l.external=n("./external"),o.exports=l},{"./defaults":5,"./external":6,"./load":11,"./object":15,"./support":30}],11:[function(n,o,a){var l=n("./utils"),f=n("./external"),_=n("./utf8"),h=n("./zipEntries"),g=n("./stream/Crc32Probe"),M=n("./nodejsUtils");function w(C){return new f.Promise(function(k,z){var S=C.decompressed.getContentWorker().pipe(new g);S.on("error",function(P){z(P)}).on("end",function(){S.streamInfo.crc32!==C.decompressed.crc32?z(new Error("Corrupted zip : CRC32 mismatch")):k()}).resume()})}o.exports=function(C,k){var z=this;return k=l.extend(k||{},{base64:!1,checkCRC32:!1,optimizedBinaryString:!1,createFolders:!1,decodeFileName:_.utf8decode}),M.isNode&&M.isStream(C)?f.Promise.reject(new Error("JSZip can't accept a stream when loading a zip file.")):l.prepareContent("the loaded zip file",C,!0,k.optimizedBinaryString,k.base64).then(function(S){var P=new h(k);return P.load(S),P}).then(function(S){var P=[f.Promise.resolve(S)],y=S.files;if(k.checkCRC32)for(var x=0;x<y.length;x++)P.push(w(y[x]));return f.Promise.all(P)}).then(function(S){for(var P=S.shift(),y=P.files,x=0;x<y.length;x++){var I=y[x],U=I.fileNameStr,O=l.resolve(I.fileNameStr);z.file(O,I.decompressed,{binary:!0,optimizedBinaryString:!0,date:I.date,dir:I.dir,comment:I.fileCommentStr.length?I.fileCommentStr:null,unixPermissions:I.unixPermissions,dosPermissions:I.dosPermissions,createFolders:k.createFolders}),I.dir||(z.file(O).unsafeOriginalName=U)}return P.zipComment.length&&(z.comment=P.zipComment),z})}},{"./external":6,"./nodejsUtils":14,"./stream/Crc32Probe":25,"./utf8":31,"./utils":32,"./zipEntries":33}],12:[function(n,o,a){var l=n("../utils"),f=n("../stream/GenericWorker");function _(h,g){f.call(this,"Nodejs stream input adapter for "+h),this._upstreamEnded=!1,this._bindStream(g)}l.inherits(_,f),_.prototype._bindStream=function(h){var g=this;(this._stream=h).pause(),h.on("data",function(M){g.push({data:M,meta:{percent:0}})}).on("error",function(M){g.isPaused?this.generatedError=M:g.error(M)}).on("end",function(){g.isPaused?g._upstreamEnded=!0:g.end()})},_.prototype.pause=function(){return!!f.prototype.pause.call(this)&&(this._stream.pause(),!0)},_.prototype.resume=function(){return!!f.prototype.resume.call(this)&&(this._upstreamEnded?this.end():this._stream.resume(),!0)},o.exports=_},{"../stream/GenericWorker":28,"../utils":32}],13:[function(n,o,a){var l=n("readable-stream").Readable;function f(_,h,g){l.call(this,h),this._helper=_;var M=this;_.on("data",function(w,C){M.push(w)||M._helper.pause(),g&&g(C)}).on("error",function(w){M.emit("error",w)}).on("end",function(){M.push(null)})}n("../utils").inherits(f,l),f.prototype._read=function(){this._helper.resume()},o.exports=f},{"../utils":32,"readable-stream":16}],14:[function(n,o,a){o.exports={isNode:typeof Buffer<"u",newBufferFrom:function(l,f){if(Buffer.from&&Buffer.from!==Uint8Array.from)return Buffer.from(l,f);if(typeof l=="number")throw new Error('The "data" argument must not be a number');return new Buffer(l,f)},allocBuffer:function(l){if(Buffer.alloc)return Buffer.alloc(l);var f=new Buffer(l);return f.fill(0),f},isBuffer:function(l){return Buffer.isBuffer(l)},isStream:function(l){return l&&typeof l.on=="function"&&typeof l.pause=="function"&&typeof l.resume=="function"}}},{}],15:[function(n,o,a){function l(O,N,j){var D,Y=_.getTypeOf(N),de=_.extend(j||{},M);de.date=de.date||new Date,de.compression!==null&&(de.compression=de.compression.toUpperCase()),typeof de.unixPermissions=="string"&&(de.unixPermissions=parseInt(de.unixPermissions,8)),de.unixPermissions&&16384&de.unixPermissions&&(de.dir=!0),de.dosPermissions&&16&de.dosPermissions&&(de.dir=!0),de.dir&&(O=y(O)),de.createFolders&&(D=P(O))&&x.call(this,D,!0);var Ce=Y==="string"&&de.binary===!1&&de.base64===!1;j&&j.binary!==void 0||(de.binary=!Ce),(N instanceof w&&N.uncompressedSize===0||de.dir||!N||N.length===0)&&(de.base64=!1,de.binary=!0,N="",de.compression="STORE",Y="string");var ee=null;ee=N instanceof w||N instanceof h?N:z.isNode&&z.isStream(N)?new S(O,N):_.prepareContent(O,N,de.binary,de.optimizedBinaryString,de.base64);var ye=new C(O,ee,de);this.files[O]=ye}var f=n("./utf8"),_=n("./utils"),h=n("./stream/GenericWorker"),g=n("./stream/StreamHelper"),M=n("./defaults"),w=n("./compressedObject"),C=n("./zipObject"),k=n("./generate"),z=n("./nodejsUtils"),S=n("./nodejs/NodejsStreamInputAdapter"),P=function(O){O.slice(-1)==="/"&&(O=O.substring(0,O.length-1));var N=O.lastIndexOf("/");return 0<N?O.substring(0,N):""},y=function(O){return O.slice(-1)!=="/"&&(O+="/"),O},x=function(O,N){return N=N!==void 0?N:M.createFolders,O=y(O),this.files[O]||l.call(this,O,null,{dir:!0,createFolders:N}),this.files[O]};function I(O){return Object.prototype.toString.call(O)==="[object RegExp]"}var U={load:function(){throw new Error("This method has been removed in JSZip 3.0, please check the upgrade guide.")},forEach:function(O){var N,j,D;for(N in this.files)D=this.files[N],(j=N.slice(this.root.length,N.length))&&N.slice(0,this.root.length)===this.root&&O(j,D)},filter:function(O){var N=[];return this.forEach(function(j,D){O(j,D)&&N.push(D)}),N},file:function(O,N,j){if(arguments.length!==1)return O=this.root+O,l.call(this,O,N,j),this;if(I(O)){var D=O;return this.filter(function(de,Ce){return!Ce.dir&&D.test(de)})}var Y=this.files[this.root+O];return Y&&!Y.dir?Y:null},folder:function(O){if(!O)return this;if(I(O))return this.filter(function(Y,de){return de.dir&&O.test(Y)});var N=this.root+O,j=x.call(this,N),D=this.clone();return D.root=j.name,D},remove:function(O){O=this.root+O;var N=this.files[O];if(N||(O.slice(-1)!=="/"&&(O+="/"),N=this.files[O]),N&&!N.dir)delete this.files[O];else for(var j=this.filter(function(Y,de){return de.name.slice(0,O.length)===O}),D=0;D<j.length;D++)delete this.files[j[D].name];return this},generate:function(){throw new Error("This method has been removed in JSZip 3.0, please check the upgrade guide.")},generateInternalStream:function(O){var N,j={};try{if((j=_.extend(O||{},{streamFiles:!1,compression:"STORE",compressionOptions:null,type:"",platform:"DOS",comment:null,mimeType:"application/zip",encodeFileName:f.utf8encode})).type=j.type.toLowerCase(),j.compression=j.compression.toUpperCase(),j.type==="binarystring"&&(j.type="string"),!j.type)throw new Error("No output type specified.");_.checkSupport(j.type),j.platform!=="darwin"&&j.platform!=="freebsd"&&j.platform!=="linux"&&j.platform!=="sunos"||(j.platform="UNIX"),j.platform==="win32"&&(j.platform="DOS");var D=j.comment||this.comment||"";N=k.generateWorker(this,j,D)}catch(Y){(N=new h("error")).error(Y)}return new g(N,j.type||"string",j.mimeType)},generateAsync:function(O,N){return this.generateInternalStream(O).accumulate(N)},generateNodeStream:function(O,N){return(O=O||{}).type||(O.type="nodebuffer"),this.generateInternalStream(O).toNodejsStream(N)}};o.exports=U},{"./compressedObject":2,"./defaults":5,"./generate":9,"./nodejs/NodejsStreamInputAdapter":12,"./nodejsUtils":14,"./stream/GenericWorker":28,"./stream/StreamHelper":29,"./utf8":31,"./utils":32,"./zipObject":35}],16:[function(n,o,a){o.exports=n("stream")},{stream:void 0}],17:[function(n,o,a){var l=n("./DataReader");function f(_){l.call(this,_);for(var h=0;h<this.data.length;h++)_[h]=255&_[h]}n("../utils").inherits(f,l),f.prototype.byteAt=function(_){return this.data[this.zero+_]},f.prototype.lastIndexOfSignature=function(_){for(var h=_.charCodeAt(0),g=_.charCodeAt(1),M=_.charCodeAt(2),w=_.charCodeAt(3),C=this.length-4;0<=C;--C)if(this.data[C]===h&&this.data[C+1]===g&&this.data[C+2]===M&&this.data[C+3]===w)return C-this.zero;return-1},f.prototype.readAndCheckSignature=function(_){var h=_.charCodeAt(0),g=_.charCodeAt(1),M=_.charCodeAt(2),w=_.charCodeAt(3),C=this.readData(4);return h===C[0]&&g===C[1]&&M===C[2]&&w===C[3]},f.prototype.readData=function(_){if(this.checkOffset(_),_===0)return[];var h=this.data.slice(this.zero+this.index,this.zero+this.index+_);return this.index+=_,h},o.exports=f},{"../utils":32,"./DataReader":18}],18:[function(n,o,a){var l=n("../utils");function f(_){this.data=_,this.length=_.length,this.index=0,this.zero=0}f.prototype={checkOffset:function(_){this.checkIndex(this.index+_)},checkIndex:function(_){if(this.length<this.zero+_||_<0)throw new Error("End of data reached (data length = "+this.length+", asked index = "+_+"). Corrupted zip ?")},setIndex:function(_){this.checkIndex(_),this.index=_},skip:function(_){this.setIndex(this.index+_)},byteAt:function(){},readInt:function(_){var h,g=0;for(this.checkOffset(_),h=this.index+_-1;h>=this.index;h--)g=(g<<8)+this.byteAt(h);return this.index+=_,g},readString:function(_){return l.transformTo("string",this.readData(_))},readData:function(){},lastIndexOfSignature:function(){},readAndCheckSignature:function(){},readDate:function(){var _=this.readInt(4);return new Date(Date.UTC(1980+(_>>25&127),(_>>21&15)-1,_>>16&31,_>>11&31,_>>5&63,(31&_)<<1))}},o.exports=f},{"../utils":32}],19:[function(n,o,a){var l=n("./Uint8ArrayReader");function f(_){l.call(this,_)}n("../utils").inherits(f,l),f.prototype.readData=function(_){this.checkOffset(_);var h=this.data.slice(this.zero+this.index,this.zero+this.index+_);return this.index+=_,h},o.exports=f},{"../utils":32,"./Uint8ArrayReader":21}],20:[function(n,o,a){var l=n("./DataReader");function f(_){l.call(this,_)}n("../utils").inherits(f,l),f.prototype.byteAt=function(_){return this.data.charCodeAt(this.zero+_)},f.prototype.lastIndexOfSignature=function(_){return this.data.lastIndexOf(_)-this.zero},f.prototype.readAndCheckSignature=function(_){return _===this.readData(4)},f.prototype.readData=function(_){this.checkOffset(_);var h=this.data.slice(this.zero+this.index,this.zero+this.index+_);return this.index+=_,h},o.exports=f},{"../utils":32,"./DataReader":18}],21:[function(n,o,a){var l=n("./ArrayReader");function f(_){l.call(this,_)}n("../utils").inherits(f,l),f.prototype.readData=function(_){if(this.checkOffset(_),_===0)return new Uint8Array(0);var h=this.data.subarray(this.zero+this.index,this.zero+this.index+_);return this.index+=_,h},o.exports=f},{"../utils":32,"./ArrayReader":17}],22:[function(n,o,a){var l=n("../utils"),f=n("../support"),_=n("./ArrayReader"),h=n("./StringReader"),g=n("./NodeBufferReader"),M=n("./Uint8ArrayReader");o.exports=function(w){var C=l.getTypeOf(w);return l.checkSupport(C),C!=="string"||f.uint8array?C==="nodebuffer"?new g(w):f.uint8array?new M(l.transformTo("uint8array",w)):new _(l.transformTo("array",w)):new h(w)}},{"../support":30,"../utils":32,"./ArrayReader":17,"./NodeBufferReader":19,"./StringReader":20,"./Uint8ArrayReader":21}],23:[function(n,o,a){a.LOCAL_FILE_HEADER="PK",a.CENTRAL_FILE_HEADER="PK
",a.CENTRAL_DIRECTORY_END="PK",a.ZIP64_CENTRAL_DIRECTORY_LOCATOR="PK\x07",a.ZIP64_CENTRAL_DIRECTORY_END="PK",a.DATA_DESCRIPTOR="PK\x07\b"},{}],24:[function(n,o,a){var l=n("./GenericWorker"),f=n("../utils");function _(h){l.call(this,"ConvertWorker to "+h),this.destType=h}f.inherits(_,l),_.prototype.processChunk=function(h){this.push({data:f.transformTo(this.destType,h.data),meta:h.meta})},o.exports=_},{"../utils":32,"./GenericWorker":28}],25:[function(n,o,a){var l=n("./GenericWorker"),f=n("../crc32");function _(){l.call(this,"Crc32Probe"),this.withStreamInfo("crc32",0)}n("../utils").inherits(_,l),_.prototype.processChunk=function(h){this.streamInfo.crc32=f(h.data,this.streamInfo.crc32||0),this.push(h)},o.exports=_},{"../crc32":4,"../utils":32,"./GenericWorker":28}],26:[function(n,o,a){var l=n("../utils"),f=n("./GenericWorker");function _(h){f.call(this,"DataLengthProbe for "+h),this.propName=h,this.withStreamInfo(h,0)}l.inherits(_,f),_.prototype.processChunk=function(h){if(h){var g=this.streamInfo[this.propName]||0;this.streamInfo[this.propName]=g+h.data.length}f.prototype.processChunk.call(this,h)},o.exports=_},{"../utils":32,"./GenericWorker":28}],27:[function(n,o,a){var l=n("../utils"),f=n("./GenericWorker");function _(h){f.call(this,"DataWorker");var g=this;this.dataIsReady=!1,this.index=0,this.max=0,this.data=null,this.type="",this._tickScheduled=!1,h.then(function(M){g.dataIsReady=!0,g.data=M,g.max=M&&M.length||0,g.type=l.getTypeOf(M),g.isPaused||g._tickAndRepeat()},function(M){g.error(M)})}l.inherits(_,f),_.prototype.cleanUp=function(){f.prototype.cleanUp.call(this),this.data=null},_.prototype.resume=function(){return!!f.prototype.resume.call(this)&&(!this._tickScheduled&&this.dataIsReady&&(this._tickScheduled=!0,l.delay(this._tickAndRepeat,[],this)),!0)},_.prototype._tickAndRepeat=function(){this._tickScheduled=!1,this.isPaused||this.isFinished||(this._tick(),this.isFinished||(l.delay(this._tickAndRepeat,[],this),this._tickScheduled=!0))},_.prototype._tick=function(){if(this.isPaused||this.isFinished)return!1;var h=null,g=Math.min(this.max,this.index+16384);if(this.index>=this.max)return this.end();switch(this.type){case"string":h=this.data.substring(this.index,g);break;case"uint8array":h=this.data.subarray(this.index,g);break;case"array":case"nodebuffer":h=this.data.slice(this.index,g)}return this.index=g,this.push({data:h,meta:{percent:this.max?this.index/this.max*100:0}})},o.exports=_},{"../utils":32,"./GenericWorker":28}],28:[function(n,o,a){function l(f){this.name=f||"default",this.streamInfo={},this.generatedError=null,this.extraStreamInfo={},this.isPaused=!0,this.isFinished=!1,this.isLocked=!1,this._listeners={data:[],end:[],error:[]},this.previous=null}l.prototype={push:function(f){this.emit("data",f)},end:function(){if(this.isFinished)return!1;this.flush();try{this.emit("end"),this.cleanUp(),this.isFinished=!0}catch(f){this.emit("error",f)}return!0},error:function(f){return!this.isFinished&&(this.isPaused?this.generatedError=f:(this.isFinished=!0,this.emit("error",f),this.previous&&this.previous.error(f),this.cleanUp()),!0)},on:function(f,_){return this._listeners[f].push(_),this},cleanUp:function(){this.streamInfo=this.generatedError=this.extraStreamInfo=null,this._listeners=[]},emit:function(f,_){if(this._listeners[f])for(var h=0;h<this._listeners[f].length;h++)this._listeners[f][h].call(this,_)},pipe:function(f){return f.registerPrevious(this)},registerPrevious:function(f){if(this.isLocked)throw new Error("The stream '"+this+"' has already been used.");this.streamInfo=f.streamInfo,this.mergeStreamInfo(),this.previous=f;var _=this;return f.on("data",function(h){_.processChunk(h)}),f.on("end",function(){_.end()}),f.on("error",function(h){_.error(h)}),this},pause:function(){return!this.isPaused&&!this.isFinished&&(this.isPaused=!0,this.previous&&this.previous.pause(),!0)},resume:function(){if(!this.isPaused||this.isFinished)return!1;var f=this.isPaused=!1;return this.generatedError&&(this.error(this.generatedError),f=!0),this.previous&&this.previous.resume(),!f},flush:function(){},processChunk:function(f){this.push(f)},withStreamInfo:function(f,_){return this.extraStreamInfo[f]=_,this.mergeStreamInfo(),this},mergeStreamInfo:function(){for(var f in this.extraStreamInfo)Object.prototype.hasOwnProperty.call(this.extraStreamInfo,f)&&(this.streamInfo[f]=this.extraStreamInfo[f])},lock:function(){if(this.isLocked)throw new Error("The stream '"+this+"' has already been used.");this.isLocked=!0,this.previous&&this.previous.lock()},toString:function(){var f="Worker "+this.name;return this.previous?this.previous+" -> "+f:f}},o.exports=l},{}],29:[function(n,o,a){var l=n("../utils"),f=n("./ConvertWorker"),_=n("./GenericWorker"),h=n("../base64"),g=n("../support"),M=n("../external"),w=null;if(g.nodestream)try{w=n("../nodejs/NodejsStreamOutputAdapter")}catch{}function C(z,S){return new M.Promise(function(P,y){var x=[],I=z._internalType,U=z._outputType,O=z._mimeType;z.on("data",function(N,j){x.push(N),S&&S(j)}).on("error",function(N){x=[],y(N)}).on("end",function(){try{var N=function(j,D,Y){switch(j){case"blob":return l.newBlob(l.transformTo("arraybuffer",D),Y);case"base64":return h.encode(D);default:return l.transformTo(j,D)}}(U,function(j,D){var Y,de=0,Ce=null,ee=0;for(Y=0;Y<D.length;Y++)ee+=D[Y].length;switch(j){case"string":return D.join("");case"array":return Array.prototype.concat.apply([],D);case"uint8array":for(Ce=new Uint8Array(ee),Y=0;Y<D.length;Y++)Ce.set(D[Y],de),de+=D[Y].length;return Ce;case"nodebuffer":return Buffer.concat(D);default:throw new Error("concat : unsupported type '"+j+"'")}}(I,x),O);P(N)}catch(j){y(j)}x=[]}).resume()})}function k(z,S,P){var y=S;switch(S){case"blob":case"arraybuffer":y="uint8array";break;case"base64":y="string"}try{this._internalType=y,this._outputType=S,this._mimeType=P,l.checkSupport(y),this._worker=z.pipe(new f(y)),z.lock()}catch(x){this._worker=new _("error"),this._worker.error(x)}}k.prototype={accumulate:function(z){return C(this,z)},on:function(z,S){var P=this;return z==="data"?this._worker.on(z,function(y){S.call(P,y.data,y.meta)}):this._worker.on(z,function(){l.delay(S,arguments,P)}),this},resume:function(){return l.delay(this._worker.resume,[],this._worker),this},pause:function(){return this._worker.pause(),this},toNodejsStream:function(z){if(l.checkSupport("nodestream"),this._outputType!=="nodebuffer")throw new Error(this._outputType+" is not supported by this method");return new w(this,{objectMode:this._outputType!=="nodebuffer"},z)}},o.exports=k},{"../base64":1,"../external":6,"../nodejs/NodejsStreamOutputAdapter":13,"../support":30,"../utils":32,"./ConvertWorker":24,"./GenericWorker":28}],30:[function(n,o,a){if(a.base64=!0,a.array=!0,a.string=!0,a.arraybuffer=typeof ArrayBuffer<"u"&&typeof Uint8Array<"u",a.nodebuffer=typeof Buffer<"u",a.uint8array=typeof Uint8Array<"u",typeof ArrayBuffer>"u")a.blob=!1;else{var l=new ArrayBuffer(0);try{a.blob=new Blob([l],{type:"application/zip"}).size===0}catch{try{var f=new(self.BlobBuilder||self.WebKitBlobBuilder||self.MozBlobBuilder||self.MSBlobBuilder);f.append(l),a.blob=f.getBlob("application/zip").size===0}catch{a.blob=!1}}}try{a.nodestream=!!n("readable-stream").Readable}catch{a.nodestream=!1}},{"readable-stream":16}],31:[function(n,o,a){for(var l=n("./utils"),f=n("./support"),_=n("./nodejsUtils"),h=n("./stream/GenericWorker"),g=new Array(256),M=0;M<256;M++)g[M]=252<=M?6:248<=M?5:240<=M?4:224<=M?3:192<=M?2:1;g[254]=g[254]=1;function w(){h.call(this,"utf-8 decode"),this.leftOver=null}function C(){h.call(this,"utf-8 encode")}a.utf8encode=function(k){return f.nodebuffer?_.newBufferFrom(k,"utf-8"):function(z){var S,P,y,x,I,U=z.length,O=0;for(x=0;x<U;x++)(64512&(P=z.charCodeAt(x)))==55296&&x+1<U&&(64512&(y=z.charCodeAt(x+1)))==56320&&(P=65536+(P-55296<<10)+(y-56320),x++),O+=P<128?1:P<2048?2:P<65536?3:4;for(S=f.uint8array?new Uint8Array(O):new Array(O),x=I=0;I<O;x++)(64512&(P=z.charCodeAt(x)))==55296&&x+1<U&&(64512&(y=z.charCodeAt(x+1)))==56320&&(P=65536+(P-55296<<10)+(y-56320),x++),P<128?S[I++]=P:(P<2048?S[I++]=192|P>>>6:(P<65536?S[I++]=224|P>>>12:(S[I++]=240|P>>>18,S[I++]=128|P>>>12&63),S[I++]=128|P>>>6&63),S[I++]=128|63&P);return S}(k)},a.utf8decode=function(k){return f.nodebuffer?l.transformTo("nodebuffer",k).toString("utf-8"):function(z){var S,P,y,x,I=z.length,U=new Array(2*I);for(S=P=0;S<I;)if((y=z[S++])<128)U[P++]=y;else if(4<(x=g[y]))U[P++]=65533,S+=x-1;else{for(y&=x===2?31:x===3?15:7;1<x&&S<I;)y=y<<6|63&z[S++],x--;1<x?U[P++]=65533:y<65536?U[P++]=y:(y-=65536,U[P++]=55296|y>>10&1023,U[P++]=56320|1023&y)}return U.length!==P&&(U.subarray?U=U.subarray(0,P):U.length=P),l.applyFromCharCode(U)}(k=l.transformTo(f.uint8array?"uint8array":"array",k))},l.inherits(w,h),w.prototype.processChunk=function(k){var z=l.transformTo(f.uint8array?"uint8array":"array",k.data);if(this.leftOver&&this.leftOver.length){if(f.uint8array){var S=z;(z=new Uint8Array(S.length+this.leftOver.length)).set(this.leftOver,0),z.set(S,this.leftOver.length)}else z=this.leftOver.concat(z);this.leftOver=null}var P=function(x,I){var U;for((I=I||x.length)>x.length&&(I=x.length),U=I-1;0<=U&&(192&x[U])==128;)U--;return U<0||U===0?I:U+g[x[U]]>I?U:I}(z),y=z;P!==z.length&&(f.uint8array?(y=z.subarray(0,P),this.leftOver=z.subarray(P,z.length)):(y=z.slice(0,P),this.leftOver=z.slice(P,z.length))),this.push({data:a.utf8decode(y),meta:k.meta})},w.prototype.flush=function(){this.leftOver&&this.leftOver.length&&(this.push({data:a.utf8decode(this.leftOver),meta:{}}),this.leftOver=null)},a.Utf8DecodeWorker=w,l.inherits(C,h),C.prototype.processChunk=function(k){this.push({data:a.utf8encode(k.data),meta:k.meta})},a.Utf8EncodeWorker=C},{"./nodejsUtils":14,"./stream/GenericWorker":28,"./support":30,"./utils":32}],32:[function(n,o,a){var l=n("./support"),f=n("./base64"),_=n("./nodejsUtils"),h=n("./external");function g(S){return S}function M(S,P){for(var y=0;y<S.length;++y)P[y]=255&S.charCodeAt(y);return P}n("setimmediate"),a.newBlob=function(S,P){a.checkSupport("blob");try{return new Blob([S],{type:P})}catch{try{var y=new(self.BlobBuilder||self.WebKitBlobBuilder||self.MozBlobBuilder||self.MSBlobBuilder);return y.append(S),y.getBlob(P)}catch{throw new Error("Bug : can't construct the Blob.")}}};var w={stringifyByChunk:function(S,P,y){var x=[],I=0,U=S.length;if(U<=y)return String.fromCharCode.apply(null,S);for(;I<U;)P==="array"||P==="nodebuffer"?x.push(String.fromCharCode.apply(null,S.slice(I,Math.min(I+y,U)))):x.push(String.fromCharCode.apply(null,S.subarray(I,Math.min(I+y,U)))),I+=y;return x.join("")},stringifyByChar:function(S){for(var P="",y=0;y<S.length;y++)P+=String.fromCharCode(S[y]);return P},applyCanBeUsed:{uint8array:function(){try{return l.uint8array&&String.fromCharCode.apply(null,new Uint8Array(1)).length===1}catch{return!1}}(),nodebuffer:function(){try{return l.nodebuffer&&String.fromCharCode.apply(null,_.allocBuffer(1)).length===1}catch{return!1}}()}};function C(S){var P=65536,y=a.getTypeOf(S),x=!0;if(y==="uint8array"?x=w.applyCanBeUsed.uint8array:y==="nodebuffer"&&(x=w.applyCanBeUsed.nodebuffer),x)for(;1<P;)try{return w.stringifyByChunk(S,y,P)}catch{P=Math.floor(P/2)}return w.stringifyByChar(S)}function k(S,P){for(var y=0;y<S.length;y++)P[y]=S[y];return P}a.applyFromCharCode=C;var z={};z.string={string:g,array:function(S){return M(S,new Array(S.length))},arraybuffer:function(S){return z.string.uint8array(S).buffer},uint8array:function(S){return M(S,new Uint8Array(S.length))},nodebuffer:function(S){return M(S,_.allocBuffer(S.length))}},z.array={string:C,array:g,arraybuffer:function(S){return new Uint8Array(S).buffer},uint8array:function(S){return new Uint8Array(S)},nodebuffer:function(S){return _.newBufferFrom(S)}},z.arraybuffer={string:function(S){return C(new Uint8Array(S))},array:function(S){return k(new Uint8Array(S),new Array(S.byteLength))},arraybuffer:g,uint8array:function(S){return new Uint8Array(S)},nodebuffer:function(S){return _.newBufferFrom(new Uint8Array(S))}},z.uint8array={string:C,array:function(S){return k(S,new Array(S.length))},arraybuffer:function(S){return S.buffer},uint8array:g,nodebuffer:function(S){return _.newBufferFrom(S)}},z.nodebuffer={string:C,array:function(S){return k(S,new Array(S.length))},arraybuffer:function(S){return z.nodebuffer.uint8array(S).buffer},uint8array:function(S){return k(S,new Uint8Array(S.length))},nodebuffer:g},a.transformTo=function(S,P){if(P=P||"",!S)return P;a.checkSupport(S);var y=a.getTypeOf(P);return z[y][S](P)},a.resolve=function(S){for(var P=S.split("/"),y=[],x=0;x<P.length;x++){var I=P[x];I==="."||I===""&&x!==0&&x!==P.length-1||(I===".."?y.pop():y.push(I))}return y.join("/")},a.getTypeOf=function(S){return typeof S=="string"?"string":Object.prototype.toString.call(S)==="[object Array]"?"array":l.nodebuffer&&_.isBuffer(S)?"nodebuffer":l.uint8array&&S instanceof Uint8Array?"uint8array":l.arraybuffer&&S instanceof ArrayBuffer?"arraybuffer":void 0},a.checkSupport=function(S){if(!l[S.toLowerCase()])throw new Error(S+" is not supported by this platform")},a.MAX_VALUE_16BITS=65535,a.MAX_VALUE_32BITS=-1,a.pretty=function(S){var P,y,x="";for(y=0;y<(S||"").length;y++)x+="\\x"+((P=S.charCodeAt(y))<16?"0":"")+P.toString(16).toUpperCase();return x},a.delay=function(S,P,y){setImmediate(function(){S.apply(y||null,P||[])})},a.inherits=function(S,P){function y(){}y.prototype=P.prototype,S.prototype=new y},a.extend=function(){var S,P,y={};for(S=0;S<arguments.length;S++)for(P in arguments[S])Object.prototype.hasOwnProperty.call(arguments[S],P)&&y[P]===void 0&&(y[P]=arguments[S][P]);return y},a.prepareContent=function(S,P,y,x,I){return h.Promise.resolve(P).then(function(U){return l.blob&&(U instanceof Blob||["[object File]","[object Blob]"].indexOf(Object.prototype.toString.call(U))!==-1)&&typeof FileReader<"u"?new h.Promise(function(O,N){var j=new FileReader;j.onload=function(D){O(D.target.result)},j.onerror=function(D){N(D.target.error)},j.readAsArrayBuffer(U)}):U}).then(function(U){var O=a.getTypeOf(U);return O?(O==="arraybuffer"?U=a.transformTo("uint8array",U):O==="string"&&(I?U=f.decode(U):y&&x!==!0&&(U=function(N){return M(N,l.uint8array?new Uint8Array(N.length):new Array(N.length))}(U))),U):h.Promise.reject(new Error("Can't read the data of '"+S+"'. Is it in a supported JavaScript type (String, Blob, ArrayBuffer, etc) ?"))})}},{"./base64":1,"./external":6,"./nodejsUtils":14,"./support":30,setimmediate:54}],33:[function(n,o,a){var l=n("./reader/readerFor"),f=n("./utils"),_=n("./signature"),h=n("./zipEntry"),g=n("./support");function M(w){this.files=[],this.loadOptions=w}M.prototype={checkSignature:function(w){if(!this.reader.readAndCheckSignature(w)){this.reader.index-=4;var C=this.reader.readString(4);throw new Error("Corrupted zip or bug: unexpected signature ("+f.pretty(C)+", expected "+f.pretty(w)+")")}},isSignature:function(w,C){var k=this.reader.index;this.reader.setIndex(w);var z=this.reader.readString(4)===C;return this.reader.setIndex(k),z},readBlockEndOfCentral:function(){this.diskNumber=this.reader.readInt(2),this.diskWithCentralDirStart=this.reader.readInt(2),this.centralDirRecordsOnThisDisk=this.reader.readInt(2),this.centralDirRecords=this.reader.readInt(2),this.centralDirSize=this.reader.readInt(4),this.centralDirOffset=this.reader.readInt(4),this.zipCommentLength=this.reader.readInt(2);var w=this.reader.readData(this.zipCommentLength),C=g.uint8array?"uint8array":"array",k=f.transformTo(C,w);this.zipComment=this.loadOptions.decodeFileName(k)},readBlockZip64EndOfCentral:function(){this.zip64EndOfCentralSize=this.reader.readInt(8),this.reader.skip(4),this.diskNumber=this.reader.readInt(4),this.diskWithCentralDirStart=this.reader.readInt(4),this.centralDirRecordsOnThisDisk=this.reader.readInt(8),this.centralDirRecords=this.reader.readInt(8),this.centralDirSize=this.reader.readInt(8),this.centralDirOffset=this.reader.readInt(8),this.zip64ExtensibleData={};for(var w,C,k,z=this.zip64EndOfCentralSize-44;0<z;)w=this.reader.readInt(2),C=this.reader.readInt(4),k=this.reader.readData(C),this.zip64ExtensibleData[w]={id:w,length:C,value:k}},readBlockZip64EndOfCentralLocator:function(){if(this.diskWithZip64CentralDirStart=this.reader.readInt(4),this.relativeOffsetEndOfZip64CentralDir=this.reader.readInt(8),this.disksCount=this.reader.readInt(4),1<this.disksCount)throw new Error("Multi-volumes zip are not supported")},readLocalFiles:function(){var w,C;for(w=0;w<this.files.length;w++)C=this.files[w],this.reader.setIndex(C.localHeaderOffset),this.checkSignature(_.LOCAL_FILE_HEADER),C.readLocalPart(this.reader),C.handleUTF8(),C.processAttributes()},readCentralDir:function(){var w;for(this.reader.setIndex(this.centralDirOffset);this.reader.readAndCheckSignature(_.CENTRAL_FILE_HEADER);)(w=new h({zip64:this.zip64},this.loadOptions)).readCentralPart(this.reader),this.files.push(w);if(this.centralDirRecords!==this.files.length&&this.centralDirRecords!==0&&this.files.length===0)throw new Error("Corrupted zip or bug: expected "+this.centralDirRecords+" records in central dir, got "+this.files.length)},readEndOfCentral:function(){var w=this.reader.lastIndexOfSignature(_.CENTRAL_DIRECTORY_END);if(w<0)throw this.isSignature(0,_.LOCAL_FILE_HEADER)?new Error("Corrupted zip: can't find end of central directory"):new Error("Can't find end of central directory : is this a zip file ? If it is, see https://stuk.github.io/jszip/documentation/howto/read_zip.html");this.reader.setIndex(w);var C=w;if(this.checkSignature(_.CENTRAL_DIRECTORY_END),this.readBlockEndOfCentral(),this.diskNumber===f.MAX_VALUE_16BITS||this.diskWithCentralDirStart===f.MAX_VALUE_16BITS||this.centralDirRecordsOnThisDisk===f.MAX_VALUE_16BITS||this.centralDirRecords===f.MAX_VALUE_16BITS||this.centralDirSize===f.MAX_VALUE_32BITS||this.centralDirOffset===f.MAX_VALUE_32BITS){if(this.zip64=!0,(w=this.reader.lastIndexOfSignature(_.ZIP64_CENTRAL_DIRECTORY_LOCATOR))<0)throw new Error("Corrupted zip: can't find the ZIP64 end of central directory locator");if(this.reader.setIndex(w),this.checkSignature(_.ZIP64_CENTRAL_DIRECTORY_LOCATOR),this.readBlockZip64EndOfCentralLocator(),!this.isSignature(this.relativeOffsetEndOfZip64CentralDir,_.ZIP64_CENTRAL_DIRECTORY_END)&&(this.relativeOffsetEndOfZip64CentralDir=this.reader.lastIndexOfSignature(_.ZIP64_CENTRAL_DIRECTORY_END),this.relativeOffsetEndOfZip64CentralDir<0))throw new Error("Corrupted zip: can't find the ZIP64 end of central directory");this.reader.setIndex(this.relativeOffsetEndOfZip64CentralDir),this.checkSignature(_.ZIP64_CENTRAL_DIRECTORY_END),this.readBlockZip64EndOfCentral()}var k=this.centralDirOffset+this.centralDirSize;this.zip64&&(k+=20,k+=12+this.zip64EndOfCentralSize);var z=C-k;if(0<z)this.isSignature(C,_.CENTRAL_FILE_HEADER)||(this.reader.zero=z);else if(z<0)throw new Error("Corrupted zip: missing "+Math.abs(z)+" bytes.")},prepareReader:function(w){this.reader=l(w)},load:function(w){this.prepareReader(w),this.readEndOfCentral(),this.readCentralDir(),this.readLocalFiles()}},o.exports=M},{"./reader/readerFor":22,"./signature":23,"./support":30,"./utils":32,"./zipEntry":34}],34:[function(n,o,a){var l=n("./reader/readerFor"),f=n("./utils"),_=n("./compressedObject"),h=n("./crc32"),g=n("./utf8"),M=n("./compressions"),w=n("./support");function C(k,z){this.options=k,this.loadOptions=z}C.prototype={isEncrypted:function(){return(1&this.bitFlag)==1},useUTF8:function(){return(2048&this.bitFlag)==2048},readLocalPart:function(k){var z,S;if(k.skip(22),this.fileNameLength=k.readInt(2),S=k.readInt(2),this.fileName=k.readData(this.fileNameLength),k.skip(S),this.compressedSize===-1||this.uncompressedSize===-1)throw new Error("Bug or corrupted zip : didn't get enough information from the central directory (compressedSize === -1 || uncompressedSize === -1)");if((z=function(P){for(var y in M)if(Object.prototype.hasOwnProperty.call(M,y)&&M[y].magic===P)return M[y];return null}(this.compressionMethod))===null)throw new Error("Corrupted zip : compression "+f.pretty(this.compressionMethod)+" unknown (inner file : "+f.transformTo("string",this.fileName)+")");this.decompressed=new _(this.compressedSize,this.uncompressedSize,this.crc32,z,k.readData(this.compressedSize))},readCentralPart:function(k){this.versionMadeBy=k.readInt(2),k.skip(2),this.bitFlag=k.readInt(2),this.compressionMethod=k.readString(2),this.date=k.readDate(),this.crc32=k.readInt(4),this.compressedSize=k.readInt(4),this.uncompressedSize=k.readInt(4);var z=k.readInt(2);if(this.extraFieldsLength=k.readInt(2),this.fileCommentLength=k.readInt(2),this.diskNumberStart=k.readInt(2),this.internalFileAttributes=k.readInt(2),this.externalFileAttributes=k.readInt(4),this.localHeaderOffset=k.readInt(4),this.isEncrypted())throw new Error("Encrypted zip are not supported");k.skip(z),this.readExtraFields(k),this.parseZIP64ExtraField(k),this.fileComment=k.readData(this.fileCommentLength)},processAttributes:function(){this.unixPermissions=null,this.dosPermissions=null;var k=this.versionMadeBy>>8;this.dir=!!(16&this.externalFileAttributes),k==0&&(this.dosPermissions=63&this.externalFileAttributes),k==3&&(this.unixPermissions=this.externalFileAttributes>>16&65535),this.dir||this.fileNameStr.slice(-1)!=="/"||(this.dir=!0)},parseZIP64ExtraField:function(){if(this.extraFields[1]){var k=l(this.extraFields[1].value);this.uncompressedSize===f.MAX_VALUE_32BITS&&(this.uncompressedSize=k.readInt(8)),this.compressedSize===f.MAX_VALUE_32BITS&&(this.compressedSize=k.readInt(8)),this.localHeaderOffset===f.MAX_VALUE_32BITS&&(this.localHeaderOffset=k.readInt(8)),this.diskNumberStart===f.MAX_VALUE_32BITS&&(this.diskNumberStart=k.readInt(4))}},readExtraFields:function(k){var z,S,P,y=k.index+this.extraFieldsLength;for(this.extraFields||(this.extraFields={});k.index+4<y;)z=k.readInt(2),S=k.readInt(2),P=k.readData(S),this.extraFields[z]={id:z,length:S,value:P};k.setIndex(y)},handleUTF8:function(){var k=w.uint8array?"uint8array":"array";if(this.useUTF8())this.fileNameStr=g.utf8decode(this.fileName),this.fileCommentStr=g.utf8decode(this.fileComment);else{var z=this.findExtraFieldUnicodePath();if(z!==null)this.fileNameStr=z;else{var S=f.transformTo(k,this.fileName);this.fileNameStr=this.loadOptions.decodeFileName(S)}var P=this.findExtraFieldUnicodeComment();if(P!==null)this.fileCommentStr=P;else{var y=f.transformTo(k,this.fileComment);this.fileCommentStr=this.loadOptions.decodeFileName(y)}}},findExtraFieldUnicodePath:function(){var k=this.extraFields[28789];if(k){var z=l(k.value);return z.readInt(1)!==1||h(this.fileName)!==z.readInt(4)?null:g.utf8decode(z.readData(k.length-5))}return null},findExtraFieldUnicodeComment:function(){var k=this.extraFields[25461];if(k){var z=l(k.value);return z.readInt(1)!==1||h(this.fileComment)!==z.readInt(4)?null:g.utf8decode(z.readData(k.length-5))}return null}},o.exports=C},{"./compressedObject":2,"./compressions":3,"./crc32":4,"./reader/readerFor":22,"./support":30,"./utf8":31,"./utils":32}],35:[function(n,o,a){function l(z,S,P){this.name=z,this.dir=P.dir,this.date=P.date,this.comment=P.comment,this.unixPermissions=P.unixPermissions,this.dosPermissions=P.dosPermissions,this._data=S,this._dataBinary=P.binary,this.options={compression:P.compression,compressionOptions:P.compressionOptions}}var f=n("./stream/StreamHelper"),_=n("./stream/DataWorker"),h=n("./utf8"),g=n("./compressedObject"),M=n("./stream/GenericWorker");l.prototype={internalStream:function(z){var S=null,P="string";try{if(!z)throw new Error("No output type specified.");var y=(P=z.toLowerCase())==="string"||P==="text";P!=="binarystring"&&P!=="text"||(P="string"),S=this._decompressWorker();var x=!this._dataBinary;x&&!y&&(S=S.pipe(new h.Utf8EncodeWorker)),!x&&y&&(S=S.pipe(new h.Utf8DecodeWorker))}catch(I){(S=new M("error")).error(I)}return new f(S,P,"")},async:function(z,S){return this.internalStream(z).accumulate(S)},nodeStream:function(z,S){return this.internalStream(z||"nodebuffer").toNodejsStream(S)},_compressWorker:function(z,S){if(this._data instanceof g&&this._data.compression.magic===z.magic)return this._data.getCompressedWorker();var P=this._decompressWorker();return this._dataBinary||(P=P.pipe(new h.Utf8EncodeWorker)),g.createWorkerFrom(P,z,S)},_decompressWorker:function(){return this._data instanceof g?this._data.getContentWorker():this._data instanceof M?this._data:new _(this._data)}};for(var w=["asText","asBinary","asNodeBuffer","asUint8Array","asArrayBuffer"],C=function(){throw new Error("This method has been removed in JSZip 3.0, please check the upgrade 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e}de=65535&D,(Y&=15)&&(I<Y&&(x+=R[h++]<<I,I+=8),de+=x&(1<<Y)-1,x>>>=Y,I-=Y),I<15&&(x+=R[h++]<<I,I+=8,x+=R[h++]<<I,I+=8),D=O[x&j];r:for(;;){if(x>>>=Y=D>>>24,I-=Y,!(16&(Y=D>>>16&255))){if(!(64&Y)){D=O[(65535&D)+(x&(1<<Y)-1)];continue r}l.msg="invalid distance code",_.mode=30;break e}if(Ce=65535&D,I<(Y&=15)&&(x+=R[h++]<<I,(I+=8)<Y&&(x+=R[h++]<<I,I+=8)),k<(Ce+=x&(1<<Y)-1)){l.msg="invalid distance too far back",_.mode=30;break e}if(x>>>=Y,I-=Y,(Y=M-w)<Ce){if(S<(Y=Ce-Y)&&_.sane){l.msg="invalid distance too far back",_.mode=30;break e}if(ye=y,(ee=0)===P){if(ee+=z-Y,Y<de){for(de-=Y;Me[M++]=y[ee++],--Y;);ee=M-Ce,ye=Me}}else if(P<Y){if(ee+=z+P-Y,(Y-=P)<de){for(de-=Y;Me[M++]=y[ee++],--Y;);if(ee=0,P<de){for(de-=Y=P;Me[M++]=y[ee++],--Y;);ee=M-Ce,ye=Me}}}else if(ee+=P-Y,Y<de){for(de-=Y;Me[M++]=y[ee++],--Y;);ee=M-Ce,ye=Me}for(;2<de;)Me[M++]=ye[ee++],Me[M++]=ye[ee++],Me[M++]=ye[ee++],de-=3;de&&(Me[M++]=ye[ee++],1<de&&(Me[M++]=ye[ee++]))}else{for(ee=M-Ce;Me[M++]=Me[ee++],Me[M++]=Me[ee++],Me[M++]=Me[ee++],2<(de-=3););de&&(Me[M++]=Me[ee++],1<de&&(Me[M++]=Me[ee++]))}break}}break}}while(h<g&&M<C);h-=de=I>>3,x&=(1<<(I-=de<<3))-1,l.next_in=h,l.next_out=M,l.avail_in=h<g?g-h+5:5-(h-g),l.avail_out=M<C?C-M+257:257-(M-C),_.hold=x,_.bits=I}},{}],49:[function(n,o,a){var l=n("../utils/common"),f=n("./adler32"),_=n("./crc32"),h=n("./inffast"),g=n("./inftrees"),M=1,w=2,C=0,k=-2,z=1,S=852,P=592;function y(ee){return(ee>>>24&255)+(ee>>>8&65280)+((65280&ee)<<8)+((255&ee)<<24)}function x(){this.mode=0,this.last=!1,this.wrap=0,this.havedict=!1,this.flags=0,this.dmax=0,this.check=0,this.total=0,this.head=null,this.wbits=0,this.wsize=0,this.whave=0,this.wnext=0,this.window=null,this.hold=0,this.bits=0,this.length=0,this.offset=0,this.extra=0,this.lencode=null,this.distcode=null,this.lenbits=0,this.distbits=0,this.ncode=0,this.nlen=0,this.ndist=0,this.have=0,this.next=null,this.lens=new l.Buf16(320),this.work=new l.Buf16(288),this.lendyn=null,this.distdyn=null,this.sane=0,this.back=0,this.was=0}function I(ee){var ye;return ee&&ee.state?(ye=ee.state,ee.total_in=ee.total_out=ye.total=0,ee.msg="",ye.wrap&&(ee.adler=1&ye.wrap),ye.mode=z,ye.last=0,ye.havedict=0,ye.dmax=32768,ye.head=null,ye.hold=0,ye.bits=0,ye.lencode=ye.lendyn=new l.Buf32(S),ye.distcode=ye.distdyn=new l.Buf32(P),ye.sane=1,ye.back=-1,C):k}function U(ee){var ye;return ee&&ee.state?((ye=ee.state).wsize=0,ye.whave=0,ye.wnext=0,I(ee)):k}function O(ee,ye){var R,Me;return ee&&ee.state?(Me=ee.state,ye<0?(R=0,ye=-ye):(R=1+(ye>>4),ye<48&&(ye&=15)),ye&&(ye<8||15<ye)?k:(Me.window!==null&&Me.wbits!==ye&&(Me.window=null),Me.wrap=R,Me.wbits=ye,U(ee))):k}function N(ee,ye){var R,Me;return ee?(Me=new x,(ee.state=Me).window=null,(R=O(ee,ye))!==C&&(ee.state=null),R):k}var j,D,Y=!0;function de(ee){if(Y){var ye;for(j=new l.Buf32(512),D=new l.Buf32(32),ye=0;ye<144;)ee.lens[ye++]=8;for(;ye<256;)ee.lens[ye++]=9;for(;ye<280;)ee.lens[ye++]=7;for(;ye<288;)ee.lens[ye++]=8;for(g(M,ee.lens,0,288,j,0,ee.work,{bits:9}),ye=0;ye<32;)ee.lens[ye++]=5;g(w,ee.lens,0,32,D,0,ee.work,{bits:5}),Y=!1}ee.lencode=j,ee.lenbits=9,ee.distcode=D,ee.distbits=5}function Ce(ee,ye,R,Me){var Qe,ge=ee.state;return ge.window===null&&(ge.wsize=1<<ge.wbits,ge.wnext=0,ge.whave=0,ge.window=new l.Buf8(ge.wsize)),Me>=ge.wsize?(l.arraySet(ge.window,ye,R-ge.wsize,ge.wsize,0),ge.wnext=0,ge.whave=ge.wsize):(Me<(Qe=ge.wsize-ge.wnext)&&(Qe=Me),l.arraySet(ge.window,ye,R-Me,Qe,ge.wnext),(Me-=Qe)?(l.arraySet(ge.window,ye,R-Me,Me,0),ge.wnext=Me,ge.whave=ge.wsize):(ge.wnext+=Qe,ge.wnext===ge.wsize&&(ge.wnext=0),ge.whave<ge.wsize&&(ge.whave+=Qe))),0}a.inflateReset=U,a.inflateReset2=O,a.inflateResetKeep=I,a.inflateInit=function(ee){return N(ee,15)},a.inflateInit2=N,a.inflate=function(ee,ye){var R,Me,Qe,ge,Q,ae,Se,X,me,Ke,De,Be,We,ot,dt,Ge,Te,je,Ye,tt,A,Ae,$e,se,te=0,we=new l.Buf8(4),B=[16,17,18,0,8,7,9,6,10,5,11,4,12,3,13,2,14,1,15];if(!ee||!ee.state||!ee.output||!ee.input&&ee.avail_in!==0)return k;(R=ee.state).mode===12&&(R.mode=13),Q=ee.next_out,Qe=ee.output,Se=ee.avail_out,ge=ee.next_in,Me=ee.input,ae=ee.avail_in,X=R.hold,me=R.bits,Ke=ae,De=Se,Ae=C;e:for(;;)switch(R.mode){case z:if(R.wrap===0){R.mode=13;break}for(;me<16;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}if(2&R.wrap&&X===35615){we[R.check=0]=255&X,we[1]=X>>>8&255,R.check=_(R.check,we,2,0),me=X=0,R.mode=2;break}if(R.flags=0,R.head&&(R.head.done=!1),!(1&R.wrap)||(((255&X)<<8)+(X>>8))%31){ee.msg="incorrect header check",R.mode=30;break}if((15&X)!=8){ee.msg="unknown compression method",R.mode=30;break}if(me-=4,A=8+(15&(X>>>=4)),R.wbits===0)R.wbits=A;else if(A>R.wbits){ee.msg="invalid window size",R.mode=30;break}R.dmax=1<<A,ee.adler=R.check=1,R.mode=512&X?10:12,me=X=0;break;case 2:for(;me<16;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}if(R.flags=X,(255&R.flags)!=8){ee.msg="unknown compression method",R.mode=30;break}if(57344&R.flags){ee.msg="unknown header flags set",R.mode=30;break}R.head&&(R.head.text=X>>8&1),512&R.flags&&(we[0]=255&X,we[1]=X>>>8&255,R.check=_(R.check,we,2,0)),me=X=0,R.mode=3;case 3:for(;me<32;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}R.head&&(R.head.time=X),512&R.flags&&(we[0]=255&X,we[1]=X>>>8&255,we[2]=X>>>16&255,we[3]=X>>>24&255,R.check=_(R.check,we,4,0)),me=X=0,R.mode=4;case 4:for(;me<16;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}R.head&&(R.head.xflags=255&X,R.head.os=X>>8),512&R.flags&&(we[0]=255&X,we[1]=X>>>8&255,R.check=_(R.check,we,2,0)),me=X=0,R.mode=5;case 5:if(1024&R.flags){for(;me<16;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}R.length=X,R.head&&(R.head.extra_len=X),512&R.flags&&(we[0]=255&X,we[1]=X>>>8&255,R.check=_(R.check,we,2,0)),me=X=0}else R.head&&(R.head.extra=null);R.mode=6;case 6:if(1024&R.flags&&(ae<(Be=R.length)&&(Be=ae),Be&&(R.head&&(A=R.head.extra_len-R.length,R.head.extra||(R.head.extra=new Array(R.head.extra_len)),l.arraySet(R.head.extra,Me,ge,Be,A)),512&R.flags&&(R.check=_(R.check,Me,Be,ge)),ae-=Be,ge+=Be,R.length-=Be),R.length))break e;R.length=0,R.mode=7;case 7:if(2048&R.flags){if(ae===0)break e;for(Be=0;A=Me[ge+Be++],R.head&&A&&R.length<65536&&(R.head.name+=String.fromCharCode(A)),A&&Be<ae;);if(512&R.flags&&(R.check=_(R.check,Me,Be,ge)),ae-=Be,ge+=Be,A)break e}else R.head&&(R.head.name=null);R.length=0,R.mode=8;case 8:if(4096&R.flags){if(ae===0)break e;for(Be=0;A=Me[ge+Be++],R.head&&A&&R.length<65536&&(R.head.comment+=String.fromCharCode(A)),A&&Be<ae;);if(512&R.flags&&(R.check=_(R.check,Me,Be,ge)),ae-=Be,ge+=Be,A)break e}else R.head&&(R.head.comment=null);R.mode=9;case 9:if(512&R.flags){for(;me<16;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}if(X!==(65535&R.check)){ee.msg="header crc mismatch",R.mode=30;break}me=X=0}R.head&&(R.head.hcrc=R.flags>>9&1,R.head.done=!0),ee.adler=R.check=0,R.mode=12;break;case 10:for(;me<32;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}ee.adler=R.check=y(X),me=X=0,R.mode=11;case 11:if(R.havedict===0)return ee.next_out=Q,ee.avail_out=Se,ee.next_in=ge,ee.avail_in=ae,R.hold=X,R.bits=me,2;ee.adler=R.check=1,R.mode=12;case 12:if(ye===5||ye===6)break e;case 13:if(R.last){X>>>=7&me,me-=7&me,R.mode=27;break}for(;me<3;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}switch(R.last=1&X,me-=1,3&(X>>>=1)){case 0:R.mode=14;break;case 1:if(de(R),R.mode=20,ye!==6)break;X>>>=2,me-=2;break e;case 2:R.mode=17;break;case 3:ee.msg="invalid block type",R.mode=30}X>>>=2,me-=2;break;case 14:for(X>>>=7&me,me-=7&me;me<32;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}if((65535&X)!=(X>>>16^65535)){ee.msg="invalid stored block lengths",R.mode=30;break}if(R.length=65535&X,me=X=0,R.mode=15,ye===6)break e;case 15:R.mode=16;case 16:if(Be=R.length){if(ae<Be&&(Be=ae),Se<Be&&(Be=Se),Be===0)break e;l.arraySet(Qe,Me,ge,Be,Q),ae-=Be,ge+=Be,Se-=Be,Q+=Be,R.length-=Be;break}R.mode=12;break;case 17:for(;me<14;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}if(R.nlen=257+(31&X),X>>>=5,me-=5,R.ndist=1+(31&X),X>>>=5,me-=5,R.ncode=4+(15&X),X>>>=4,me-=4,286<R.nlen||30<R.ndist){ee.msg="too many length or distance symbols",R.mode=30;break}R.have=0,R.mode=18;case 18:for(;R.have<R.ncode;){for(;me<3;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}R.lens[B[R.have++]]=7&X,X>>>=3,me-=3}for(;R.have<19;)R.lens[B[R.have++]]=0;if(R.lencode=R.lendyn,R.lenbits=7,$e={bits:R.lenbits},Ae=g(0,R.lens,0,19,R.lencode,0,R.work,$e),R.lenbits=$e.bits,Ae){ee.msg="invalid code lengths set",R.mode=30;break}R.have=0,R.mode=19;case 19:for(;R.have<R.nlen+R.ndist;){for(;Ge=(te=R.lencode[X&(1<<R.lenbits)-1])>>>16&255,Te=65535&te,!((dt=te>>>24)<=me);){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}if(Te<16)X>>>=dt,me-=dt,R.lens[R.have++]=Te;else{if(Te===16){for(se=dt+2;me<se;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}if(X>>>=dt,me-=dt,R.have===0){ee.msg="invalid bit length repeat",R.mode=30;break}A=R.lens[R.have-1],Be=3+(3&X),X>>>=2,me-=2}else if(Te===17){for(se=dt+3;me<se;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}me-=dt,A=0,Be=3+(7&(X>>>=dt)),X>>>=3,me-=3}else{for(se=dt+7;me<se;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}me-=dt,A=0,Be=11+(127&(X>>>=dt)),X>>>=7,me-=7}if(R.have+Be>R.nlen+R.ndist){ee.msg="invalid bit length repeat",R.mode=30;break}for(;Be--;)R.lens[R.have++]=A}}if(R.mode===30)break;if(R.lens[256]===0){ee.msg="invalid code -- missing end-of-block",R.mode=30;break}if(R.lenbits=9,$e={bits:R.lenbits},Ae=g(M,R.lens,0,R.nlen,R.lencode,0,R.work,$e),R.lenbits=$e.bits,Ae){ee.msg="invalid literal/lengths set",R.mode=30;break}if(R.distbits=6,R.distcode=R.distdyn,$e={bits:R.distbits},Ae=g(w,R.lens,R.nlen,R.ndist,R.distcode,0,R.work,$e),R.distbits=$e.bits,Ae){ee.msg="invalid distances set",R.mode=30;break}if(R.mode=20,ye===6)break e;case 20:R.mode=21;case 21:if(6<=ae&&258<=Se){ee.next_out=Q,ee.avail_out=Se,ee.next_in=ge,ee.avail_in=ae,R.hold=X,R.bits=me,h(ee,De),Q=ee.next_out,Qe=ee.output,Se=ee.avail_out,ge=ee.next_in,Me=ee.input,ae=ee.avail_in,X=R.hold,me=R.bits,R.mode===12&&(R.back=-1);break}for(R.back=0;Ge=(te=R.lencode[X&(1<<R.lenbits)-1])>>>16&255,Te=65535&te,!((dt=te>>>24)<=me);){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}if(Ge&&!(240&Ge)){for(je=dt,Ye=Ge,tt=Te;Ge=(te=R.lencode[tt+((X&(1<<je+Ye)-1)>>je)])>>>16&255,Te=65535&te,!(je+(dt=te>>>24)<=me);){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}X>>>=je,me-=je,R.back+=je}if(X>>>=dt,me-=dt,R.back+=dt,R.length=Te,Ge===0){R.mode=26;break}if(32&Ge){R.back=-1,R.mode=12;break}if(64&Ge){ee.msg="invalid literal/length code",R.mode=30;break}R.extra=15&Ge,R.mode=22;case 22:if(R.extra){for(se=R.extra;me<se;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}R.length+=X&(1<<R.extra)-1,X>>>=R.extra,me-=R.extra,R.back+=R.extra}R.was=R.length,R.mode=23;case 23:for(;Ge=(te=R.distcode[X&(1<<R.distbits)-1])>>>16&255,Te=65535&te,!((dt=te>>>24)<=me);){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}if(!(240&Ge)){for(je=dt,Ye=Ge,tt=Te;Ge=(te=R.distcode[tt+((X&(1<<je+Ye)-1)>>je)])>>>16&255,Te=65535&te,!(je+(dt=te>>>24)<=me);){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}X>>>=je,me-=je,R.back+=je}if(X>>>=dt,me-=dt,R.back+=dt,64&Ge){ee.msg="invalid distance code",R.mode=30;break}R.offset=Te,R.extra=15&Ge,R.mode=24;case 24:if(R.extra){for(se=R.extra;me<se;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}R.offset+=X&(1<<R.extra)-1,X>>>=R.extra,me-=R.extra,R.back+=R.extra}if(R.offset>R.dmax){ee.msg="invalid distance too far back",R.mode=30;break}R.mode=25;case 25:if(Se===0)break e;if(Be=De-Se,R.offset>Be){if((Be=R.offset-Be)>R.whave&&R.sane){ee.msg="invalid distance too far back",R.mode=30;break}We=Be>R.wnext?(Be-=R.wnext,R.wsize-Be):R.wnext-Be,Be>R.length&&(Be=R.length),ot=R.window}else ot=Qe,We=Q-R.offset,Be=R.length;for(Se<Be&&(Be=Se),Se-=Be,R.length-=Be;Qe[Q++]=ot[We++],--Be;);R.length===0&&(R.mode=21);break;case 26:if(Se===0)break e;Qe[Q++]=R.length,Se--,R.mode=21;break;case 27:if(R.wrap){for(;me<32;){if(ae===0)break e;ae--,X|=Me[ge++]<<me,me+=8}if(De-=Se,ee.total_out+=De,R.total+=De,De&&(ee.adler=R.check=R.flags?_(R.check,Qe,De,Q-De):f(R.check,Qe,De,Q-De)),De=Se,(R.flags?X:y(X))!==R.check){ee.msg="incorrect data check",R.mode=30;break}me=X=0}R.mode=28;case 28:if(R.wrap&&R.flags){for(;me<32;){if(ae===0)break e;ae--,X+=Me[ge++]<<me,me+=8}if(X!==(4294967295&R.total)){ee.msg="incorrect length check",R.mode=30;break}me=X=0}R.mode=29;case 29:Ae=1;break e;case 30:Ae=-3;break e;case 31:return-4;case 32:default:return k}return ee.next_out=Q,ee.avail_out=Se,ee.next_in=ge,ee.avail_in=ae,R.hold=X,R.bits=me,(R.wsize||De!==ee.avail_out&&R.mode<30&&(R.mode<27||ye!==4))&&Ce(ee,ee.output,ee.next_out,De-ee.avail_out)?(R.mode=31,-4):(Ke-=ee.avail_in,De-=ee.avail_out,ee.total_in+=Ke,ee.total_out+=De,R.total+=De,R.wrap&&De&&(ee.adler=R.check=R.flags?_(R.check,Qe,De,ee.next_out-De):f(R.check,Qe,De,ee.next_out-De)),ee.data_type=R.bits+(R.last?64:0)+(R.mode===12?128:0)+(R.mode===20||R.mode===15?256:0),(Ke==0&&De===0||ye===4)&&Ae===C&&(Ae=-5),Ae)},a.inflateEnd=function(ee){if(!ee||!ee.state)return k;var ye=ee.state;return ye.window&&(ye.window=null),ee.state=null,C},a.inflateGetHeader=function(ee,ye){var R;return ee&&ee.state&&2&(R=ee.state).wrap?((R.head=ye).done=!1,C):k},a.inflateSetDictionary=function(ee,ye){var R,Me=ye.length;return ee&&ee.state?(R=ee.state).wrap!==0&&R.mode!==11?k:R.mode===11&&f(1,ye,Me,0)!==R.check?-3:Ce(ee,ye,Me,Me)?(R.mode=31,-4):(R.havedict=1,C):k},a.inflateInfo="pako inflate (from Nodeca 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