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if(e.tag===19)Jv(e,r,t);else if(e.child!==null){e.child.return=e,e=e.child;continue}if(e===t)break e;for(;e.sibling===null;){if(e.return===null||e.return===t)break e;e=e.return}e.sibling.return=e.return,e=e.sibling}o&=1}if(Qr(sn,o),!(t.mode&1))t.memoizedState=null;else switch(a){case"forwards":for(r=t.child,a=null;r!==null;)e=r.alternate,e!==null&&Uh(e)===null&&(a=r),r=r.sibling;r=a,r===null?(a=t.child,t.child=null):(a=r.sibling,r.sibling=null),Tg(t,!1,a,r,l);break;case"backwards":for(r=null,a=t.child,t.child=null;a!==null;){if(e=a.alternate,e!==null&&Uh(e)===null){t.child=a;break}e=a.sibling,a.sibling=r,r=a,a=e}Tg(t,!0,r,null,l);break;case"together":Tg(t,!1,null,null,void 0);break;default:t.memoizedState=null}return t.child}function bh(e,t){!(t.mode&1)&&e!==null&&(e.alternate=null,t.alternate=null,t.flags|=2)}function zo(e,t,r){if(e!==null&&(t.dependencies=e.dependencies),da|=t.lanes,!(r&t.childLanes))return null;if(e!==null&&t.child!==e.child)throw Error(xt(153));if(t.child!==null){for(e=t.child,r=xs(e,e.pendingProps),t.child=r,r.return=t;e.sibling!==null;)e=e.sibling,r=r.sibling=xs(e,e.pendingProps),r.return=t;r.sibling=null}return t.child}function Uk(e,t,r){switch(t.tag){case 3:h2(t),eu();break;case 5:Ub(t);break;case 1:ci(t.type)&&Dh(t);break;case 4:e0(t,t.stateNode.containerInfo);break;case 10:var o=t.type._context,a=t.memoizedProps.value;Qr(Bh,o._currentValue),o._currentValue=a;break;case 13:if(o=t.memoizedState,o!==null)return o.dehydrated!==null?(Qr(sn,sn.current&1),t.flags|=128,null):r&t.child.childLanes?m2(e,t,r):(Qr(sn,sn.current&1),e=zo(e,t,r),e!==null?e.sibling:null);Qr(sn,sn.current&1);break;case 19:if(o=(r&t.childLanes)!==0,e.flags&128){if(o)return g2(e,t,r);t.flags|=128}if(a=t.memoizedState,a!==null&&(a.rendering=null,a.tail=null,a.lastEffect=null),Qr(sn,sn.current),o)break;return null;case 22:case 23:return t.lanes=0,p2(e,t,r)}return zo(e,t,r)}var _2,d_,w2,y2;_2=function(e,t){for(var r=t.child;r!==null;){if(r.tag===5||r.tag===6)e.appendChild(r.stateNode);else if(r.tag!==4&&r.child!==null){r.child.return=r,r=r.child;continue}if(r===t)break;for(;r.sibling===null;){if(r.return===null||r.return===t)return;r=r.return}r.sibling.return=r.return,r=r.sibling}};d_=function(){};w2=function(e,t,r,o){var a=e.memoizedProps;if(a!==o){e=t.stateNode,oa(po.current);var l=null;switch(r){case"input":a=Fg(e,a),o=Fg(e,o),l=[];break;case"select":a=ln({},a,{value:void 0}),o=ln({},o,{value:void 0}),l=[];break;case"textarea":a=Dg(e,a),o=Dg(e,o),l=[];break;default:typeof a.onClick!="function"&&typeof o.onClick=="function"&&(e.onclick=Oh)}Rg(r,o);var p;r=null;for(g in a)if(!o.hasOwnProperty(g)&&a.hasOwnProperty(g)&&a[g]!=null)if(g==="style"){var _=a[g];for(p in _)_.hasOwnProperty(p)&&(r||(r={}),r[p]="")}else 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gp(e,t){if(!nn)switch(e.tailMode){case"hidden":t=e.tail;for(var r=null;t!==null;)t.alternate!==null&&(r=t),t=t.sibling;r===null?e.tail=null:r.sibling=null;break;case"collapsed":r=e.tail;for(var o=null;r!==null;)r.alternate!==null&&(o=r),r=r.sibling;o===null?t||e.tail===null?e.tail=null:e.tail.sibling=null:o.sibling=null}}function Gn(e){var t=e.alternate!==null&&e.alternate.child===e.child,r=0,o=0;if(t)for(var a=e.child;a!==null;)r|=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;)r|=a.lanes|a.childLanes,o|=a.subtreeFlags,o|=a.flags,a.return=e,a=a.sibling;return e.subtreeFlags|=o,e.childLanes=r,t}function Vk(e,t,r){var o=t.pendingProps;switch(q_(t),t.tag){case 2:case 16:case 15:case 0:case 11:case 7:case 8:case 12:case 9:case 14:return Gn(t),null;case 1:return ci(t.type)&&zh(),Gn(t),null;case 3:return o=t.stateNode,ru(),tn(ui),tn(qn),r0(),o.pendingContext&&(o.context=o.pendingContext,o.pendingContext=null),(e===null||e.child===null)&&(oh(t)?t.flags|=4:e===null||e.memoizedState.isDehydrated&&!(t.flags&256)||(t.flags|=1024,Xi!==null&&(y_(Xi),Xi=null))),d_(e,t),Gn(t),null;case 5:t0(t);var a=oa(Wp.current);if(r=t.type,e!==null&&t.stateNode!=null)w2(e,t,r,o,a),e.ref!==t.ref&&(t.flags|=512,t.flags|=2097152);else{if(!o){if(t.stateNode===null)throw Error(xt(166));return Gn(t),null}if(e=oa(po.current),oh(t)){o=t.stateNode,r=t.type;var l=t.memoizedProps;switch(o[uo]=t,o[Up]=l,e=(t.mode&1)!==0,r){case"dialog":Jr("cancel",o),Jr("close",o);break;case"iframe":case"object":case"embed":Jr("load",o);break;case"video":case"audio":for(a=0;a<bp.length;a++)Jr(bp[a],o);break;case"source":Jr("error",o);break;case"img":case"image":case"link":Jr("error",o),Jr("load",o);break;case"details":Jr("toggle",o);break;case"input":lv(o,l),Jr("invalid",o);break;case"select":o._wrapperState={wasMultiple:!!l.multiple},Jr("invalid",o);break;case"textarea":cv(o,l),Jr("invalid",o)}Rg(r,l),a=null;for(var p in l)if(l.hasOwnProperty(p)){var _=l[p];p==="children"?typeof _=="string"?o.textContent!==_&&(l.suppressHydrationWarning!==!0&&ih(o.textContent,_,e),a=["children",_]):typeof 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o.is=="string"?e=p.createElement(r,{is:o.is}):(e=p.createElement(r),r==="select"&&(p=e,o.multiple?p.multiple=!0:o.size&&(p.size=o.size))):e=p.createElementNS(e,r),e[uo]=t,e[Up]=o,_2(e,t,!1,!1),t.stateNode=e;e:{switch(p=Bg(r,o),r){case"dialog":Jr("cancel",e),Jr("close",e),a=o;break;case"iframe":case"object":case"embed":Jr("load",e),a=o;break;case"video":case"audio":for(a=0;a<bp.length;a++)Jr(bp[a],e);a=o;break;case"source":Jr("error",e),a=o;break;case"img":case"image":case"link":Jr("error",e),Jr("load",e),a=o;break;case"details":Jr("toggle",e),a=o;break;case"input":lv(e,o),a=Fg(e,o),Jr("invalid",e);break;case"option":a=o;break;case"select":e._wrapperState={wasMultiple:!!o.multiple},a=ln({},o,{value:void 0}),Jr("invalid",e);break;case"textarea":cv(e,o),a=Dg(e,o),Jr("invalid",e);break;default:a=o}Rg(r,a),_=a;for(l in _)if(_.hasOwnProperty(l)){var h=_[l];l==="style"?Q1(e,h):l==="dangerouslySetInnerHTML"?(h=h?h.__html:void 0,h!=null&&K1(e,h)):l==="children"?typeof 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Error(xt(166));if(r=oa(Wp.current),oa(po.current),oh(t)){if(o=t.stateNode,r=t.memoizedProps,o[uo]=t,(l=o.nodeValue!==r)&&(e=yi,e!==null))switch(e.tag){case 3:ih(o.nodeValue,r,(e.mode&1)!==0);break;case 5:e.memoizedProps.suppressHydrationWarning!==!0&&ih(o.nodeValue,r,(e.mode&1)!==0)}l&&(t.flags|=4)}else o=(r.nodeType===9?r:r.ownerDocument).createTextNode(o),o[uo]=t,t.stateNode=o}return Gn(t),null;case 13:if(tn(sn),o=t.memoizedState,e===null||e.memoizedState!==null&&e.memoizedState.dehydrated!==null){if(nn&&wi!==null&&t.mode&1&&!(t.flags&128))Lb(),eu(),t.flags|=98560,l=!1;else if(l=oh(t),o!==null&&o.dehydrated!==null){if(e===null){if(!l)throw Error(xt(318));if(l=t.memoizedState,l=l!==null?l.dehydrated:null,!l)throw Error(xt(317));l[uo]=t}else eu(),!(t.flags&128)&&(t.memoizedState=null),t.flags|=4;Gn(t),l=!1}else Xi!==null&&(y_(Xi),Xi=null),l=!0;if(!l)return t.flags&65536?t:null}return t.flags&128?(t.lanes=r,t):(o=o!==null,o!==(e!==null&&e.memoizedState!==null)&&o&&(t.child.flags|=8192,t.mode&1&&(e===null||sn.current&1?En===0&&(En=3):h0())),t.updateQueue!==null&&(t.flags|=4),Gn(t),null);case 4:return ru(),d_(e,t),e===null&&Np(t.stateNode.containerInfo),Gn(t),null;case 10:return Y_(t.type._context),Gn(t),null;case 17:return ci(t.type)&&zh(),Gn(t),null;case 19:if(tn(sn),l=t.memoizedState,l===null)return Gn(t),null;if(o=(t.flags&128)!==0,p=l.rendering,p===null)if(o)gp(l,!1);else{if(En!==0||e!==null&&e.flags&128)for(e=t.child;e!==null;){if(p=Uh(e),p!==null){for(t.flags|=128,gp(l,!1),o=p.updateQueue,o!==null&&(t.updateQueue=o,t.flags|=4),t.subtreeFlags=0,o=r,r=t.child;r!==null;)l=r,e=o,l.flags&=14680066,p=l.alternate,p===null?(l.childLanes=0,l.lanes=e,l.child=null,l.subtreeFlags=0,l.memoizedProps=null,l.memoizedState=null,l.updateQueue=null,l.dependencies=null,l.stateNode=null):(l.childLanes=p.childLanes,l.lanes=p.lanes,l.child=p.child,l.subtreeFlags=0,l.deletions=null,l.memoizedProps=p.memoizedProps,l.memoizedState=p.memoizedState,l.updateQueue=p.updateQueue,l.type=p.type,e=p.dependencies,l.dependencies=e===null?null:{lanes:e.lanes,firstContext:e.firstContext}),r=r.sibling;return Qr(sn,sn.current&1|2),t.child}e=e.sibling}l.tail!==null&&mn()>iu&&(t.flags|=128,o=!0,gp(l,!1),t.lanes=4194304)}else{if(!o)if(e=Uh(p),e!==null){if(t.flags|=128,o=!0,r=e.updateQueue,r!==null&&(t.updateQueue=r,t.flags|=4),gp(l,!0),l.tail===null&&l.tailMode==="hidden"&&!p.alternate&&!nn)return Gn(t),null}else 2*mn()-l.renderingStartTime>iu&&r!==1073741824&&(t.flags|=128,o=!0,gp(l,!1),t.lanes=4194304);l.isBackwards?(p.sibling=t.child,t.child=p):(r=l.last,r!==null?r.sibling=p:t.child=p,l.last=p)}return l.tail!==null?(t=l.tail,l.rendering=t,l.tail=t.sibling,l.renderingStartTime=mn(),t.sibling=null,r=sn.current,Qr(sn,o?r&1|2:r&1),t):(Gn(t),null);case 22:case 23:return f0(),o=t.memoizedState!==null,e!==null&&e.memoizedState!==null!==o&&(t.flags|=8192),o&&t.mode&1?_i&1073741824&&(Gn(t),t.subtreeFlags&6&&(t.flags|=8192)):Gn(t),null;case 24:return null;case 25:return null}throw Error(xt(156,t.tag))}function Wk(e,t){switch(q_(t),t.tag){case 1:return ci(t.type)&&zh(),e=t.flags,e&65536?(t.flags=e&-65537|128,t):null;case 3:return ru(),tn(ui),tn(qn),r0(),e=t.flags,e&65536&&!(e&128)?(t.flags=e&-65537|128,t):null;case 5:return t0(t),null;case 13:if(tn(sn),e=t.memoizedState,e!==null&&e.dehydrated!==null){if(t.alternate===null)throw Error(xt(340));eu()}return e=t.flags,e&65536?(t.flags=e&-65537|128,t):null;case 19:return tn(sn),null;case 4:return ru(),null;case 10:return Y_(t.type._context),null;case 22:case 23:return f0(),null;case 24:return null;default:return null}}var lh=!1,Hn=!1,Gk=typeof WeakSet=="function"?WeakSet:Set,jt=null;function Wl(e,t){var r=e.ref;if(r!==null)if(typeof r=="function")try{r(null)}catch(o){fn(e,t,o)}else r.current=null}function p_(e,t,r){try{r()}catch(o){fn(e,t,o)}}var e1=!1;function Hk(e,t){if(Xg=Ah,e=Tb(),G_(e)){if("selectionStart"in e)var r={start:e.selectionStart,end:e.selectionEnd};else e:{r=(r=e.ownerDocument)&&r.defaultView||window;var 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_{constructor(g,M,y){(0,l.checkTypedArray)();let E,T;if(typeof g=="object"&&"location"in g)switch(this.dataLocation=g.location,E=g.type,T=g.dims,g.location){case"cpu-pinned":{const S=l.NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.get(E);if(!S)throw new TypeError(`unsupported type "${E}" to create tensor from pinned buffer`);if(!(g.data instanceof S))throw new TypeError(`buffer should be of type ${S.name}`);this.cpuData=g.data;break}case"texture":{if(E!=="float32")throw new TypeError(`unsupported type "${E}" to create tensor from texture`);this.gpuTextureData=g.texture,this.downloader=g.download,this.disposer=g.dispose;break}case"gpu-buffer":{if(E!=="float32"&&E!=="float16"&&E!=="int32"&&E!=="int64"&&E!=="uint32"&&E!=="uint8"&&E!=="bool")throw new TypeError(`unsupported type "${E}" to create tensor from gpu buffer`);this.gpuBufferData=g.gpuBuffer,this.downloader=g.download,this.disposer=g.dispose;break}default:throw new Error(`Tensor constructor: unsupported location 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Most likely the range contains negative values in them.");c*=i[f]}return c}static computeStrides(i){let s=i.length;if(s===0)return[];if(s===1)return[1];let u=new Array(s);u[s-1]=1,u[s-2]=i[s-1];for(let c=s-3;c>=0;--c)u[c]=u[c+1]*i[c+1];return u}static normalizeAxis(i,s){if(i<-s&&i>=s)throw new Error("unsupported axis for this operation.");return i<0?i+s:i}static normalizeAxes(i,s){return i.map(u=>this.normalizeAxis(u,s??i.length))}static sortBasedOnPerm(i,s){return s?s.map(u=>i[u]):i.slice().reverse()}static padShape(i,s){let u=i.length;return i.map((c,f)=>c+s[f]+s[f+u])}static areEqual(i,s){return i.length!==s.length?!1:i.every((u,c)=>u===s[c])}},Kn=class xp{static adjustPoolAttributes(i,s,u,c,f,d){if(!i&&u.length!==s.length-2)throw new Error("length of specified kernel shapes should be 2 less than length of input dimensions");if(i)for(let x=0;x<s.length-2;x++)x>=u.length?u.push(s[x+2]):u[x]=s[x+2];for(let x=0;x<u.length;x++)if(x<c.length){if(c[x]<0)throw new Error("strides should be greater than or equal to 1")}else c.push(1);for(let x=0;x<u.length;x++)if(x<f.length){if(f[x]<0)throw new Error("dilations should be greater than or equal to 1")}else f.push(1);for(let x=0;x<u.length*2;x++)if(x<d.length){if(d[x]<0)throw new Error("pad should be greater than or equal to 1")}else d.push(0);for(let x=0;x<u.length;x++){if(u[x]<=0)throw new Error("kernel shapes need to be greater than 0");if(d[x]>=u[x]||d[x+u.length]>=u[x])throw new Error("pads should be smaller than kernel")}}static adjustPadsBasedOnAutoPad(i,s,u,c,f,d,x){if(x){if(f.length!==2*(i.length-2))throw new Error("length of pads should be twice the length of data dimensions");if(s.length!==i.length-2)throw new Error("length of strides should be the length of data dimensions");if(c.length!==i.length-2)throw new Error("length of kernel shapes should be the length of data dimensions");for(let k=0;k<i.length-2;k++)xp.adjustPadAndReturnShape(i[k+(d?1:2)],s[k],u[k],c[k],f,k,k+i.length-2,x)}}static computePoolOutputShape(i,s,u,c,f,d,x){if(s.length<=0)throw new Error("input shape must be of size greater than 0");let k=[s[0],s[1]];return xp.computeShapeHelper(i,s,k,u,c,f,d,x),k}static computeConvOutputShape(i,s,u,c,f,d,x){if(i.length<=0||s.length<=0)throw new Error("invalid input tensor dims or invalid filter tensor dims");let k=[i[0],s[0]];return xp.computeShapeHelper(!1,i,k,u,c,f,d,x),k}static computeShapeHelper(i,s,u,c,f,d,x,k){if(i)for(let $=0;$<s.length-2;$++)u.push(1);else for(let $=0;$<s.length-2;$++)u.push(xp.adjustPadAndReturnShape(s[$+2],c[$],f[$],d[$],x,$,$+s.length-2,k))}static adjustPadAndReturnShape(i,s,u,c,f,d,x,k){let $=u*(c-1)+1;if(k&&k!=="NOTSET")switch(k){case"VALID":return f[d]=0,f[x]=0,Math.floor((i-$)/s+1);case"SAME_LOWER":case"SAME_UPPER":if(u!==1)throw new Error("Dilation not supported for SAME_UPPER or SAME_LOWER");{let H=((i+s-1)/s-1)*s+c-i;return f[d]=Math.floor(k==="SAME_LOWER"?(H+1)/2:H/2),f[x]=H-f[d],Math.floor((i+H-c)/s+1)}default:throw new Error("Unsupported AutoPad type")}else return Math.floor((i+f[d]+f[x]-$)/s+1)}},Tr=class{static getShapeOfGemmResult(n,i,s,u,c){if(n.length!==2||s.length!==2)throw new Error("shape need to be of size 2");let f,d,x;i?(f=n[1],d=n[0]):(f=n[0],d=n[1]);let k=-1;if(u?(x=s[0],k=1):(x=s[1],k=0),s[k]!==d)throw new Error("dimension mismatch");if(f<=0||x<=0||d<=0)throw new Error("invalid shape specified");if(c&&!gn.isValidBroadcast(c,[f,x]))throw new Error("gemm: invalid bias shape for broadcast");return[f,x,d]}},cn=-34028234663852886e22,On=34028234663852886e22}),Un,yn,Sr,Er,At,vr,Lr,Xr,Vn,zt,$s,_t,Gt,ma,ga,cu,wo,ar=h(()=>{Zt(),Jt(),Un=64,yn=(n,i)=>{if(i===3)throw new Error("vec3 has same alignment as vec4, use vec4 instead");switch(n){case 10:return i>1?`vec${i}<f16>`:"f16";case 1:return i>1?`vec${i}<f32>`:"f32";case 6:return i>1?`vec${i}<i32>`:"i32";case 12:return i>1?`vec${i}<u32>`:"u32";case 7:if(i>1)throw new Error("currently not supported vecX of uint64 yet");return["vec2<u32>","i32"];case 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: ${n}`)}},Sr=(n,i=1)=>{let s=yn(n,i);return typeof s=="string"?s:s[0]},Er=(n,i=1)=>{let s=yn(n,i);return typeof s=="string"?s:s[1]},At=(...n)=>{let i=[];return n.forEach(s=>{s.length!==0&&i.push({type:12,data:s},{type:12,data:ct.computeStrides(s)})}),i},vr=n=>n%4===0?4:n%2===0?2:1,Lr=(n="f32",i,s="0")=>!i||i===1?`${n}(${s})`:`vec${i}<${n}>(${s})`,Xr=(n,i,s)=>n==="f32"?s:i===1?`f32(${s})`:`vec${i}<f32>(${s})`,Vn=(n,i)=>i===4?`(${n}.x + ${n}.y + ${n}.z + ${n}.w)`:i===2?`(${n}.x + ${n}.y)`:i===3?`(${n}.x + ${n}.y + ${n}.z)`:n,zt=(n,i,s,u)=>n.startsWith("uniforms.")&&s>4?typeof i=="string"?u==="f16"?`${n}[(${i}) / 8][(${i}) % 8 / 4][(${i}) % 8 % 4]`:`${n}[(${i}) / 4][(${i}) % 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    let dim${ot} = current / ${zt(be,ot,d)};
    let rest${ot} = current % ${zt(be,ot,d)};
    indices[${ot}] = dim${ot};
    current = rest${ot};
    `;he+=`indices[${d-1}] = current;`;let De=d<2?"":`
  fn o2i_${n}(offset: u32) -> ${v.indices} {
    var indices: ${v.indices};
    var current = offset;
    ${he}
    return indices;
  }`,Ae=ot=>(te.offsetToIndices=!0,d<2?ot:`o2i_${n}(${ot})`),Ie=[];if(d>=2)for(let ot=d-1;ot>=0;ot--)Ie.push(`${zt(be,ot,d)} * (indices[${ot}])`);let gt=d<2?"":`
  fn i2o_${n}(indices: ${v.indices}) -> u32 {
    return ${Ie.join("+")};
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             return ${Wr.length>0?Wr.join("+"):"0u"};
           }`,`${nr}(${ot})`},ir=(ot,Vt)=>(()=>{if(v.storage===v.value)return`${n}[${ot}]=${Vt};`;if(v.storage==="vec2<u32>"&&v.value==="i32")return`${n}[${ot}]=vec2<u32>(u32(${Vt}), select(0u, 0xFFFFFFFFu, ${Vt} < 0));`;if(v.storage==="vec2<u32>"&&v.value==="u32")return`${n}[${ot}]=vec2<u32>(u32(${Vt}), 0u);`;if(v.storage==="u32"&&v.value==="vec4<bool>")return`${n}[${ot}]=dot(vec4<u32>(0x1, 0x100, 0x10000, 0x1000000), vec4<u32>(${Vt}));`;throw new Error(`not supported combination of storage type ${v.storage} and value type ${v.value} yet`)})(),Fr=ot=>(()=>{if(v.storage===v.value)return`${n}[${ot}]`;if(v.storage==="vec2<u32>"&&v.value==="i32")return`i32(${n}[${ot}].x)`;if(v.storage==="vec2<u32>"&&v.value==="u32")return`u32(${n}[${ot}].x)`;if(v.storage==="u32"&&v.value==="vec4<bool>")return`vec4<bool>(bool(${n}[${ot}] & 0xFFu), bool(${n}[${ot}] & 0xFF00u), bool(${n}[${ot}] & 0xFF0000u), bool(${n}[${ot}] & 0xFF000000u))`;throw new Error(`not supported combination of storage type ${v.storage} and value type ${v.value} yet`)})(),Zr=d<2?"":`
  fn get_${n}ByIndices(indices: ${v.indices}) -> ${H} {
    return ${Fr(`i2o_${n}(indices)`)};
  }`,hr=d<2?"":(()=>{let ot=x.map(nr=>`d${nr}: u32`).join(", "),Vt=x.map(nr=>`d${nr}`).join(", ");return`
  fn get_${n}(${ot}) -> ${H} {
    return get_${n}ByIndices(${vt(Vt)});
  }`})(),Hr=(...ot)=>{if(ot.length!==d)throw new Error(`indices length must be ${d}`);let Vt=ot.map(oe).join(",");return d===0?Fr("0u"):d===1?Fr(Vt[0]):(te.get=!0,te.getByIndices=!0,te.indicesToOffset=!0,`get_${n}(${Vt})`)},Nt=ot=>d<2?Fr(ot):(te.getByIndices=!0,te.indicesToOffset=!0,`get_${n}ByIndices(${ot})`),er=d<2?"":`
  fn set_${n}ByIndices(indices: ${v.indices}, value: ${H}) {
    ${ir(`i2o_${n}(indices)`,"value")}
  }`,yr=d<2?"":(()=>{let ot=x.map(nr=>`d${nr}: u32`).join(", "),Vt=x.map(nr=>`d${nr}`).join(", ");return`
  fn set_${n}(${ot}, value: ${H}) {
    set_${n}ByIndices(${vt(Vt)}, value);
  }`})();return{impl:()=>{let ot=[],Vt=!1;return te.offsetToIndices&&(ot.push(De),Vt=!0),te.indicesToOffset&&(ot.push(gt),Vt=!0),te.broadcastedIndicesToOffset&&(Object.values(gr).forEach(nr=>ot.push(nr)),Vt=!0),te.set&&(ot.push(yr),Vt=!0),te.setByIndices&&(ot.push(er),Vt=!0),te.get&&(ot.push(hr),Vt=!0),te.getByIndices&&(ot.push(Zr),Vt=!0),!f&&Vt&&ot.unshift(`const ${we} = ${v.indices}(${s.join(",")});`,`const ${be} = ${v.indices}(${ct.computeStrides(s).join(",")});`),ot.join(`
`)},type:v,offsetToIndices:Ae,indicesToOffset:ut,broadcastedIndicesToOffset:Mr,indices:vt,indicesGet:Dt,indicesSet:Rt,set:(...ot)=>{if(ot.length!==d+1)throw new Error(`indices length must be ${d}`);let Vt=ot[d];if(typeof Vt!="string")throw new Error("value must be string");let nr=ot.slice(0,d).map(oe).join(",");return d===0?ir("0u",Vt):d===1?ir(nr[0],Vt):(te.set=!0,te.setByIndices=!0,te.indicesToOffset=!0,`set_${n}(${nr}, ${Vt})`)},setByOffset:ir,setByIndices:(ot,Vt)=>d<2?ir(ot,Vt):(te.setByIndices=!0,te.indicesToOffset=!0,`set_${n}ByIndices(${ot}, ${Vt});`),get:Hr,getByOffset:Fr,getByIndices:Nt,usage:u,name:n,strides:be,shape:we,rank:d}},_t=(n,i,s,u=1)=>$s(n,i,s,"input",u),Gt=(n,i,s,u=1)=>$s(n,i,s,"output",u),ma=(n,i,s,u=1)=>$s(n,i,s,"internal",u),ga=class{constructor(n,i){this.normalizedDispatchGroup=n,this.limits=i,this.internalVariables=[],this.variables=[],this.uniforms=[],this.variableIndex=0}guardAgainstOutOfBoundsWorkgroupSizes(n){return`if (global_idx >= ${typeof n=="number"?`${n}u`:n}) { return; }`}mainStart(n=Un){let i=typeof n=="number"?n:n[0],s=typeof n=="number"?1:n[1],u=typeof n=="number"?1:n[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,f=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}, ${u})
  fn main(${f}) {
    ${d}
  `}appendVariableUniforms(n){n.rank!==0&&(n.shape.startsWith("uniforms.")&&this.uniforms.push({name:n.shape.replace("uniforms.",""),type:"u32",length:n.rank}),n.strides.startsWith("uniforms.")&&this.uniforms.push({name:n.strides.replace("uniforms.",""),type:"u32",length:n.rank}))}declareVariable(n,i){if(n.usage==="internal")throw new Error("cannot use internal variable with declareVariable(). use registerInternalVariables() instead.");this.variables.push(n),this.appendVariableUniforms(n);let s=n.usage==="input"?"read":"read_write",u=n.type.storage;return`@group(0) @binding(${i}) var<storage, ${s}> ${n.name}: array<${u}>;`}declareVariables(...n){return n.map(i=>this.declareVariable(i,this.variableIndex++)).join(`
`)}registerInternalVariable(n){if(n.usage!=="internal")throw new Error("cannot use input or output variable with registerInternalVariable(). use declareVariables() instead.");this.internalVariables.push(n),this.appendVariableUniforms(n)}registerInternalVariables(...n){return n.forEach(i=>this.registerInternalVariable(i)),this}registerUniform(n,i,s=1){return this.uniforms.push({name:n,type:i,length:s}),this}registerUniforms(n){return this.uniforms=this.uniforms.concat(n),this}uniformDeclaration(){if(this.uniforms.length===0)return"";let n=[];for(let{name:i,type:s,length:u}of this.uniforms)if(u&&u>4)s==="f16"?n.push(`@align(16) ${i}:array<mat2x4<${s}>, ${Math.ceil(u/8)}>`):n.push(`${i}:array<vec4<${s}>, ${Math.ceil(u/4)}>`);else{let c=u==null||u===1?s:`vec${u}<${s}>`;n.push(`${i}:${c}`)}return`
      struct Uniforms { ${n.join(", ")} };
      @group(0) @binding(${this.variableIndex}) var<uniform> uniforms: Uniforms;`}get additionalImplementations(){return this.uniformDeclaration()+this.variables.map(n=>n.impl()).join(`
`)+this.internalVariables.map(n=>n.impl()).join(`
`)}get variablesInfo(){if(this.uniforms.length===0)return;let n=i=>[12,10,1,6][["u32","f16","f32","i32"].indexOf(i)];return this.uniforms.map(i=>[n(i.type),i.length??1])}},cu=(n,i)=>new ga(n,i),wo=(n,i)=>{let s=n.length,u=[];for(let c=0;c<s;c++){let f=s-1-c,d=n[f]||1;(i[i.length-1-c]||1)>1&&d===1&&u.unshift(f)}return u}}),du,_a,Ho,pu,hi,fu,wa,yo=h(()=>{Zt(),Jt(),_r(),ar(),du=n=>{if(!n||n.length!==1)throw new Error("Transpose requires 1 input.")},_a=(n,i)=>i&&i.length!==n?[...new Array(n).keys()].reverse():i,Ho=(n,i)=>ct.sortBasedOnPerm(n,_a(n.length,i)),pu=(n,i,s,u)=>{let c=[];c.push(`fn perm(i: ${u.type.indices}) -> ${s.type.indices} {
    var a: ${s.type.indices};`);for(let f=0;f<i;++f)c.push(s.indicesSet("a",n[f],`i[${f}]`));return c.push("return a;}"),c.join(`
`)},hi=(n,i)=>{let s=n.dataType,u=n.dims.length,c=_a(u,i),f=Ho(n.dims,c),d=Gt("output",s,f.length),x=_t("a",s,u),k;if(c.length===2&&c[0]===1&&c[1]===0){let $=d.type.value,H=[16,16,1];k=q=>`
  ${q.registerUniform("output_size","u32").declareVariables(x,d)}
  var<workgroup> tile : array<array<${$}, ${H[0]+1}>, ${H[0]}>;
  ${q.mainStart(H)}
    var x = workgroup_id.x * ${H[0]}u + local_id.x;
    var y = workgroup_id.y * ${H[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] = ${x.getByOffset("y * width + x")};
    }
    workgroupBarrier();
    x = workgroup_id.y * ${H[0]}u + local_id.x;
    y = workgroup_id.x * ${H[0]}u + local_id.y;
    if (x < height && y < width) {
      ${d.setByOffset("y * height + x","tile[local_id.x][local_id.y]")}
    }
  }`}else k=$=>`
  ${$.registerUniform("output_size","u32").declareVariables(x,d)}

  ${pu(c,u,x,d)}

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

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

    ${d.setByOffset("global_idx",x.getByIndices("aIndices"))}
  }`;return{name:"Transpose",shaderCache:{hint:`${i}`,inputDependencies:["rank"]},getRunData:$=>{let H=ct.size(f);return{outputs:[{dims:f,dataType:$[0].dataType}],dispatchGroup:{x:Math.ceil(H/64)},programUniforms:[{type:12,data:H},...At($[0].dims,f)]}},getShaderSource:k}},fu=(n,i)=>{du(n.inputs),n.compute(hi(n.inputs[0],i.perm))},wa=n=>qt({perm:n.perm})}),hu,mu,gu,_u,ya,wu,yu,va,vu,bu,Xn,xu,Mu,ba,Tu,ku,xa,Su,Eu,Ma,Cu,rf=h(()=>{Zt(),Jt(),ar(),$a(),yo(),hu={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"},mu={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"},gu={max:"_A[offset]",min:"_A[offset]",mean:"0",sum:"0",prod:"1",sumSquare:"0",logSumExp:"0",l1:"0",l2:"0",logSum:"0"},_u={max:"bestValue",min:"bestValue",sum:"bestValue",prod:"bestValue",sumSquare:"bestValue",logSumExp:"log(bestValue)",l1:"bestValue",l2:"sqrt(bestValue)",logSum:"log(bestValue)"},ya=(n,i)=>{let s=[];for(let u=i-n;u<i;++u)s.push(u);return s},wu=(n,i)=>{let s=[],u=n.length;for(let f=0;f<u;f++)i.indexOf(f)===-1&&s.push(n[f]);let c=i.map(f=>n[f]);return[s,c]},yu=(n,i)=>{let s=n.length+i.length,u=[],c=0;for(let f=0;f<s;f++)i.indexOf(f)===-1?u.push(n[c++]):u.push(1);return u},va=(n,i)=>{for(let s=0;s<n.length;++s)if(n[n.length-s-1]!==i-1-s)return!1;return!0},vu=(n,i)=>{let s=[];if(!va(n,i)){for(let u=0;u<i;++u)n.indexOf(u)===-1&&s.push(u);n.forEach(u=>s.push(u))}return s},bu=(n,i,s,u,c,f,d)=>{let x=s[0].dims,k=ct.size(f),$=ct.size(d),H=_t("_A",s[0].dataType,x),q=Gt("output",c,f),v=32,oe=`
          var<workgroup> aBestValues : array<f32, ${v}>;
       `;return{name:n,shaderCache:i,getShaderSource:te=>`
        ${te.registerUniform("reduceSize","u32").declareVariables(H,q)}
        ${oe}
        fn DIV_CEIL(a : u32, b : u32) -> u32 {
          return ((a - 1u) / b + 1u);
         }
         ${te.mainStart(v)}

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

          var bestValue = f32(${gu[u]});
          let Length = uniforms.reduceSize;
          for (var k = local_idx; k < Length; k = k + ${v}) {
           let candidate = f32(${H.getByOffset("offset + k")});
           bestValue = ${hu[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 = ${mu[u]};
            aBestValues[local_idx] = bestValue;
           }
           reduceSize = interval;
           workgroupBarrier();
         }

         if (local_idx == 0u) {
          ${q.setByOffset("outputIndex",`${u==="mean"?`${q.type.storage}(bestValue / f32(uniforms.reduceSize))`:`${q.type.storage}(${_u[u]})`}`)};
         }
        }`,getRunData:()=>({outputs:[{dims:f,dataType:c}],dispatchGroup:{x:k},programUniforms:[{type:12,data:$}]})}},Xn=(n,i,s,u)=>{let c=n.inputs.length===1?s:Is(n.inputs,s),f=c.axes;f.length===0&&!c.noopWithEmptyAxes&&(f=n.inputs[0].dims.map((oe,te)=>te));let d=ct.normalizeAxes(f,n.inputs[0].dims.length),x=d,k=n.inputs[0],$=vu(x,n.inputs[0].dims.length);$.length>0&&(k=n.compute(hi(n.inputs[0],$),{inputs:[0],outputs:[-1]})[0],x=ya(x.length,k.dims.length));let[H,q]=wu(k.dims,x),v=H;c.keepDims&&(v=yu(H,d)),n.compute(bu(i,{hint:c.cacheKey,inputDependencies:["type"]},[k],u,n.inputs[0].dataType,v,q),{inputs:[k]})},xu=(n,i)=>{Xn(n,"ReduceMeanShared",i,"mean")},Mu=(n,i)=>{Xn(n,"ReduceL1Shared",i,"l1")},ba=(n,i)=>{Xn(n,"ReduceL2Shared",i,"l2")},Tu=(n,i)=>{Xn(n,"ReduceLogSumExpShared",i,"logSumExp")},ku=(n,i)=>{Xn(n,"ReduceMaxShared",i,"max")},xa=(n,i)=>{Xn(n,"ReduceMinShared",i,"min")},Su=(n,i)=>{Xn(n,"ReduceProdShared",i,"prod")},Eu=(n,i)=>{Xn(n,"ReduceSumShared",i,"sum")},Ma=(n,i)=>{Xn(n,"ReduceSumSquareShared",i,"sumSquare")},Cu=(n,i)=>{Xn(n,"ReduceLogSumShared",i,"logSum")}}),Qn,Pu,As,Is,ii,$u,Ta,Au,Iu,ka,Fu,Ou,Sa,zu,Du,Yn,Lu,Ru,Ea,Bu,Nu,Ca,ju,Uu,Pa,Vu,$a=h(()=>{Zt(),Jt(),_r(),ar(),rf(),Qn=n=>{if(!n||n.length===0||n.length>2)throw new Error("Reduce op requires 1 or 2 inputs.");if(n.length===2&&n[1].dims.length!==1)throw new Error("Invalid axes input dims.")},Pu=n=>["","",`var value = ${n.getByIndices("input_indices")};`,""],As=(n,i,s,u,c,f,d=!1,x=!1)=>{let k=[],$=s[0].dims,H=$.length,q=ct.normalizeAxes(c,H),v=!x&&q.length===0;$.forEach((de,we)=>{v||q.indexOf(we)>=0?d&&k.push(1):k.push(de)});let oe=k.length,te=ct.size(k);return{name:n,shaderCache:i,getShaderSource:de=>{let we=[],be=_t("_A",s[0].dataType,H),he=Gt("output",f,oe),De=u(be,he,q),Ae=De[2];for(let Ie=0,gt=0;Ie<H;Ie++)v||q.indexOf(Ie)>=0?(d&&gt++,Ae=`for(var j${Ie}: u32 = 0; j${Ie} < ${$[Ie]}; j${Ie}++) {
                  ${De[2].includes("last_index")?`let last_index = j${Ie};`:""}
                  ${be.indicesSet("input_indices",Ie,`j${Ie}`)}
                  ${Ae}
                }`):(we.push(`${be.indicesSet("input_indices",Ie,he.indicesGet("output_indices",gt))};`),gt++);return`

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

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

          ${we.join(`
`)}
          ${De[0]}       // init ops for reduce max/min
          ${De[1]}
          ${Ae}
          ${De[3]}
          ${De.length===4?he.setByOffset("global_idx","value"):De.slice(4).join(`
`)}
        }`},getRunData:()=>({outputs:[{dims:k,dataType:f}],dispatchGroup:{x:Math.ceil(te/64)},programUniforms:[{type:12,data:te},...At($,k)]})}},Is=(n,i)=>{let s=[];return n[1].dims[0]>0&&n[1].getBigInt64Array().forEach(u=>s.push(Number(u))),qt({axes:s,keepDims:i.keepDims,noopWithEmptyAxes:i.noopWithEmptyAxes})},ii=(n,i,s,u)=>{let c=n.inputs,f=c.length===1?s:Is(c,s);n.compute(As(i,{hint:f.cacheKey,inputDependencies:["rank"]},[c[0]],f.noopWithEmptyAxes&&f.axes.length===0?Pu:u,f.axes,c[0].dataType,f.keepDims,f.noopWithEmptyAxes),{inputs:[0]})},$u=(n,i)=>{Qn(n.inputs),ii(n,"ReduceLogSum",i,(s,u)=>[`var value = ${u.type.storage}(0);`,"",`value += ${s.getByIndices("input_indices")};`,"value = log(value);"])},Ta=(n,i)=>{Qn(n.inputs),ii(n,"ReduceL1",i,(s,u)=>[`var value = ${u.type.storage}(0);`,"",`value += abs(${s.getByIndices("input_indices")});`,""])},Au=(n,i)=>{Qn(n.inputs),ii(n,"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);"])},Iu=(n,i)=>{Qn(n.inputs),ii(n,"ReduceLogSumExp",i,(s,u)=>[`var value = ${u.type.storage}(0);`,"",`value += exp(${s.getByIndices("input_indices")});`,"value = log(value);"])},ka=(n,i)=>{Qn(n.inputs),ii(n,"ReduceMax",i,(s,u,c)=>{let f=[];for(let d=0;d<s.rank;d++)(c.indexOf(d)>=0||c.length===0)&&f.push(s.indicesSet("input_indices",d,0));return[`${f.join(`
`)}`,`var value = ${s.getByIndices("input_indices")};`,`value = max(value, ${s.getByIndices("input_indices")});`,""]})},Fu=(n,i)=>{Qn(n.inputs),ii(n,"ReduceMean",i,(s,u,c)=>{let f=1;for(let d=0;d<s.rank;d++)(c.indexOf(d)>=0||c.length===0)&&(f*=n.inputs[0].dims[d]);return["var sum = f32(0);","",`sum += f32(${s.getByIndices("input_indices")});`,`let value = ${u.type.value}(sum / ${f});`]})},Ou=(n,i)=>{Qn(n.inputs),ii(n,"ReduceMin",i,(s,u,c)=>{let f=[];for(let d=0;d<s.rank;d++)(c.indexOf(d)>=0||c.length===0)&&f.push(`input_indices[${d}] = 0;`);return[`${f.join(`
`)}`,`var value = ${s.getByIndices("input_indices")};`,`value = min(value, ${s.getByIndices("input_indices")});`,""]})},Sa=(n,i)=>{Qn(n.inputs),ii(n,"ReduceProd",i,(s,u)=>[`var value = ${u.type.storage}(1);`,"",`value *= ${s.getByIndices("input_indices")};`,""])},zu=(n,i)=>{Qn(n.inputs),ii(n,"ReduceSum",i,(s,u)=>[`var value = ${u.type.storage}(0);`,"",`value += ${s.getByIndices("input_indices")};`,""])},Du=(n,i)=>{Qn(n.inputs),ii(n,"ReduceSumSquare",i,(s,u)=>[`var t = ${u.type.value}(0); var value = ${u.type.value}(0);`,"",`t = ${s.getByIndices("input_indices")}; value += t * t;`,""])},Yn=(n,i,s)=>{if(i.length===0)return s;let u=1,c=1;for(let f=0;f<i.length;f++)i.indexOf(f)===-1?u*=n[f]:c*=n[f];return c<32&&u>1024},Lu=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Fu(n,i):xu(n,i)},Ru=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Ta(n,i):Mu(n,i)},Ea=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Au(n,i):ba(n,i)},Bu=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Iu(n,i):Tu(n,i)},Nu=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?ka(n,i):ku(n,i)},Ca=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Ou(n,i):xa(n,i)},ju=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Sa(n,i):Su(n,i)},Uu=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?zu(n,i):Eu(n,i)},Pa=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?Du(n,i):Ma(n,i)},Vu=(n,i)=>{Yn(n.inputs[0].dims,i.axes,i.noopWithEmptyAxes)?$u(n,i):Cu(n,i)}}),Fs,Wu,Gu,Os,nf=h(()=>{Zt(),_r(),$a(),Fs=n=>{if(!n||n.length===0||n.length>2)throw new Error("ArgMinMaxOp op requires 1 or 2 inputs.");if(n[0].dataType!==1)throw new Error("Invalid input type.")},Wu=(n,i)=>{Fs(n.inputs);let s=(u,c,f)=>{let d=[];for(let x=0;x<u.rank;x++)(f.indexOf(x)>=0||f.length===0)&&d.push(`input_indices[${x}] = 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 = ${u.getByIndices("input_indices")};
         best_index = i32(last_index);
       }`,"",c.setByOffset("global_idx","best_index")]};n.compute(As("ArgMin",{hint:i.cacheKey,inputDependencies:["rank"]},[n.inputs[0]],s,[i.axis],7,i.keepDims),{inputs:[0]})},Gu=(n,i)=>{Fs(n.inputs);let s=(u,c,f)=>{let d=[];for(let x=0;x<u.rank;x++)(f.indexOf(x)>=0||f.length===0)&&d.push(`input_indices[${x}] = 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 = ${u.getByIndices("input_indices")};
         best_index = i32(last_index);
       }`,"",c.setByOffset("global_idx","best_index")]};n.compute(As("argMax",{hint:i.cacheKey,inputDependencies:["rank"]},[n.inputs[0]],s,[i.axis],7,i.keepDims),{inputs:[0]})},Os=n=>qt(n)}),Hu,Aa,qu,Ku,vo,Xu,Qu,zs=h(()=>{Zt(),pe(),ar(),Hu=(n,i)=>{let s=n[0],u=n[1],c=n[2],f=n[3],d=n[4],x=n[5];if(d&&x)throw new Error("Attention cannot have both past and relative_position_bias");if(s.dims.length!==3)throw new Error('Input "input" must have 3 dimensions');let k=s.dims[0],$=s.dims[1],H=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]!==H)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 q=c.dims[0]/3,v=q,oe=v;if(i.qkvHiddenSizes.length>0){if(i.qkvHiddenSizes.length!==3)throw new Error("qkv_hidden_sizes attribute should have 3 elements");for(let De of i.qkvHiddenSizes)if(De%i.numHeads!==0)throw new Error("qkv_hidden_sizes should be divisible by num_heads");q=i.qkvHiddenSizes[0],v=i.qkvHiddenSizes[1],oe=i.qkvHiddenSizes[2]}let te=$;if(q!==v)throw new Error("qkv_hidden_sizes first element should be same as the second");if(c.dims[0]!==q+v+oe)throw new Error('Input "bias" dimension 0 should have same length as sum of Q/K/V hidden sizes');let de=0;if(d){if(v!==oe)throw new Error('Input "past" expect k_hidden_size == v_hidden_size');if(d.dims.length!==5)throw new Error('Input "past" must have 5 dimensions');if(d.dims[0]!==2)throw new Error('Input "past" first dimension must be 2');if(d.dims[1]!==k)throw new Error('Input "past" second dimension must be batch_size');if(d.dims[2]!==i.numHeads)throw new Error('Input "past" third dimension must be num_heads');if(d.dims[4]!==v/i.numHeads)throw new Error('Input "past" fifth dimension must be k_hidden_size / num_heads');i.pastPresentShareBuffer||(de=d.dims[3])}let we=te+de,be=-1,he=0;if(f)throw new Error("Mask not supported");if(d)throw new Error("past is not supported");return{batchSize:k,sequenceLength:$,pastSequenceLength:de,kvSequenceLength:te,totalSequenceLength:we,maxSequenceLength:be,inputHiddenSize:H,hiddenSize:q,vHiddenSize:oe,headSize:Math.floor(q/i.numHeads),vHeadSize:Math.floor(oe/i.numHeads),numHeads:i.numHeads,isUnidirectional:!1,pastPresentShareBuffer:!1,maskFilterValue:i.maskFilterValue,maskType:he,scale:i.scale,broadcastResPosBias:!1,passPastInKv:!1,qkvFormat:1}},Aa=(n,i,s,u)=>{let c=vr(u),f=64,d=u/c;d<f?f=1:d/8<64&&(f=Math.ceil(d/8));let x=Math.ceil(u/c/f),k=[{type:i.dataType,data:1/u},{type:12,data:d},{type:12,data:x}],$=Sr(i.dataType,c),H=Er(1,c),q=v=>{let oe=Gt("x",i.dataType,i.dims,c),te=[{name:"d_inv",type:Er(i.dataType)},{name:"d_comp",type:"u32"},{name:"elements_per_thread",type:"u32"}];return`
  var<workgroup> thread_max: array<f32, ${f}>;
  var<workgroup> thread_sum: array<f32, ${f}>;
  ${v.registerUniforms(te).declareVariables(oe)}
  ${v.mainStart([f,1,1])}
    let local_offset = local_idx * uniforms.elements_per_thread;
    let offset = workgroup_id.x * uniforms.d_comp + local_offset;

    var thread_max_vector = ${H}(-3.402823e+38f);
    for (var i: u32 = 0; i < uniforms.elements_per_thread && i + local_offset < uniforms.d_comp; i++) {
      thread_max_vector = max(${H}(x[offset + i]), thread_max_vector);
    }
    thread_max[local_idx] = ${(()=>{switch(c){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: ${c}`)}})()};
    workgroupBarrier();

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

    var sum_vector = ${H}(0);
    for (var i: u32 = 0; i < uniforms.elements_per_thread && i + local_offset < uniforms.d_comp; i++) {
      sum_vector += exp(${H}(x[offset + i]) - max_value);
    }
    thread_sum[local_idx] = ${(()=>{switch(c){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: ${c}`)}})()};
    workgroupBarrier();

    var sum: f32 = 0;
    for (var i = 0u; i < ${f}; 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] = ${oe.type.value}(uniforms.d_inv);
      }
    } else {
      for (var i: u32 = 0; i < uniforms.elements_per_thread && i + local_offset < uniforms.d_comp; i++) {
        var f32input = ${H}(x[offset + i]);
        x[offset + i] = ${oe.type.value}(exp(f32input - max_value) / sum);
      }
    }
  }`};return{name:"AttentionProbsSoftmax",shaderCache:{hint:`${f};${$};${c}`},getShaderSource:q,getRunData:()=>({outputs:[],dispatchGroup:{x:s},programUniforms:k})}},qu=(n,i,s,u,c,f,d,x)=>{let k=x+f.kvSequenceLength,$=[f.batchSize,f.numHeads,f.sequenceLength,k],H=f.kvNumHeads===void 0&&n.outputCount>1,q=H?[f.batchSize,f.numHeads,k,f.headSize]:void 0,v=d.scale===0?1/Math.sqrt(f.headSize):d.scale,oe=vr(f.headSize),te=f.headSize/oe,de=12,we={x:Math.ceil(k/de),y:Math.ceil(f.sequenceLength/de),z:f.batchSize*f.numHeads},be=[{type:12,data:f.sequenceLength},{type:12,data:te},{type:12,data:k},{type:12,data:f.numHeads},{type:1,data:v},{type:12,data:x},{type:12,data:f.kvSequenceLength}],he=["type","type"];u&&he.push("type"),c&&he.push("type");let De=[{dims:$,dataType:i.dataType,gpuDataType:0}];H&&De.push({dims:q,dataType:i.dataType,gpuDataType:0});let Ae=Ie=>{let gt=_t("q",i.dataType,i.dims,oe),ut=_t("key",s.dataType,s.dims,oe),vt=[gt,ut];if(u){let ir=_t("past_key",u.dataType,u.dims,oe);vt.push(ir)}c&&vt.push(_t("relative_position_bias",c.dataType,c.dims));let Dt=Gt("output",i.dataType,$),Rt=[Dt];H&&Rt.push(Gt("present_key",i.dataType,q,oe));let gr=Er(1,oe),Mr=[{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 = ${de}u;

  var<workgroup> tileQ: array<${gt.type.storage}, ${de*de}>;
  var<workgroup> tileK: array<${gt.type.storage}, ${de*de}>;
  ${Ie.registerUniforms(Mr).declareVariables(...vt,...Rt)}
  ${Ie.mainStart([de,de,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;
    ${u&&H?`
    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;`}
    ${H?"let presentKeyOffset = headIdx * uniforms.N * uniforms.K;":""}
    var value = ${gr}(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;
      ${u&&H?`
              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];"}
      ${H?"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 += ${gr}(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(oe){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: ${oe}`)}})()};
        output[outputIdx] = ${Dt.type.value} (sum * uniforms.alpha) + ${c?"relative_position_bias[outputIdx]":"0.0"};
    }
  }`};return{name:"AttentionProbs",shaderCache:{hint:`${oe};${c!==void 0};${u!==void 0};${n.outputCount}`,inputDependencies:he},getRunData:()=>({outputs:De,dispatchGroup:we,programUniforms:be}),getShaderSource:Ae}},Ku=(n,i,s,u,c,f)=>{let d=f+c.kvSequenceLength,x=c.nReps?c.nReps:1,k=c.vHiddenSize*x,$=c.kvNumHeads==null&&n.outputCount>1,H=$?[c.batchSize,c.numHeads,d,c.headSize]:void 0,q=[c.batchSize,c.sequenceLength,k],v=12,oe={x:Math.ceil(c.vHeadSize/v),y:Math.ceil(c.sequenceLength/v),z:c.batchSize*c.numHeads},te=[{type:12,data:c.sequenceLength},{type:12,data:d},{type:12,data:c.vHeadSize},{type:12,data:c.numHeads},{type:12,data:k},{type:12,data:f},{type:12,data:c.kvSequenceLength}],de=u?["type","type","type"]:["type","type"],we=[{dims:q,dataType:i.dataType,gpuDataType:0}];$&&we.push({dims:H,dataType:i.dataType,gpuDataType:0});let be=he=>{let De=_t("probs",i.dataType,i.dims),Ae=_t("v",s.dataType,s.dims),Ie=[De,Ae];u&&Ie.push(_t("past_value",u.dataType,u.dims));let gt=[Gt("output",i.dataType,q)];$&&gt.push(Gt("present_value",i.dataType,H));let ut=[{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 = ${v}u;
  var<workgroup> tileQ: array<${De.type.value}, ${v*v}>;
  var<workgroup> tileK: array<${De.type.value}, ${v*v}>;
  ${he.registerUniforms(ut).declareVariables(...Ie,...gt)}
  ${he.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;
   ${u&&$?`
    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;
            `}
    ${$?"let presentValueOffset = headIdx * uniforms.N * uniforms.K + n;":""}
   var value = ${De.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;
        ${u&&$?`
        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];
      `}
        ${$?"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:`${u!==void 0};${n.outputCount}`,inputDependencies:de},getRunData:()=>({outputs:we,dispatchGroup:oe,programUniforms:te}),getShaderSource:be}},vo=(n,i,s,u,c,f,d,x,k,$,H)=>{let q=n.outputCount,v=$.kvNumHeads!==void 0||q>1?$.pastSequenceLength:0,oe=v+$.kvSequenceLength,te=$.kvNumHeads===void 0&&q>1&&d?[i,s,d]:[i,s];k&&te.push(k);let de=n.compute(qu(n,i,s,q>1?d:void 0,k,$,H,v),{inputs:te,outputs:$.kvNumHeads===void 0&&q>1?[-1,1]:[-1]})[0];n.compute(Aa(n,de,$.batchSize*$.numHeads*$.sequenceLength,oe),{inputs:[de],outputs:[]});let we=$.kvNumHeads===void 0&&q>1&&x?[de,u,x]:[de,u];n.compute(Ku(n,de,u,q>1&&x?x:void 0,$,v),{inputs:we,outputs:$.kvNumHeads===void 0&&q>1?[0,2]:[0]})},Xu=(n,i)=>{let s=[i.batchSize,i.numHeads,i.sequenceLength,i.headSize],u=i.sequenceLength,c=i.inputHiddenSize,f=i.headSize,d=12,x={x:Math.ceil(i.headSize/d),y:Math.ceil(i.sequenceLength/d),z:i.batchSize*i.numHeads},k=[n.inputs[0],n.inputs[1],n.inputs[2]],$=[{type:12,data:u},{type:12,data:c},{type:12,data:f},{type:12,data:i.numHeads},{type:12,data:i.headSize},{type:12,data:i.hiddenSize},{type:12,data:i.hiddenSize+i.hiddenSize+i.vHiddenSize}],H=q=>{let v=Gt("output_q",k[0].dataType,s),oe=Gt("output_k",k[0].dataType,s),te=Gt("output_v",k[0].dataType,s),de=_t("input",k[0].dataType,k[0].dims),we=_t("weight",k[1].dataType,k[1].dims),be=_t("bias",k[2].dataType,k[2].dims),he=de.type.storage,De=[{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}>;
  ${q.registerUniforms(De).declareVariables(de,we,be,v,oe,te)}
  ${q.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 n.compute({name:"AttentionPrepare",shaderCache:{inputDependencies:["type","type","type"]},getRunData:()=>({outputs:[{dims:s,dataType:n.inputs[0].dataType,gpuDataType:0},{dims:s,dataType:n.inputs[0].dataType,gpuDataType:0},{dims:s,dataType:n.inputs[0].dataType,gpuDataType:0}],dispatchGroup:x,programUniforms:$}),getShaderSource:H},{inputs:k,outputs:[-1,-1,-1]})},Qu=(n,i)=>{let s=Hu(n.inputs,i),[u,c,f]=Xu(n,s);return vo(n,u,c,f,n.inputs[4],void 0,void 0,void 0,n.inputs[5],s,i)}}),Yu,Zu,Ju,ec,tc=h(()=>{Z(),Zt(),Jt(),_r(),ar(),Yu=(n,i)=>{if(!n||n.length!==5)throw new Error("BatchNormalization requires 5 inputs");let s=(u,c,f)=>{let d=c.length;if(d!==u.length)throw new Error(`${f}: num dimensions != ${d}`);c.forEach((x,k)=>{if(x!==u[k])throw new Error(`${f}: dim[${k}] do not match`)})};if(n[0].dims.length>1){let u=i.format==="NHWC"?i.spatial?n[0].dims.slice(-1):n[0].dims.slice(-1).concat(n[0].dims.slice(1,n[0].dims.length-1)):n[0].dims.slice(1,i.spatial?2:void 0);s(n[1].dims,u,"Invalid input scale"),s(n[2].dims,u,"Invalid input B"),s(n[3].dims,u,"Invalid input mean"),s(n[4].dims,u,"Invalid input var")}else s(n[1].dims,[1],"Invalid input scale"),s(n[2].dims,[1],"Invalid input B"),s(n[3].dims,[1],"Invalid input mean"),s(n[4].dims,[1],"Invalid input var")},Zu=(n,i)=>{let{epsilon:s,spatial:u,format:c}=i,f=n[0].dims,d=u?vr(f[f.length-1]):1,x=c==="NHWC"&&f.length>1?d:1,k=ct.size(f)/d,$=u,H=$?f.length:f,q=_t("x",n[0].dataType,n[0].dims,d),v=_t("scale",n[1].dataType,n[1].dims,x),oe=_t("bias",n[2].dataType,n[2].dims,x),te=_t("inputMean",n[3].dataType,n[3].dims,x),de=_t("inputVar",n[4].dataType,n[4].dims,x),we=Gt("y",n[0].dataType,H,d),be=()=>{let De="";if(u)De=`let cOffset = ${f.length===1?"0u":c==="NHWC"?`outputIndices[${f.length-1}] / ${d}`:"outputIndices[1]"};`;else if(c==="NCHW")De=`
            ${we.indicesSet("outputIndices","0","0")}
            let cOffset = ${we.indicesToOffset("outputIndices")};`;else{De=`var cIndices = ${v.type.indices}(0);
                       cIndices[0] = outputIndices[${f.length-1}];`;for(let Ae=1;Ae<v.rank;Ae++)De+=`cIndices[${Ae}] = outputIndices[${Ae}];`;De+=`let cOffset = ${v.indicesToOffset("cIndices")};`}return De},he=De=>`
  const epsilon = ${s};
  ${De.registerUniform("outputSize","u32").declareVariables(q,v,oe,te,de,we)}
  ${De.mainStart()}
  ${De.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}
    var outputIndices = ${we.offsetToIndices(`global_idx * ${d}`)};
    ${be()}
    let scale = ${v.getByOffset("cOffset")};
    let bias = ${oe.getByOffset("cOffset")};
    let inputMean = ${te.getByOffset("cOffset")};
    let inputVar = ${de.getByOffset("cOffset")};
    let x = ${q.getByOffset("global_idx")};
    let value = (x - inputMean) * inverseSqrt(inputVar + epsilon) * scale + bias;
    ${we.setByOffset("global_idx","value")}
  }`;return{name:"BatchNormalization",shaderCache:{hint:`${i.epsilon}_${i.format}_${u}_${d}`,inputDependencies:$?["rank","type","type","type","type"]:void 0},getShaderSource:he,getRunData:()=>({outputs:[{dims:n[0].dims,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(k/64)},programUniforms:$?[{type:12,data:k},...At(f)]:[{type:12,data:k}]})}},Ju=n=>qt(n),ec=(n,i)=>{let{inputs:s,outputCount:u}=n,c=Ju({...i,outputCount:u});if(N.webgpu.validateInputContent&&Yu(s,c),i.trainingMode)throw new Error("BatchNormalization trainingMode is not supported yet.");n.compute(Zu(s,c))}}),rc,nc,Ia,of=h(()=>{Jt(),ar(),rc=n=>{if(n[0].dims.length!==3)throw new Error("input should have 3 dimensions");if(![320,640,1280].includes(n[0].dims[2]))throw new Error("number of channels should be 320, 640 or 1280");if(n[1].dims.length!==1)throw new Error("bias is expected to have 1 dimensions");if(n[0].dims[2]!==n[1].dims[0])throw new Error("last dimension of input and bias are not the same")},nc=n=>{let i=n[0].dims,s=n[0].dims[2],u=ct.size(i)/4,c=n[0].dataType,f=_t("input",c,i,4),d=_t("bias",c,[s],4),x=_t("residual",c,i,4),k=Gt("output",c,i,4);return{name:"BiasAdd",getRunData:()=>({outputs:[{dims:i,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(u/64)}}),getShaderSource:$=>`
  const channels = ${s}u / 4;
  ${$.declareVariables(f,d,x,k)}

  ${$.mainStart()}
    ${$.guardAgainstOutOfBoundsWorkgroupSizes(u)}
    let value = ${f.getByOffset("global_idx")}
      + ${d.getByOffset("global_idx % channels")} + ${x.getByOffset("global_idx")};
    ${k.setByOffset("global_idx","value")}
  }`}},Ia=n=>{rc(n.inputs),n.compute(nc(n.inputs))}}),ic,br,oc,sc,Fa,ac,lc,Oa,uc,cc,Ds,dc,pc,fc,za,hc,bo,mc,Ls,gc,Da,_c,wc,yc,La,vc,bc,Ra,xc,Mc,Ba,Tc,kc,Na,Sc,ja,Ua,Va,Wa,Ec,Cc,Ga,Pc,$c,Ac,Ha=h(()=>{Zt(),Jt(),_r(),ar(),ic=(n,i,s,u,c,f)=>{let d=Math.ceil(i/4),x="";typeof c=="string"?x=`${c}(a)`:x=c("a");let k=_t("inputData",s,[d],4),$=Gt("outputData",u,[d],4);return`
      ${n.registerUniform("vec_size","u32").declareVariables(k,$)}

  ${f??""}

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

    let a = ${k.getByOffset("global_idx")};
    ${$.setByOffset("global_idx",x)}
  }`},br=(n,i,s,u,c,f=n.dataType)=>({name:i,shaderCache:{hint:c,inputDependencies:["type"]},getShaderSource:d=>ic(d,ct.size(n.dims),n.dataType,f,s,u),getRunData:d=>({outputs:[{dims:n.dims,dataType:f}],dispatchGroup:{x:Math.ceil(ct.size(d[0].dims)/64/4)},programUniforms:[{type:12,data:Math.ceil(ct.size(n.dims)/4)}]})}),oc=n=>{n.compute(br(n.inputs[0],"Abs","abs"))},sc=n=>{n.compute(br(n.inputs[0],"Acos","acos"))},Fa=n=>{n.compute(br(n.inputs[0],"Acosh","acosh"))},ac=n=>{n.compute(br(n.inputs[0],"Asin","asin"))},lc=n=>{n.compute(br(n.inputs[0],"Asinh","asinh"))},Oa=n=>{n.compute(br(n.inputs[0],"Atan","atan"))},uc=n=>{n.compute(br(n.inputs[0],"Atanh","atanh"))},cc=n=>qt(n),Ds=(n,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): ${i.to}`)}n.compute(br(n.inputs[0],"Cast",s,void 0,i.cacheKey,i.to))},dc=n=>{let i=n.length>=2&&n[1].data!==0?n[1].getFloat32Array()[0]:cn,s=n.length>=3&&n[2].data!==0?n[2].getFloat32Array()[0]:On;return qt({min:i,max:s})},pc=(n,i)=>{let s=n.inputs.length===1?i:dc(n.inputs),u=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"Clip",c=>`clamp(${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]})},fc=n=>{n.compute(br(n.inputs[0],"Ceil","ceil"))},za=n=>{n.compute(br(n.inputs[0],"Cos","cos"))},hc=n=>{n.compute(br(n.inputs[0],"Cosh","cosh"))},bo=n=>qt(n),mc=(n,i)=>{let s=Er(n.inputs[0].dataType);n.compute(br(n.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))},Ls=(n="f32")=>`
const r0: ${n} = 0.3275911;
const r1: ${n} = 0.254829592;
const r2: ${n} = -0.284496736;
const r3: ${n} = 1.421413741;
const r4: ${n} = -1.453152027;
const r5: ${n} = 1.061405429;

fn erf_vf32(v: vec4<${n}>) -> vec4<${n}> {
  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));
}`,gc=n=>{let i=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"Erf",s=>`erf_vf32(${s})`,Ls(i)))},Da=n=>{n.compute(br(n.inputs[0],"Exp","exp"))},_c=n=>{n.compute(br(n.inputs[0],"Floor","floor"))},wc=n=>{let i=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"Gelu",s=>`0.5 * ${s} * (1.0 + erf_vf32(${s} * 0.7071067811865475))`,Ls(i)))},yc=(n,i)=>{let s=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"LeakyRelu",u=>`select(leaky_relu_alpha_ * ${u}, ${u}, ${u} >= vec4<${s}>(0.0))`,`const leaky_relu_alpha_ = ${s}(${i.alpha});`,i.cacheKey))},La=n=>{n.compute(br(n.inputs[0],"Not",i=>`!${i}`))},vc=n=>{n.compute(br(n.inputs[0],"Neg",i=>`-${i}`))},bc=n=>{n.compute(br(n.inputs[0],"Reciprocal",i=>`1.0/${i}`))},Ra=n=>{let i=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"Relu",s=>`select(vec4<${i}>(0.0), ${s}, ${s} > vec4<${i}>(0.0))`))},xc=n=>{n.compute(br(n.inputs[0],"Sigmoid",i=>`(1.0 / (1.0 + exp(-${i})))`))},Mc=n=>qt(n),Ba=(n,i)=>{let s=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"HardSigmoid",u=>`max(vec4<${s}>(0.0), min(vec4<${s}>(1.0), ${i.alpha} * ${u} + vec4<${s}>(${i.beta})))`,void 0,i.cacheKey))},Tc=n=>{n.compute(br(n.inputs[0],"Sin","sin"))},kc=n=>{n.compute(br(n.inputs[0],"Sinh","sinh"))},Na=n=>{n.compute(br(n.inputs[0],"Sqrt","sqrt"))},Sc=n=>{n.compute(br(n.inputs[0],"Tan","tan"))},ja=n=>`sign(${n}) * (1 - exp(-2 * abs(${n}))) / (1 + exp(-2 * abs(${n})))`,Ua=n=>{n.compute(br(n.inputs[0],"Tanh",ja))},Va=(n="f32")=>`
const fast_gelu_a: ${n} = 0.5;
const fast_gelu_b: ${n} = 0.7978845608028654;
const fast_gelu_c: ${n} = 0.035677408136300125;

fn tanh_v(v: vec4<${n}>) -> vec4<${n}> {
  return ${ja("v")};
}
`,Wa=n=>`(fast_gelu_a + fast_gelu_a * tanh_v(${n} * (fast_gelu_c * ${n} * ${n} + fast_gelu_b))) * ${n}`,Ec=n=>{let i=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"FastGelu",Wa,Va(i),void 0,n.inputs[0].dataType))},Cc=(n,i)=>{let s=Er(n.inputs[0].dataType);return n.compute(br(n.inputs[0],"ThresholdedRelu",u=>`select(vec4<${s}>(0.0), ${u}, ${u} > thresholded_relu_alpha_)`,`const thresholded_relu_alpha_ = vec4<${s}>(${i.alpha});`,i.cacheKey)),0},Ga=n=>{n.compute(br(n.inputs[0],"Log","log"))},Pc=(n,i)=>`
const alpha = vec4<${n}>(${i});
const one = ${n}(1.0);
const zero = ${n}(0.0);

fn quick_gelu_impl(x: vec4<${n}>) -> vec4<${n}> {
  let v = x *alpha;
  var x1 : vec4<${n}>;
  for (var i = 0; i < 4; i = i + 1) {
    if (v[i] >= zero) {
      x1[i] = one / (one + exp(-v[i]));
    } else {
      x1[i] = one - one / (one + exp(v[i]));
    }
  }
  return x * x1;
}
`,$c=n=>`quick_gelu_impl(${n})`,Ac=(n,i)=>{let s=Er(n.inputs[0].dataType);n.compute(br(n.inputs[0],"QuickGelu",$c,Pc(s,i.alpha),i.cacheKey,n.inputs[0].dataType))}}),qa,Ic,Fc,Oc=h(()=>{Jt(),ar(),Ha(),qa=n=>{if(n[0].dims.length!==3)throw new Error("input should have 3 dimensions");if(![2560,5120,10240].includes(n[0].dims[2]))throw new Error("hidden state should be 2560, 5120 or 10240");if(n[1].dims.length!==1)throw new Error("bias is expected to have 1 dimensions");if(n[0].dims[2]!==n[1].dims[0])throw new Error("last dimension of input and bias are not the same")},Ic=n=>{let i=n[0].dims.slice();i[2]=i[2]/2;let s=_t("input",n[0].dataType,n[0].dims,4),u=_t("bias",n[0].dataType,[n[0].dims[2]],4),c=Gt("output",n[0].dataType,i,4),f=ct.size(i)/4,d=Sr(n[0].dataType);return{name:"BiasSplitGelu",getRunData:()=>({outputs:[{dims:i,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(f/64)}}),getShaderSource:x=>`
  const M_SQRT2 = sqrt(2.0);
  const halfChannels = ${n[0].dims[2]/4/2}u;

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

  ${Ls(d)}

  ${x.mainStart()}
    ${x.guardAgainstOutOfBoundsWorkgroupSizes(f)}
    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);

    ${c.setByOffset("global_idx","valueLeft * geluRight")}
  }`}},Fc=n=>{qa(n.inputs),n.compute(Ic(n.inputs))}}),zc,Dc,Zn,Lc,Rc,Ka,Bc,Nc,jc,Uc,Vc,Wc,Xa,sf=h(()=>{Zt(),Jt(),ar(),zc=(n,i,s,u,c,f,d,x,k,$,H,q)=>{let v,oe;typeof x=="string"?v=oe=(he,De)=>`${x}((${he}),(${De}))`:typeof x=="function"?v=oe=x:(v=x.scalar,oe=x.vector);let te=Gt("outputData",H,u.length,4),de=_t("aData",k,i.length,4),we=_t("bData",$,s.length,4),be;if(c)if(f){let he=ct.size(i)===1,De=ct.size(s)===1,Ae=i.length>0&&i[i.length-1]%4===0,Ie=s.length>0&&s[s.length-1]%4===0;he||De?be=te.setByOffset("global_idx",oe(he?`${de.type.value}(${de.getByOffset("0")}.x)`:de.getByOffset("global_idx"),De?`${we.type.value}(${we.getByOffset("0")}.x)`:we.getByOffset("global_idx"))):be=`
            let outputIndices = ${te.offsetToIndices("global_idx * 4u")};
            let offsetA = ${de.broadcastedIndicesToOffset("outputIndices",te)};
            let offsetB = ${we.broadcastedIndicesToOffset("outputIndices",te)};
            ${te.setByOffset("global_idx",oe(d||Ae?de.getByOffset("offsetA / 4u"):`${de.type.value}(${de.getByOffset("offsetA / 4u")}[offsetA % 4u])`,d||Ie?we.getByOffset("offsetB / 4u"):`${we.type.value}(${we.getByOffset("offsetB / 4u")}[offsetB % 4u])`))}
          `}else be=te.setByOffset("global_idx",oe(de.getByOffset("global_idx"),we.getByOffset("global_idx")));else{if(!f)throw new Error("no necessary to use scalar implementation for element-wise binary op implementation.");let he=(De,Ae,Ie="")=>{let gt=`aData[indexA${Ae}][componentA${Ae}]`,ut=`bData[indexB${Ae}][componentB${Ae}]`;return`
            let outputIndices${Ae} = ${te.offsetToIndices(`global_idx * 4u + ${Ae}u`)};
            let offsetA${Ae} = ${de.broadcastedIndicesToOffset(`outputIndices${Ae}`,te)};
            let offsetB${Ae} = ${we.broadcastedIndicesToOffset(`outputIndices${Ae}`,te)};
            let indexA${Ae} = offsetA${Ae} / 4u;
            let indexB${Ae} = offsetB${Ae} / 4u;
            let componentA${Ae} = offsetA${Ae} % 4u;
            let componentB${Ae} = offsetB${Ae} % 4u;
            ${De}[${Ae}] = ${Ie}(${v(gt,ut)});
          `};H===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`
        ${n.registerUniform("vec_size","u32").declareVariables(de,we,te)}

        ${q??""}

        ${n.mainStart()}
        ${n.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.vec_size")}
        ${be}
      }`},Dc=(n,i,s,u,c,f,d=s.dataType)=>{let x=!ct.areEqual(s.dims,u.dims),k=s.dims,$=ct.size(s.dims),H=!1,q=!1,v=[x];if(x){let oe=gn.calcShape(s.dims,u.dims,!1);if(!oe)throw new Error("Can't perform binary op on the given tensors");k=oe,$=ct.size(k);let te=ct.size(s.dims)===1,de=ct.size(u.dims)===1,we=s.dims.length>0&&s.dims[s.dims.length-1]%4===0,be=u.dims.length>0&&u.dims[u.dims.length-1]%4===0;v.push(te),v.push(de),v.push(we),v.push(be);let he=1;for(let De=1;De<k.length;De++){let Ae=s.dims[s.dims.length-De]??1,Ie=u.dims[u.dims.length-De]??1;if(Ae===Ie)he*=Ae;else break}he%4===0?(q=!0,H=!0):(te||de||we||be)&&(H=!0)}else H=!0;return v.push(H),{name:n,shaderCache:{hint:i+v.map(oe=>oe.toString()).join("_"),inputDependencies:["rank","rank"]},getShaderSource:oe=>zc(oe,s.dims,u.dims,k,H,x,q,c,s.dataType,u.dataType,d,f),getRunData:()=>({outputs:[{dims:k,dataType:d}],dispatchGroup:{x:Math.ceil($/64/4)},programUniforms:[{type:12,data:Math.ceil(ct.size(k)/4)},...At(s.dims,u.dims,k)]})}},Zn=(n,i,s,u,c,f)=>{n.compute(Dc(i,c??"",n.inputs[0],n.inputs[1],s,u,f))},Lc=n=>{Zn(n,"Add",(i,s)=>`${i}+${s}`)},Rc=n=>{Zn(n,"Div",(i,s)=>`${i}/${s}`)},Ka=n=>{Zn(n,"Equal",{scalar:(i,s)=>`u32(${i}==${s})`,vector:(i,s)=>`vec4<u32>(${i}==${s})`},void 0,void 0,9)},Bc=n=>{Zn(n,"Mul",(i,s)=>`${i}*${s}`)},Nc=n=>{let i=_t("input",n.inputs[0].dataType,n.inputs[0].dims).type.value;Zn(n,"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));
    }
      `)},jc=n=>{Zn(n,"Sub",(i,s)=>`${i}-${s}`)},Uc=n=>{Zn(n,"Greater",{scalar:(i,s)=>`u32(${i}>${s})`,vector:(i,s)=>`vec4<u32>(${i}>${s})`},void 0,void 0,9)},Vc=n=>{Zn(n,"Less",{scalar:(i,s)=>`u32(${i}<${s})`,vector:(i,s)=>`vec4<u32>(${i}<${s})`},void 0,void 0,9)},Wc=n=>{Zn(n,"GreaterOrEqual",{scalar:(i,s)=>`u32(${i}>=${s})`,vector:(i,s)=>`vec4<u32>(${i}>=${s})`},void 0,void 0,9)},Xa=n=>{Zn(n,"LessOrEqual",{scalar:(i,s)=>`u32(${i}<=${s})`,vector:(i,s)=>`vec4<u32>(${i}<=${s})`},void 0,void 0,9)}}),Gc,Qa,Hc,qc,Ui,Kc,af=h(()=>{Zt(),Jt(),_r(),ar(),Gc=(n,i)=>{if(!n||n.length<1)throw new Error("too few inputs");let s=0,u=n[s],c=u.dataType,f=u.dims.length;n.forEach((d,x)=>{if(x!==s){if(d.dataType!==c)throw new Error("input tensors should be one type");if(d.dims.length!==f)throw new Error("input tensors should have the same shape");d.dims.forEach((k,$)=>{if($!==i&&k!==u.dims[$])throw new Error("non concat dimensions must match")})}})},Qa=(n,i)=>`
  fn calculateInputIndex(index: u32) -> u32 {
    let sizeInConcatAxis = array<u32, ${n}u>(${i});
    for (var i: u32 = 0u; i < ${n}; i += 1u ) {
      if (index < sizeInConcatAxis[i]) {
        return i;
      }
    }
    return ${n}u;
  }`,Hc=(n,i)=>{let s=n.length,u=[];for(let c=0;c<s;++c){let f=i.setByOffset("global_idx",n[c].getByIndices("indices"));s===1?u.push(f):c===0?u.push(`if (inputIndex == ${c}u) { ${f} }`):c===s-1?u.push(`else { ${f} }`):u.push(`else if (inputIndex == ${c}) { ${f} }`)}return u.join(`
`)},qc=(n,i,s,u)=>{let c=ct.size(s),f=new Array(n.length),d=new Array(n.length),x=0,k=[],$=[],H=[{type:12,data:c}];for(let de=0;de<n.length;++de)x+=n[de].dims[i],f[de]=x,$.push(n[de].dims.length),d[de]=_t(`input${de}`,u,$[de]),k.push("rank"),H.push({type:12,data:f[de]});for(let de=0;de<n.length;++de)H.push(...At(n[de].dims));H.push(...At(s));let q=Gt("output",u,s.length),v=q.indicesGet("indices",i),oe=Array.from(Array(f.length).keys()).map(de=>`uniforms.sizeInConcatAxis${de}`).join(","),te=de=>`

  ${(()=>{de.registerUniform("outputSize","u32");for(let we=0;we<n.length;we++)de.registerUniform(`sizeInConcatAxis${we}`,"u32");return de.declareVariables(...d,q)})()}

  ${Qa(f.length,oe)}

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

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

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

    ${Hc(d,q)}
  }`;return{name:"Concat",shaderCache:{hint:`${i}`,inputDependencies:k},getRunData:()=>({outputs:[{dims:s,dataType:u}],dispatchGroup:{x:Math.ceil(c/64)},programUniforms:H}),getShaderSource:te}},Ui=(n,i)=>{let s=n.inputs,u=s[0].dims,c=ct.normalizeAxis(i.axis,u.length);Gc(s,c);let f=u.slice();f[c]=s.reduce((x,k)=>x+(k.dims.length>c?k.dims[c]:0),0);let d=s.filter(x=>ct.size(x.dims)>0);n.compute(qc(d,c,f,s[0].dataType),{inputs:d})},Kc=n=>qt({axis:n.axis})}),Vi,Wi,Ei,Ya,Gi=h(()=>{Zt(),Jt(),Vi=(n,i,s="f32")=>{switch(n.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 ${n.activation}`)}},Wi=(n,i)=>{n.activation==="Clip"?i.push({type:1,data:n.clipMax},{type:1,data:n.clipMin}):n.activation==="HardSigmoid"?i.push({type:1,data:n.alpha},{type:1,data:n.beta}):n.activation==="LeakyRelu"&&i.push({type:1,data:n.alpha})},Ei=(n,i)=>{n.activation==="Clip"?i.push({name:"clip_max",type:"f32"},{name:"clip_min",type:"f32"}):n.activation==="HardSigmoid"?i.push({name:"alpha",type:"f32"},{name:"beta",type:"f32"}):n.activation==="LeakyRelu"&&i.push({name:"alpha",type:"f32"})},Ya=n=>{let i=(n==null?void 0:n.activation)||"";if(i==="HardSigmoid"){let[s,u]=(n==null?void 0:n.activation_params)||[.2,.5];return{activation:i,alpha:s,beta:u}}else if(i==="Clip"){let[s,u]=(n==null?void 0:n.activation_params)||[cn,On];return{activation:i,clipMax:u,clipMin:s}}else if(i==="LeakyRelu"){let[s]=(n==null?void 0:n.activation_params)||[.01];return{activation:i,alpha:s}}return{activation:i}}}),vn,Za,xo=h(()=>{vn=(n,i)=>{switch(n){case 1:return i;case 2:return`vec2<${i}>`;case 3:return`vec3<${i}>`;case 4:return`vec4<${i}>`;default:throw new Error(`${n}-component is not supported.`)}},Za=n=>`
      ${n?"value = value + getBiasByOutputCoords(coords);":""}
      `}),Ja,Xc=h(()=>{Ja=n=>`
fn getIndexFromCoords4D(coords : vec4<i32>, shape : vec4<i32>) -> i32 {
  return dot(coords, vec4<i32>(
      shape.y * shape.z * shape.w, shape.z * shape.w, shape.w, 1));
}
fn getOutputIndexFromCoords(coords : vec4<i32>) -> i32 {
  return dot(coords, vec4<i32>(
    i32(${n}.x), i32(${n}.y), i32(${n}.z), 1));
}
`}),Qc,qo,Rs,el,Yc,Bs,Ns,tl,js=h(()=>{Zt(),Jt(),ar(),Gi(),xo(),Qc=(n,i)=>n?`
        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":""});
        `,qo=(n,i)=>n?`
        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];
          ${i===3?"":"acc[i] = BCached3 * ACached.w + acc[i];"}
        }`,Rs=(n,i,s="f32",u,c=!1,f=32,d=!1,x=32)=>{let k=i[1]*n[1],$=i[0]*n[0],H=c?k:f,q=c?f:k,v=H/i[0],oe=f/i[1];if(!((c&&v===4&&n[1]===4||!c&&(v===3||v===4))&&H%i[0]===0&&f%i[1]===0&&n[0]===4))throw new Error(`If transposeA ${c} is true, innerElementSize ${v} and workPerThread[1] ${n[1]} must be 4.
      Otherwise, innerElementSize ${v} must be 3 or 4.
  tileAWidth ${H} must be divisible by workgroupSize[0]${i[0]}. tileInner ${f} must be divisible by workgroupSize[1] ${i[1]}. colPerThread ${n[0]} must be 4.`);return`
var<workgroup> mm_Asub: array<array<vec${v}<${s}>, ${H/v}>, ${q}>;
var<workgroup> mm_Bsub: array<array<vec4<${s}>, ${$/n[0]}>, ${f}>;

const rowPerThread = ${n[1]};
const colPerThread = ${n[0]};
const innerElementSize = ${v};
const tileInner = ${f};

@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) * ${k};

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

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

  // Loop over shared dimension.
  let tileRowB = localRow * ${oe};
  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 < ${oe}; innerRow = innerRow + 1) {
          let inputRow = tileRowB + innerRow;
          let inputCol = tileCol;
          mm_Bsub[inputRow][inputCol] = mm_readB(batch, kStart + inputRow, globalCol${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];"}

          ${qo(c,v)}
      }

      workgroupBarrier();
  }

  for (var innerRow = 0; innerRow < rowPerThread; innerRow = innerRow + 1) {
      mm_write(batch, globalRow + innerRow, globalCol, acc[innerRow]);
  }
}`},el=(n,i)=>n?`
            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":""});
            `,Yc=n=>n?"let ACached = mm_Asub[k][tileRow + innerRow];":"let ACached = mm_Asub[tileRow + innerRow][k];",Bs=(n,i,s="f32",u,c=!1,f=32,d=!1,x=32,k=!1)=>{let $=n[1]*i[1],H=n[0]*i[0],q=c?$:f,v=c?f:$;if(!(v%i[1]===0&&q%i[0]===0&&f%i[1]===0))throw new Error(`tileAHight ${v} must be divisible by workgroupSize[1]${i[1]}, tileAWidth ${q} must be divisible by workgroupSize[0]${i[0]}, tileInner ${f} must be divisible by workgroupSize[1]${i[1]}`);let oe=v/i[1],te=q/i[0],de=f/i[1],we=k?`
    let localRow = i32(localId.y);
    let localCol = i32(localId.x);
    let globalRowStart = i32(workgroupId.y) * ${$};
    let globalColStart = i32(workgroupId.x) * ${H};

    // 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 < ${q}; inputCol = inputCol + ${i[0]}) {
          ${el(c,u)}
        }
      }
      // Load one tile of B into local memory.
      for (var inputRow = localRow; inputRow < ${f}; inputRow = inputRow + ${i[1]}) {
            for (var inputCol = localCol; inputCol < ${H}; 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) * ${$};

let tileRowA = i32(localId.y) * ${oe};
let tileColA = i32(localId.x) * ${te};
let tileRowB = i32(localId.y) * ${de};
// 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 < ${oe}; innerRow = innerRow + 1) {
    for (var innerCol = 0; innerCol < ${te}; innerCol = innerCol + 1) {
      let inputRow = tileRowA + innerRow;
      let inputCol = tileColA + innerCol;
      ${el(c,u)}
    }
  }

  // Load one tile of B into local memory.
  for (var innerRow = 0; innerRow < ${de}; innerRow = innerRow + 1) {
    for (var innerCol = 0; innerCol < colPerThread; innerCol = innerCol + 1) {
      let inputRow = tileRowB + innerRow;
      let inputCol = tileCol + innerCol;
      mm_Bsub[inputRow][inputCol] = mm_readB(batch,
        kStart + inputRow,
        globalCol + innerCol${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) {
      ${Yc(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}, ${q}>, ${v}>;
  var<workgroup> mm_Bsub : array<array<${s}, ${H}>, ${f}>;
  const rowPerThread = ${n[1]};
  const colPerThread = ${n[0]};
  const tileInner = ${f};

@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(x/f)}`:"(uniforms.dim_inner - 1) / tileInner + 1"};
    var kStart = ${d?`i32(globalId.z) * ${x}`:"0"};

    var acc : array<array<${s}, colPerThread>, rowPerThread>;
    ${we}
  }
`},Ns=(n,i,s,u,c,f=!1)=>{let[d,x,k]=c,[$,H,q,v]=u,oe=wo(d,k),te=wo(x,k),de=Sr(u[0].type.tensor),we=()=>{let he=H.rank,De=$.rank,Ae=`var aIndices: ${H.type.indices};`;for(let Ie=he-2-1,gt=De-1;Ie>=0;Ie--,gt--)Ae+=`
aIndices[${Ie}] = ${De>1?`batchIndices[${gt}]`:"batchIndices"};`;return oe.forEach(Ie=>{Ae+=`
aIndices[${Ie}] = 0;`}),Ae+=`
aIndices[${he-2}] = u32(row);
                   aIndices[${he-1}] = u32(colIn);`,Ae},be=()=>{let he=q.rank,De=$.rank,Ae=`var bIndices: ${q.type.indices};`;for(let Ie=he-2-1,gt=De-1;Ie>=0;Ie--,gt--)Ae+=`
bIndices[${Ie}] = ${De>1?`batchIndices[${gt}]`:"batchIndices"};`;return te.forEach(Ie=>{Ae+=`
bIndices[${Ie}] = 0;`}),Ae+=`
bIndices[${he-2}] = u32(row);
                   bIndices[${he-1}] = u32(colIn);`,Ae};return`
    fn mm_readA(batch: i32, row: i32, colIn: i32, batchIndices: ${$.type.indices}) -> ${vn(n,de)} {
      var value = ${vn(n,de)}(0.0);
      let col = colIn * ${n};
      if(row < uniforms.dim_a_outer && col < uniforms.dim_inner)
      {
        ${we()}
        value = ${H.getByIndices("aIndices")};
      }
      return value;
    }

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

    fn mm_write(batch: i32, row: i32, colIn: i32, valueIn: ${vn(n,de)}) {
      let col = colIn * ${n};
      if (row < uniforms.dim_a_outer && col < uniforms.dim_b_outer) {
        var value = valueIn;
        let coords = vec3<i32>(batch, row, colIn);
        ${i?`value = value + ${f?"bias[colIn]":`${vn(n,de)}(bias[row])`};`:""}
        ${s}
        ${v.setByIndices("vec3<u32>(coords)","value")}
      }
    }
    `},tl=(n,i,s,u,c=!1)=>{let f=n[0].dims,d=n[1].dims,x=f.slice(0,-2),k=d.slice(0,-2),$=u?u.slice(0,-2):s.slice(0,-2),H=ct.size($),q=f[f.length-2],v=f[f.length-1],oe=d[d.length-1],te=v%4===0&&oe%4===0,de=q<=8?[4,1,1]:[4,4,1],we=[8,8,1],be=[Math.ceil(oe/we[0]/de[0]),Math.ceil(q/we[1]/de[1]),Math.ceil(H/we[2]/de[2])],he=te?4:1,De=[...x,q,v/he],Ae=De.length,Ie=[...k,v,oe/he],gt=Ie.length,ut=[H,q,oe/he],vt=[{type:6,data:q},{type:6,data:oe},{type:6,data:v}];Wi(i,vt),vt.push(...At($,De,Ie));let Dt=["rank","rank"],Rt=n.length>2;Rt&&(vt.push(...At(n[2].dims)),Dt.push("rank")),vt.push(...At(ut));let gr=Mr=>{let ir=$.length,Fr=ma("batchDims",n[0].dataType,ir,1),Zr=Sr(n[0].dataType),hr=_t("a",n[0].dataType,Ae,he),Hr=_t("b",n[1].dataType,gt,he),Nt=Gt("result",n[0].dataType,ut.length,he),er=[hr,Hr];if(Rt){let Wr=c?he:1;er.push(_t("bias",n[2].dataType,n[2].dims.length,Wr))}let yr=[{name:"dim_a_outer",type:"i32"},{name:"dim_b_outer",type:"i32"},{name:"dim_inner",type:"i32"}];Ei(i,yr);let ot=Sr(Nt.type.tensor),Vt=Vi(i,Nt.type.value,ot),nr=Ns(he,Rt,Vt,[Fr,hr,Hr,Nt],[x,k,$],c);return`
  ${Mr.registerUniforms(yr).registerInternalVariables(Fr).declareVariables(...er,Nt)}
  ${nr}
  ${te?Rs(de,we,Zr,Fr):Bs(de,we,Zr,Fr)}
                   `};return{name:"MatMul",shaderCache:{hint:`${de};${i.activation};${te};${c}`,inputDependencies:Dt},getRunData:()=>({outputs:[{dims:s,dataType:n[0].dataType}],dispatchGroup:{x:be[0],y:be[1],z:be[2]},programUniforms:vt}),getShaderSource:gr}}}),Zc,lf,uf=h(()=>{Zt(),jn(),ar(),Gi(),xo(),Xc(),js(),Zc=(n,i,s,u,c=!1,f,d=4,x=4,k=4,$="f32")=>{let H=Dt=>{switch(Dt){case 1:return"resData = x[xIndex];";case 3:return`resData = vec3<${$}>(x[xIndex], x[xIndex + 1], x[xIndex + 2]);`;case 4:return"resData = x[xIndex / 4];";default:throw new Error(`innerElementSize ${Dt} is not supported.`)}},q=Dt=>{switch(Dt){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 ${Dt} is not supported.`)}},v=n?`
    let coord = vec4<i32>(batch, xRow, xCol, xCh);
    `:`
    let coord = vec4<i32>(batch, xCh, xRow, xCol);
    `,oe=n?`
    let coords = vec4<i32>(
      batch,
      row / outWidth,
      row % outWidth,
      col);
    `:`
    let coords = vec4<i32>(
      batch,
      row,
      col / outWidth,
      col % outWidth);
    `,te=n?"i32(uniforms.x_shape[1])":"i32(uniforms.x_shape[2])",de=n?"i32(uniforms.x_shape[2])":"i32(uniforms.x_shape[3])",we=n?"row":"col",be=n?"col":"row",he=`
    let inChannels = i32(uniforms.w_shape[2]);
    let outWidth = ${n?"i32(uniforms.result_shape[2])":"i32(uniforms.result_shape[3])"};
    let outRow = ${we} / outWidth;
    let outCol = ${we} % 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 = ${vn(d,$)}(0.0);
    // The bounds checking is always needed since we use it to pad zero for
    // the 'same' padding type.
    if (xRow >= 0 && xRow < ${te} && xCol >= 0 && xCol < ${de}) {
      ${v}
      let xIndex = getIndexFromCoords4D(coord, vec4<i32>(uniforms.x_shape));
      ${H(d)}
    }
    return resData;`,De=n?i&&u?`
    let col = colIn * ${d};
    ${he}`:`
    let col = colIn * ${d};
    if (row < uniforms.dim_a_outer && col < uniforms.dim_inner) {
      ${he}
    }
    return ${vn(d,$)}(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 ${vn(d,$)}(0.0);`,Ae=`${q(x)}`,Ie=vn(k,$),gt=vn(n?d:x,$),ut=vn(n?x:d,$),vt=Vi(f,Ie,$);return`
    fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${gt} {
      ${n?De:Ae}
    }

    fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${ut} {
      ${n?Ae:De}
    }

    fn mm_write(batch: i32, row : i32, colIn : i32, valueIn : ${Ie}) {
      let col = colIn * ${k};
      if (row < uniforms.dim_a_outer && col < uniforms.dim_b_outer)
      {
      var value = valueIn;
      let outWidth = ${n?"i32(uniforms.result_shape[2])":"i32(uniforms.result_shape[3])"};
      ${oe}
      ${Za(c)}
      ${vt}
      setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
      }
    }`},lf=(n,i,s,u,c,f,d,x)=>{let k=i.format==="NHWC",$=k?n[0].dims[3]:n[0].dims[1],H=s[0],q=k?s[2]:s[3],v=k?s[1]:s[2],oe=k?s[3]:s[1],te=k&&($%4===0||$%3===0)&&oe%4===0,de=k?oe:q*v,we=k?q*v:oe,be=[8,8,1],he=u<=8?[4,1,1]:[4,4,1],De=[Math.ceil(de/be[0]/he[0]),Math.ceil(we/be[1]/he[1]),Math.ceil(H/be[2]/he[2])];Vr("verbose",()=>`[conv2d_mm_webgpu] dispatch = ${De}`);let Ae=te?k&&$%4!==0?3:4:1,Ie=be[1]*he[1],gt=be[0]*he[0],ut=Math.max(be[0]*Ae,be[1]),vt=u%Ie===0,Dt=c%gt===0,Rt=f%ut===0,gr=te?[Ae,4,4]:[1,1,1],Mr=[{type:6,data:u},{type:6,data:c},{type:6,data:f},{type:6,data:[i.pads[0],i.pads[1]]},{type:6,data:i.strides},{type:6,data:i.dilations}];Wi(i,Mr),Mr.push(...At(n[0].dims,n[1].dims));let ir=["rank","rank"];d&&(Mr.push(...At(n[2].dims)),ir.push("rank")),Mr.push(...At(s));let Fr=Zr=>{let hr=[{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}];Ei(i,hr);let Hr=te?4:1,Nt=Sr(n[0].dataType),er=`
      fn setOutputAtIndex(flatIndex : i32, value : ${te?`vec4<${Nt}>`:Nt}) {
        result[flatIndex] = ${te?`vec4<${Nt}>`:Nt}(value);
      }
      fn setOutputAtCoords(d0 : i32, d1 : i32, d2 : i32, d3 : i32, value : ${te?`vec4<${Nt}>`:Nt}) {
        let flatIndex = getOutputIndexFromCoords(vec4<i32>(d0, d1, d2, d3));
        setOutputAtIndex(flatIndex ${te?"/ 4":""}, value);
      }`,yr=_t("x",n[0].dataType,n[0].dims.length,Ae===3?1:Ae),ot=_t("w",n[1].dataType,n[1].dims.length,Hr),Vt=[yr,ot],nr=Gt("result",n[0].dataType,s.length,Hr);if(d){let Wr=_t("bias",n[2].dataType,n[2].dims.length,Hr);Vt.push(Wr),er+=`
        fn getBiasByOutputCoords(coords : vec4<i32>) -> ${te?`vec4<${Nt}>`:Nt} {
          return bias[coords.${k?"w":"y"}${te?"/ 4":""}];
        }`}return`
        ${Ja("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 };
        ${Zr.registerUniforms(hr).declareVariables(...Vt,nr)}
        ${er}
        ${Zc(k,vt,Dt,Rt,d,i,gr[0],gr[1],gr[2],Nt)}
        ${te?Rs(he,be,Nt,void 0,!k,ut):Bs(he,be,Nt,void 0,!k,ut,!1,void 0,x)}`};return{name:"Conv2DMatMul",shaderCache:{hint:`${i.cacheKey};${Ae};${te};${vt};${Dt};${Rt};${Ie};${gt};${ut}`,inputDependencies:ir},getRunData:()=>({outputs:[{dims:s,dataType:n[0].dataType}],dispatchGroup:{x:De[0],y:De[1],z:De[2]},programUniforms:Mr}),getShaderSource:Fr}}}),Jc,rl,Ci,ed,nl,td,rd,nd,il=h(()=>{Zt(),jn(),Jt(),ar(),Gi(),xo(),Jc=n=>{let i=1;for(let s=0;s<n.length;s++)i*=n[s];return i},rl=n=>typeof n=="number"?[n,n,n]:n,Ci=(n,i)=>i<=1?n:n+(n-1)*(i-1),ed=(n,i,s,u=1)=>{let c=Ci(i,u);return Math.floor((n[0]*(s-1)-s+c)/2)},nl=(n,i,s,u,c)=>{c==null&&(c=ed(n,i[0],u[0]));let f=[0,0,0,s];for(let d=0;d<3;d++)n[d]+2*c>=i[d]&&(f[d]=Math.trunc((n[d]-i[d]+2*c)/u[d]+1));return f},td=(n,i,s,u,c,f,d,x,k,$)=>{let H,q,v,oe;if(n==="VALID"&&(n=0),typeof n=="number"){H={top:n,bottom:n,left:n,right:n,front:n,back:n};let te=nl([i,s,u,1],[x,k,$],1,[c,f,d],n);q=te[0],v=te[1],oe=te[2]}else if(Array.isArray(n)){if(!n.every((de,we,be)=>de===be[0]))throw Error(`Unsupported padding parameter: ${n}`);H={top:n[0],bottom:n[1],left:n[2],right:n[3],front:n[4],back:n[5]};let te=nl([i,s,u,1],[x,k,$],1,[c,f,d],n[0]);q=te[0],v=te[1],oe=te[2]}else if(n==="SAME_UPPER"){q=Math.ceil(i/c),v=Math.ceil(s/f),oe=Math.ceil(u/d);let te=(q-1)*c+x-i,de=(v-1)*f+k-s,we=(oe-1)*d+$-u,be=Math.floor(te/2),he=te-be,De=Math.floor(de/2),Ae=de-De,Ie=Math.floor(we/2),gt=we-Ie;H={top:De,bottom:Ae,left:Ie,right:gt,front:be,back:he}}else throw Error(`Unknown padding parameter: ${n}`);return{padInfo:H,outDepth:q,outHeight:v,outWidth:oe}},rd=(n,i,s,u,c,f=!1,d="channelsLast")=>{let x,k,$,H,q;if(d==="channelsLast")[x,k,$,H,q]=n;else if(d==="channelsFirst")[x,q,k,$,H]=n;else throw new Error(`Unknown dataFormat ${d}`);let[v,,oe,te,de]=i,[we,be,he]=rl(s),[De,Ae,Ie]=rl(u),gt=Ci(oe,De),ut=Ci(te,Ae),vt=Ci(de,Ie),{padInfo:Dt,outDepth:Rt,outHeight:gr,outWidth:Mr}=td(c,k,$,H,we,be,he,gt,ut,vt),ir=f?v*q:v,Fr=[0,0,0,0,0];return d==="channelsFirst"?Fr=[x,ir,Rt,gr,Mr]:d==="channelsLast"&&(Fr=[x,Rt,gr,Mr,ir]),{batchSize:x,dataFormat:d,inDepth:k,inHeight:$,inWidth:H,inChannels:q,outDepth:Rt,outHeight:gr,outWidth:Mr,outChannels:ir,padInfo:Dt,strideDepth:we,strideHeight:be,strideWidth:he,filterDepth:oe,filterHeight:te,filterWidth:de,effectiveFilterDepth:gt,effectiveFilterHeight:ut,effectiveFilterWidth:vt,dilationDepth:De,dilationHeight:Ae,dilationWidth:Ie,inShape:n,outShape:Fr,filterShape:i}},nd=(n,i,s,u,c,f)=>{let d=f==="channelsLast";d?n[0].dims[3]:n[0].dims[1];let x=[64,1,1],k={x:s.map((we,be)=>be)},$=[Math.ceil(Jc(k.x.map(we=>s[we]))/x[0]),1,1];Vr("verbose",()=>`[conv3d_naive_webgpu] dispatch = ${$}`);let H=1,q=ct.size(s),v=[{type:12,data:q},{type:12,data:u},{type:12,data:c},{type:12,data:i.strides},{type:12,data:i.dilations}];Wi(i,v),v.push(...At(n[0].dims,n[1].dims));let oe=["rank","rank"],te=n.length===3;te&&(v.push(...At(n[2].dims)),oe.push("rank")),v.push(...At(s));let de=we=>{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}];Ei(i,be);let he=1,De=Sr(n[0].dataType),Ae=_t("x",n[0].dataType,n[0].dims.length,H),Ie=_t("W",n[1].dataType,n[1].dims.length,he),gt=[Ae,Ie],ut=Gt("result",n[0].dataType,s.length,he),vt="";if(te){let gr=_t("bias",n[2].dataType,n[2].dims.length,he);gt.push(gr),vt+=`
        fn getBiasByOutputCoords(coords : array<u32, 5>) -> ${De} {
          return bias[${d?zt("coords",4,5):zt("coords",1,5)}];
        }`}let Dt=vn(H,De),Rt=Vi(i,Dt,De);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 ${Ae.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")};
            }
          ${we.registerUniforms(be).declareVariables(...gt,ut)}
          ${we.mainStart()}
          ${we.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
              let coords = ${ut.offsetToIndices("global_idx")};
              let batch = ${zt("coords",0,Ae.rank)};
              let d2 = ${d?zt("coords",Ae.rank-1,Ae.rank):zt("coords",1,Ae.rank)};
              let xFRCCorner = vec3<u32>(${d?zt("coords",1,Ae.rank):zt("coords",2,Ae.rank)},
              ${d?zt("coords",2,Ae.rank):zt("coords",3,Ae.rank)},
              ${d?zt("coords",3,Ae.rank):zt("coords",4,Ae.rank)}) * uniforms.strides - uniforms.pads;
              let xFCorner = xFRCCorner.x;
              let xRCorner = xFRCCorner.y;
              let xCCorner = xFRCCorner.z;
              let xShapeY = ${d?zt("uniforms.x_shape",1,Ae.rank):zt("uniforms.x_shape",2,Ae.rank)};
              let xShapeZ = ${d?zt("uniforms.x_shape",2,Ae.rank):zt("uniforms.x_shape",3,Ae.rank)};
              let xShapeW = ${d?zt("uniforms.x_shape",3,Ae.rank):zt("uniforms.x_shape",4,Ae.rank)};
              let xShapeU = ${d?zt("uniforms.x_shape",4,Ae.rank):zt("uniforms.x_shape",1,Ae.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);
                    }
                  }
                }
              }
              ${te?"value = value + getBiasByOutputCoords(coords)":""};
              ${Rt}
              result[global_idx] = f32(value);
          }`};return{name:"Conv3DNaive",shaderCache:{hint:`${i.cacheKey};${d};${H};${te}`,inputDependencies:oe},getRunData:()=>({outputs:[{dims:s,dataType:n[0].dataType}],dispatchGroup:{x:$[0],y:$[1],z:$[2]},programUniforms:v}),getShaderSource:de}}}),id,od,cf=h(()=>{Zt(),Jt(),ar(),cd(),Gi(),id=(n,i,s)=>{let u=n.length>2,c=u?"value += b[output_channel];":"",f=n[0].dims,d=n[1].dims,x=d[0]/i.group,k=i.format==="NHWC",$=Us(f,d,i.dilations,i.pads,i.strides,k),H=ct.size($),q=[{type:12,data:H},{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:x}];Wi(i,q),q.push(...At(f,d));let v=["rank","rank"];u&&(q.push(...At(n[2].dims)),v.push("rank")),q.push(...At($));let oe=te=>{let de=Gt("output",n[0].dataType,$.length),we=Sr(de.type.tensor),be=Vi(i,de.type.value,we),he=_t("x",n[0].dataType,f.length),De=_t("w",n[1].dataType,d.length),Ae=[he,De];u&&Ae.push(_t("b",n[2].dataType,n[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 Ei(i,Ie),`
  ${te.registerUniforms(Ie).declareVariables(...Ae,de)}

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

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

    var value: ${de.type.value} = ${de.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[${k?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[${k?2:3}]) {
            continue;
          }

          let xVal = ${k?he.get("batch","xHeight","xWidth","input_channel"):he.get("batch","input_channel","xHeight","xWidth")};
          let wVal = ${De.get("output_channel","wInChannel","wHeight","wWidth")};
          value += xVal*wVal;
        }
      }
    }
    ${c}
    ${be}
    ${de.setByOffset("global_idx","value")}
  }`};return{name:"GroupedConv",shaderCache:{hint:i.cacheKey,inputDependencies:v},getRunData:()=>({outputs:[{dims:s?s($):$,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(H/64)},programUniforms:q}),getShaderSource:oe}},od=(n,i,s)=>{let u=n.length>2,c=vr(s[3]),f=vr(s[2]),d=ct.size(s)/c/f,x=[n[0].dims[0],n[0].dims[1],n[0].dims[2],n[0].dims[3]/c],k=[n[1].dims[0],n[1].dims[1],n[1].dims[2],n[1].dims[3]/c],$=[s[0],s[1],s[2],s[3]/c],H=[{type:12,data:d},{type:6,data:[i.strides[0],i.strides[1]]},{type:6,data:[i.pads[0],i.pads[1]]}];Wi(i,H),H.push(...At(x,k,$));let q=(f-1)*i.strides[1]+k[1],v=oe=>{let te=Gt("output",n[0].dataType,$.length,c),de=Sr(te.type.tensor),we=Vi(i,te.type.value,de),be=_t("x",n[0].dataType,x.length,c),he=_t("w",n[1].dataType,k.length,c),De=[be,he];u&&De.push(_t("b",n[2].dataType,n[2].dims,c));let Ae=u?"value += b[output_channel];":"",Ie=[{name:"output_size",type:"u32"},{name:"strides",type:"i32",length:2},{name:"pads",type:"i32",length:2}];return Ei(i,Ie),`
  ${oe.registerUniforms(Ie).declareVariables(...De,te)}
  ${oe.mainStart()}
    ${oe.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] / ${f}u;
    let col = (index1 % width1) * ${f}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}, ${q}>;
    var values: array<${te.type.value}, ${f}>;
    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 < ${k[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 < ${q}; 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 < ${k[1]}; w_width++) {
          let w_val = ${he.get("w_height","w_width","0","output_channel")};
          for (var i = 0u; i < ${f}u; i++) {
            values[i] = fma(x_vals[i * u32(uniforms.strides[1]) + w_width], w_val, values[i]);
          }
        }
      }
    }

    for (var i = 0u; i < ${f}u; i++) {
      var value = values[i];
      ${Ae}
      ${we}
      ${te.set("batch","row","col + i","output_channel","value")};
    }
  }`};return{name:"GroupedConv-Vectorize",shaderCache:{hint:`${i.cacheKey};${c};${f};${q};${k[0]};${k[1]}`,inputDependencies:u?["rank","rank","type"]:["rank","rank"]},getRunData:()=>({outputs:[{dims:s,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(d/64)},programUniforms:H}),getShaderSource:v}}}),ol,sd,ad,sl=h(()=>{Zt(),Jt(),js(),ar(),Gi(),ol=(n,i,s,u,c=!1)=>{let f=n[0].dims,d=n[1].dims,x=f[f.length-2],k=d[d.length-1],$=f[f.length-1],H=vr(k),q=vr($),v=vr(x),oe=ct.size(s)/H/v,te=n.length>2,de=u?u.slice(0,-2):s.slice(0,-2),we=[ct.size(de),x,k],be=[{type:12,data:oe},{type:12,data:x},{type:12,data:k},{type:12,data:$}];Wi(i,be),be.push(...At(de,f,d)),te&&be.push(...At(n[2].dims)),be.push(...At(we));let he=De=>{let Ae=ma("batch_dims",n[0].dataType,de.length),Ie=_t("a",n[0].dataType,f.length,q),gt=_t("b",n[1].dataType,d.length,H),ut=Gt("output",n[0].dataType,we.length,H),vt=Sr(ut.type.tensor),Dt=Vi(i,ut.type.value,vt),Rt=[Ie,gt],gr="";if(te){let er=c?H:1;Rt.push(_t("bias",n[2].dataType,n[2].dims.length,er)),gr=`${c?`value += bias[col / ${er}];`:`value += ${ut.type.value}(bias[row + i]);`}`}let Mr=f.slice(0,-2),ir=d.slice(0,-2),Fr=wo(Mr,de),Zr=wo(ir,de),hr=[{name:"output_size",type:"u32"},{name:"M",type:"u32"},{name:"N",type:"u32"},{name:"K",type:"u32"}];Ei(i,hr);let Hr=(er,yr)=>{let ot=er.rank,Vt=er.name;if(ot===2)return`var ${Vt}_indices = ${er.type.indices}(0u, 0u);`;let nr=Ae.rank,Wr=`var ${Vt}_indices: ${er.type.indices};`;for(let pn=ot-2-1,kn=nr-1;pn>=0;pn--,kn--)Wr+=`
${Vt}_indices[${pn}] = ${nr>1?`batch_indices[${kn}]`:"batch_indices"};`;return yr.forEach(pn=>{Wr+=`
${Vt}_indices[${pn}] = 0;`}),Wr+=`${Vt}_indices[${ot-2}] = 0u;
                     ${Vt}_indices[${ot-1}] = 0u;`,Wr},Nt=()=>{let er=`var a_data: ${Ie.type.value};`;for(let yr=0;yr<q;yr++)er+=`
              let b_data${yr} = b[(b_offset + (k + ${yr}) * uniforms.N + col) / ${H}];`;for(let yr=0;yr<v;yr++){er+=`a_data = a[(a_offset + (row + ${yr}) * uniforms.K + k) / ${q}];`;for(let ot=0;ot<q;ot++)er+=`
            values[${yr}] = fma(${gt.type.value}(a_data${q===1?"":`[${ot}]`}), b_data${ot}, values[${yr}]);
`}return er};return`
  ${De.registerUniforms(hr).registerInternalVariables(Ae).declareVariables(...Rt,ut)}
  ${De.mainStart()}
    ${De.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
    let col = (global_idx % (uniforms.N / ${H})) * ${H};
    var index1 = global_idx / (uniforms.N / ${H});
    let stride1 = uniforms.M / ${v};
    let row = (index1 % stride1) * ${v};
    let batch = index1 / stride1;

    ${s.length===2?"":`let batch_indices = ${Ae.offsetToIndices("batch")};`}
    ${Hr(Ie,Fr)}
    let a_offset = ${Ie.indicesToOffset("a_indices")};
    ${Hr(gt,Zr)}
    let b_offset = ${gt.indicesToOffset("b_indices")};
    var values: array<${ut.type.value}, ${v}>;
    for (var k: u32 = 0u; k < uniforms.K; k = k + ${q}) {
      ${Nt()}
    }
    for (var i = 0u; i < ${v}u; i++) {
      var value = values[i];
      ${gr}
      ${Dt}
      let cur_indices = ${ut.type.indices}(batch, row + i, col);
      let offset = ${ut.indicesToOffset("cur_indices")};
      ${ut.setByOffset(`offset / ${H}`,"value")};
    }
  }
  `};return{name:"MatMulNaive",shaderCache:{hint:`${i.activation};${H};${q};${v};${c}`,inputDependencies:te?["rank","rank","rank"]:["rank","rank"]},getRunData:()=>({outputs:[{dims:s,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(oe/64)},programUniforms:be}),getShaderSource:he}},sd=n=>{if(!n||n.length!==2)throw new Error("MatMul requires 2 inputs.");if(n[0].dims[n[0].dims.length-1]!==n[1].dims[n[1].dims.length-2])throw new Error("shared dimension does not match.")},ad=n=>{sd(n.inputs);let i=gn.calcShape(n.inputs[0].dims,n.inputs[1].dims,!0);if(!i)throw new Error("Can't use matmul on the given tensors");let s=i[i.length-1],u=n.inputs[0].dims[n.inputs[0].dims.length-1];s<8&&u<8?n.compute(ol(n.inputs,{activation:""},i)):n.compute(tl(n.inputs,{activation:""},i))}}),Us,Vs,al,Ws,ll,ul,ld,ud,Ko,cd=h(()=>{Jt(),uf(),il(),js(),cf(),Gi(),sl(),yo(),Us=(n,i,s,u,c,f)=>{let d=n[0],x=n.slice(f?1:2,f?3:4),k=x.length,$=i[0],H=i.slice(2).map((v,oe)=>v+(v-1)*(s[oe]-1)),q=x.map((v,oe)=>v+u[oe]+u[oe+k]).map((v,oe)=>Math.floor((v-H[oe]+c[oe])/c[oe]));return q.splice(0,0,d),q.splice(f?3:1,0,$),q},Vs=[2,3,1,0],al=(n,i)=>{if(!n||n.length!==2&&n.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(n[0].dims.length>5)throw new Error("greater than 5D is not supported");if(n[0].dims.length!==n[1].dims.length)throw new Error("filter does not have same dimension as input");let s=n[0].dims[i.format==="NHWC"?n[0].dims.length-1:1],u=n[1].dims[1]*i.group;if(s!==u)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");if(n.length===3&&(n[2].dims.length!==1||n[1].dims[0]!==n[2].dims[0]))throw new Error("invalid bias");let c=n[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 ${c*2}D`);if(i.kernelShape.length!==0&&i.kernelShape.length!==n[1].dims.length-2)throw new Error("invalid kernel shape")},Ws=(n,i)=>{let s=n.kernelShape.slice();for(let f=2;f<i[1].dims.length;++f)s[f-2]===0&&(s[f-2]=i[1].dims[f]);let u=n.pads.slice();Kn.adjustPadsBasedOnAutoPad(i[0].dims,n.strides,n.dilations,s,u,n.format==="NHWC",n.autoPad);let c=Object.assign({},n);return Object.assign(c,{kernelShape:s,pads:u}),c},ll=n=>{let i=Ya(n),s=n.format,u=["NOTSET","VALID","SAME_UPPER","SAME_LOWER"][n.auto_pad],c=n.dilations,f=n.group,d=n.kernel_shape,x=n.pads,k=n.strides,$=n.w_is_const();return{autoPad:u,format:s,dilations:c,group:f,kernelShape:d,pads:x,strides:k,wIsConst:$,...i,cacheKey:`${n.format};${i.activation};`}},ul=(n,i,s)=>{let u=Ws(s,i),c=s.format==="NHWC";if(s.group!==1){if(!n.adapterInfo.isArchitecture("ampere")&&c&&i[1].dims[0]===s.group&&i[1].dims[1]===1&&s.dilations[0]===1&&s.dilations[1]===1){let gt=Us(i[0].dims,i[1].dims,s.dilations,u.pads,s.strides,c),ut=n.kernelCustomData.wT??n.compute(hi(i[1],Vs),{inputs:[1],outputs:[s.wIsConst?-2:-1]})[0];s.wIsConst&&!n.kernelCustomData.wT&&(n.kernelCustomData.wT=ut);let vt=[i[0],ut];i.length===3&&vt.push(i[2]),n.compute(od(vt,u,gt),{inputs:vt})}else n.compute(id(i,u));return}let f=i.length===3,d=i[0].dims[c?1:2],x=i[0].dims[c?2:3],k=i[0].dims[c?3:1],$=i[1].dims[2],H=i[1].dims[3],q=Us(i[0].dims,i[1].dims,s.dilations,u.pads,s.strides,c),v=q[c?1:2],oe=q[c?2:3],te=q[c?3:1],de=c&&$===d&&H===x&&s.pads[0]===0&&s.pads[1]===0;if(de||$===1&&H===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 gt=q[0],ut,vt,Dt,Rt=[];if(c){let ir=n.kernelCustomData.wT??n.compute(hi(i[1],Vs),{inputs:[1],outputs:[s.wIsConst?-2:-1]})[0];if(s.wIsConst&&!n.kernelCustomData.wT&&(n.kernelCustomData.wT=ir),de){let Fr=d*x*k;ut=i[0].reshape([1,gt,Fr]),vt=ir.reshape([1,Fr,te]),Dt=[1,gt,te]}else ut=i[0].reshape([gt,d*x,k]),vt=ir.reshape([1,k,te]),Dt=[gt,v*oe,te];Rt.push(ut),Rt.push(vt)}else ut=i[0].reshape([gt,k,d*x]),vt=i[1].reshape([1,te,k]),Dt=[gt,te,v*oe],Rt.push(vt),Rt.push(ut);f&&Rt.push(i[2]);let gr=Dt[2],Mr=Rt[0].dims[Rt[0].dims.length-1];gr<8&&Mr<8?n.compute(ol(Rt,u,q,Dt,c),{inputs:Rt}):n.compute(tl(Rt,u,q,Dt,c),{inputs:Rt});return}let we=!0,be=n.kernelCustomData.wT??n.compute(hi(i[1],Vs),{inputs:[1],outputs:[s.wIsConst?-2:-1]})[0];s.wIsConst&&!n.kernelCustomData.wT&&(n.kernelCustomData.wT=be);let he=[i[0],be];f&&he.push(i[2]);let De=c?v*oe:te,Ae=c?te:v*oe,Ie=$*H*k;n.compute(lf(he,u,q,De,Ae,Ie,f,we),{inputs:he})},ld=(n,i)=>{let s=i.format==="NHWC",u=[n.inputs[0].reshape(s?[n.inputs[0].dims[0],1,n.inputs[0].dims[1],n.inputs[0].dims[2]]:[n.inputs[0].dims[0],n.inputs[0].dims[1],1,n.inputs[0].dims[2]]),n.inputs[1].reshape([n.inputs[1].dims[0],n.inputs[1].dims[1],1,n.inputs[1].dims[2]])];n.inputs.length===3&&u.push(n.inputs[2]);let c=[0,i.pads[0],0,i.pads[1]],f=[1].concat(i.strides),d=[1].concat(i.dilations),x=[1].concat(i.kernelShape),k=Ws({...i,pads:c,strides:f,dilations:d,kernelShape:x},u);n.compute(id(u,k,$=>s?[$[0],$[2],$[3]]:[]))},ud=(n,i,s)=>{let u=s.format==="NHWC"?"channelsLast":"channelsFirst",c=Ws(s,i),f=s.autoPad==="NOTSET"?s.pads:s.autoPad,d=rd(i[0].dims,i[1].dims,s.strides,s.dilations,f,!1,u);n.compute(nd(i,c,d.outShape,[d.filterDepth,d.filterHeight,d.filterWidth],[d.padInfo.front,d.padInfo.top,d.padInfo.left],u))},Ko=(n,i)=>{al(n.inputs,i),n.inputs[0].dims.length===3?ld(n,i):n.inputs[0].dims.length===5?ud(n,n.inputs,i):ul(n,n.inputs,i)}}),dd,pd,df=h(()=>{Zt(),jn(),ar(),Gi(),xo(),Xc(),js(),dd=(n,i=!1,s,u,c=4)=>{let f=we=>{switch(we){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 ${we} is not supported.`)}},d=n?`
      let coord = vec4<i32>(batch, iXR, iXC, xCh);
      `:`
      let coord = vec4<i32>(batch, xCh, iXR, iXC);
      `,x=n?`
    let coords = vec4<i32>(
      batch,
      row / outWidth,
      row % outWidth,
      col);
    `:`
    let coords = vec4<i32>(
      batch,
      row,
      col / outWidth,
      col % outWidth);
    `,k=n?"i32(uniforms.x_shape[1])":"i32(uniforms.x_shape[2])",$=n?"i32(uniforms.x_shape[2])":"i32(uniforms.x_shape[3])",H=n?"row":"col",q=n?"col":"row",v=`
      let inChannels = ${n?"i32(uniforms.x_shape[3])":"i32(uniforms.x_shape[1])"};
      let outWidth = ${n?"i32(uniforms.result_shape[2])":"i32(uniforms.result_shape[3])"};
      let outRow = ${H} / outWidth;
      let outCol = ${H} % outWidth;

      let WRow = ${q} / (uniforms.filter_dims[1] * inChannels);
      let WCol = ${q} / inChannels % uniforms.filter_dims[1];
      let xR = f32(outRow - uniforms.pads[0] + uniforms.dilations[0] * WRow) / f32(uniforms.strides[0]);
      let xC = f32(outCol - uniforms.pads[1] + uniforms.dilations[1] * WCol) / f32(uniforms.strides[1]);
      if (xR < 0.0 || xR >= f32(${k}) || fract(xR) > 0.0) {
        return ${u}(0.0);
      }
      if (xC < 0.0 || xC >= f32(${$}) || fract(xC) > 0.0) {
        return ${u}(0.0);
      }
      let iXR = i32(xR);
      let iXC = i32(xC);
      let xCh = ${q} % inChannels;
      ${d}
      return x[getIndexFromCoords4D(coord, vec4<i32>(uniforms.x_shape))/${c}];`,oe=n?`
      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);`,te=`
      let col = colIn * ${c};
      let inChannels = ${n?"i32(uniforms.x_shape[3])":"i32(uniforms.x_shape[1])"};
      let coordX = uniforms.filter_dims[0] - 1 - row / (uniforms.filter_dims[1] * inChannels);
      let coordY = uniforms.filter_dims[1] - 1 - (row / inChannels) % uniforms.filter_dims[1];
      if (${n?"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);
        ${f(c)}
      }
      return ${u}(0.0);
      `,de=Vi(s,u);return`
  fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${u} {
    ${n?oe:te}
  }

  fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${u} {
    ${n?te:oe}
  }

  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 = ${n?"i32(uniforms.result_shape[2])":"i32(uniforms.result_shape[3])"};
      ${x}
      ${Za(i)}
      ${de}
      result[getIndexFromCoords4D(coords, vec4<i32>(uniforms.result_shape))/${c}] = value;
    }
  }`},pd=(n,i,s,u,c,f,d,x)=>{let k=i.format==="NHWC",$=k?n[0].dims[3]:n[0].dims[1],H=s[0],q=k?s[2]:s[3],v=k?s[1]:s[2],oe=k?s[3]:s[1],te=k&&$%4===0&&$%3&&oe%4===0,de=k?oe:q*v,we=k?q*v:oe,be=[8,8,1],he=u<=8?[4,1,1]:[4,4,1],De=[Math.ceil(de/be[0]/he[0]),Math.ceil(we/be[1]/he[1]),Math.ceil(H/be[2]/he[2])];Vr("verbose",()=>`[conv_backprop_mm_webgpu] dispatch = ${De}`);let Ae=te?4:1,Ie=Math.max(be[0]*Ae,be[1]),gt=te?4:1,ut=[i.kernelShape[k?1:2],i.kernelShape[k?2:3]],vt=[ut[0]+(i.dilations[0]<=1?0:(ut[0]-1)*(i.dilations[0]-1)),ut[1]+(i.dilations[1]<=1?0:(ut[1]-1)*(i.dilations[1]-1))],Dt=[vt[0]-1-Math.floor((i.pads[0]+i.pads[2])/2),vt[1]-1-Math.floor((i.pads[1]+i.pads[3])/2)],Rt=[{type:6,data:u},{type:6,data:c},{type:6,data:f},{type:6,data:i.strides},{type:6,data:i.dilations},{type:6,data:ut},{type:6,data:Dt}];Wi(i,Rt),Rt.push(...At(n[0].dims,n[1].dims));let gr=["rank","rank"];d&&(Rt.push(...At(n[2].dims)),gr.push("rank")),Rt.push(...At(s));let Mr=ir=>{let Fr=_t("x",n[0].dataType,n[0].dims.length,gt),Zr=_t("w",n[1].dataType,n[1].dims.length,1),hr=Gt("result",n[0].dataType,s.length,gt),Hr=[Fr,Zr],Nt="";if(d){let ot=_t("bias",n[2].dataType,n[2].dims.length,gt);Hr.push(ot),Nt+=`
          fn getBiasByOutputCoords(coords : vec4<i32>) -> ${ot.type.value} {
            return bias[coords.${k?"w":"y"}${te?"/ 4":""}];
          }`}let er=[{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:ut.length},{name:"pads",type:"i32",length:Dt.length}];Ei(i,er);let yr=Sr(n[0].dataType,1);if(yr!=="f16"&&yr!=="f32")throw new Error(`elemType ${yr} is not supported.`);return`
        ${Ja("uniforms.result_strides")}
        ${ir.registerUniforms(er).declareVariables(...Hr,hr)};
        ${Nt}
        ${dd(k,d,i,Fr.type.value,Ae)}
        ${te?Rs(he,be,yr,void 0,!k,Ie):Bs(he,be,yr,void 0,!k,Ie,!1,void 0,x)}`};return{name:"Conv2DTransposeMatMul",shaderCache:{hint:`${i.cacheKey};${he};${be};${te}`,inputDependencies:gr},getRunData:()=>({outputs:[{dims:s,dataType:n[0].dataType}],dispatchGroup:{x:De[0],y:De[1],z:De[2]},programUniforms:Rt}),getShaderSource:Mr}}}),cl,Xo,mm=h(()=>{Zt(),jn(),Jt(),ar(),cl=(n,i,s,u,c,f=!1,d,x,k=!1)=>{let $=k?1:2,H=k?2:3,q=k?3:1,v=f?2:1,oe=`
  fn setOutputAtIndex(flatIndex : u32, value : ${f?`vec4<${d}>`:d}) {
    result[flatIndex] = ${f?`vec4<${d}>`:d}(value);
  }`;u&&(oe+=`
    fn getBiasByOutputCoords(coords : vec4<u32>) -> ${f?`vec4<${d}>`:d} {
      return bias[coords.${k?"w":"y"}${f?"/ 4":""}];
    }`);let te=f?4:1,de=_t("W",i[1].dataType,i[1].dims.length,te),we=_t("Dy",i[0].dataType,i[0].dims.length,te),be=[we,de];u&&be.push(_t("bias",i[2].dataType,[s[q]].length,te));let he=Gt("result",i[0].dataType,s.length,te),De=`{
        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 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1","d2")};
                let wValue1 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 1","d2")};
                let wValue2 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 2","d2")};
                let wValue3 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 3","d2")};

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

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

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

                var xValue = ${we.get("batch","idyR","idyC","d2")};
                let tmpval = vec4<${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 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1","d2")};
                let wValue1 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 1","d2")};
                let wValue2 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 2","d2")};
                let wValue3 = ${de.get("u32(wRPerm)","u32(wCPerm)","d1 + 3","d2")};

                var xValue = ${we.get("batch","idyR","idyC2","d2")};
                let tmpval = vec4<${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")};
        }
      }`,Ae=`
          let outputIndices = ${he.offsetToIndices("global_idx")};
          let batch = ${he.indicesGet("outputIndices",0)};
          let d1 = ${he.indicesGet("outputIndices",q)};
          let r = ${he.indicesGet("outputIndices",$)};
          let c = ${he.indicesGet("outputIndices",H)};
          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 >= ${d}(uniforms.Dy_shape[${$}]) || 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 >= ${d}(uniforms.Dy_shape[${H}]) ||
                  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 = ${k?we.get("batch","idyR","idyC","inputChannel"):we.get("batch","inputChannel","idyR","idyC")};
                let wValue = ${de.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`
  ${n.registerUniforms(x).declareVariables(...be,he)}
  ${oe}

    ${n.mainStart()}
    ${n.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")};
  ${f?De:Ae}}`},Xo=(n,i,s)=>{let u=n.length>2,c=i.outputShape,f=ct.size(c),d=[Math.ceil(f/64),1,1];Vr("verbose",()=>`[conv2d_backprop_webgpu] dispatch = ${d}`);let x=i.format==="NHWC",k=["rank","rank"],$=[i.strides[0],i.strides[1]],H=[i.kernelShape[x?1:2],i.kernelShape[x?2:3]],q=[i.dilations[0],i.dilations[1]],v=[H[0]+(i.dilations[0]<=1?0:(i.kernelShape[x?1:2]-1)*(i.dilations[0]-1)),H[1]+(i.dilations[1]<=1?0:(i.kernelShape[x?2:3]-1)*(i.dilations[1]-1))],oe=[v[0]-1-Math.floor((i.pads[0]+i.pads[2])/2),v[1]-1-Math.floor(i.pads[1]+i.pads[3])/2],te=!1,de=i.group,we=n[1].dims,be=we[0]/de,he=we[1],De=[{type:12,data:f},{type:12,data:$},{type:12,data:H},{type:12,data:q},{type:12,data:v},{type:6,data:oe},{type:12,data:be},{type:12,data:he},...At(n[0].dims,n[1].dims)];u&&(De.push(...At(n[2].dims)),k.push("rank")),De.push(...At(c));let Ae=d[1]===1&&d[2]===1,Ie=gt=>{let ut=[{name:"output_size",type:"u32"},{name:"strides",type:"u32",length:$.length},{name:"filter_dims",type:"u32",length:H.length},{name:"dilations",type:"u32",length:H.length},{name:"effective_filter_dims",type:"u32",length:v.length},{name:"pads",type:"i32",length:oe.length},{name:"input_channels_per_group",type:"u32"},{name:"output_channels_per_group",type:"u32"}],vt=Sr(n[0].dataType);return`${cl(gt,n,c,u,Ae,te,vt,ut,x)}`};return{name:"ConvTranspose2D",shaderCache:{hint:`${i.cacheKey};`,inputDependencies:k},getRunData:()=>({dispatchGroup:{x:d[0],y:d[1],z:d[2]},outputs:[{dims:s?s(c):c,dataType:n[0].dataType}],programUniforms:De}),getShaderSource:Ie}}}),fd,hd,dl,pl,md,fl,gd,_d,hl,pf,gm=h(()=>{df(),mm(),Gi(),yo(),fd=(n,i,s,u,c,f)=>(n-1)*i+s+(u-1)*c+1-f,hd=(n,i,s,u,c)=>{let f=Math.floor(n/2);i==="SAME_UPPER"?(s[u]=f,s[c]=n-f):i==="SAME_LOWER"&&(s[u]=n-f,s[c]=f)},dl=(n,i,s,u,c,f,d,x,k,$)=>{let H=n.length-2,q=$.length===0;if(k.length===0)for(let te=0;te<H;++te)k.push(0);let v=n[0],oe=i[x?3:1]*c;for(let te=0,de=n.length-H-(x?1:0);te<H;++te,++de){let we=n[de],be=q?we*d[te]:$[te],he=fd(we,d[te],f[te],i[de],s[te],be);hd(he,u,f,te,te+H),q&&$.push(d[te]*(we-1)+k[te]+(i[de]-1)*s[te]+1-f[te]-f[te+H])}$.splice(0,0,v),$.splice(x?3:1,0,oe)},pl=(n,i)=>{let s=n.kernelShape.slice();if(n.kernelShape.length===0||n.kernelShape.reduce((q,v)=>q*v,1)===0){s.length=0;for(let q=2;q<i[1].dims.length;++q)s.push(i[1].dims[q])}let u=n.format==="NHWC";s.splice(0,0,i[1].dims[0]),s.splice(u?3:1,0,i[1].dims[1]);let c=n.pads.slice(),f=n.outputShape.slice(),d=n.outputPadding.slice(),x=i[0].dims,k=n.dilations.slice();if(k.reduce((q,v)=>q+v,0)===0){let q=i[0].dims.length-2;k=new Array(q).fill(1)}let $=n.strides.slice();if($.reduce((q,v)=>q+v,0)===0){let q=i[0].dims.length-2;$=new Array(q).fill(1)}dl(x,s,k,n.autoPad,n.group,c,$,u,d,f);let H=Object.assign({},n);return Object.assign(H,{kernelShape:s,pads:c,outputPadding:d,outputShape:f,dilations:k,strides:$}),H},md=n=>{let i=Ya(n),s=n.format,u=["NOTSET","VALID","SAME_UPPER","SAME_LOWER"][typeof n.autoPad>"u"?0:n.autoPad],c=n.dilations,f=n.group,d=n.kernelShape,x=n.pads,k=n.strides,$=n.wIsConst(),H=n.outputPadding,q=n.outputShape;return{autoPad:u,format:s,dilations:c,group:f,kernelShape:d,outputPadding:H,outputShape:q,pads:x,strides:k,wIsConst:$,...i,cacheKey:`${n.format};${i.activation};`}},fl=(n,i)=>{if(!n||n.length!==2&&n.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(n[0].dims.length!==4&&n[0].dims.length!==3)throw new Error("currently only support 2-dimensional conv");if(n[0].dims.length!==n[1].dims.length)throw new Error("filter does not have same dimension as input");let s=n[0].dims[i.format==="NHWC"?n[0].dims.length-1:1],u=n[1].dims[0];if(s!==u)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");let c=n[1].dims[1]*i.group;if(n.length===3&&(n[2].dims.length!==1||n[2].dims[0]!==c))throw new Error("invalid bias");let f=n[0].dims.length-2;if(i.dilations.reduce((d,x)=>d+x,0)>0&&i.dilations.length!==f)throw new Error(`dilations should be ${f}D`);if(i.strides.reduce((d,x)=>d+x,0)>0&&i.strides.length!==f)throw new Error(`strides should be ${f}D`);if(i.pads.reduce((d,x)=>d+x,0)>0&&i.pads.length!==f*2)throw new Error(`pads should be ${f*2}D`);if(i.outputPadding.length!==f&&i.outputPadding.length!==0)throw new Error(`output_padding should be ${f}D`);if(i.kernelShape.reduce((d,x)=>d+x,0)>0&&i.kernelShape.length!==0&&i.kernelShape.length!==n[1].dims.length-2)throw new Error("invalid kernel shape");if(i.outputShape.length!==0&&i.outputShape.length!==n[0].dims.length-2)throw new Error("invalid output shape")},gd=[2,3,1,0],_d=(n,i,s)=>{let u=pl(s,i),c=s.format==="NHWC",f=u.outputShape,d=f[c?3:1],x=i[0].dims[c?3:1];if(u.group!==1||d===1&&x===1){n.compute(Xo(i,u));return}let k=f[c?1:2],$=f[c?2:3],H=i[1].dims[2],q=i[1].dims[3],v=c?k*$:d,oe=c?d:k*$,te=H*q*x,de=!0,we=n.kernelCustomData.wT??n.compute(hi(i[1],gd),{inputs:[1],outputs:[s.wIsConst?-2:-1]})[0];s.wIsConst&&!n.kernelCustomData.wT&&(n.kernelCustomData.wT=we);let be=[i[0],we],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])),n.compute(pd(be,u,f,v,oe,te,he,de),{inputs:be})},hl=(n,i)=>{let s=i.format==="NHWC",u=[n.inputs[0].reshape(s?[n.inputs[0].dims[0],1,n.inputs[0].dims[1],n.inputs[0].dims[2]]:[n.inputs[0].dims[0],n.inputs[0].dims[1],1,n.inputs[0].dims[2]]),n.inputs[1].reshape([n.inputs[1].dims[0],n.inputs[1].dims[1],1,n.inputs[1].dims[2]])];n.inputs.length===3&&u.push(n.inputs[2]);let c=i.kernelShape;(c.length===0||c[0]===0)&&(c=[n.inputs[1].dims[2]]);let f=i.dilations;(f.length===0||f[0]===0)&&(f=[1]);let d=i.strides;(d.length===0||d[0]===0)&&(d=[1]);let x=i.pads;x.length===0&&(x=[0,0]),x=[0,x[0],0,x[1]],d=[1].concat(d),f=[1].concat(f),c=[1].concat(c);let k=pl({...i,pads:x,strides:d,dilations:f,kernelShape:c},u);n.compute(Xo(u,k,$=>s?[$[0],$[2],$[3]]:[$[0],$[1],$[3]]))},pf=(n,i)=>{fl(n.inputs,i),n.inputs[0].dims.length===3?hl(n,i):_d(n,n.inputs,i)}}),ml,gl,wd,ff=h(()=>{Zt(),Jt(),_r(),ar(),ml=(n,i,s,u)=>{let c=ct.size(i),f=i.length,d=_t("input",n,f),x=Gt("output",n,f),k=s.dataType===6?s.getInt32Array()[0]:Number(s.getBigInt64Array()[0]),$=ct.normalizeAxis(k,f),H=q=>{let v=` i32(${d.indicesGet("inputIndices","uniforms.axis")}) `,oe=zt("uniforms.input_shape","uniforms.axis",f),te=u.reverse?v+(u.exclusive?" + 1":""):"0",de=u.reverse?oe:v+(u.exclusive?"":" + 1");return`
                ${q.registerUniform("outputSize","u32").registerUniform("axis","u32").declareVariables(d,x)}
                ${q.mainStart()}
                  ${q.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}
                  var inputIndices = ${x.offsetToIndices("global_idx")};
                  var sum = ${x.type.value}(0);
                  let first : i32 = ${te};
                  let last : i32 = ${de};
                  for (var i : i32 = first; i < last; i++) {
                    ${d.indicesSet("inputIndices","uniforms.axis","u32(i)")};
                    sum = sum + ${d.getByIndices("inputIndices")};
                  }
                  ${x.setByOffset("global_idx","sum")};
                }`};return{name:"CumSum",shaderCache:{hint:u.cacheKey,inputDependencies:["rank"]},getRunData:()=>({outputs:[{dims:i,dataType:n}],dispatchGroup:{x:Math.ceil(c/64)},programUniforms:[{type:12,data:c},{type:12,data:$},...At(i,i)]}),getShaderSource:H}},gl=(n,i)=>{let s=n.inputs[0].dims,u=n.inputs[0].dataType,c=n.inputs[1];n.compute(ml(u,s,c,i),{inputs:[0]})},wd=n=>{let i=n.exclusive===1,s=n.reverse===1;return qt({exclusive:i,reverse:s})}}),_l,yd,vd,wl,bd,hf=h(()=>{Zt(),Jt(),_r(),ar(),_l=n=>{if(!n||n.length!==1)throw new Error("DepthToSpace requires 1 input.");if(n[0].dims.length!==4)throw new Error("DepthToSpace requires 4D input.")},yd=(n,i,s,u)=>{let c=[];c.push(`fn perm(i: ${u.type.indices}) -> ${s.type.indices} {
    var a: ${s.type.indices};`);for(let f=0;f<i;++f)c.push(s.indicesSet("a",n[f],`i[${f}]`));return c.push("return a;}"),c.join(`
`)},vd=(n,i)=>{let s,u,c,f,d,x,k=i.format==="NHWC",$=i.blocksize,H=i.mode==="DCR";k?([s,u,c,f]=n.dims,d=H?[s,u,c,$,$,f/$**2]:[s,u,c,f/$**2,$,$],x=H?[0,1,3,2,4,5]:[0,1,4,2,5,3]):([s,u,c,f]=[n.dims[0],n.dims[2],n.dims[3],n.dims[1]],d=H?[s,$,$,f/$**2,u,c]:[s,f/$**2,$,$,u,c],x=H?[0,3,4,1,5,2]:[0,1,4,2,5,3]);let q=n.reshape(d),v=q.dims.length,oe=n.dataType,te=_t("a",oe,v),de=Gt("output",oe,v),we=be=>`
  ${be.registerUniform("output_size","u32").declareVariables(te,de)}

  ${yd(x,v,te,de)}

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

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

    ${de.setByOffset("global_idx",te.getByIndices("aIndices"))}
  }`;return{name:"DepthToSpace",shaderCache:{hint:`${n.dims};${i.blocksize};${i.mode}`,inputDependencies:["rank"]},getRunData:be=>{let he=k?[s,u*$,c*$,f/$**2]:[s,f/$**2,u*$,c*$],De=ct.size(he),Ae=q.dims,Ie=ct.sortBasedOnPerm(Ae,x);return{outputs:[{dims:he,dataType:be[0].dataType}],dispatchGroup:{x:Math.ceil(De/64)},programUniforms:[{type:12,data:De},...At(Ae,Ie)]}},getShaderSource:we}},wl=(n,i)=>{_l(n.inputs),n.compute(vd(n.inputs[0],i))},bd=n=>qt({blocksize:n.blocksize,mode:n.mode,format:n.format})}),Qo,Yo,yl,Rr,mf,gf,_f,Gs,xd,Md,Td,wf=h(()=>{Zt(),Jt(),_r(),ar(),Qo="[a-zA-Z]|\\.\\.\\.",Yo="("+Qo+")+",yl="^"+Yo+"$",Rr="("+Yo+",)*"+Yo,mf="^"+Rr+"$",gf=class{constructor(n=-1){this.symbolToIndices=new Map,this.inputIndex=n}addSymbol(n,i){let s=this.symbolToIndices.get(n);s===void 0?s=[i]:s.push(i),this.symbolToIndices.set(n,s)}},_f=class{constructor(n,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(mf)))throw new Error("Invalid LHS term");if(s.split(",").forEach((f,d)=>{let x=n[d].dims.slice();if(!f.match(RegExp(yl)))throw new Error("Invalid LHS term");let k=this.processTerm(f,!0,x,d);this.lhs.push(k)}),u==="")u+=[...this.symbolToInfo.entries()].filter(([f,d])=>d.count===1||f==="...").map(([f])=>f).join("");else if(!u.match(RegExp(Yo)))throw new Error("Invalid RHS");(c=u.match(RegExp(Qo,"g")))==null||c.forEach(f=>{if(f==="...")this.outputDims=this.outputDims.concat(this.ellipsisDims);else{let d=this.symbolToInfo.get(f);if(d===void 0)throw new Error("Invalid RHS symbol");this.outputDims.push(d.dimValue)}}),this.rhs=this.processTerm(u,!1,this.outputDims)}addSymbol(n,i,s){let u=this.symbolToInfo.get(n);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(n,u)}processTerm(n,i,s,u=-1){let c=s.length,f=!1,d=[],x=0;if(!n.match(RegExp(yl))&&!i&&n!=="")throw new Error("Invalid LHS term");let k=n.match(RegExp(Qo,"g")),$=new gf(u);return k==null||k.forEach((H,q)=>{if(H==="..."){if(f)throw new Error("Only one ellipsis is allowed per input term");f=!0;let v=c-k.length+1;if(v<0)throw new Error("Ellipsis out of bounds");if(d=s.slice(x,x+v),this.hasEllipsis){if(this.ellipsisDims.length!==d.length||this.ellipsisDims.toString()!==d.toString())throw new Error("Ellipsis dimensions mismatch")}else if(i)this.hasEllipsis=!0,this.ellipsisDims=d;else throw new Error("Ellipsis must be specified in the LHS");for(let oe=0;oe<d.length;oe++){let te=String.fromCharCode(48+oe);$.addSymbol(te,q+oe),this.addSymbol(te,s[x++],u)}}else $.addSymbol(H,q+(this.hasEllipsis?this.ellipsisDims.length-1:0)),this.addSymbol(H,s[x++],u)}),$}},Gs=n=>n+"_max",xd=(n,i,s,u)=>{let c=n.map($=>$.length).map(($,H)=>_t(`input${H}`,i,$)),f=ct.size(u),d=Gt("output",i,u.length),x=[...s.symbolToInfo.keys()].filter($=>!s.rhs.symbolToIndices.has($)),k=$=>{let H=[],q="var prod = 1.0;",v="var sum = 0.0;",oe="sum += prod;",te=[],de=[],we=[],be=[],he=s.symbolToInfo.size===s.rhs.symbolToIndices.size;s.symbolToInfo.forEach((Ae,Ie)=>{var gt;if(s.rhs.symbolToIndices.has(Ie)){let ut=(gt=s.rhs.symbolToIndices.get(Ie))==null?void 0:gt[0];ut!==void 0&&s.lhs.forEach((vt,Dt)=>{if(Ae.inputIndices.includes(Dt)){let Rt=vt.symbolToIndices.get(Ie);if(Rt===void 0)throw new Error("Invalid symbol error");Rt.forEach(gr=>{H.push(`${c[Dt].indicesSet(`input${Dt}Indices`,gr,d.indicesGet("outputIndices",ut))}`)})}})}else s.lhs.forEach((ut,vt)=>{if(Ae.inputIndices.includes(vt)){let Dt=ut.symbolToIndices.get(Ie);if(Dt===void 0)throw new Error("Invalid symbol error");Dt.forEach(Rt=>{te.push(`${c[vt].indicesSet(`input${vt}Indices`,Rt,`${Ie}`)}`)}),be.push(`prod *= ${c[vt].getByIndices(`input${vt}Indices`)};`)}}),de.push(`for(var ${Ie}: u32 = 0; ${Ie} < uniforms.${Gs(Ie)}; ${Ie}++) {`),we.push("}")});let De=he?[...H,`let sum = ${c.map((Ae,Ie)=>Ae.getByIndices(`input${Ie}Indices`)).join(" * ")};`]:[...H,v,...de,...te,q,...be,oe,...we];return`
            ${$.registerUniforms(x.map(Ae=>({name:`${Gs(Ae)}`,type:"u32"}))).registerUniform("outputSize","u32").declareVariables(...c,d)}

            ${$.mainStart()}
            ${$.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}
            var outputIndices = ${d.offsetToIndices("global_idx")};
            ${c.map((Ae,Ie)=>`var input${Ie}Indices: ${c[Ie].type.indices};`).join(`
`)}
            ${De.join(`
`)};
            ${d.setByOffset("global_idx","sum")};
          }`};return{name:"Einsum",shaderCache:{hint:s.equation,inputDependencies:n.map(()=>"rank")},getRunData:()=>{let $=x.filter(q=>s.symbolToInfo.has(q)).map(q=>{var v;return{type:12,data:((v=s.symbolToInfo.get(q))==null?void 0:v.dimValue)||0}});$.push({type:12,data:f});let H=n.map((q,v)=>[...At(q)]).reduce((q,v)=>q.concat(v),$);return H.push(...At(u)),{outputs:[{dims:u,dataType:i}],dispatchGroup:{x:Math.ceil(f/64)},programUniforms:H}},getShaderSource:k}},Md=(n,i)=>{let s=new _f(n.inputs,i.equation),u=s.outputDims,c=n.inputs.map((f,d)=>f.dims);n.compute(xd(c,n.inputs[0].dataType,s,u))},Td=n=>{let i=n.equation.replace(/\s+/g,"");return qt({equation:i})}}),vl,Hs,kd,Sd,bl,_m=h(()=>{Zt(),Jt(),ar(),vl=n=>{if(!n||n.length!==2)throw new Error("Expand requires 2 input.");let i=n[0].dims,s=Array.from(n[1].getBigInt64Array(),Number),u=s.length<i.length?0:s.length-i.length,c=i.length<s.length?0:i.length-s.length;for(;u<s.length&&c<i.length;++u,++c)if(s[u]!==i[c]&&s[u]!==1&&i[c]!==1)throw new Error("Expand requires shape to be broadcastable to input")},Hs=(n,i)=>{let s=n.length-i.length,u=[];for(let c=0;c<s;++c)u.push(n[c]);for(let c=0;c<i.length;++c)u.push(i[c]===1?n[c+s]:i[c]);return u},kd=(n,i)=>n.length>i.length?Hs(n,i):Hs(i,n),Sd=n=>{let i=n[0].dims,s=Array.from(n[1].getBigInt64Array(),Number),u=kd(i,s),c=n[0].dataType,f=c===9?4:1,d=Math.ceil(ct.size(u)/f),x=$=>{let H=_t("input",c,i.length,f),q=Gt("output",c,u.length,f),v;if(c===9){let oe=(te,de,we="")=>`
          let outputIndices${de} = ${q.offsetToIndices(`outputOffset + ${de}u`)};
          let offset${de} = ${H.broadcastedIndicesToOffset(`outputIndices${de}`,q)};
          let index${de} = offset${de} / 4u;
          let component${de} = offset${de} % 4u;
          ${te}[${de}] = ${we}(${H.getByOffset(`index${de}`)}[component${de}]);
        `;v=`
        let outputOffset = global_idx * ${f};
        var data = vec4<u32>(0);
        ${oe("data",0,"u32")}
        ${oe("data",1,"u32")}
        ${oe("data",2,"u32")}
        ${oe("data",3,"u32")}
        ${q.setByOffset("global_idx","data")}
      }`}else v=`
        let outputIndices = ${q.offsetToIndices("global_idx")};
        let inputOffset = ${H.broadcastedIndicesToOffset("outputIndices",q)};
        ${q.setByOffset("global_idx",H.getByOffset("inputOffset"))}
      }`;return`
    ${$.registerUniform("vec_size","u32").declareVariables(H,q)}
    ${$.mainStart()}
    ${$.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.vec_size")}
    ${v}`},k=[{type:12,data:d},...At(i,u)];return{name:"Expand",shaderCache:{hint:`${u.length}`,inputDependencies:["rank"]},getShaderSource:x,getRunData:()=>({outputs:[{dims:u,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(d/64)},programUniforms:k})}},bl=n=>{vl(n.inputs),n.compute(Sd(n.inputs),{inputs:[0]})}}),yf,Ed,vf=h(()=>{Zt(),Jt(),ar(),Ha(),yf=n=>{let i=n[0].dataType,s=ct.size(n[0].dims),u=ct.size(n[1].dims),c=u%4===0,f=d=>{let x=_t("x",i,[1],4),k=_t("bias",i,[1],4),$=Gt("y",i,[1],4),H=[{name:"output_vec_size",type:"u32"},{name:"bias_size",type:"u32"}],q=oe=>`
      let bias${oe}_offset: u32 = (global_idx * 4 + ${oe}) % uniforms.bias_size;
      let bias${oe} = ${k.getByOffset(`bias${oe}_offset / 4`)}[bias${oe}_offset % 4];`,v=c?`
      let bias = ${k.getByOffset("global_idx % (uniforms.bias_size / 4)")};`:`${q(0)}${q(1)}${q(2)}${q(3)}
      let bias = ${x.type.value}(bias0, bias1, bias2, bias3);`;return`${d.registerUniforms(H).declareVariables(x,k,$)}

    ${Va(Er(i))}

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

      let x = ${x.getByOffset("global_idx")};
      ${v}
      let x_in = x + bias;
      ${$.setByOffset("global_idx",Wa("x_in"))}
    }`};return{name:"FastGeluWithBias",shaderCache:{hint:`${c}`,inputDependencies:["type","type"]},getShaderSource:f,getRunData:d=>({outputs:[{dims:d[0].dims,dataType:d[0].dataType}],programUniforms:[{type:12,data:Math.ceil(s/4)},{type:12,data:u}],dispatchGroup:{x:Math.ceil(s/Un/4)}})}},Ed=n=>{n.inputs.length<2||ct.size(n.inputs[1].dims)===0?Ec(n):n.compute(yf(n.inputs))}}),Cd,Pd,$d,Ad,bf=h(()=>{Zt(),Jt(),_r(),ar(),Cd=n=>{if(!n||n.length!==2)throw new Error("Gather requires 2 inputs.")},Pd=(n,i)=>{let s=n[0].dims,u=n[1].dims,c=s.length,f=ct.normalizeAxis(i.axis,c),d=s.slice(0);d.splice(f,1,...u);let x=s[f],k=n[0].dataType===9?4:1,$=Math.ceil(ct.size(d)/k),H=[{type:12,data:$},{type:6,data:x},{type:12,data:f},...At(n[0].dims,n[1].dims,d)],q=v=>{let oe=_t("data",n[0].dataType,n[0].dims.length,k),te=_t("inputIndices",n[1].dataType,n[1].dims.length),de=Gt("output",n[0].dataType,d.length,k),we=he=>{let De=u.length,Ae=`var indicesIndices${he}  = ${te.type.indices}(0);`;for(let Ie=0;Ie<De;Ie++)Ae+=`${De>1?`indicesIndices${he}[${Ie}]`:`indicesIndices${he}`} = ${d.length>1?`outputIndices${he}[uniforms.axis + ${Ie}]`:`outputIndices${he}`};`;Ae+=`
          var idx${he} = ${te.getByIndices(`indicesIndices${he}`)};
          if (idx${he} < 0) {
            idx${he} = idx${he} + uniforms.axisDimLimit;
          }
          var dataIndices${he} : ${oe.type.indices};
        `;for(let Ie=0,gt=0;Ie<c;Ie++)Ie===f?(Ae+=`${c>1?`dataIndices${he}[${Ie}]`:`dataIndices${he}`} = u32(idx${he});`,gt+=De):(Ae+=`${c>1?`dataIndices${he}[${Ie}]`:`dataIndices${he}`} = ${d.length>1?`outputIndices${he}[${gt}]`:`outputIndices${he}`};`,gt++);return Ae},be;if(n[0].dataType===9){let he=(De,Ae,Ie="")=>`
          let outputIndices${Ae} = ${de.offsetToIndices(`outputOffset + ${Ae}u`)};
          ${we(Ae)};
          let offset${Ae} = ${oe.indicesToOffset(`dataIndices${Ae}`)};
          let index${Ae} = offset${Ae} / 4u;
          let component${Ae} = offset${Ae} % 4u;
          ${De}[${Ae}] = ${Ie}(${oe.getByOffset(`index${Ae}`)}[component${Ae}]);
        `;be=`
        let outputOffset = global_idx * ${k};
        var value = vec4<u32>(0);
        ${he("value",0,"u32")}
        ${he("value",1,"u32")}
        ${he("value",2,"u32")}
        ${he("value",3,"u32")}
        ${de.setByOffset("global_idx","value")}
      `}else be=`
      let outputIndices = ${de.offsetToIndices("global_idx")};
      ${we("")};
      let value = ${oe.getByIndices("dataIndices")};
      ${de.setByOffset("global_idx","value")};
      `;return`
      ${v.registerUniform("outputSize","u32").registerUniform("axisDimLimit","i32").registerUniform("axis","u32").declareVariables(oe,te,de)}
      ${v.mainStart()}
        ${v.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}
        ${be}
      }`};return{name:"Gather",shaderCache:{hint:i.cacheKey,inputDependencies:["rank","rank"]},getRunData:()=>({outputs:[{dims:d,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil($/64)},programUniforms:H}),getShaderSource:q}},$d=n=>qt({axis:n.axis}),Ad=(n,i)=>{let s=n.inputs;Cd(s),n.compute(Pd(n.inputs,i))}}),Id,Fd,Od,zd,xf=h(()=>{Zt(),Jt(),_r(),ar(),Id=n=>{if(!n||n.length!==2)throw new Error("GatherElements requires 2 inputs.");if(n[0].dims.length<1)throw new Error("GatherElements requires that the data input be rank >= 1.");if(n[0].dims.length!==n[1].dims.length)throw new Error(`GatherElements requires that the data input and
                     indices input tensors be of same rank.`)},Fd=(n,i)=>{let s=n[0].dims,u=n[0].dataType,c=s.length,f=n[1].dims,d=n[1].dataType,x=ct.normalizeAxis(i.axis,c),k=s[x],$=f.slice(0),H=ct.size($),q=_t("input",u,c),v=_t("indicesInput",d,f.length),oe=Gt("output",u,$.length),te=[{type:12,data:H},{type:6,data:k},{type:12,data:x}];return te.push(...At(s,f,$)),{name:"GatherElements",shaderCache:{inputDependencies:["rank","rank"]},getRunData:()=>({outputs:[{dims:$,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(H/64)},programUniforms:te}),getShaderSource:de=>`
      ${de.registerUniform("outputSize","u32").registerUniform("axisDimLimit","i32").registerUniform("axis","u32").declareVariables(q,v,oe)}
      ${de.mainStart()}
      ${de.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}

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

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

      ${oe.setByOffset("global_idx","value")};
  }`}},Od=n=>qt({axis:n.axis}),zd=(n,i)=>{let s=n.inputs;Id(s),n.compute(Fd(n.inputs,i))}}),Dd,Ld,Rd,Mf,Bd=h(()=>{Zt(),Jt(),ar(),Dd=n=>{if(!n)throw new Error("Input is missing");if(n.length<2||n.length>3)throw new Error("Invaid input number.");if(n.length===3&&n[2].dims.length>2)throw new Error("Invalid input shape of C");if(n[0].dataType!==n[1].dataType||n.length===3&&n[0].dataType!==n[2].dataType)throw new Error("Input types are mismatched")},Ld=(n,i)=>{let s=n[0].dims.slice(),u=n[1].dims.slice(),[c,f,d]=Tr.getShapeOfGemmResult(s,i.transA,u,i.transB,n.length===3?n[2].dims:void 0),x=[c,f];if(!x)throw new Error("Can't use gemm on the given tensors");let k=ct.size(x),$=[{type:12,data:k},{type:12,data:c},{type:12,data:f},{type:12,data:d},{type:1,data:i.alpha},{type:1,data:i.beta}],H=["type","type"];n.length===3&&($.push(...At(n[2].dims)),H.push("rank")),$.push(...At(x));let q=v=>{let oe="";i.transA&&i.transB?oe="value += a[k * uniforms.M + m] * b[n * uniforms.K + k];":i.transA&&!i.transB?oe="value += a[k * uniforms.M + m] * b[k * uniforms.N + n];":!i.transA&&i.transB?oe="value += a[m * uniforms.K + k] * b[n * uniforms.K + k];":!i.transA&&!i.transB&&(oe="value += a[m * uniforms.K + k] * b[k * uniforms.N + n];");let te=i.alpha===1?"":"value *= uniforms.alpha;",de=_t("a",n[0].dataType,n[0].dims),we=_t("b",n[1].dataType,n[1].dims),be=de.type.value,he=null,De=[de,we];n.length===3&&(he=_t("c",n[2].dataType,n[2].dims.length),De.push(he));let Ae=Gt("output",n[0].dataType,x.length);De.push(Ae);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(...De)}

  ${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++) {
      ${oe}
    }

    ${te}
    ${he!=null?`let cOffset = ${he.broadcastedIndicesToOffset("vec2(m, n)",Ae)}; value += ${be}(uniforms.beta) * ${he.getByOffset("cOffset")};`:""}
    output[global_idx] = value;
  }`};return{name:"Gemm",shaderCache:{hint:`${i.cacheKey}`,inputDependencies:H},getRunData:()=>({outputs:[{dims:x,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(k/64)},programUniforms:$}),getShaderSource:q}},Rd=n=>{let i=n.transA,s=n.transB,u=n.alpha,c=n.beta;return{transA:i,transB:s,alpha:u,beta:c,cacheKey:`${n.transA};${n.transB};${n.alpha===1}`}},Mf=(n,i)=>{Dd(n.inputs),n.compute(Ld(n.inputs,i))}}),Pn,Nd,jd,xl,Ud,Zo,Vd,Wd=h(()=>{Zt(),Jt(),_r(),pe(),zs(),ar(),yo(),Pn=(n,i)=>n.length>i&&n[i].dims.length>0&&ct.size(n[i].dims)>0?n[i]:void 0,Nd=(n,i)=>{let s=n[0],u=Pn(n,1),c=Pn(n,2),f=Pn(n,3),d=Pn(n,4),x=Pn(n,5),k=Pn(n,6),$=Pn(n,7);if(s.dims.length!==3&&s.dims.length!==5)throw new Error("Input query is expected to have 3 or 5 dimensions");let H=!1,q=s.dims[0],v=s.dims[1],oe=s.dims.length===3?H?s.dims[2]/3:s.dims[2]:i.numHeads*s.dims[4],te=v,de=0,we=0,be=Math.floor(oe/i.numHeads);if(k&&$){if(k.dims.length!==4)throw new Error('Input "past_key" is expected to have 4 dimensions');if(k.dims[0]!==q||k.dims[1]!==i.numHeads||k.dims[3]!==be)throw new Error('Input "past_key" shape (batch_size, num_heads, past_sequence_length, head_size)');if($.dims[0]!==q||$.dims[1]!==i.numHeads||$.dims[3]!==be)throw new Error('Input "past_value" shape (batch_size, num_heads, past_sequence_length, head_size)');if(k.dims[2]!==$.dims[2])throw new Error('Input "past_key" and "past_value" shall have same dim 2 (past_sequence_length)');if($.dims.length!==4)throw new Error('Input "past_value" is expected to have 4 dimensions');de=k.dims[2],we=k.dims[2]}else if(k||$)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(u.dims[2]!==s.dims[2])throw new Error('Input "query" and "key" shall have same dim 2 (hidden_size)');he=2,te=u.dims[1]}else if(u.dims.length===5){if(u.dims[2]!==i.numHeads||u.dims[3]!==2||u.dims[4]!==be)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,te=u.dims[1]}else{if(u.dims[1]!==i.numHeads||u.dims[3]!==be)throw new Error('Expect "key" shape (batch_size, num_heads, kv_sequence_length, head_size) for past_key');he=0,te=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}if(f){if(f.dims.length!==1)throw new Error('Input "bias" is expected to have 1 dimension');if(c&&s.dims.length===5&&s.dims[3]===2)throw new Error("bias is not allowed for packed kv.")}let De=0;if(d){De=8;let vt=d.dims;throw vt.length===1?vt[0]===q?De=1:vt[0]===3*q+2&&(De=3):vt.length===2&&vt[0]===q&&vt[1]===te&&(De=5),De===8?new Error('Input "key_padding_mask" shape shall be (batch_size) or (batch_size, kv_sequence_length)'):new Error("Mask not supported")}let Ae=!1,Ie=oe;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(te!==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(te!==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],Ae=!0}}let gt=de+te,ut=!1;if(d)throw new Error("Key padding mask is not supported");if(x){if(x.dims.length!==4)throw new Error('Input "relative_position_bias" is expected to have 4 dimensions');if(x.dims[0]!==q&&x.dims[0]!==1||x.dims[1]!==i.numHeads||x.dims[2]!==v||x.dims[3]!==gt)throw new Error('Input "relative_position_bias" shape (batch_size, 1, sequence_length, kv_sequence_length)')}return{batchSize:q,sequenceLength:v,pastSequenceLength:de,kvSequenceLength:te,totalSequenceLength:gt,maxSequenceLength:we,inputHiddenSize:0,hiddenSize:oe,vHiddenSize:Ie,headSize:be,vHeadSize:Math.floor(Ie/i.numHeads),numHeads:i.numHeads,isUnidirectional:!1,pastPresentShareBuffer:!1,maskFilterValue:i.maskFilterValue,maskType:De,scale:i.scale,broadcastResPosBias:ut,passPastInKv:Ae,qkvFormat:he}},jd=n=>qt({...n}),xl=qt({perm:[0,2,1,3]}),Ud=(n,i,s,u,c,f,d)=>{let x=[u,c,f],k=ct.size(x),$=[{type:12,data:k},{type:12,data:d},{type:12,data:f}],H=q=>{let v=Gt("qkv_with_bias",i.dataType,x),oe=_t("qkv",i.dataType,x),te=_t("bias",s.dataType,x),de=[{name:"output_size",type:"u32"},{name:"bias_offset",type:"u32"},{name:"hidden_size",type:"u32"}];return`
  ${q.registerUniforms(de).declareVariables(oe,te,v)}
  ${q.mainStart()}
    ${q.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 n.compute({name:"MultiHeadAttentionAddBias",shaderCache:{inputDependencies:["type","type"]},getRunData:()=>({outputs:[{dims:x,dataType:i.dataType,gpuDataType:0}],dispatchGroup:{x:Math.ceil(k/64)},programUniforms:$}),getShaderSource:H},{inputs:[i,s],outputs:[-1]})[0]},Zo=(n,i,s,u,c,f,d,x)=>{let k=f;if(d){if(u===1)throw new Error("AddBiasReshape is not implemented. Please export your model with packed QKV or KV");return k=Ud(n,f,d,i,u,s*c,x),k=k.reshape([i,u,s,c]),n.compute(hi(k,xl.perm),{inputs:[k],outputs:[-1]})[0]}else return f.dims.length===3&&(k=f.reshape([i,u,s,c])),n.compute(hi(k,xl.perm),{inputs:[k],outputs:[-1]})[0]},Vd=(n,i)=>{let s=Nd(n.inputs,i),u=n.inputs[0],c=Pn(n.inputs,1),f=Pn(n.inputs,2),d=Pn(n.inputs,3),x=Pn(n.inputs,4),k=Pn(n.inputs,5),$=Pn(n.inputs,6),H=Pn(n.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 q=c&&f&&c.dims.length===4&&f.dims.length===4,v=Zo(n,s.batchSize,s.numHeads,s.sequenceLength,s.headSize,u,d,0);if(q)return vo(n,v,c,f,x,void 0,$,H,k,s,i);if(!c||!f)throw new Error("key and value must be provided");let oe=Zo(n,s.batchSize,s.numHeads,s.kvSequenceLength,s.headSize,c,d,s.hiddenSize),te=Zo(n,s.batchSize,s.numHeads,s.kvSequenceLength,s.vHeadSize,f,d,2*s.hiddenSize);vo(n,v,oe,te,x,void 0,$,H,k,s,i)}}),Ml,Gd,Hd,Tl,qd,Kd=h(()=>{Zt(),Jt(),ar(),Ml=n=>Array.from(n.getBigInt64Array(),Number),Gd=n=>{if(!n||n.length!==2)throw new Error("Tile requires 2 inputs.");if(n[0].dataType!==1&&n[0].dataType!==10&&n[0].dataType!==6&&n[0].dataType!==12)throw new Error("Tile only support float, float16, int32, and uint32 data types");if(n[1].dataType!==7)throw new Error("Tile `repeats` input should be of int64 data type");if(n[1].dims.length!==1)throw new Error("Tile `repeats` input should be 1-D");if(Ml(n[1]).length!==n[0].dims.length)throw new Error("Tile `repeats` input should have same number of elements as rank of input data tensor")},Hd=(n,i)=>{let s=[];for(let u=0;u<n.length;++u)s.push(n[u]*i[u]);return s},Tl=(n,i)=>{let s=n[0].dims,u=i??Ml(n[1]),c=Hd(s,u),f=ct.size(c),d=n[0].dataType,x=_t("input",d,s.length),k=Gt("output",d,c.length),$=H=>`
      const inputShape = ${x.indices(...s)};
      ${H.registerUniform("output_size","u32").declareVariables(x,k)}
      ${H.mainStart()}
      ${H.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
      let output_indices = ${k.offsetToIndices("global_idx")};
      var input_indices: ${x.type.indices};
      for (var i = 0; i < ${s.length}; i++) {
        let input_dim_i = ${x.indicesGet("uniforms.input_shape","i")};
        let input_dim_value = ${k.indicesGet("output_indices","i")}  % input_dim_i;

        ${x.indicesSet("input_indices","i","input_dim_value")}
      }
      ${k.setByOffset("global_idx",x.getByIndices("input_indices"))}
    }`;return{name:"Tile",shaderCache:{hint:`${u}`,inputDependencies:["rank"]},getRunData:()=>({outputs:[{dims:c,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(f/64)},programUniforms:[{type:12,data:f},...At(n[0].dims,c)]}),getShaderSource:$}},qd=n=>{Gd(n.inputs),n.compute(Tl(n.inputs),{inputs:[0]})}}),Xd,kl,Qd,Yd,Sl,Zd,Tf=h(()=>{Zt(),Jt(),_r(),zs(),ar(),Wd(),Kd(),yo(),Xd=(n,i)=>{let s=n[0],u=n[1],c=n[2],f=n[3],d=n[4];if(s.dims.length!==3&&s.dims.length!==5)throw new Error("Input query is expected to have 3 or 5 dimensions");let x=!1,k=s.dims[0],$=s.dims[1],H=s.dims.length===3?x?s.dims[2]/3:s.dims[2]:i.numHeads*s.dims[4],q=$,v=0,oe=0,te=Math.floor(H/i.numHeads),de=f&&f.dims.length!==0,we=d&&d.dims.length!==0,be=!0;if(de&&we){if(f.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=f.dims[1],oe=f.dims[1]}else if(de||we)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,q=u.dims[1]}else if(u.dims.length===5){if(u.dims[2]!==i.numHeads||u.dims[3]!==2||u.dims[4]!==te)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,q=u.dims[1]}else{if(u.dims[1]!==i.numHeads||u.dims[3]!==te)throw new Error('Expect "key" shape (batch_size, num_heads, kv_sequence_length, head_size) for past_key');he=0,q=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 De=0,Ae=!1,Ie=H;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(q!==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(q!==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],Ae=!0}}let gt=v+q;return{batchSize:k,sequenceLength:$,pastSequenceLength:v,kvSequenceLength:q,totalSequenceLength:gt,maxSequenceLength:oe,inputHiddenSize:0,hiddenSize:H,vHiddenSize:Ie,headSize:te,vHeadSize:Math.floor(Ie/i.kvNumHeads),numHeads:i.numHeads,kvNumHeads:i.kvNumHeads,nReps:i.numHeads/i.kvNumHeads,pastPresentShareBuffer:!1,maskType:De,scale:i.scale,broadcastResPosBias:!1,passPastInKv:Ae,qkvFormat:he,isPastkvBSNH:be}},kl=(n,i,s,u)=>{let c=[u.batchSize,u.totalSequenceLength,u.kvNumHeads,u.headSize],f=4,d=ct.size(c)/f,x=u.totalSequenceLength,k=Gt("present_kv",s,c.length,f),$=_t("new_kv",n.dataType,n.dims.length,f),H=i?_t("past_kv",i.dataType,i.dims.length,f):void 0,q=Math.ceil(u.headSize/f),v={x,y:n.dims[0],z:1},oe=i?["rank","rank"]:["rank"],te=[{type:12,data:d},{type:12,data:u.pastSequenceLength},{type:12,data:u.kvSequenceLength},{type:12,data:u.totalSequenceLength}],de=[$];H?(te.push(...At(n.dims),...At(i.dims),...At(c)),de.push(H)):te.push(...At(n.dims),...At(c));let we=[{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];`,De=i?`if (s < past_seqlen) {
        ${be}
        } else if (s < past_seqlen + uniforms.new_seqlen) {
        ${he}
        }`:`if (s < past_seqlen + uniforms.new_seqlen) {
          ${he}
        }`,Ae=Ie=>`

  ${Ie.registerUniforms(we).declareVariables(...de,k)}
  ${Ie.mainStart([q,u.kvNumHeads,1])}
    ${Ie.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
    var indices = ${k.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 = ${q}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;
    ${De}
  }`;return{name:"ConcatPastNew",shaderCache:{hint:`${u.kvNumHeads}${q}${!!i}`,inputDependencies:oe},getRunData:()=>({outputs:[{dims:c,dataType:s}],dispatchGroup:v,programUniforms:te}),getShaderSource:Ae}},Qd=n=>qt({...n}),Yd=qt({perm:[0,2,1,3]}),Sl=(n,i,s,u,c)=>{let f=i,d=u.kvNumHeads,x=u.nReps;return i.dims.length===3&&u.kvSequenceLength!==0&&(f=i.reshape([u.batchSize,u.kvSequenceLength,d,u.headSize])),s?f=n.compute(kl(f,s,f.dataType,u),{inputs:[f,s],outputs:[u.isPastkvBSNH?c:-1]})[0]:f=n.compute(kl(f,void 0,f.dataType,u),{inputs:[f],outputs:[u.isPastkvBSNH?c:-1]})[0],x!==1&&(f=n.compute(Tl([f],[1,1,1,x]),{inputs:[f],outputs:[-1]})[0],f=f.reshape([u.batchSize,u.totalSequenceLength,d*x,u.headSize])),n.compute(hi(f,Yd.perm),{inputs:[f],outputs:[-1]})[0]},Zd=(n,i)=>{var k;let s=Xd(n.inputs,i);if(n.inputs[0].dims.length===5)throw new Error("Packed QKV is not implemented");if(((k=n.inputs[1])==null?void 0:k.dims.length)===5)throw new Error("Packed KV is not implemented");let u=Zo(n,s.batchSize,s.numHeads,s.sequenceLength,s.headSize,n.inputs[0],void 0,0),c=n.inputs[3]&&n.inputs[3].dims.length!==0?n.inputs[3]:void 0,f=n.inputs[4]&&n.inputs[4].dims.length!==0?n.inputs[4]:void 0,d=Sl(n,n.inputs[1],c,s,1),x=Sl(n,n.inputs[2],f,s,2);vo(n,u,d,x,void 0,void 0,void 0,void 0,void 0,s,i)}}),Jd,ep,tp,rp,wm=h(()=>{Zt(),Jt(),ar(),Jd=(n,i)=>{let s=n[0].dims,u=s,c=2,f=ct.sizeToDimension(s,c),d=ct.sizeFromDimension(s,c),x=vr(d),k=d/x,$=[s[0],s[1],k],H=["rank","type","type"],q=[{type:12,data:d},{type:12,data:k}];q.push(...At($,$));let v=oe=>{let te=_t("x",n[0].dataType,$.length,x),de=_t("scale",n[1].dataType,n[1].dims),we=_t("bias",n[2].dataType,n[2].dims),be=Gt("output",n[0].dataType,$.length,x),he=[te,de,we,be],De=te.type.value,Ae=x===1?"f32":`vec${x}<f32>`,Ie=64,gt=[{name:"normSize",type:"u32"},{name:"normPackedSize",type:"u32"}];return`
  var<workgroup> meanShared : f32;
  var<workgroup> squaredNormShared : f32;
  var<workgroup> workgroupShared : array<${Ae}, ${Ie}>;
  const workgroupSize = ${Ie}u;
  ${oe.registerUniforms(gt).declareVariables(...he)}
  ${oe.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 = ${Ae}(0);
    for (var h = localIndex; h < uniforms.normPackedSize; h += workgroupSize) {
      initial = initial + ${Ae}(${te.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 = ${Vn("workgroupShared[0]",x)} / f32(uniforms.normSize);
    }
    workgroupBarrier();

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

    let invStdDev = inverseSqrt(squaredNormShared / f32(uniforms.normSize) + f32(${i.epsilon}));
    let channelScale = invStdDev * f32(${de.getByOffset("channel")});
    let channelShift = f32(${we.getByOffset("channel")}) - meanShared * channelScale;
    for (var h = localIndex; h < uniforms.normPackedSize; h += workgroupSize) {
      let value = ${te.get("batch","channel","h")} * ${De}(${Ae}(channelScale)) + ${De}(${Ae}(channelShift));
      ${be.set("batch","channel","h","value")};
    }
  }`};return{name:"InstanceNormalization",shaderCache:{hint:`${i.epsilon};${x}`,inputDependencies:H},getRunData:()=>({outputs:[{dims:u,dataType:n[0].dataType}],dispatchGroup:{x:f},programUniforms:q}),getShaderSource:v}},ep=(n,i,s,u,c,f,d,x)=>{let k=vr(d),$=64,H=k===1?"vec2f":`mat2x${k}f`,q=k===1?"f32":`vec${k}f`,v=(gt,ut)=>`${H}(${gt}, ${ut})`,oe=c*d/k,te=Math.ceil(f/$),de=["type"],we=[{type:12,data:te},{type:12,data:f},{type:12,data:Math.floor(d/k)},{type:12,data:Math.floor(f*d/k)}],be=gt=>{let ut=_t("input",i.dataType,i.dims,k);return`
  ${gt.declareVariables(ut)}
  @group(0) @binding(1) var<storage, read_write> output : array<${H}>;
  struct Uniforms {wg_size:u32, H:u32, C:u32, image_size:u32};
  @group(0) @binding(2) var<uniform> uniforms: Uniforms;

  ${gt.mainStart($)}
    let currentImageNumber = global_idx / ${$} / uniforms.C;
    let currentChannelNumber = (global_idx / ${$}) % 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 = ${Lr("f32",k)};
    var squaredSum = ${Lr("f32",k)};
    for (var i: u32 = wgOffset; i < wgMax; i++) {
        let value = ${q}(input[offset + i * uniforms.C]);
        sum += value;
        squaredSum += value * value;
    }
    output[global_idx] = ${v("sum","squaredSum")};
  }`},he=n.compute({name:"InstanceNormComputeMean",shaderCache:{hint:`${k}`,inputDependencies:de},getRunData:()=>({outputs:[{dims:[c,d,$,2],dataType:1}],dispatchGroup:{x:c*d/k},programUniforms:we}),getShaderSource:be},{inputs:[i],outputs:[-1]})[0],De=[{type:12,data:oe},{type:12,data:f},{type:12,data:Math.floor(d/k)},{type:12,data:Math.floor($*d/k)}],Ae=["type","type","type"],Ie=gt=>{let ut=_t("scale",s.dataType,s.dims,k),vt=_t("bias",u.dataType,u.dims,k);return`
  @group(0) @binding(0) var<storage, read> input : array<${H}>;
  @group(0) @binding(1) var<storage, read> scale : array<${ut.type.storage}>;
  @group(0) @binding(2) var<storage, read> bias : array<${vt.type.storage}>;
  @group(0) @binding(3) var<storage, read_write> output : array<${H}>;
  struct Uniforms {units_of_work : u32, H: u32, C : u32, image_size : u32};
  @group(0) @binding(4) var<uniform> uniforms: Uniforms;

  ${gt.mainStart()}
    ${gt.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 = ${Lr("f32",k)};
    var squaredSum = ${Lr("f32",k)};
    for (var i: u32 = 0; i < min(${$}, uniforms.H); i++) {
        let value = input[offset + i + currentChannelNumber * ${$}];
        sum += value[0];
        squaredSum += value[1];
    }
    sum = sum / f32(uniforms.H);
    squaredSum = squaredSum / f32(uniforms.H);
    let invStdDev = inverseSqrt(squaredSum - sum * sum + f32(${x}));
    let channelScale = invStdDev * ${q}(scale[currentChannelNumber]);
    let channelShift = ${q}(bias[currentChannelNumber]) - sum * channelScale;

    output[global_idx] = ${v("channelScale","channelShift")};
  }`};return n.compute({name:"InstanceNormComputeChannelScaleShift",shaderCache:{hint:`${k};${x}`,inputDependencies:Ae},getRunData:()=>({outputs:[{dims:[c,d,2],dataType:1}],dispatchGroup:{x:Math.ceil(oe/64)},programUniforms:De}),getShaderSource:Ie},{inputs:[he,s,u],outputs:[-1]})[0]},tp=(n,i,s)=>{let u=i[0].dims,c=u,f=u[0],d=u[u.length-1],x=ct.sizeFromDimension(u,1)/d,k=vr(d),$=ct.size(c)/k,H=[{type:12,data:x},{type:12,data:Math.floor(d/k)}],q=["type","type"],v=ep(n,i[0],i[1],i[2],f,x,d,s.epsilon),oe=te=>{let de=Sr(i[0].dataType),we=k===1?"vec2f":`mat2x${k}f`,be=k===1?de:`vec${k}<${de}>`,he=_t("input",i[0].dataType,i[0].dims,k),De=Gt("output",i[0].dataType,c,k);return`
  @group(0) @binding(0) var<storage, read> input : array<${he.type.storage}>;
  @group(0) @binding(1) var<storage, read> scaleInput : array<${we}>;
  @group(0) @binding(2) var<storage, read_write> output : array<${De.type.storage}>;
  struct Uniforms {H: u32, C : u32};
  @group(0) @binding(3) var<uniform> uniforms: Uniforms;

  ${te.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]), ${be}(scale[1]));
  }`};n.compute({name:"InstanceNormalizationNHWC",shaderCache:{hint:`${k}`,inputDependencies:q},getRunData:()=>({outputs:[{dims:c,dataType:i[0].dataType}],dispatchGroup:{x:Math.ceil($/64)},programUniforms:H}),getShaderSource:oe},{inputs:[i[0],v]})},rp=(n,i)=>{i.format==="NHWC"?tp(n,n.inputs,i):n.compute(Jd(n.inputs,i))}}),ur,np,hn,bn=h(()=>{Zt(),Jt(),ar(),ur=n=>{if(!n||n.length<2)throw new Error("layerNorm requires at least 2 inputs.")},np=(n,i,s)=>{let u=i.simplified,c=n[0].dims,f=n[1],d=!u&&n[2],x=c,k=ct.normalizeAxis(i.axis,c.length),$=ct.sizeToDimension(c,k),H=ct.sizeFromDimension(c,k),q=ct.size(f.dims),v=d?ct.size(d.dims):0;if(q!==H||d&&v!==H)throw new Error(`Size of X.shape()[axis:] == ${H}.
       Size of scale and bias (if provided) must match this.
       Got scale size of ${q} and bias size of ${v}`);let oe=[];for(let Ie=0;Ie<c.length;++Ie)Ie<k?oe.push(c[Ie]):oe.push(1);let te=vr(H),de=["type","type"],we=[{type:12,data:$},{type:1,data:H},{type:12,data:Math.floor(H/te)},{type:1,data:i.epsilon}];d&&de.push("type");let be=s>1,he=s>2,De=Ie=>{let gt=Sr(n[0].dataType),ut=[_t("x",n[0].dataType,n[0].dims,te),_t("scale",f.dataType,f.dims,te)];d&&ut.push(_t("bias",d.dataType,d.dims,te)),ut.push(Gt("output",n[0].dataType,x,te)),be&&ut.push(Gt("mean_data_output",1,oe)),he&&ut.push(Gt("inv_std_output",1,oe));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(...ut)}
  ${Ie.mainStart()}
    ${Ie.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.norm_count")}
    let offset = global_idx * uniforms.norm_size_vectorized;
    var mean_vector = ${Lr("f32",te)};
    var mean_square_vector = ${Lr("f32",te)};

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

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

    ${be?"mean_data_output[global_idx] = mean":""};
    ${he?"inv_std_output[global_idx] = inv_std_dev":""};
  }`},Ae=[{dims:x,dataType:n[0].dataType}];return be&&Ae.push({dims:oe,dataType:1}),he&&Ae.push({dims:oe,dataType:1}),{name:"LayerNormalization",shaderCache:{hint:`${te};${s};${u}`,inputDependencies:de},getRunData:()=>({outputs:Ae,dispatchGroup:{x:Math.ceil($/64)},programUniforms:we}),getShaderSource:De}},hn=(n,i)=>{ur(n.inputs),n.compute(np(n.inputs,i,n.outputCount))}}),xn,to,kf,ip,Sf=h(()=>{Zt(),Jt(),_r(),ar(),xn=(n,i)=>{if(n.length<3||n.length>4)throw new Error("MatMulNBits requires 3 or 4 inputs");let s=n[0],u=s.dims.length;if(s.dims[u-1]!==i.k)throw new Error("The last dim of input shape does not match the k value");let c=Math.floor((i.k+i.blockSize-1)/i.blockSize),f=i.blockSize/8*i.bits,d=n[1];if(!ct.areEqual(d.dims,[i.n,c,f]))throw new Error("The second inputs must be 3D tensor with shape N X nBlocksPerCol X blobSize");let x=n[2].dims;if(ct.size(x)!==i.n*c)throw new Error("scales input size error.");if(n.length===4){let k=n[3].dims,$=i.bits>4?i.n*c:i.n*Math.floor((c+1)/2);if(ct.size(k)!==$)throw new Error("zeroPoints input size error.")}},to=(n,i,s,u)=>{let c=n[0].dims,f=c.length,d=Math.floor((i.k+i.blockSize-1)/i.blockSize),x=c[f-2],k=i.k,$=i.n,H=c.slice(0,f-2),q=ct.size(H),v=i.blockSize/8*i.bits/4,oe=n[0].dataType,te=vr(x),de=vr(i.k),we=vr(v),be=ki(oe),he=x*d*be,De=Math.floor(u/he),Ae=d<=s[0]&&De>0,Ie=!Ae||De>=4?vr($):De>=2&&vr($)>=2?2:1,gt=H.concat([x,$]),ut=ct.size(gt)/Ie/te,vt=Ae?[]:[{type:12,data:ut},{type:12,data:i.blockSize}],Dt=[q,x,k/de],Rt=ct.convertShape(n[1].dims).slice();Rt.splice(-1,1,v/we),vt.push(...At(Dt)),vt.push(...At(Rt)),vt.push(...At(n[2].dims)),n.length===4&&vt.push(...At(ct.convertShape(n[3].dims)));let gr=[q,x,$/Ie];vt.push(...At(gr));let Mr=ir=>{let Fr=Dt.length,Zr=_t("a",n[0].dataType,Fr,de),hr=_t("b",12,Rt.length,we),Hr=_t("scales",n[2].dataType,n[2].dims.length),Nt=[Zr,hr,Hr],er=n.length===4?_t("zero_points",12,n[3].dims.length):void 0;er&&Nt.push(er);let yr=gr.length,ot=Gt("output",n[0].dataType,yr,Ie),Vt=[{name:"output_size",type:"u32"},{name:"block_size",type:"u32"}],nr=Sr(n[0].dataType),Wr=(()=>{switch(de){case 1:return`array<${nr}, 8>`;case 2:return`mat4x2<${nr}>`;case 4:return`mat2x4<${nr}>`;default:throw new Error(`${de}-component is not supported.`)}})(),pn=`
        for (var word: u32 = 0; word < ${v}; word += ${we}) {
          ${hr.indicesSet("b_indices","2","word")};
          let b_data = ${hr.getByIndices("b_indices")};
          for (var i: u32 = 0; i < ${we}; i++) {
            let b_value: u32 = ${we===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 = ${Wr}(${Array.from({length:4},(rs,si)=>`${nr}(b_value_lower[${si}]), ${nr}(b_value_upper[${si}])`).join(", ")});
            let b_dequantized_values = ${de===1?`${Wr}(${Array.from({length:8},(rs,si)=>`(b_quantized_values[${si}] - zero_point) * scale`).join(", ")});`:`(b_quantized_values - ${Wr}(${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 < ${Ae?x:te}u; m++) {
              ${Zr.indicesSet("a_indices",Fr-2,Ae?"m":`row * ${te} + m`)};
              ${Zr.indicesSet("a_indices",Fr-1,"word_offset")};
              var input_offset = ${Zr.indicesToOffset("a_indices")};
              var a_data: ${Wr};
              for (var j: u32 = 0; j < ${8/de}; j++) {
                a_data[j] = ${Zr.getByOffset("input_offset")};
                input_offset++;
              }
              ${Ae?"workgroup_shared[workgroup_shared_offset + m]":"output_values[m]"}${Ie>1?"[c]":""} += ${Array.from({length:8/de},(rs,si)=>`${de===1?`a_data[${si}] * b_dequantized_values[${si}]`:`dot(a_data[${si}], b_dequantized_values[${si}])`}`).join(" + ")};
            }
            word_offset += ${8/de};
          }
        }`,kn=er?`
          zero_point_offset += 4;
          if (zero_point_offset == 32) {
            zero_point_offset = 0;
            zero_point_index++;
            zero_point_word = ${er.getByOffset("zero_point_index")};
          }`:"";return Ae?`
        var<workgroup> workgroup_shared: array<${ot.type.value}, ${x*d}>;
        ${ir.declareVariables(...Nt,ot)}
        ${ir.mainStart([d,1,1])}
          var a_indices: ${Zr.type.indices};
          var block = local_id.x;
          var col = workgroup_id.y;
          var batch = workgroup_id.z;
          ${Zr.indicesSet("a_indices","0","batch")};
          // Two zero points are packed into one byte when uniforms.bits is 4.
          for (var c: u32 = 0; c < ${Ie}; c++) {
            let col_times_components_plus_c = col * ${Ie} + c;
              ${er?`
            var zero_point_bytes_per_col: u32 = (${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 = ${er.getByOffset("zero_point_word_index")} >> zero_point_bits_offset;`:""}
            var b_indices: ${hr.type.indices};
            ${hr.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 = ${Hr.getByOffset("scales_index")};
            // The default zero point is 8 for unsigned 4-bit quantization.
            let zero_point = ${nr}(${er?"(zero_point_word) & 0xFu":8});
            ${hr.indicesSet("b_indices","1","block")};
            var word_offset: u32 = block * ${i.blockSize/de};
            var workgroup_shared_offset: u32 = block * ${x};
            ${pn}
          }
          workgroupBarrier();
          var output_indices: ${ot.type.indices};
          var elements_per_thread: u32 = ${Math.ceil(x/d)};
          ${ot.indicesSet("output_indices","0","batch")};
          ${ot.indicesSet("output_indices",yr-1,"col")};
          ${ot.indicesSet("output_indices",yr-2,"local_id.x * elements_per_thread")};
          var output_offset = ${ot.indicesToOffset("output_indices")};
          for (var m: u32 = 0u; m < elements_per_thread; m++) {
            var row = m + local_id.x * elements_per_thread;
            if (row < ${x}) {
              var output_value: ${ot.type.value} = ${ot.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 += ${x};
              }
              ${ot.setByOffset("output_offset","output_value")};
              output_offset += ${$/Ie};
            }
          }
        }`:`
        ${ir.registerUniforms(Vt).declareVariables(...Nt,ot)}
        ${ir.mainStart()}
          ${ir.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
          var output_values: array<${ot.type.value}, ${te}>;
          var output_indices = ${ot.offsetToIndices("global_idx")};
          var col = ${ot.indicesGet("output_indices",yr-1)};
          var row = ${ot.indicesGet("output_indices",yr-2)};
          var a_indices: ${Zr.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
          ${er?`
          var zero_point_abs_offset = col * ${Ie} * ((${d} + 1) / 2);
          var zero_point_index: u32 = zero_point_abs_offset / 4;
          var zero_point_word: u32 = ${er.getByOffset("zero_point_index")};
          var zero_point_offset: u32 = (zero_point_abs_offset % 4) * 8;`:""}
          var scale_index = col * ${d*Ie};
          var b_indices: ${hr.type.indices};
          for (var c: u32 = 0; c < ${Ie}; c++) {
            ${hr.indicesSet("b_indices","0",`col * ${Ie} + 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 = ${Hr.getByOffset("scale_index")};
              // The default zero point is 8 for unsigned 4-bit quantization.
              let zero_point = ${nr}(${er?"extractBits(zero_point_word, zero_point_offset, 4)":8});
              ${hr.indicesSet("b_indices","1","block")};
              var word_offset: u32 = block_offset;
              ${pn}
              scale_index++;
              ${kn}
              block_offset += uniforms.block_size / ${de};
            }
            // Drop the trailing 4 bits if the zero_poit_offset is not a byte boundary to align with the next byte.
            ${er?`if (zero_point_offset % 8 > 0) {
                ${kn}
              }`:""}
            }
            for (var k: u32 = 0u; k < ${te}u; k++) {
              ${ot.indicesSet("output_indices",yr-2,`${te} * row + k`)};
              ${ot.setByIndices("output_indices","output_values[k]")}
            }
        }`};return{name:Ae?"BlockwiseMatMulNBits":"MatMulNBits",shaderCache:{hint:`${i.cacheKey};${x};${oe};${n.length}`,inputDependencies:Array(n.length).fill("rank")},getRunData:()=>({outputs:[{dims:gt,dataType:oe}],name:Ae?"BlockwiseMatMulNBits":"MatMulNBits",dispatchGroup:Ae?{x:1,y:Math.ceil($/Ie),z:q}:{x:Math.ceil(ut/64)},programUniforms:vt}),getShaderSource:Mr}},kf=(n,i)=>{xn(n.inputs,i);let s=n.getMaxComputeWorkgroupSizes(),u=n.getMaxComputeWorkgroupStoragesize();n.compute(to(n.inputs,i,s,u))},ip=n=>qt(n)}),V,G,ne,Ee,Ze,it,wt,Ct,Wt,cr=h(()=>{Zt(),Jt(),ar(),V=n=>{if(!n||n.length<1)throw new Error("Too few inputs");if(n[0].dataType!==1&&n[0].dataType!==10)throw new Error("Input type must be float or float16.");if(n.length>=2){let i=n[0].dims.length*2===n[1].dims[0];if(n.length===4&&(i=n[3].dims[0]*2===n[1].dims[0]),!i)throw new Error("The pads should be a 1D tensor of shape [2 * input_rank] or [2 * num_axes].")}},G=(n,i,s)=>{let u="";for(let c=i-1;c>=0;--c)u+=`
            k = i32(${n.indicesGet("indices",c)}) - ${zt("uniforms.pads",c,s)};
            if (k < 0) {
              break;
            }
            if (k >= i32(${zt("uniforms.x_shape",c,i)})) {
              break;
            }
            offset += k * i32(${zt("uniforms.x_strides",c,i)});
        `;return`
          value = ${n.type.value}(uniforms.constant_value);
          for (var i = 0; i < 1; i++) {
            var offset = 0;
            var k = 0;
            ${u}
            value = x[offset];
          }
      `},ne=(n,i,s)=>{let u="";for(let c=i-1;c>=0;--c)u+=`
                k = i32(${n.indicesGet("indices",c)}) - ${zt("uniforms.pads",c,s)};
                if (k < 0) {
                  k = -k;
                }
                {
                  let _2n_1 = 2 * (i32(${zt("uniforms.x_shape",c,i)}) - 1);
                  k = k % _2n_1;
                  if(k >= i32(${zt("uniforms.x_shape",c,i)})) {
                    k = _2n_1 - k;
                  }
                }
                offset += k * i32(${zt("uniforms.x_strides",c,i)});
            `;return`
              var offset = 0;
              var k = 0;
              ${u}
              value = x[offset];
          `},Ee=(n,i,s)=>{let u="";for(let c=i-1;c>=0;--c)u+=`
                k = i32(${n.indicesGet("indices",c)}) - ${zt("uniforms.pads",c,s)};
                if (k < 0) {
                  k = 0;
                }
                if (k >= i32(${zt("uniforms.x_shape",c,i)})) {
                  k = i32(${zt("uniforms.x_shape",c,i)}) - 1;
                }
                offset += k * i32(${zt("uniforms.x_strides",c,i)});
            `;return`
              var offset = 0;
              var k = 0;
              ${u}
              value = x[offset];
          `},Ze=(n,i,s)=>{let u="";for(let c=i-1;c>=0;--c)u+=`
                k = i32(${n.indicesGet("indices",c)}) - ${zt("uniforms.pads",c,s)};
                if (k < 0)  {
                  k += i32(${zt("uniforms.x_shape",c,i)}]);
                }
                if (k >= i32(${zt("uniforms.x_shape",c,i)})) {
                  k -= i32(${zt("uniforms.x_shape",c,i)});
                }
                offset += k * i32(${zt("uniforms.x_strides",c,i)});
            `;return`
              var offset = 0;
              var k = 0;
              ${u}
              value = x[offset];
          `},it=(n,i,s)=>{switch(s.mode){case 0:return G(n,i,s.pads.length);case 1:return ne(n,i,s.pads.length);case 2:return Ee(n,i,s.pads.length);case 3:return Ze(n,i,s.pads.length);default:throw new Error("Invalid mode")}},wt=(n,i)=>{let s=ct.padShape(n[0].dims.slice(),i.pads),u=n[0].dims,c=ct.size(s),f=[{type:12,data:c},{type:6,data:i.pads}];i.mode===0&&f.push({type:n[0].dataType,data:i.value}),f.push(...At(n[0].dims,s));let d=["rank"],x=k=>{let $=Gt("output",n[0].dataType,s.length),H=_t("x",n[0].dataType,u.length),q=H.type.value,v=it($,u.length,i),oe=[{name:"output_size",type:"u32"},{name:"pads",type:"i32",length:i.pads.length}];return i.mode===0&&oe.push({name:"constant_value",type:q}),`
            ${k.registerUniforms(oe).declareVariables(H,$)}
            ${k.mainStart()}
            ${k.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}

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

            var value = ${q}(0);
            ${v}
            output[global_idx] = value;
        }`};return{name:"Pad",shaderCache:{hint:`${i.mode}`,inputDependencies:d},getRunData:()=>({outputs:[{dims:s,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(ct.size(s)/64)},programUniforms:f}),getShaderSource:x}},Ct=(n,i)=>{if(n.length>1){let s=n[1].getBigInt64Array(),u=n.length>=3&&n[2].data?n[2].getFloat32Array()[0]:0,c=n[0].dims.length,f=new Int32Array(2*c).fill(0);if(n.length>=4){let x=n[3].getBigInt64Array();for(let k=0;k<x.length;k++)f[Number(x[k])]=Number(s[k]),f[Number(x[k])+c]=Number(s[k+x.length])}else s.forEach((x,k)=>f[Number(k)]=Number(x));let d=[];return f.forEach(x=>d.push(x)),{mode:i.mode,value:u,pads:d}}else return i},Wt=(n,i)=>{V(n.inputs);let s=Ct(n.inputs,i);n.compute(wt(n.inputs,s),{inputs:[0]})}}),lr,Ir,dr,wr,pr,mr,xr,Nr,$n,zn,Pi,Mn,dn,Tn,qs,Ks,El,ym,mi,Jo=h(()=>{Z(),Zt(),Jt(),ar(),lr=n=>{if(N.webgpu.validateInputContent&&(!n||n.length!==1))throw new Error("Pool ops requires 1 input.")},Ir=(n,i,s)=>{let u=i.format==="NHWC",c=n.dims.slice();u&&c.splice(1,0,c.pop());let f=Object.hasOwnProperty.call(i,"dilations"),d=i.kernelShape.slice(),x=i.strides.slice(),k=f?i.dilations.slice():[],$=i.pads.slice();Kn.adjustPoolAttributes(s,c,d,x,k,$);let H=Kn.computePoolOutputShape(s,c,x,k,d,$,i.autoPad),q=Object.assign({},i);f?Object.assign(q,{kernelShape:d,strides:x,pads:$,dilations:k,cacheKey:i.cacheKey}):Object.assign(q,{kernelShape:d,strides:x,pads:$,cacheKey:i.cacheKey});let v=H.slice();return v.push(v.splice(1,1)[0]),[q,u?v:H]},dr=(n,i)=>{let s=i.format==="NHWC",u=ct.size(n),c=ct.size(i.kernelShape),f=[{type:12,data:u},{type:12,data:c}],d=[{name:"outputSize",type:"u32"},{name:"kernelSize",type:"u32"}];if(i.kernelShape.length<=2){let x=i.kernelShape[i.kernelShape.length-1],k=i.strides[i.strides.length-1],$=i.pads[i.pads.length/2-1],H=i.pads[i.pads.length-1],q=!!($+H);f.push({type:12,data:x},{type:12,data:k},{type:12,data:$},{type:12,data:H}),d.push({name:"kw",type:"u32"},{name:"sw",type:"u32"},{name:"pwStart",type:"u32"},{name:"pwEnd",type:"u32"});let v=!1;if(i.kernelShape.length===2){let oe=i.kernelShape[i.kernelShape.length-2],te=i.strides[i.strides.length-2],de=i.pads[i.pads.length/2-2],we=i.pads[i.pads.length-2];v=!!(de+we),f.push({type:12,data:oe},{type:12,data:te},{type:12,data:de},{type:12,data:we}),d.push({name:"kh",type:"u32"},{name:"sh",type:"u32"},{name:"phStart",type:"u32"},{name:"phEnd",type:"u32"})}return[f,d,!0,q,v]}else{if(s)throw new Error("Pooling with kernelShape.length > 2 is not supported for NHWC format.");let x=ct.computeStrides(i.kernelShape);f.push({type:12,data:x},{type:12,data:i.pads},{type:12,data:i.strides}),d.push({name:"kernelStrides",type:"u32",length:x.length},{name:"pads",type:"u32",length:i.pads.length},{name:"strides",type:"u32",length:i.strides.length});let k=i.pads.reduce(($,H)=>$+H);return[f,d,!!k,!1,!1]}},wr=(n,i,s,u,c,f,d,x,k,$,H,q)=>{let v=c.format==="NHWC",oe=i.type.value,te=Gt("output",i.type.tensor,u);if(c.kernelShape.length<=2){let de="",we="",be="",he=s-(v?2:1);if(H?de=`
                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")}];
                  ${f}
                }`:de=`
                for (var i: u32 = 0u; i < uniforms.kw; i++) {
                  xIndices[${he}] = indices[${he}] * uniforms.sw - uniforms.pwStart + i;
                  let x_val = x[${i.indicesToOffset("xIndices")}];
                  ${f}
                }`,c.kernelShape.length===2){let De=s-(v?3:2);q?we=`
                for (var j: u32 = 0u; j < uniforms.kh; j++) {
                  xIndices[${De}] = indices[${De}] * uniforms.sh - uniforms.phStart + j;
                  if (xIndices[${De}] < 0 || xIndices[${De}] >= uniforms.x_shape[${De}]) {
                    pad += i32(uniforms.kw);
                    continue;
                  }
              `:we=`
                for (var j: u32 = 0u; j < uniforms.kh; j++) {
                  xIndices[${De}] = indices[${De}] * uniforms.sh - uniforms.phStart + j;
                `,be=`
              }
            `}return`
            ${n.registerUniforms(k).declareVariables(i,te)}

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

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

              var value = ${oe}(${x});
              var pad = 0;
              ${we}
              ${de}
              ${be}
              ${d}

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

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

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

              var value = ${oe}(${x});
              var pad = 0;
              var isPad = false;

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

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

              output[global_idx] = value;
            }`}},pr=n=>`${n.format};${n.ceilMode};${n.autoPad};${n.kernelShape.length}`,mr=n=>`${pr(n)};${n.countIncludePad}`,xr=n=>`${pr(n)};${n.storageOrder};${n.dilations}`,Nr=n=>({format:n.format,autoPad:["NOTSET","VALID","SAME_UPPER","SAME_LOWER"][n.auto_pad],ceilMode:n.ceil_mode,kernelShape:n.kernel_shape,strides:n.strides,pads:n.pads}),$n=(n,i,s,u)=>{let[c,f]=Ir(i,u,s),d=_t("x",i.dataType,i.dims.length),x=d.type.value,k="value += x_val;",$="";c.countIncludePad?$+=`value /= ${x}(uniforms.kernelSize);`:$+=`value /= ${x}(i32(uniforms.kernelSize) - pad);`;let[H,q,v,oe,te]=dr(f,c);H.push(...At(i.dims,f));let de=["rank"];return{name:n,shaderCache:{hint:`${u.cacheKey};${v};${oe};${te}`,inputDependencies:de},getRunData:()=>({outputs:[{dims:f,dataType:i.dataType}],dispatchGroup:{x:Math.ceil(ct.size(f)/64)},programUniforms:H}),getShaderSource:we=>wr(we,d,i.dims.length,f.length,c,k,$,0,q,v,oe,te)}},zn=n=>{let i=n.count_include_pad!==0,s=Nr(n);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:mr(u)}},Pi=(n,i)=>{lr(n.inputs),n.compute($n("AveragePool",n.inputs[0],!1,i))},Mn={autoPad:"",ceilMode:0,countIncludePad:!1,kernelShape:[],strides:[],pads:[],storageOrder:0,dilations:[]},dn=n=>{let i=n.format;return{format:i,...Mn,cacheKey:i}},Tn=(n,i)=>{lr(n.inputs),n.compute($n("GlobalAveragePool",n.inputs[0],!0,i))},qs=(n,i,s,u)=>{let[c,f]=Ir(i,u,s),d=`
      value = max(x_val, value);
    `,x="",k=_t("x",i.dataType,i.dims.length),$=["rank"],[H,q,v,oe,te]=dr(f,c);return H.push(...At(i.dims,f)),{name:n,shaderCache:{hint:`${u.cacheKey};${v};${oe};${te}`,inputDependencies:$},getRunData:()=>({outputs:[{dims:f,dataType:i.dataType}],dispatchGroup:{x:Math.ceil(ct.size(f)/64)},programUniforms:H}),getShaderSource:de=>wr(de,k,i.dims.length,f.length,c,d,x,i.dataType===10?-65504:-1e5,q,v,oe,te)}},Ks=(n,i)=>{lr(n.inputs),n.compute(qs("MaxPool",n.inputs[0],!1,i))},El=n=>{let i=n.storage_order,s=n.dilations,u=Nr(n);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:xr(c)}},ym=n=>{let i=n.format;return{format:i,...Mn,cacheKey:i}},mi=(n,i)=>{lr(n.inputs),n.compute(qs("GlobalMaxPool",n.inputs[0],!0,i))}}),Ef,Cf,Pf,$f=h(()=>{Z(),Zt(),ar(),Ef=(n,i,s)=>{let u=n===i,c=n<i&&s<0,f=n>i&&s>0;if(u||c||f)throw new Error("Range these inputs' contents are invalid.")},Cf=(n,i,s,u)=>{let c=Math.abs(Math.ceil((i-n)/s)),f=[c],d=c,x=[{type:12,data:d},{type:u,data:n},{type:u,data:s},...At(f)],k=$=>{let H=Gt("output",u,f.length),q=H.type.value,v=[{name:"outputSize",type:"u32"},{name:"start",type:q},{name:"delta",type:q}];return`
        ${$.registerUniforms(v).declareVariables(H)}
        ${$.mainStart()}
        ${$.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}
        output[global_idx] = uniforms.start + ${q}(global_idx) * uniforms.delta;
      }`};return{name:"Range",shaderCache:{hint:`${u}`},getShaderSource:k,getRunData:()=>({outputs:[{dims:f,dataType:u}],dispatchGroup:{x:Math.ceil(d/64)},programUniforms:x})}},Pf=n=>{let i=0,s=0,u=0;n.inputs[0].dataType===6?(i=n.inputs[0].getInt32Array()[0],s=n.inputs[1].getInt32Array()[0],u=n.inputs[2].getInt32Array()[0]):n.inputs[0].dataType===1&&(i=n.inputs[0].getFloat32Array()[0],s=n.inputs[1].getFloat32Array()[0],u=n.inputs[2].getFloat32Array()[0]),N.webgpu.validateInputContent&&Ef(i,s,u),n.compute(Cf(i,s,u,n.inputs[0].dataType),{inputs:[]})}}),b0,x0,M0,T0,k0,S0,E0,C0,P0,$0,A0,vm,I0,F0,O0,z0,D0,L0,R0,nx=h(()=>{Zt(),Jt(),_r(),ar(),b0=(n,i)=>{if(n.every(s=>s>0||(()=>{throw new Error("Resize requires scales input values to be positive")})),n.length>0){if(i.mode==="linear"){if(!(n.length===2||n.length===3||n.length===4&&n[0]===1&&n[1]===1||n.length===4&&n[0]===1&&n[3]===1||n.length===5&&n[0]===1&&n[1]===1))throw new Error(`For linear mode, Resize requires scales to be 2D, 3D, 4D with either two outermost or one innermost and
            one outermost scale values equal to 1, or 5D with two outermost scale values equal to 1`)}else if(i.mode==="cubic"&&!(n.length===2||n.length===4&&n[0]===1&&n[1]===1||n.length===4&&n[0]===1&&n[3]===1))throw new Error("Resize requires scales input size to be 2 or 4 for cubic mode")}},x0=(n,i,s)=>{i.every(c=>c>=0&&c<s||(()=>{throw new Error("Resize requires axes input values to be positive and less than rank")}));let u=new Array(s).fill(1);return i.forEach((c,f)=>u[c]=n[f]),u},M0=(n,i,s,u,c,f)=>{let[d,x,k]=s>10?[1,2,3]:[-1,n.length>1?1:-1,-1],$=n[0].dims.length;if(d>0&&n.length>d&&n[d].dims.length>0)n[d].getFloat32Array().forEach(H=>f.push(H));else if(i.coordinateTransformMode==="tf_crop_and_resize")throw new Error("Resize requires RoI input to be specified when coordinateTransformMode is tfCropAndResize");if(x>0&&n.length>x&&n[x].dims.length>0){if(n[x].getFloat32Array().forEach(H=>u.push(H)),u.length!==0&&u.length!==$&&s>=18&&u.length!==i.axes.length)throw new Error("Resize requires scales input size to be same as input rank or axes size for opset 18 and up");b0(u,i),i.axes.length>0&&x0(u,i.axes,$).forEach((H,q)=>u[q]=H)}if(k>0&&n.length>k&&(n[k].getBigInt64Array().forEach(H=>c.push(Number(H))),c.length!==$||s>=18&&c.length===i.axes.length))throw new Error("Resize requires sizes input size to be same as input rank or axes size for opset 18 and up");if(i.axes.length>0){if(u.length!==i.axes.length)throw new Error('Resize requires "scales" input size to be of axes rank when axes attributes is specified');if(c.length!==i.axes.length)throw new Error('Resize requires "sizes" input size to be of rank axes rank when axes attributes is specified')}if(typeof u<"u"&&typeof c<"u"&&u.length>0&&c.length>$)throw new Error("Resize requires only of scales or sizes to be specified")},T0=(n,i)=>`fn getOriginalCoordinateFromResizedCoordinate(xResized: u32, xScale: f32, lengthResized: u32,
     lengthOriginal: u32, roiStart: f32, roiEnd: f32) -> ${i} { `+(()=>{switch(n){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 ${n} is not supported`)}})()+"}",k0=(n,i,s)=>`fn getNearestPixelFromOriginal(xOriginal: ${s}, isDownSample: bool) -> ${s} {`+(()=>{switch(n){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 ${n} is not supported`)}})()+"}",S0=(n,i,s)=>{let u=new Array(s).fill(0).concat(new Array(s).fill(1)),c=n.length===0?u:n.slice();return i.length>0?(i.forEach((f,d)=>{u[f]=c[d],u[d+s]=c[i.length+d]}),u):c},E0=(n,i,s,u)=>{let c=[];if(s.length>0)if(u.length>0){if(n.forEach(f=>c.push(f)),Math.max(...u)>n.length)throw new Error("axes is out of bound");u.forEach((f,d)=>c[f]=s[d])}else s.forEach(f=>c.push(f));else{if(i.length===0)throw new Error("Resize requires either scales or sizes.");c=n.map((f,d)=>Math.round(f*i[d]))}return c},C0=(n,i,s)=>{let u=(()=>{switch(s.keepAspectRatioPolicy){case"not_larger":return s.axes.length>0?Math.min(...s.axes.map(f=>i[f]),Number.MAX_VALUE):Math.min(...i,Number.MAX_VALUE);case"not_smaller":return s.axes.length>0?Math.max(...s.axes.map(f=>i[f]),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=n.slice();return s.axes.length>0?(s.axes.forEach(f=>i[f]=u),s.axes.forEach(f=>c[f]=Math.round(n[f]*i[f]))):(i.fill(u,0,i.length),c.forEach((f,d)=>c[d]=Math.round(f*i[d]))),c},P0=(n,i,s,u,c)=>`
    fn calculateOriginalIndicesFromOutputIndices(output_indices: ${n.type.indices}) -> array<${n.type.value}, ${s.length}> {
      var original_indices: array<${n.type.value}, ${s.length}>;
      for (var i:u32 = 0; i < ${s.length}; i++) {
        var output_index = ${n.indicesGet("output_indices","i")};
        var scale = ${zt("uniforms.scales","i",u)};
        var roi_low = ${zt("uniforms.roi","i",c)};
        var roi_hi = ${zt("uniforms.roi",`i + ${i.length}`,c)};
        if (scale == 1.0) {
          original_indices[i] = ${n.type.value}(output_index);
        } else {
          var input_shape_i = ${zt("uniforms.input_shape","i",i.length)};
          var output_shape_i = ${zt("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;
    }`,$0=(n,i,s,u,c,f,d)=>`
    fn calculateInputIndicesFromOutputIndices(output_indices: ${i.type.indices}) -> ${n.type.indices} {
      var input_indices: ${n.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 = ${zt("uniforms.scales","i",c)};
        if (scale == 1.0) {
          input_index = output_index;
        } else {
          var roi_low = ${zt("uniforms.roi","i",f)};
          var roi_hi = ${zt("uniforms.roi",`i + ${s.length}`,f)};
          var input_shape_i = ${zt("uniforms.input_shape","i",s.length)};
          var output_shape_i = ${zt("uniforms.output_shape","i",u.length)};
          var original_idx = getOriginalCoordinateFromResizedCoordinate(output_index, scale, output_shape_i,
                                                                        input_shape_i, roi_low, roi_hi);
          if (!${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);
          }
        }
        ${n.indicesSet("input_indices","i"," input_index")}
      }
      return input_indices;
    }`,A0=(n,i)=>`
    fn checkInputIndices(input_indices: ${n.type.indices}) -> bool {
      for (var i:u32 = 0; i < ${i.length}; i++) {
        var input_index = ${n.indicesGet("input_indices","i")};
        if (input_index < 0 || input_index >= ${zt("uniforms.input_shape","i",i.length)}) {
          return false;
        }
      }
      return true;
    }`,vm=(n,i,s,u)=>n.rank>u?`
    ${n.indicesSet("input_indices",i,"channel")};
    ${n.indicesSet("input_indices",s,"batch")};
`:"",I0=(n,i,s,u,c)=>{let[f,d,x,k]=s.length===2?[-1,0,1,-1]:[0,2,3,1],$=n.type.value;return`
    fn getInputValue(batch: u32, channel: u32, row: u32, col: u32) -> ${$} {
      var input_indices: ${n.type.indices};
      ${n.indicesSet("input_indices",d,`max(0, min(row, ${s[d]} - 1))`)};
      ${n.indicesSet("input_indices",x,`max(0, min(col, ${s[x]} - 1))`)};
      ${vm(n,k,f,2)}
      return ${n.getByIndices("input_indices")};
    }

    fn bilinearInterpolation(output_indices: ${i.type.indices}) -> ${$} {
      var originalIndices = calculateOriginalIndicesFromOutputIndices(output_indices);
      var row:${$} = originalIndices[${d}];
      var col:${$} = originalIndices[${x}];
      ${u?`if (row < 0 || row > (${s[d]} - 1) || col < 0 || col > (${s[x]} - 1)) {
        return ${c};
      }`:""};
      row = max(0, min(row, ${s[d]} - 1));
      col = max(0, min(col, ${s[x]} - 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 = ${s.length>2?`u32(originalIndices[${k}])`:"0"};
      var batch: u32 =  ${s.length>2?`u32(originalIndices[${f}])`:"0"};
      var x11: ${$} = getInputValue(batch, channel, row1, col1);
      var x12: ${$} = getInputValue(batch, channel, row1, col2);
      var x21: ${$} = getInputValue(batch, channel, row2, col1);
      var x22: ${$} = getInputValue(batch, channel, row2, col2);
      var dx1: ${$} = abs(row - ${$}(row1));
      var dx2: ${$} = abs(${$}(row2) - row);
      var dy1: ${$} = abs(col - ${$}(col1));
      var dy2: ${$} = abs(${$}(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);
    }`},F0=(n,i,s,u,c,f,d,x,k,$)=>{let H=s.length===2,[q,v]=H?[0,1]:[2,3],oe=n.type.value,te=de=>{let we=de===q?"row":"col";return`
      fn ${we}CubicInterpolation(input_indices: ${n.type.indices}, output_indices: ${i.type.indices}) -> ${oe} {
        var output_index = ${i.indicesGet("output_indices",de)};
        var originalIdx: ${oe} = getOriginalCoordinateFromResizedCoordinate(output_index, ${c[de]},
        ${u[de]}, ${s[de]}, ${f[de]}, ${f[de]} + ${s.length});
        var fractOriginalIdx: ${oe} = originalIdx - floor(originalIdx);
        var coefs = getCubicInterpolationCoefs(fractOriginalIdx);

        if (${x} && (originalIdx < 0 || originalIdx > (${s[de]} - 1))) {
          return ${k};
        }
        var data: array<${oe}, 4> = array<${oe}, 4>(0.0, 0.0, 0.0, 0.0);
        for (var i: i32 = -1; i < 3; i++) {
          var ${we}: ${oe} = originalIdx + ${oe}(i);
          if (${we} < 0 || ${we} >= ${s[de]}) {
            ${$?`coefs[i + 1] = 0.0;
                        continue;`:x?`return ${k};`:`${we} = max(0, min(${we}, ${s[de]} - 1));`};
          }
        var input_indices_copy: ${n.type.indices} = input_indices;
          ${n.indicesSet("input_indices_copy",de,`u32(${we})`)};
          data[i + 1] = ${de===q?n.getByIndices("input_indices_copy"):"rowCubicInterpolation(input_indices_copy, output_indices)"};
        }
        return cubicInterpolation1D(data, coefs);
      }`};return`
    ${te(q)};
    ${te(v)};
  fn getCubicInterpolationCoefs(s: ${oe}) -> array<${oe}, 4> {
    var absS = abs(s);
    var coeffs: array<${oe}, 4> = array<${oe}, 4>(0.0, 0.0, 0.0, 0.0);
    var oneMinusAbsS: ${oe} = 1.0 - absS;
    var twoMinusAbsS: ${oe} = 2.0 - absS;
    var onePlusAbsS: ${oe} = 1.0 + absS;
    coeffs[0] = ((${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<${oe}, 4>, coefs: array<${oe}, 4>) -> ${oe} {
    var coefsSum: ${oe} = 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}) -> ${oe} {
    var input_indices: ${n.type.indices} = output_indices;
    return colCubicInterpolation(input_indices, output_indices);
  }
    `},O0=(n,i,s,u,c)=>{let[f,d,x,k,$]=s.length===3?[-1,0,1,2,-1]:[0,2,3,4,1],H=n.type.value;return`
    fn getInputValue(batch: u32, channel: u32, depth:u32, height: u32, width: u32) -> ${H} {
      var input_indices: ${n.type.indices};
      ${n.indicesSet("input_indices",d,`max(0, min(depth, ${s[d]} - 1))`)};
      ${n.indicesSet("input_indices",x,`max(0, min(height, ${s[x]} - 1))`)};
      ${n.indicesSet("input_indices",k,`max(0, min(width, ${s[k]} - 1))`)};
      ${vm(n,$,f,3)}
      return ${n.getByIndices("input_indices")};
    }

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

    depth = max(0, min(depth, ${s[d]} - 1));
      height = max(0, min(height, ${s[x]} - 1));
      width = max(0, min(width, ${s[k]} - 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 = ${s.length>3?`u32(originalIndices[${$}])`:"0"};
      var batch: u32 =  ${s.length>3?`u32(originalIndices[${f}])`:"0"};

      var x111: ${H} = getInputValue(batch, channel, depth1, height1, width1);
      var x112: ${H} = getInputValue(batch, channel, depth1, height1, width2);
      var x121: ${H} = getInputValue(batch, channel, depth1, height2, width1);
      var x122: ${H} = getInputValue(batch, channel, depth1, height2, width2);
      var x211: ${H} = getInputValue(batch, channel, depth2, height1, width1);
      var x212: ${H} = getInputValue(batch, channel, depth2, height1, width2);
      var x221: ${H} = getInputValue(batch, channel, depth2, height2, width1);
      var x222: ${H} = getInputValue(batch, channel, depth2, height2, width2);
      var dx1: ${H} = abs(depth - ${H}(depth1));
      var dx2: ${H} = abs(${H}(depth2) - depth);
      var dy1: ${H} = abs(height - ${H}(height1));
      var dy2: ${H} = abs(${H}(height2) - height);
      var dz1: ${H} = abs(width - ${H}(width1));
      var dz2: ${H} = abs(${H}(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=(n,i,s,u,c,f)=>{let d=n.dims,x=S0(f,i.axes,d.length),k=E0(d,u,c,i.axes),$=u.slice();u.length===0&&($=d.map((he,De)=>he===0?1:k[De]/he),i.keepAspectRatioPolicy!=="stretch"&&(k=C0(d,$,i)));let H=Gt("output",n.dataType,k.length),q=_t("input",n.dataType,d.length),v=ct.size(k),oe=d.length===k.length&&d.every((he,De)=>he===k[De]),te=i.coordinateTransformMode==="tf_crop_and_resize",de=i.extrapolationValue,we=q.type.value,be=he=>`
      ${oe?"":`
      ${T0(i.coordinateTransformMode,we)};
      ${(()=>{switch(i.mode){case"nearest":return`
              ${A0(q,d)};
              ${k0(i.nearestMode,s,we)};
              ${$0(q,H,d,k,$.length,x.length,te)};
              `;case"linear":return`
              ${P0(H,d,k,$.length,x.length)};
              ${(()=>{if(d.length===2||d.length===4)return`${I0(q,H,d,te,de)}`;if(d.length===3||d.length===5)return`${O0(q,H,d,te,de)}`;throw Error("Linear mode only supports input dims 2, 3, 4 and 5 are supported in linear mode.")})()};
            `;case"cubic":return`
            ${(()=>{if(d.length===2||d.length===4)return`${F0(q,H,d,k,$,x,i.cubicCoeffA,te,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")}})()};
      `}
      ${he.registerUniform("output_size","u32").registerUniform("scales","f32",$.length).registerUniform("roi","f32",x.length).declareVariables(q,H)}
      ${he.mainStart()}
        ${he.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")}
        ${oe?"output[global_idx] = input[global_idx];":`
        let output_indices = ${H.offsetToIndices("global_idx")};
        var input_indices: ${q.type.indices};
        ${(()=>{switch(i.mode){case"nearest":return`input_indices = calculateInputIndicesFromOutputIndices(output_indices);
                if (checkInputIndices(input_indices)) {
                  output[global_idx] = ${q.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}|${s}|${$.length>0?$:""}|${c.length>0?c:""}|${x.length>0?x:""}|${oe}|${d}`,inputDependencies:["rank"]},getShaderSource:be,getRunData:()=>({outputs:[{dims:k,dataType:n.dataType}],dispatchGroup:{x:Math.ceil(v/64)},programUniforms:[{type:12,data:v},{type:1,data:$},{type:1,data:x},...At(d,k)]})}},D0=n=>{let i=n.customDataBuffer;return new Uint32Array(i,i.byteOffset,1)[0]},L0=(n,i)=>{let s=[],u=[],c=[],f=D0(n);if(i.antialias!==0)throw Error("Only default value (0) for Antialias attribute is supported");M0(n.inputs,i,f,s,u,c),n.compute(z0(n.inputs[0],i,f,s,u,c),{inputs:[0]})},R0=n=>{let i=n.antialias,s=n.axes,u=n.coordinateTransformMode,c=n.cubicCoeffA,f=n.excludeOutside!==0,d=n.extrapolationValue,x=n.keepAspectRatioPolicy,k=n.mode,$=n.nearestMode===""?"simple":n.nearestMode;return qt({antialias:i,axes:s,coordinateTransformMode:u,cubicCoeffA:c,excludeOutside:f,extrapolationValue:d,keepAspectRatioPolicy:x,mode:k,nearestMode:$})}}),B0,N0,j0,ix=h(()=>{Zt(),Jt(),_r(),ar(),B0=(n,i)=>{let[s,u,c,f]=n,{numHeads:d,rotaryEmbeddingDim:x}=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(!ct.areEqual(u.dims,[])&&!ct.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(f.dims.length!==2)throw new Error(`Input 'sin_cache' is expected to have 2 dimensions, got ${f.dims.length}`);if(!ct.areEqual(c.dims,f.dims))throw new Error("Inputs 'cos_cache' and 'sin_cache' are expected to have the same shape");if(x>0&&d===0)throw new Error("num_heads must be provided if rotary_embedding_dim is specified");let k=s.dims[0],$=s.dims[s.dims.length-2],H=c.dims[0],q=ct.sizeFromDimension(s.dims,1)/$,v=x===0?c.dims[1]*2:q/d;if(x>v)throw new Error("rotary_embedding_dim must be less than or equal to head_size");if(u.dims.length===2){if(k!==u.dims[0])throw new Error(`Input 'position_ids' dimension 0 should be of size batch_size, got ${u.dims[0]}`);if($!==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]&&x/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 ${c.dims[1]}`);if($>H)throw new Error("Updating cos_cache and sin_cache in RotaryEmbedding is not currently supported")},N0=(n,i)=>{let{interleaved:s,numHeads:u,rotaryEmbeddingDim:c,scale:f}=i,d=n[0].dims[0],x=ct.sizeFromDimension(n[0].dims,1),k=n[0].dims[n[0].dims.length-2],$=x/k,H=n[2].dims[1],q=c===0?H*2:$/u,v=new Array(d,k,$/q,q-H),oe=ct.computeStrides(v),te=[{type:1,data:f},{type:12,data:v},{type:12,data:oe},...n[0].dims.length===3?new Array({type:12,data:[x,$,q,1]}):[],...n[0].dims.length===4?new Array({type:12,data:[x,q,k*q,1]}):[],...At(n[0].dims,n[1].dims,n[2].dims,n[3].dims,n[0].dims)],de=we=>{let be=_t("input",n[0].dataType,n[0].dims.length),he=_t("position_ids",n[1].dataType,n[1].dims.length),De=_t("cos_cache",n[2].dataType,n[2].dims.length),Ae=_t("sin_cache",n[3].dataType,n[3].dims.length),Ie=Gt("output",n[0].dataType,n[0].dims.length);return we.registerUniforms([{name:"scale",type:"f32"},{name:"global_shape",type:"u32",length:v.length},{name:"global_strides",type:"u32",length:oe.length},{name:"input_output_strides",type:"u32",length:oe.length}]),`
        ${we.declareVariables(be,he,De,Ae,Ie)}

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

          if (bsnh[3] < half_rotary_emb_dim) {
            let position_ids_idx =
                ${he.broadcastedIndicesToOffset("bsnh.xy",Gt("",he.type.tensor,2))};
            let position_id =
                u32(${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")} * ${De.get("position_id","bsnh[3]")} -
                ${be.getByOffset("j")} * ${Ae.get("position_id","bsnh[3]")};
            ${Ie.setByOffset("i","re")}
            let im = ${be.getByOffset("i")} * ${Ae.get("position_id","bsnh[3]")} +
                ${be.getByOffset("j")} * ${De.get("position_id","bsnh[3]")};
            ${Ie.setByOffset("j","im")}
          } else {
            let k = dot(bsnh, uniforms.input_output_strides) + half_rotary_emb_dim;
            ${Ie.setByOffset("k",be.getByOffset("k"))}
          }
        }`};return{name:"RotaryEmbedding",shaderCache:{hint:qt({interleaved:s}).cacheKey,inputDependencies:["rank","rank","rank","rank"]},getShaderSource:de,getRunData:()=>({outputs:[{dims:n[0].dims,dataType:n[0].dataType}],dispatchGroup:{x:Math.ceil(ct.size(v)/Un)},programUniforms:te})}},j0=(n,i)=>{B0(n.inputs,i),n.compute(N0(n.inputs,i))}}),U0,V0,W0,ox=h(()=>{Zt(),Jt(),ar(),U0=n=>{if(!n||n.length<3)throw new Error("layerNorm requires at least 3 inputs.");let i=n[0],s=n[1],u=n[2];if(i.dataType!==s.dataType||i.dataType!==u.dataType)throw new Error("All inputs must have the same data type");if(i.dims.length!==3&&i.dims.length!==2)throw new Error("Input must be 2D or 3D");if(s.dims.length!==3&&s.dims.length!==2)throw new Error("Skip must be 2D or 3D");let c=i.dims[i.dims.length-1],f=i.dims[i.dims.length-2];if(s.dims[s.dims.length-1]!==c)throw new Error("Skip must have the same hidden size as input");if(s.dims[s.dims.length-2]!==f)throw new Error("Skip must have the same sequence length as input");if(u.dims.length!==1)throw new Error("Gamma must be 1D");if(u.dims[u.dims.length-1]!==c)throw new Error("Gamma must have the same hidden size as input");if(n.length>3){let d=n[3];if(d.dims.length!==1)throw new Error("Beta must be 1D");if(d.dims[d.dims.length-1]!==c)throw new Error("Beta must have the same hidden size as input")}if(n.length>4){let d=n[4];if(d.dims.length!==1)throw new Error("Bias must be 1D");if(d.dims[d.dims.length-1]!==c)throw new Error("Bias must have the same hidden size as input")}},V0=(n,i,s,u)=>{let c=i.simplified,f=n[0].dims,d=ct.size(f),x=f,k=d,$=f.slice(-1)[0],H=u?f.slice(0,-1).concat(1):[],q=!c&&n.length>3,v=n.length>4,oe=u&&s>1,te=u&&s>2,de=s>3,we=64,be=vr($),he=[{type:12,data:k},{type:12,data:be},{type:12,data:$},{type:1,data:i.epsilon}],De=Ie=>{let gt=[{name:"output_size",type:"u32"},{name:"components",type:"u32"},{name:"hidden_size",type:"u32"},{name:"epsilon",type:"f32"}],ut=[_t("x",n[0].dataType,n[0].dims,be),_t("skip",n[1].dataType,n[1].dims,be),_t("gamma",n[2].dataType,n[2].dims,be)];q&&ut.push(_t("beta",n[3].dataType,n[3].dims,be)),v&&ut.push(_t("bias",n[4].dataType,n[4].dims,be)),ut.push(Gt("output",n[0].dataType,x,be)),oe&&ut.push(Gt("mean_output",1,H)),te&&ut.push(Gt("inv_std_output",1,H)),de&&ut.push(Gt("input_skip_bias_sum",n[0].dataType,x,be));let vt=Sr(n[0].dataType),Dt=Sr(1,be);return`

      ${Ie.registerUniforms(gt).declareVariables(...ut)}
      var<workgroup> sum_shared : array<${Dt}, ${we}>;
      var<workgroup> sum_squared_shared : array<${Dt}, ${we}>;

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

        let hidden_size_vectorized: u32 = uniforms.hidden_size / uniforms.components;
        var stride = hidden_size_vectorized / ${we};
        let offset = ix * stride + iy * hidden_size_vectorized;
        let offset1d = stride * ix;
        if (ix == ${we-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;
          ${de?"input_skip_bias_sum[offset + i] = value;":""}
          output[offset + i] = value;
          let f32_value = ${Xr(vt,be,"value")};
          sum_shared[ix] += f32_value;
          sum_squared_shared[ix] += f32_value * f32_value;
        }
        workgroupBarrier();

        var reduce_size : u32 = ${we};
        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 = ${Vn("sum",be)} / f32(uniforms.hidden_size);
        let inv_std_dev = inverseSqrt(${Vn("square_sum",be)} / f32(uniforms.hidden_size) ${c?"":"- mean * mean"} + uniforms.epsilon);
        ${oe?"mean_output[global_idx] = mean;":""}
        ${te?"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]
            ${q?"+ beta[offset1d + i]":""};
        }
      }`},Ae=[{dims:x,dataType:n[0].dataType}];return s>1&&Ae.push({dims:H,dataType:1}),s>2&&Ae.push({dims:H,dataType:1}),s>3&&Ae.push({dims:f,dataType:n[0].dataType}),{name:"SkipLayerNormalization",shaderCache:{hint:`${be};${oe};${te};${de}`,inputDependencies:n.map((Ie,gt)=>"type")},getShaderSource:De,getRunData:()=>({outputs:Ae,dispatchGroup:{x:Math.ceil(k/$)},programUniforms:he})}},W0=(n,i)=>{U0(n.inputs);let s=[0];n.outputCount>1&&s.push(-3),n.outputCount>2&&s.push(-3),n.outputCount>3&&s.push(3),n.compute(V0(n.inputs,i,n.outputCount,!1),{outputs:s})}}),G0,op,H0,bm,q0,K0,X0,Q0,sx=h(()=>{Zt(),Jt(),_r(),ar(),G0=(n,i)=>{if(!n||n.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");n.slice(1).forEach((s,u)=>{if(n[u+1].dataType!==6&&n[u+1].dataType!==7)throw new Error(`Input ${u} must be an array of int32 or int64`)})},op=(n,i)=>{let s=[];if(n.length>i)if(n[i].dataType===7)n[i].getBigInt64Array().forEach(u=>s.push(Number(u)));else if(n[i].dataType===6)n[i].getInt32Array().forEach(u=>s.push(Number(u)));else throw new Error(`Input ${i} must be an array of int32 or int64`);return s},H0=(n,i)=>{if(n.length>1){let s=op(n,1),u=op(n,2),c=op(n,3);return c.length===0&&(c=[...Array(n[0].dims.length).keys()]),qt({starts:s,ends:u,axes:c})}else return i},bm=(n,i,s,u,c)=>{let f=n;return n<0&&(f+=s[u[i]]),c[i]<0?Math.max(0,Math.min(f,s[u[i]]-1)):Math.max(0,Math.min(f,s[u[i]]))},q0=(n,i,s)=>`fn calculateInputIndices(output_indices: ${i.type.indices}) -> ${n.type.indices} {
          var input_indices: ${n.type.indices};
          var carry = 0u;
          for (var i = ${s.length}; i >= 0; i--) {
            let input_shape_i = ${zt("uniforms.input_shape","i",s.length)};
            let steps_i = ${zt("uniforms.steps","i",s.length)};
            let signs_i = ${zt("uniforms.signs","i",s.length)};
            let starts_i = ${zt("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;
            }
            ${n.indicesSet("input_indices","i","input_index")};
          }
          return input_indices;
      }`,K0=(n,i)=>{let s=n[0].dims,u=ct.size(s),c=i.axes.length>0?ct.normalizeAxes(i.axes,s.length):[...Array(s.length).keys()],f=op(n,4);f.forEach(be=>be!==0||(()=>{throw new Error("step cannot be 0")})),f.length===0&&(f=Array(c.length).fill(1));let d=i.starts.map((be,he)=>bm(be,he,s,c,f)),x=i.ends.map((be,he)=>bm(be,he,s,c,f));if(c.length!==d.length||c.length!==x.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),x.splice(be,0,s[be]),f.splice(be,0,1));let k=f.map(be=>Math.sign(be));f.forEach((be,he,De)=>{if(be<0){let Ae=(x[he]-d[he])/be,Ie=d[he],gt=Ie+Ae*f[he];d[he]=gt,x[he]=Ie,De[he]=-be}});let $=s.slice(0);c.forEach((be,he)=>{$[be]=Math.ceil((x[be]-d[be])/f[be])});let H={dims:$,dataType:n[0].dataType},q=Gt("output",n[0].dataType,$.length),v=_t("input",n[0].dataType,n[0].dims.length),oe=ct.size($),te=[{name:"outputSize",type:"u32"},{name:"starts",type:"u32",length:d.length},{name:"signs",type:"i32",length:k.length},{name:"steps",type:"u32",length:f.length}],de=[{type:12,data:oe},{type:12,data:d},{type:6,data:k},{type:12,data:f},...At(n[0].dims,$)],we=be=>`
      ${be.registerUniforms(te).declareVariables(v,q)}
        ${q0(v,q,s)}
        ${be.mainStart()}
          ${be.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.outputSize")}
          let output_indices = ${q.offsetToIndices("global_idx")};
          let input_indices = calculateInputIndices(output_indices);
          ${q.setByOffset("global_idx",v.getByIndices("input_indices"))}
      }`;return{name:"Slice",shaderCache:{hint:`${k.length}_${d.length}_${f.length}`,inputDependencies:["rank"]},getShaderSource:we,getRunData:()=>({outputs:[H],dispatchGroup:{x:Math.ceil(u/64)},programUniforms:de})}},X0=(n,i)=>{G0(n.inputs,i);let s=H0(n.inputs,i);n.compute(K0(n.inputs,s),{inputs:[0]})},Q0=n=>{let i=n.starts,s=n.ends,u=n.axes;return qt({starts:i,ends:s,axes:u})}}),Y0,Z0,J0,ew,ax=h(()=>{Zt(),Jt(),_r(),ar(),Y0=n=>{if(!n||n.length!==1)throw new Error("Softmax op requires 1 input.")},Z0=(n,i)=>{let s=n.dims,u=ct.size(s),c=64,f=i.axis;if(f<0&&(f=s.length+f),f<s.length-1)throw new Error("softmax only supports last axis for now.");let d=s[f],x=u/d,k=vr(d),$=d/k,H=(we,be)=>be===4?`max(max(${we}.x, ${we}.y), max(${we}.z, ${we}.w))`:be===2?`max(${we}.x, ${we}.y)`:be===3?`max(max(${we}.x, ${we}.y), ${we}.z)`:we,q=_t("x",n.dataType,n.dims,k),v=Gt("result",n.dataType,n.dims,k),oe=q.type.value,te=Sr(n.dataType)==="f32"?`var threadMax = ${oe}(-3.402823e+38f);`:`var threadMax = ${oe}(-65504.0h);`,de=we=>`
      var<workgroup> rowMaxShared : ${oe};
      var<workgroup> rowSumShared : ${oe};
      var<workgroup> threadShared : array<${oe}, ${c}>;

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

      fn setValue(row: i32, col: i32, row_stride: i32, value: ${oe}) {
        let index = row * row_stride + col;
        result[index] = value;
      }
      ${we.registerUniform("packedCols","i32").declareVariables(q,v)}
      ${we.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
        ${te}
        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 = ${oe}(${H("threadShared[0]",k)});
        }
        workgroupBarrier();

        // find the rows sum
        var threadSum = ${oe}(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 = ${oe}(${Vn("threadShared[0]",k)});
        }
        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:`${k}`,inputDependencies:["type"]},getRunData:()=>({outputs:[{dims:s,dataType:n.dataType}],dispatchGroup:{x},programUniforms:[{type:6,data:$}]}),getShaderSource:de}},J0=(n,i)=>{Y0(n.inputs),n.compute(Z0(n.inputs[0],i))},ew=n=>qt({axis:n.axis})}),tw,rw,nw,iw,ow,sw,aw,lx=h(()=>{Zt(),Jt(),_r(),ar(),tw=n=>{if(!n||n.length<1)throw new Error("too few inputs")},rw=(n,i)=>{let s=[],u=i.numOutputs;return n[1].dims[0]>0&&(n[1].getBigInt64Array().forEach(c=>s.push(Number(c))),u=s.length),qt({numOutputs:u,axis:i.axis,splitSizes:s})},nw=n=>`
fn calculateOutputIndex(index: u32) -> u32 {
    for (var i: u32 = 0u; i < ${n}u; i += 1u ) {
    if (index < ${zt("uniforms.size_in_split_axis","i",n)}) {
        return i;
    }
    }
    return ${n}u;
}`,iw=n=>{let i=n.length,s=[];for(let u=0;u<i;++u){let c=n[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: ${n[0].type.indices}, global_idx: u32) {
        ${s.join(`
`)}
      }`},ow=(n,i)=>{let s=n[0].dims,u=ct.size(s),c=n[0].dataType,f=ct.normalizeAxis(i.axis,s.length),d=new Array(i.numOutputs),x=_t("input",c,s.length),k=new Array(i.numOutputs),$=[],H=[],q=0,v=[{type:12,data:u}];for(let te=0;te<i.numOutputs;te++){q+=i.splitSizes[te],k[te]=q;let de=s.slice();de[i.axis]=i.splitSizes[te],H.push(de),d[te]=Gt(`output${te}`,c,de.length),$.push({dims:H[te],dataType:n[0].dataType})}v.push({type:12,data:k},...At(s,...H));let oe=te=>`
  ${te.registerUniform("input_size","u32").registerUniform("size_in_split_axis","u32",k.length).declareVariables(x,...d)}
  ${nw(k.length)}
  ${iw(d)}

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

    var indices = ${x.offsetToIndices("global_idx")};
    var index = ${x.indicesGet("indices",f)};
    let output_number = calculateOutputIndex(index);
    if (output_number != 0) {
      index -= ${zt("uniforms.size_in_split_axis","output_number - 1u",k.length)};
      ${x.indicesSet("indices",f,"index")};
    }
    writeBufferData(output_number, indices, global_idx);
  }`;return{name:"Split",shaderCache:{hint:i.cacheKey,inputDependencies:["rank"]},getShaderSource:oe,getRunData:()=>({outputs:$,dispatchGroup:{x:Math.ceil(u/64)},programUniforms:v})}},sw=(n,i)=>{tw(n.inputs);let s=n.inputs.length===1?i:rw(n.inputs,i);n.compute(ow(n.inputs,s),{inputs:[0]})},aw=n=>{let i=n.axis,s=n.splitSizes,u=n.numOutputs<0?s.length:n.numOutputs;if(u!==s.length)throw new Error("numOutputs and splitSizes lengh must be equal");return qt({axis:i,numOutputs:u,splitSizes:s})}}),lw,uw,cw,ux=h(()=>{Zt(),Jt(),ar(),lw=(n,i,s,u,c)=>{let f=Gt("output_data",c,s.length,4),d=_t("a_data",i[1].dataType,i[1].dims.length,4),x=_t("b_data",i[2].dataType,i[2].dims.length,4),k=_t("c_data",i[0].dataType,i[0].dims.length,4),$,H=(q,v,oe)=>`select(${v}, ${q}, ${oe})`;if(!u)$=f.setByOffset("global_idx",H(d.getByOffset("global_idx"),x.getByOffset("global_idx"),k.getByOffset("global_idx")));else{let q=(v,oe,te="")=>{let de=`a_data[index_a${oe}][component_a${oe}]`,we=`b_data[index_b${oe}][component_b${oe}]`,be=`bool(c_data[index_c${oe}] & (0xffu << (component_c${oe} * 8)))`;return`
            let output_indices${oe} = ${f.offsetToIndices(`global_idx * 4u + ${oe}u`)};
            let offset_a${oe} = ${d.broadcastedIndicesToOffset(`output_indices${oe}`,f)};
            let offset_b${oe} = ${x.broadcastedIndicesToOffset(`output_indices${oe}`,f)};
            let offset_c${oe} = ${k.broadcastedIndicesToOffset(`output_indices${oe}`,f)};
            let index_a${oe} = offset_a${oe} / 4u;
            let index_b${oe} = offset_b${oe} / 4u;
            let index_c${oe} = offset_c${oe} / 4u;
            let component_a${oe} = offset_a${oe} % 4u;
            let component_b${oe} = offset_b${oe} % 4u;
            let component_c${oe} = offset_c${oe} % 4u;
            ${v}[${oe}] = ${te}(${H(de,we,be)});
          `};c===9?$=`
            var data = vec4<u32>(0);
            ${q("data",0,"u32")}
            ${q("data",1,"u32")}
            ${q("data",2,"u32")}
            ${q("data",3,"u32")}
            output_data[global_idx] = dot(vec4<u32>(0x1, 0x100, 0x10000, 0x1000000), vec4<u32>(data));`:$=`
            ${q("output_data[global_idx]",0)}
            ${q("output_data[global_idx]",1)}
            ${q("output_data[global_idx]",2)}
            ${q("output_data[global_idx]",3)}
          `}return`
        ${n.registerUniform("vec_size","u32").declareVariables(k,d,x,f)}
        ${n.mainStart()}
        ${n.guardAgainstOutOfBoundsWorkgroupSizes("uniforms.vec_size")}
        ${$}
      }`},uw=n=>{let i=n[1].dims,s=n[2].dims,u=n[0].dims,c=n[1].dataType,f=!(ct.areEqual(i,s)&&ct.areEqual(s,u)),d=i,x=ct.size(i);if(f){let $=gn.calcShape(gn.calcShape(i,s,!1),u,!1);if(!$)throw new Error("Can't perform where op on the given tensors");d=$,x=ct.size(d)}let k=Math.ceil(x/4);return{name:"Where",shaderCache:{inputDependencies:["rank","rank","rank"]},getShaderSource:$=>lw($,n,d,f,c),getRunData:()=>({outputs:[{dims:d,dataType:c}],dispatchGroup:{x:Math.ceil(x/64/4)},programUniforms:[{type:12,data:k},...At(u,i,s,d)]})}},cw=n=>{n.compute(uw(n.inputs))}}),dw,cx=h(()=>{nf(),zs(),tc(),of(),Oc(),sf(),af(),cd(),gm(),ff(),hf(),wf(),_m(),vf(),bf(),xf(),Bd(),Tf(),wm(),bn(),sl(),Sf(),Wd(),cr(),Jo(),$f(),$a(),nx(),ix(),ox(),sx(),ax(),lx(),Kd(),yo(),Ha(),ux(),dw=new Map([["Abs",[oc]],["Acos",[sc]],["Acosh",[Fa]],["Add",[Lc]],["ArgMax",[Gu,Os]],["ArgMin",[Wu,Os]],["Asin",[ac]],["Asinh",[lc]],["Atan",[Oa]],["Atanh",[uc]],["Attention",[Qu]],["AveragePool",[Pi,zn]],["BatchNormalization",[ec]],["BiasAdd",[Ia]],["BiasSplitGelu",[Fc]],["Cast",[Ds,cc]],["Ceil",[fc]],["Clip",[pc]],["Concat",[Ui,Kc]],["Conv",[Ko,ll]],["ConvTranspose",[pf,md]],["Cos",[za]],["Cosh",[hc]],["CumSum",[gl,wd]],["DepthToSpace",[wl,bd]],["Div",[Rc]],["Einsum",[Md,Td]],["Elu",[mc,bo]],["Equal",[Ka]],["Erf",[gc]],["Exp",[Da]],["Expand",[bl]],["FastGelu",[Ed]],["Floor",[_c]],["FusedConv",[Ko,ll]],["Gather",[Ad,$d]],["GatherElements",[zd,Od]],["Gelu",[wc]],["Gemm",[Mf,Rd]],["GlobalAveragePool",[Tn,dn]],["GlobalMaxPool",[mi,ym]],["Greater",[Uc]],["GreaterOrEqual",[Wc]],["GroupQueryAttention",[Zd,Qd]],["HardSigmoid",[Ba,Mc]],["InstanceNormalization",[rp]],["LayerNormalization",[hn]],["LeakyRelu",[yc,bo]],["Less",[Vc]],["LessOrEqual",[Xa]],["Log",[Ga]],["MatMul",[ad]],["MatMulNBits",[kf,ip]],["MaxPool",[Ks,El]],["Mul",[Bc]],["MultiHeadAttention",[Vd,jd]],["Neg",[vc]],["Not",[La]],["Pad",[Wt]],["Pow",[Nc]],["QuickGelu",[Ac,bo]],["Range",[Pf]],["Reciprocal",[bc]],["ReduceMin",[Ca]],["ReduceMean",[Lu]],["ReduceMax",[Nu]],["ReduceSum",[Uu]],["ReduceProd",[ju]],["ReduceL1",[Ru]],["ReduceL2",[Ea]],["ReduceLogSum",[Vu]],["ReduceLogSumExp",[Bu]],["ReduceSumSquare",[Pa]],["Relu",[Ra]],["Resize",[L0,R0]],["RotaryEmbedding",[j0]],["Sigmoid",[xc]],["Sin",[Tc]],["Sinh",[kc]],["Slice",[X0,Q0]],["SkipLayerNormalization",[W0]],["Split",[sw,aw]],["Sqrt",[Na]],["Softmax",[J0,ew]],["Sub",[jc]],["Tan",[Sc]],["Tanh",[Ua]],["ThresholdedRelu",[Cc,bo]],["Tile",[qd]],["Transpose",[fu,wa]],["Where",[cw]]])}),pw,dx=h(()=>{Z(),jn(),ar(),pw=class{constructor(n){this.backend=n,this.repo=new Map,this.attributesBound=!1}getArtifact(n){return this.repo.get(n)}setArtifact(n,i){this.repo.set(n,i)}run(n,i,s,u,c){et(n.programInfo.name);let f=this.backend.device,d=this.backend.getComputePassEncoder();this.backend.writeTimestamp(this.backend.pendingDispatchNumber*2);let x=[];for(let $ of i)x.push({binding:x.length,resource:{buffer:$.buffer}});for(let $ of s)x.push({binding:x.length,resource:{buffer:$.buffer}});c&&x.push({binding:x.length,resource:c});let k=f.createBindGroup({layout:n.computePipeline.getBindGroupLayout(0),entries:x,label:n.programInfo.name});if(this.backend.sessionStatus==="capturing"){let $={kernelId:this.backend.currentKernelId,computePipeline:n.computePipeline,bindGroup:k,dispatchGroup:u};this.backend.capturedCommandList.get(this.backend.currentSessionId).push($)}d.setPipeline(n.computePipeline),d.setBindGroup(0,k),d.dispatchWorkgroups(...u),this.backend.writeTimestamp(this.backend.pendingDispatchNumber*2+1),this.backend.pendingDispatchNumber++,(this.backend.pendingDispatchNumber>=this.backend.maxDispatchNumber||this.backend.queryType==="at-passes")&&this.backend.endComputePass(),this.backend.pendingDispatchNumber>=this.backend.maxDispatchNumber&&this.backend.flush(),A(n.programInfo.name)}dispose(){}build(n,i){et(n.name);let s=this.backend.device,u=[];s.features.has("shader-f16")&&u.push("enable f16;");let c=cu(i,this.backend.device.limits),f=n.getShaderSource(c),d=`${u.join(`
`)}
${c.additionalImplementations}
${f}`,x=s.createShaderModule({code:d,label:n.name});Vr("verbose",()=>`[WebGPU] ${n.name} shader code: ${d}`);let k=s.createComputePipeline({compute:{module:x,entryPoint:"main"},layout:"auto",label:n.name});return A(n.name),{programInfo:n,computePipeline:k,uniformVariablesInfo:c.variablesInfo}}normalizeDispatchGroupSize(n){let i=typeof n=="number"?n:n.x,s=typeof n=="number"?1:n.y||1,u=typeof n=="number"?1:n.z||1,c=this.backend.device.limits.maxComputeWorkgroupsPerDimension;if(i<=c&&s<=c&&u<=c)return[i,s,u];let f=i*s*u,d=Math.ceil(Math.sqrt(f));if(d>c){if(d=Math.ceil(Math.cbrt(f)),d>c)throw new Error("Total dispatch size exceeds WebGPU maximum.");return[d,d,d]}else return[d,d,1]}}}),fw,hw,mw,gw,px=h(()=>{Z(),Zt(),jn(),W(),Ar(),cx(),dx(),fw=(n,i)=>{if(i.length!==n.length)throw new Error(`inputDependencies length ${i.length} is not equal to inputTensors length ${n.length}.`);let s=[];for(let u=0;u<n.length;++u){let c=n[u].dataType;switch(i[u]){case"none":{s.push("");break}case"type":{s.push(`${c}`);break}case"rank":{let f=n[u].dims.length;s.push(`${c};${f}`);break}case"dims":{let f=n[u].dims.join(",");s.push(`${c};${f}`);break}default:throw new Error(`unsupported input dependency: ${i[u]}`)}}return s.join("|")},hw=(n,i,s)=>{var c,f;let u=n.name;return(c=n.shaderCache)!=null&&c.hint&&(u+="["+n.shaderCache.hint+"]"),u+=":"+s+`:${fw(i,((f=n.shaderCache)==null?void 0:f.inputDependencies)??new Array(i.length).fill("dims"))}`,u},mw=class{constructor(n){n&&(this.architecture=n.architecture,this.vendor=n.vendor)}isArchitecture(n){return this.architecture===n}isVendor(n){return this.vendor===n}},gw=class{constructor(){this.currentSessionId=null,this.currentKernelId=null,this.commandEncoder=null,this.computePassEncoder=null,this.maxDispatchNumber=16,this.pendingDispatchNumber=0,this.pendingKernels=[],this.pendingQueries=new Map,this.sessionStatus="default",this.capturedCommandList=new Map,this.capturedPendingKernels=new Map,this.sessionExternalDataMapping=new Map}get currentKernelCustomData(){if(this.currentKernelId===null)throw new Error("currentKernelCustomData(): currentKernelId is null. (should not happen)");let n=this.kernelCustomData.get(this.currentKernelId);return n||(n={},this.kernelCustomData.set(this.currentKernelId,n)),n}async initialize(n,i){this.env=n;let s=[],u={requiredLimits:{maxComputeWorkgroupStorageSize:i.limits.maxComputeWorkgroupStorageSize,maxComputeWorkgroupsPerDimension:i.limits.maxComputeWorkgroupsPerDimension,maxStorageBufferBindingSize:i.limits.maxStorageBufferBindingSize,maxBufferSize:i.limits.maxBufferSize,maxComputeInvocationsPerWorkgroup:i.limits.maxComputeInvocationsPerWorkgroup,maxComputeWorkgroupSizeX:i.limits.maxComputeWorkgroupSizeX,maxComputeWorkgroupSizeY:i.limits.maxComputeWorkgroupSizeY,maxComputeWorkgroupSizeZ:i.limits.maxComputeWorkgroupSizeZ},requiredFeatures:s};i.features.has("chromium-experimental-timestamp-query-inside-passes")?s.push("chromium-experimental-timestamp-query-inside-passes"):i.features.has("timestamp-query")&&s.push("timestamp-query"),i.features.has("shader-f16")&&s.push("shader-f16"),this.device=await i.requestDevice(u),this.adapterInfo=new mw(i.info||await i.requestAdapterInfo()),this.gpuDataManager=tr(this),this.programManager=new pw(this),this.kernels=new Map,this.kernelPersistentData=new Map,this.kernelCustomData=new Map,_o(n.logLevel,!!n.debug),this.device.onuncapturederror=c=>{c.error instanceof GPUValidationError&&console.error(`An uncaught WebGPU validation error was raised: ${c.error.message}`)},Object.defineProperty(this.env.webgpu,"device",{value:this.device,writable:!1,enumerable:!0,configurable:!1}),Object.defineProperty(this.env.webgpu,"adapter",{value:i,writable:!1,enumerable:!0,configurable:!1}),this.setQueryType()}dispose(){typeof this.querySet<"u"&&this.querySet.destroy(),this.gpuDataManager.dispose()}getCommandEncoder(){return this.commandEncoder||(this.commandEncoder=this.device.createCommandEncoder()),this.commandEncoder}getComputePassEncoder(){if(!this.computePassEncoder){let n=this.getCommandEncoder(),i={};this.queryType==="at-passes"&&(i.timestampWrites={querySet:this.querySet,beginningOfPassWriteIndex:this.pendingDispatchNumber*2,endOfPassWriteIndex:this.pendingDispatchNumber*2+1}),this.computePassEncoder=n.beginComputePass(i)}return this.computePassEncoder}endComputePass(){this.computePassEncoder&&(this.computePassEncoder.end(),this.computePassEncoder=null)}flush(){if(!this.commandEncoder)return;et(),this.endComputePass();let n;this.queryType!=="none"&&(this.commandEncoder.resolveQuerySet(this.querySet,0,this.pendingDispatchNumber*2,this.queryResolveBuffer,0),n=this.device.createBuffer({size:this.pendingDispatchNumber*2*8,usage:GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST}),this.pendingQueries.set(n,this.pendingKernels),this.pendingKernels=[],this.commandEncoder.copyBufferToBuffer(this.queryResolveBuffer,0,n,0,this.pendingDispatchNumber*2*8)),this.device.queue.submit([this.commandEncoder.finish()]),this.gpuDataManager.refreshPendingBuffers(),this.commandEncoder=null,this.pendingDispatchNumber=0,this.queryType!=="none"&&n.mapAsync(GPUMapMode.READ).then(()=>{var u;let i=new BigUint64Array(n.getMappedRange()),s=this.pendingQueries.get(n);for(let c=0;c<i.length/2;c++){let f=s[c],d=f.kernelId,x=this.kernels.get(d),k=x.kernelType,$=x.kernelName,H=f.programName,q=f.inputTensorViews,v=f.outputTensorViews,oe=i[c*2],te=i[c*2+1];typeof this.queryTimeBase>"u"&&(this.queryTimeBase=oe);let de=Number(oe-this.queryTimeBase),we=Number(te-this.queryTimeBase);if(!Number.isSafeInteger(de)||!Number.isSafeInteger(we))throw new RangeError("incorrect timestamp range");if((u=this.env.webgpu.profiling)!=null&&u.ondata)this.env.webgpu.profiling.ondata({version:1,inputsMetadata:q.map(be=>({dims:be.dims,dataType:fi(be.dataType)})),outputsMetadata:v.map(be=>({dims:be.dims,dataType:fi(be.dataType)})),kernelId:d,kernelType:k,kernelName:$,programName:H,startTime:de,endTime:we});else{let be="";q.forEach((De,Ae)=>{be+=`input[${Ae}]: [${De.dims}] | ${fi(De.dataType)}, `});let he="";v.forEach((De,Ae)=>{he+=`output[${Ae}]: [${De.dims}] | ${fi(De.dataType)}, `}),console.log(`[profiling] kernel "${d}|${k}|${$}|${H}" ${be}${he}execution time: ${we-de} ns`)}je("GPU",`${H}::${oe}::${te}`)}n.unmap(),this.pendingQueries.delete(n)}),A()}run(n,i,s,u,c,f){et(n.name);let d=[];for(let he=0;he<i.length;++he){let De=i[he].data;if(De===0)continue;let Ae=this.gpuDataManager.get(De);if(!Ae)throw new Error(`no GPU data for input: ${De}`);d.push(Ae)}let{outputs:x,dispatchGroup:k,programUniforms:$}=n.getRunData(i),H=s.length===0?x.map((he,De)=>De):s;if(H.length!==x.length)throw new Error(`Output size ${H.length} must be equal to ${x.length}.`);let q=[],v=[];for(let he=0;he<x.length;++he){if(!Number.isInteger(H[he])||H[he]<-3||H[he]>=f)throw new Error(`Invalid output index: ${H[he]}`);if(H[he]===-3)continue;let De=H[he]===-1,Ae=H[he]===-2,Ie=De||Ae?c(x[he].dataType,x[he].dims):u(H[he],x[he].dataType,x[he].dims);if(q.push(Ie),Ie.data===0)continue;let gt=this.gpuDataManager.get(Ie.data);if(!gt)throw new Error(`no GPU data for output: ${Ie.data}`);if(De&&this.temporaryData.push(gt),Ae){let ut=this.kernelPersistentData.get(this.currentKernelId);ut||(ut=[],this.kernelPersistentData.set(this.currentKernelId,ut)),ut.push(gt)}v.push(gt)}if(d.length!==i.length||v.length!==q.length){if(v.length===0)return A(n.name),q;throw new Error(`Program ${n.name} has zero-sized tensor(s) in inputs or outputs. This is not supported now.`)}let oe;if($){let he=0,De=[];$.forEach(ut=>{let vt=typeof ut.data=="number"?[ut.data]:ut.data;if(vt.length===0)return;let Dt=ut.type===10?2:4,Rt,gr;ut.type===10?(gr=vt.length>4?16:vt.length>2?8:vt.length*Dt,Rt=vt.length>4?16:Dt*vt.length):(gr=vt.length<=2?vt.length*Dt:16,Rt=16),he=Math.ceil(he/gr)*gr,De.push(he);let Mr=ut.type===10?8:4;he+=vt.length>4?Math.ceil(vt.length/Mr)*Rt:vt.length*Dt});let Ae=16;he=Math.ceil(he/Ae)*Ae;let Ie=new ArrayBuffer(he);$.forEach((ut,vt)=>{let Dt=De[vt],Rt=typeof ut.data=="number"?[ut.data]:ut.data;if(ut.type===6)new Int32Array(Ie,Dt,Rt.length).set(Rt);else if(ut.type===12)new Uint32Array(Ie,Dt,Rt.length).set(Rt);else if(ut.type===10)new Uint16Array(Ie,Dt,Rt.length).set(Rt);else if(ut.type===1)new Float32Array(Ie,Dt,Rt.length).set(Rt);else throw new Error(`Unsupported uniform type: ${fi(ut.type)}`)});let gt=this.gpuDataManager.create(he,GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM);this.device.queue.writeBuffer(gt.buffer,0,Ie,0,he),this.gpuDataManager.release(gt.id),oe={offset:0,size:he,buffer:gt.buffer}}let te=this.programManager.normalizeDispatchGroupSize(k),de=te[1]===1&&te[2]===1,we=hw(n,i,de),be=this.programManager.getArtifact(we);if(be||(be=this.programManager.build(n,te),this.programManager.setArtifact(we,be),Vr("info",()=>`[artifact] key: ${we}, programName: ${n.name}`)),$&&be.uniformVariablesInfo){if($.length!==be.uniformVariablesInfo.length)throw new Error(`Uniform variables count mismatch: expect ${be.uniformVariablesInfo.length}, got ${$.length} in program "${be.programInfo.name}".`);for(let he=0;he<$.length;he++){let De=$[he],Ae=De.type,Ie=typeof De.data=="number"?1:De.data.length,[gt,ut]=be.uniformVariablesInfo[he];if(Ae!==gt||Ie!==ut)throw new Error(`Uniform variable ${he} mismatch: expect type ${gt} with size ${ut}, got type ${Ae} with size ${Ie} in program "${be.programInfo.name}".`)}}if(Vr("info",()=>`[ProgramManager] run "${n.name}" (key=${we}) with ${te[0]}x${te[1]}x${te[2]}`),this.queryType!=="none"||this.sessionStatus==="capturing"){let he={kernelId:this.currentKernelId,programName:be.programInfo.name,inputTensorViews:i,outputTensorViews:q};this.pendingKernels.push(he),this.sessionStatus==="capturing"&&this.capturedPendingKernels.get(this.currentSessionId).push(he)}return this.programManager.run(be,d,v,te,oe),A(n.name),q}upload(n,i){this.gpuDataManager.upload(n,i)}memcpy(n,i){this.gpuDataManager.memcpy(n,i)}async download(n,i){await this.gpuDataManager.download(n,i)}alloc(n){return this.gpuDataManager.create(n).id}free(n){return this.gpuDataManager.release(n)}createKernel(n,i,s,u){let c=dw.get(n);if(!c)throw new Error(`kernel not implemented: ${n}`);let f={kernelType:n,kernelName:u,kernelEntry:c[0],attributes:[c[1],s]};this.kernels.set(i,f)}releaseKernel(n){let i=this.kernelPersistentData.get(n);if(i){for(let s of i)this.gpuDataManager.release(s.id);this.kernelPersistentData.delete(n)}this.kernelCustomData.delete(n),this.kernels.delete(n)}computeKernel(n,i,s){let u=this.kernels.get(n);if(!u)throw new Error(`kernel not created: ${n}`);let c=u.kernelType,f=u.kernelName,d=u.kernelEntry,x=u.attributes;if(this.currentKernelId!==null)throw new Error(`kernel "[${c}] ${f}" is not allowed to be called recursively`);this.currentKernelId=n,x[0]&&(x[1]=x[0](x[1]),x[0]=void 0),Vr("info",()=>`[WebGPU] Start to run kernel "[${c}] ${f}"...`);let k=this.env.debug;this.temporaryData=[];try{return k&&this.device.pushErrorScope("validation"),d(i,x[1]),0}catch($){return s.push(Promise.resolve(`[WebGPU] Kernel "[${c}] ${f}" failed. ${$}`)),1}finally{k&&s.push(this.device.popErrorScope().then($=>$?`GPU validation error for kernel "[${c}] ${f}": ${$.message}`:null));for(let $ of this.temporaryData)this.gpuDataManager.release($.id);this.temporaryData=[],this.currentKernelId=null}}registerBuffer(n,i,s,u){let c=this.sessionExternalDataMapping.get(n);c||(c=new Map,this.sessionExternalDataMapping.set(n,c));let f=c.get(i),d=this.gpuDataManager.registerExternalBuffer(s,u,f==null?void 0:f[1]);return c.set(i,[d,s]),d}unregisterBuffers(n){let i=this.sessionExternalDataMapping.get(n);i&&(i.forEach(s=>this.gpuDataManager.unregisterExternalBuffer(s[1])),this.sessionExternalDataMapping.delete(n))}getBuffer(n){let i=this.gpuDataManager.get(n);if(!i)throw new Error(`no GPU data for buffer: ${n}`);return i.buffer}createDownloader(n,i,s){return async()=>{let u=await kt(this,n,i);return Ue(u.buffer,s)}}writeTimestamp(n){this.queryType==="inside-passes"&&this.computePassEncoder.writeTimestamp(this.querySet,n)}setQueryType(){var n;this.queryType="none",(((n=this.env.webgpu.profiling)==null?void 0:n.mode)==="default"||(typeof this.env.trace>"u"?this.env.wasm.trace:this.env.trace))&&(this.device.features.has("chromium-experimental-timestamp-query-inside-passes")?this.queryType="inside-passes":this.device.features.has("timestamp-query")&&(this.queryType="at-passes"),this.queryType!=="none"&&typeof this.querySet>"u"&&(this.querySet=this.device.createQuerySet({type:"timestamp",count:this.maxDispatchNumber*2}),this.queryResolveBuffer=this.device.createBuffer({size:this.maxDispatchNumber*2*8,usage:GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE})))}captureBegin(){Vr("info","captureBegin"),this.capturedCommandList.get(this.currentSessionId)||this.capturedCommandList.set(this.currentSessionId,[]),this.capturedPendingKernels.get(this.currentSessionId)||this.capturedPendingKernels.set(this.currentSessionId,[]),this.flush(),this.sessionStatus="capturing"}captureEnd(){Vr("info","captureEnd"),this.flush(),this.sessionStatus="default"}replay(){Vr("info","replay"),this.sessionStatus="replaying";let n=this.capturedCommandList.get(this.currentSessionId),i=this.capturedPendingKernels.get(this.currentSessionId),s=n.length;this.pendingKernels=[];for(let u=0;u<s;u++){let c=this.getComputePassEncoder(),f=n[u];this.writeTimestamp(this.pendingDispatchNumber*2),c.setPipeline(f.computePipeline),c.setBindGroup(0,f.bindGroup),c.dispatchWorkgroups(...f.dispatchGroup),this.writeTimestamp(this.pendingDispatchNumber*2+1),this.pendingDispatchNumber++,this.queryType!=="none"&&this.pendingKernels.push(i[u]),(this.pendingDispatchNumber>=this.maxDispatchNumber||this.queryType==="at-passes")&&this.endComputePass(),this.pendingDispatchNumber>=this.maxDispatchNumber&&this.flush()}this.flush(),this.sessionStatus="default"}onReleaseSession(n){this.unregisterBuffers(n),this.capturedCommandList.has(n)&&this.capturedCommandList.delete(n),this.capturedPendingKernels.has(n)&&this.capturedPendingKernels.delete(n),this.gpuDataManager.onReleaseSession(n)}onRunStart(n){this.currentSessionId=n,this.setQueryType()}}}),_w={};g(_w,{init:()=>yw});var Af,ww,yw,fx=h(()=>{Zt(),px(),jn(),Jt(),Af=class ex{constructor(i,s,u,c){this.module=i,this.dataType=s,this.data=u,this.dims=c}getFloat32Array(){if(this.dataType!==1)throw new Error("Invalid data type");let i=ct.size(this.dims);return i===0?new Float32Array:new Float32Array(this.module.HEAP8.buffer,this.data,i)}getBigInt64Array(){if(this.dataType!==7)throw new Error("Invalid data type");let i=ct.size(this.dims);return i===0?new BigInt64Array:new BigInt64Array(this.module.HEAP8.buffer,this.data,i)}getInt32Array(){if(this.dataType!==6)throw new Error("Invalid data type");let i=ct.size(this.dims);return i===0?new Int32Array:new Int32Array(this.module.HEAP8.buffer,this.data,i)}reshape(i){if(ct.size(i)!==ct.size(this.dims))throw new Error("Invalid new shape");return new ex(this.module,this.dataType,this.data,i)}},ww=class{constructor(n,i,s){this.module=n,this.backend=i,this.customDataOffset=0,this.customDataSize=0,this.adapterInfo=i.adapterInfo;let u=n.HEAPU32,c=s>>>2;this.opKernelContext=u[c++];let f=u[c++];this.outputCount=u[c++],this.customDataOffset=u[c++],this.customDataSize=u[c++];let d=[];for(let x=0;x<f;x++){let k=u[c++],$=u[c++],H=u[c++],q=[];for(let v=0;v<H;v++)q.push(u[c++]);d.push(new Af(n,k,$,q))}this.inputs=d}get kernelCustomData(){return this.backend.currentKernelCustomData}get customDataBuffer(){return this.module.HEAPU8.subarray(this.customDataOffset,this.customDataOffset+this.customDataSize)}getMaxComputeWorkgroupSizes(){return[this.backend.device.limits.maxComputeWorkgroupSizeX,this.backend.device.limits.maxComputeWorkgroupSizeY,this.backend.device.limits.maxComputeWorkgroupSizeZ]}getMaxComputeWorkgroupStoragesize(){return this.backend.device.limits.maxComputeWorkgroupStorageSize}compute(n,i){var d;let s=((d=i==null?void 0:i.inputs)==null?void 0:d.map(x=>typeof x=="number"?this.inputs[x]:x))??this.inputs,u=(i==null?void 0:i.outputs)??[],c=(x,k,$)=>new Af(this.module,k,this.output(x,$),$),f=(x,k)=>{let $=ki(x);if(!$)throw new Error(`Unsupported data type: ${x}`);let H=$*ct.size(k),q=H>0?this.backend.gpuDataManager.create(H).id:0;return new Af(this.module,x,q,k)};return this.backend.run(n,s,u,c,f,this.outputCount)}output(n,i){let s=this.module.stackSave();try{let u=this.module.stackAlloc((1+i.length)*4),c=u>>2;this.module.HEAPU32[c++]=i.length;for(let f=0;f<i.length;f++)this.module.HEAPU32[c++]=i[f];return this.module._JsepOutput(this.opKernelContext,n,u)}catch(u){throw new Error(`Failed to generate kernel's output[${n}] with dims [${i}]. If you are running with pre-allocated output, please make sure the output type/dims are correct. Error: ${u}`)}finally{this.module.stackRestore(s)}}},yw=async(n,i,s,u)=>{let c=i.jsepInit;if(!c)throw new Error("Failed to initialize JSEP. The WebAssembly module is not built with JSEP support.");if(n==="webgpu"){let f=new gw;await f.initialize(s,u),c("webgpu",[f,d=>f.alloc(d),d=>f.free(d),(d,x,k,$=!1)=>{if($)Vr("verbose",()=>`[WebGPU] jsepCopyGpuToGpu: src=${d}, dst=${x}, size=${k}`),f.memcpy(d,x);else{Vr("verbose",()=>`[WebGPU] jsepCopyCpuToGpu: dataOffset=${d}, gpuDataId=${x}, size=${k}`);let H=i.HEAPU8.subarray(d>>>0,(d>>>0)+k);f.upload(x,H)}},async(d,x,k)=>{Vr("verbose",()=>`[WebGPU] jsepCopyGpuToCpu: gpuDataId=${d}, dataOffset=${x}, size=${k}`),await f.download(d,()=>i.HEAPU8.subarray(x>>>0,(x>>>0)+k))},(d,x,k)=>f.createKernel(d,x,k,i.UTF8ToString(i._JsepGetNodeName(x))),d=>f.releaseKernel(d),(d,x,k,$)=>{Vr("verbose",()=>`[WebGPU] jsepRun: sessionHandle=${k}, kernel=${d}, contextDataOffset=${x}`);let H=new ww(i,f,x);return f.computeKernel(d,H,$)},()=>f.captureBegin(),()=>f.captureEnd(),()=>f.replay()])}else c("webnn")}}),vw,xm,Mm,es,bw,If,Tm,km,Sm,Em,Cm,Pm,xw=h(()=>{Cs(),Ps(),Zt(),wn(),Ni(),jo(),vw=(n,i)=>{Gr()._OrtInit(n,i)!==0&&Dr("Can't initialize onnxruntime.")},xm=async n=>{vw(n.wasm.numThreads,Ji(n.logLevel))},Mm=async(n,i)=>{{let s=(fx(),y(_w)).init;if(i==="webgpu"){if(typeof navigator>"u"||!navigator.gpu)throw new Error("WebGPU is not supported in current environment");let u=n.webgpu.adapter;if(u){if(typeof u.limits!="object"||typeof u.features!="object"||typeof u.requestDevice!="function")throw new Error("Invalid GPU adapter set in `env.webgpu.adapter`. It must be a GPUAdapter object.")}else{let c=n.webgpu.powerPreference;if(c!==void 0&&c!=="low-power"&&c!=="high-performance")throw new Error(`Invalid powerPreference setting: "${c}"`);let f=n.webgpu.forceFallbackAdapter;if(f!==void 0&&typeof f!="boolean")throw new Error(`Invalid forceFallbackAdapter setting: "${f}"`);if(u=await navigator.gpu.requestAdapter({powerPreference:c,forceFallbackAdapter:f}),!u)throw new Error('Failed to get GPU adapter. 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Only 'gpu-buffer' location is supported when enableGraphCapture is true.`);he.push(ut)}}let De=null;return he.some(Ae=>Ae==="gpu-buffer")&&(x=c._OrtCreateBinding(f),x===0&&Dr("Can't create IO binding."),De={handle:x,outputPreferredLocations:he,outputPreferredLocationsEncoded:he.map(Ae=>mo(Ae))}),es.set(f,[f,$,H,De,de,!1]),[f,we,be]}catch(oe){throw $.forEach(te=>c._OrtFree(te)),H.forEach(te=>c._OrtFree(te)),x!==0&&c._OrtReleaseBinding(x),f!==0&&c._OrtReleaseSession(f),oe}finally{c._free(s),d!==0&&c._OrtReleaseSessionOptions(d),k.forEach(oe=>c._free(oe)),(v=c.unmountExternalData)==null||v.call(c)}},km=n=>{var k;let i=Gr(),s=es.get(n);if(!s)throw new Error(`cannot release session. invalid session id: ${n}`);let[u,c,f,d,x]=s;d&&(x&&i._OrtClearBoundOutputs(d.handle),i._OrtReleaseBinding(d.handle)),(k=i.jsepOnReleaseSession)==null||k.call(i,n),c.forEach($=>i._OrtFree($)),f.forEach($=>i._OrtFree($)),i._OrtReleaseSession(u),es.delete(n)},Sm=(n,i,s,u,c,f=!1)=>{if(!n){i.push(0);return}let d=Gr(),x=n[0],k=n[1],$=n[3],H,q;if(x==="string"&&$==="gpu-buffer")throw new Error("String tensor is not supported on GPU.");if(f&&$!=="gpu-buffer")throw new Error(`External buffer must be provided for input/output index ${c} when enableGraphCapture is true.`);if($==="gpu-buffer"){let te=n[2].gpuBuffer,de=ki(fo(x));q=k.reduce((be,he)=>be*he,1)*de;let we=d.jsepRegisterBuffer;if(!we)throw new Error('Tensor location "gpu-buffer" is not supported without using WebGPU.');H=we(u,c,te,q)}else{let te=n[2];if(Array.isArray(te)){q=4*te.length,H=d._malloc(q),s.push(H);let de=H/4;for(let we=0;we<te.length;we++){if(typeof te[we]!="string")throw new TypeError(`tensor data at index ${we} is not a string`);d.HEAPU32[de++]=Kr(te[we],s)}}else q=te.byteLength,H=d._malloc(q),s.push(H),d.HEAPU8.set(new Uint8Array(te.buffer,te.byteOffset,q),H)}let v=d.stackSave(),oe=d.stackAlloc(4*k.length);try{let te=oe/4;k.forEach(we=>d.HEAP32[te++]=we);let de=d._OrtCreateTensor(fo(x),H,q,oe,k.length,mo($));de===0&&Dr(`Can't create tensor for input/output. session=${u}, index=${c}.`),i.push(de)}finally{d.stackRestore(v)}},Em=async(n,i,s,u,c,f)=>{var Rt,gr;let d=Gr(),x=es.get(n);if(!x)throw new Error(`cannot run inference. invalid session id: ${n}`);let k=x[0],$=x[1],H=x[2],q=x[3],v=x[4],oe=x[5],te=i.length,de=u.length,we=0,be=[],he=[],De=[],Ae=[],Ie=d.stackSave(),gt=d.stackAlloc(te*4),ut=d.stackAlloc(te*4),vt=d.stackAlloc(de*4),Dt=d.stackAlloc(de*4);try{[we,be]=Ti(f);for(let Nt=0;Nt<te;Nt++)Sm(s[Nt],he,Ae,n,i[Nt],v);for(let Nt=0;Nt<de;Nt++)Sm(c[Nt],De,Ae,n,te+u[Nt],v);let Mr=gt/4,ir=ut/4,Fr=vt/4,Zr=Dt/4;for(let Nt=0;Nt<te;Nt++)d.HEAPU32[Mr++]=he[Nt],d.HEAPU32[ir++]=$[i[Nt]];for(let Nt=0;Nt<de;Nt++)d.HEAPU32[Fr++]=De[Nt],d.HEAPU32[Zr++]=H[u[Nt]];if(q&&!oe){let{handle:Nt,outputPreferredLocations:er,outputPreferredLocationsEncoded:yr}=q;if($.length!==te)throw new Error(`input count from feeds (${te}) is expected to be always equal to model's 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rs=d.HEAPU32[pn++],si=d.HEAPU32[pn++],gi=[];for(let Ln=0;Ln<si;Ln++)gi.push(d.HEAPU32[rs/4+Ln]);d._OrtFree(rs);let Dn=gi.reduce((Ln,Jn)=>Ln*Jn,1);nr=fi(kn);let lp=q==null?void 0:q.outputPreferredLocations[u[Nt]];if(nr==="string"){if(lp==="gpu-buffer")throw new Error("String tensor is not supported on GPU.");let Ln=[],Jn=Wr/4;for(let $i=0;$i<Dn;$i++){let ns=d.HEAPU32[Jn++],zf=$i===Dn-1?void 0:d.HEAPU32[Jn]-ns;Ln.push(d.UTF8ToString(ns,zf))}Hr.push([nr,gi,Ln,"cpu"])}else if(lp==="gpu-buffer"&&Dn>0){let Ln=d.jsepGetBuffer;if(!Ln)throw new Error('preferredLocation "gpu-buffer" is not supported without using WebGPU.');let Jn=Ln(Wr),$i=ki(kn);if($i===void 0||!ho(nr))throw new Error(`Unsupported data type: ${nr}`);Vt=!0,Hr.push([nr,gi,{gpuBuffer:Jn,download:d.jsepCreateDownloader(Jn,Dn*$i,nr),dispose:()=>{d._OrtReleaseTensor(er)}},"gpu-buffer"])}else{let Ln=Si(nr),Jn=new Ln(Dn);new 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 * @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.
 * =============================================================================
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o=r("./src/utils/generic.js");r("./src/utils/tensor.js");var a=r("./src/utils/maths.js");class l extends o.Callable{_call(B,j){throw Error("`_call` should be implemented in a subclass")}}class p extends o.Callable{_call(B,j){throw Error("`_call` should be implemented in a subclass")}}class _ extends o.Callable{constructor(){super(),this.processors=[]}push(B){this.processors.push(B)}extend(B){this.processors.push(...B)}_call(B,j){let N=j;for(const ae of this.processors)N=ae(B,N);return N}[Symbol.iterator](){return this.processors.values()}}class h extends l{constructor(B){super(),this.bos_token_id=B}_call(B,j){for(let N=0;N<B.length;++N)if(B[N].length===1){const ae=j[N];ae.data.fill(-1/0),ae.data[this.bos_token_id]=0}return j}}class g extends l{constructor(B,j){super(),this.max_length=B,this.eos_token_id=Array.isArray(j)?j:[j]}_call(B,j){for(let N=0;N<B.length;++N)if(B[N].length===this.max_length-1){const ae=j[N];ae.data.fill(-1/0);for(const ce of this.eos_token_id)ae.data[ce]=0}return j}}class M extends l{constructor(B,j){super(),this.begin_suppress_tokens=B,this.begin_index=j}_call(B,j){for(let N=0;N<B.length;++N)if(B[N].length===this.begin_index){const ae=j[N];for(const ce of this.begin_suppress_tokens)ae.data[ce]=-1/0}return j}}class y extends l{constructor(B,j){super(),this.eos_token_id=Array.isArray(B.eos_token_id)?B.eos_token_id[0]:B.eos_token_id,this.no_timestamps_token_id=B.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=B.max_initial_timestamp_index}_call(B,j){for(let N=0;N<B.length;++N){const ce=j[N].data;if(ce[this.no_timestamps_token_id]=-1/0,B[N].length===this.begin_index-1){ce.fill(-1/0),ce[this.timestamp_begin]=0;continue}const xe=B[N].slice(this.begin_index),Y=xe.length>=1&&xe[xe.length-1]>=this.timestamp_begin,_e=xe.length<2||xe[xe.length-2]>=this.timestamp_begin;if(Y&&(_e?ce.subarray(this.timestamp_begin).fill(-1/0):ce.subarray(0,this.eos_token_id).fill(-1/0)),B[N].length===this.begin_index&&this.max_initial_timestamp_index!==null){const me=this.timestamp_begin+this.max_initial_timestamp_index;ce.subarray(me+1).fill(-1/0)}const L=(0,a.log_softmax)(ce),Se=Math.log(L.subarray(this.timestamp_begin).map(Math.exp).reduce((me,X)=>me+X)),Xe=(0,a.max)(L.subarray(0,this.timestamp_begin))[0];Se>Xe&&ce.subarray(0,this.timestamp_begin).fill(-1/0)}return j}}class E extends l{constructor(B){super(),this.no_repeat_ngram_size=B}getNgrams(B){const j=B.length,N=[];for(let ce=0;ce<j+1-this.no_repeat_ngram_size;++ce){const xe=[];for(let Y=0;Y<this.no_repeat_ngram_size;++Y)xe.push(B[ce+Y]);N.push(xe.map(Number))}const ae=new Map;for(const ce of N){const xe=ce.slice(0,ce.length-1),Y=JSON.stringify(xe),_e=ae.get(Y)??[];_e.push(ce[ce.length-1]),ae.set(Y,_e)}return ae}getGeneratedNgrams(B,j){const N=j.slice(j.length+1-this.no_repeat_ngram_size,j.length);return B.get(JSON.stringify(N.map(Number)))??[]}calcBannedNgramTokens(B){const j=[];if(B.length+1<this.no_repeat_ngram_size)return j;{const N=this.getNgrams(B);return this.getGeneratedNgrams(N,B)}}_call(B,j){for(let N=0;N<B.length;++N){const ae=j[N],ce=this.calcBannedNgramTokens(B[N]);for(const xe of ce)ae.data[xe]=-1/0}return j}}class T extends l{constructor(B){super(),this.penalty=B}_call(B,j){for(let N=0;N<B.length;++N){const ae=j[N];for(const ce of B[N])ae.data[ce]<0?ae.data[ce]*=this.penalty:ae.data[ce]/=this.penalty}return j}}class O extends l{constructor(B,j){super(),this.min_length=B,this.eos_token_id=Array.isArray(j)?j:[j]}_call(B,j){for(let N=0;N<B.length;++N)if(B[N].length<this.min_length){const ae=j[N];for(const ce of this.eos_token_id)ae.data[ce]=-1/0}return j}}class S extends l{constructor(B,j,N){super(),this.prompt_length_to_skip=B,this.min_new_tokens=j,this.eos_token_id=Array.isArray(N)?N:[N]}_call(B,j){for(let N=0;N<B.length;++N)if(B[N].length-this.prompt_length_to_skip<this.min_new_tokens){const ce=j[N];for(const xe of this.eos_token_id)ce[xe]=-1/0}return j}}class C extends l{constructor(B,j){super(),this.bad_words_ids=B,this.eos_token_id=Array.isArray(j)?j:[j]}_call(B,j){for(let N=0;N<B.length;++N){const ae=j[N];for(const ce of this.bad_words_ids){let xe=!0;for(let Y=1;Y<=ce.length-1&&ce.length<B[Y].length;++Y)if(ce.at(-Y-1)!==Number(B[Y].at(-Y))){xe=!1;break}xe&&(ae[ce.at(-1)]=-1/0)}}return j}}class w extends l{constructor(B){if(super(),B<=1)throw new Error(`Require guidance scale >1 to use the classifier free guidance processor, got guidance scale ${B}.`);this.guidance_scale=B}_call(B,j){if(j.dims[0]!==2*B.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 ${B.length} for the input ids.`);const N=B.length,ae=j.slice([0,N],null),ce=j.slice([N,j.dims[0]],null);for(let xe=0;xe<ce.data.length;++xe)ce.data[xe]+=(ae.data[xe]-ce.data[xe])*this.guidance_scale;return ce}}class b extends p{constructor(B){super(),this.temperature=B}_call(B,j){const N=j.data;for(let ae=0;ae<N.length;++ae)N[ae]/=this.temperature;return j}}class I extends p{constructor(B,{filter_value:j=-1/0,min_tokens_to_keep:N=1}={}){if(super(),B<0||B>1)throw new Error(`\`top_p\` must be a float > 0 and < 1, but is ${B}`);if(!Number.isInteger(N)||N<1)throw new Error(`\`min_tokens_to_keep\` must be a positive integer, but is ${N}`);this.top_p=B,this.filter_value=j,this.min_tokens_to_keep=N}}class U extends p{constructor(B,{filter_value:j=-1/0,min_tokens_to_keep:N=1}={}){if(super(),!Number.isInteger(B)||B<0)throw new Error(`\`top_k\` must be a positive integer, but is ${B}`);this.top_k=Math.max(B,N),this.filter_value=j}}},"./src/generation/logits_sampler.js":(e,t,r)=>{r.r(t),r.d(t,{LogitsSampler:()=>p});var o=r("./src/utils/generic.js"),a=r("./src/utils/tensor.js"),l=r("./src/utils/maths.js");r("./src/generation/configuration_utils.js");class p extends o.Callable{constructor(y){super(),this.generation_config=y}async _call(y){return this.sample(y)}async sample(y){throw Error("sample should be implemented in subclasses.")}getLogits(y,E){let T=y.dims.at(-1),O=y.data;if(E===-1)O=O.slice(-T);else{let S=E*T;O=O.slice(S,S+T)}return O}randomSelect(y){let E=0;for(let O=0;O<y.length;++O)E+=y[O];let T=Math.random()*E;for(let O=0;O<y.length;++O)if(T-=y[O],T<=0)return O;return 0}static getSampler(y){if(y.do_sample)return new h(y);if(y.num_beams>1)return new g(y);if(y.num_return_sequences>1)throw Error(`num_return_sequences has to be 1 when doing greedy search, but is ${y.num_return_sequences}.`);return new _(y)}}class _ extends p{async sample(y){const E=(0,l.max)(y.data)[1];return[[BigInt(E),0]]}}class h extends p{async sample(y){let E=y.dims.at(-1);this.generation_config.top_k>0&&(E=Math.min(this.generation_config.top_k,E));const[T,O]=await(0,a.topk)(y,E),S=(0,l.softmax)(T.data);return Array.from({length:this.generation_config.num_beams},()=>{const C=this.randomSelect(S);return[O.data[C],Math.log(S[C])]})}}class g extends p{async sample(y){let E=y.dims.at(-1);this.generation_config.top_k>0&&(E=Math.min(this.generation_config.top_k,E));const[T,O]=await(0,a.topk)(y,E),S=(0,l.softmax)(T.data);return Array.from({length:this.generation_config.num_beams},(C,w)=>[O.data[w],Math.log(S[w])])}}},"./src/generation/stopping_criteria.js":(e,t,r)=>{r.r(t),r.d(t,{EosTokenCriteria:()=>_,InterruptableStoppingCriteria:()=>h,MaxLengthCriteria:()=>p,StoppingCriteria:()=>a,StoppingCriteriaList:()=>l});var o=r("./src/utils/generic.js");class a extends o.Callable{_call(M,y){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,y){const E=new Array(M.length).fill(!1);for(const T of this.criteria){const O=T(M,y);for(let S=0;S<E.length;++S)E[S]||(E[S]=O[S])}return E}[Symbol.iterator](){return this.criteria.values()}}class p extends a{constructor(M,y=null){super(),this.max_length=M,this.max_position_embeddings=y}_call(M){return M.map(y=>y.length>=this.max_length)}}class _ extends a{constructor(M){super(),Array.isArray(M)||(M=[M]),this.eos_token_id=M}_call(M,y){return M.map(E=>{const T=E.at(-1);return this.eos_token_id.some(O=>T==O)})}}class h extends a{constructor(){super(),this.interrupted=!1}interrupt(){this.interrupted=!0}reset(){this.interrupted=!1}_call(M,y){return new Array(M.length).fill(this.interrupted)}}},"./src/generation/streamers.js":(e,t,r)=>{r.r(t),r.d(t,{BaseStreamer:()=>p,TextStreamer:()=>h,WhisperTextStreamer:()=>g});var o=r("./src/utils/core.js"),a=r("./src/tokenizers.js"),l=r("./src/env.js");class p{put(y){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 p{constructor(y,{skip_prompt:E=!1,callback_function:T=null,token_callback_function:O=null,decode_kwargs:S={},...C}={}){super(),this.tokenizer=y,this.skip_prompt=E,this.callback_function=T??_,this.token_callback_function=O,this.decode_kwargs={...S,...C},this.token_cache=[],this.print_len=0,this.next_tokens_are_prompt=!0}put(y){var S;if(y.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 E=y[0];(S=this.token_callback_function)==null||S.call(this,E),this.token_cache=(0,o.mergeArrays)(this.token_cache,E);const T=this.tokenizer.decode(this.token_cache,this.decode_kwargs);let O;T.endsWith(`
`)?(O=T.slice(this.print_len),this.token_cache=[],this.print_len=0):T.length>0&&(0,a.is_chinese_char)(T.charCodeAt(T.length-1))?(O=T.slice(this.print_len),this.print_len+=O.length):(O=T.slice(this.print_len,T.lastIndexOf(" ")+1),this.print_len+=O.length),this.on_finalized_text(O,!1)}end(){let y;this.token_cache.length>0?(y=this.tokenizer.decode(this.token_cache,this.decode_kwargs).slice(this.print_len),this.token_cache=[],this.print_len=0):y="",this.next_tokens_are_prompt=!0,this.on_finalized_text(y,!0)}on_finalized_text(y,E){var T,O;y.length>0&&((T=this.callback_function)==null||T.call(this,y)),E&&this.callback_function===_&&l.apis.IS_PROCESS_AVAILABLE&&((O=this.callback_function)==null||O.call(this,`
`))}}class g extends h{constructor(y,{skip_prompt:E=!1,callback_function:T=null,token_callback_function:O=null,on_chunk_start:S=null,on_chunk_end:C=null,on_finalize:w=null,time_precision:b=.02,skip_special_tokens:I=!0,decode_kwargs:U={}}={}){super(y,{skip_prompt:E,callback_function:T,token_callback_function:O,decode_kwargs:{skip_special_tokens:I,...U}}),this.timestamp_begin=y.timestamp_begin,this.on_chunk_start=S,this.on_chunk_end=C,this.on_finalize=w,this.time_precision=b,this.waiting_for_timestamp=!1}put(y){var T,O;if(y.length>1)throw Error("WhisperTextStreamer only supports batch size of 1");const E=y[0];if(E.length===1){const S=Number(E[0])-this.timestamp_begin;if(S>=0){const C=S*this.time_precision;this.waiting_for_timestamp?(T=this.on_chunk_end)==null||T.call(this,C):(O=this.on_chunk_start)==null||O.call(this,C),this.waiting_for_timestamp=!this.waiting_for_timestamp,y=[[]]}}return super.put(y)}end(){var y;super.end(),(y=this.on_finalize)==null||y.call(this)}}},"./src/models.js":(e,t,r)=>{r.r(t),r.d(t,{ASTForAudioClassification:()=>$s,ASTModel:()=>zt,ASTPreTrainedModel:()=>Vn,AlbertForMaskedLM:()=>Zt,AlbertForQuestionAnswering:()=>mo,AlbertForSequenceClassification:()=>ho,AlbertModel:()=>Ji,AlbertPreTrainedModel:()=>Si,AutoModel:()=>Bd,AutoModelForAudioClassification:()=>Yd,AutoModelForAudioFrameClassification:()=>Zd,AutoModelForCTC:()=>Qd,AutoModelForCausalLM:()=>Vd,AutoModelForDepthEstimation:()=>tp,AutoModelForDocumentQuestionAnswering:()=>Tf,AutoModelForImageClassification:()=>Hd,AutoModelForImageFeatureExtraction:()=>rp,AutoModelForImageMatting:()=>Jd,AutoModelForImageSegmentation:()=>Tl,AutoModelForImageToImage:()=>ep,AutoModelForMaskGeneration:()=>kl,AutoModelForMaskedLM:()=>Wd,AutoModelForObjectDetection:()=>Kd,AutoModelForQuestionAnswering:()=>Ml,AutoModelForSemanticSegmentation:()=>qd,AutoModelForSeq2SeqLM:()=>jd,AutoModelForSequenceClassification:()=>Pn,AutoModelForSpeechSeq2Seq:()=>xl,AutoModelForTextToSpectrogram:()=>Ud,AutoModelForTextToWaveform:()=>Zo,AutoModelForTokenClassification:()=>Nd,AutoModelForVision2Seq:()=>Gd,AutoModelForXVector:()=>Sl,AutoModelForZeroShotObjectDetection:()=>Xd,BartForConditionalGeneration:()=>W,BartForSequenceClassification:()=>pe,BartModel:()=>Ue,BartPretrainedModel:()=>jn,BaseModelOutput:()=>Ke,BeitForImageClassification:()=>cc,BeitModel:()=>uc,BeitPreTrainedModel:()=>Oa,BertForMaskedLM:()=>We,BertForQuestionAnswering:()=>Ge,BertForSequenceClassification:()=>st,BertForTokenClassification:()=>pt,BertModel:()=>Be,BertPreTrainedModel:()=>Le,BlenderbotForConditionalGeneration:()=>It,BlenderbotModel:()=>kt,BlenderbotPreTrainedModel:()=>St,BlenderbotSmallForConditionalGeneration:()=>or,BlenderbotSmallModel:()=>Ar,BlenderbotSmallPreTrainedModel:()=>tr,BloomForCausalLM:()=>Gu,BloomModel:()=>Wu,BloomPreTrainedModel:()=>Fs,CLIPModel:()=>pu,CLIPPreTrainedModel:()=>Ho,CLIPSegForImageSegmentation:()=>yu,CLIPSegModel:()=>wu,CLIPSegPreTrainedModel:()=>ya,CLIPTextModelWithProjection:()=>hi,CLIPVisionModelWithProjection:()=>fu,CamembertForMaskedLM:()=>Re,CamembertForQuestionAnswering:()=>tt,CamembertForSequenceClassification:()=>qe,CamembertForTokenClassification:()=>Qe,CamembertModel:()=>ve,CamembertPreTrainedModel:()=>Z,CausalLMOutput:()=>to,CausalLMOutputWithPast:()=>kf,ChineseCLIPModel:()=>_u,ChineseCLIPPreTrainedModel:()=>gu,ClapAudioModelWithProjection:()=>pd,ClapModel:()=>cd,ClapPreTrainedModel:()=>Ko,ClapTextModelWithProjection:()=>dd,CodeGenForCausalLM:()=>As,CodeGenModel:()=>Pu,CodeGenPreTrainedModel:()=>Qn,CohereForCausalLM:()=>Iu,CohereModel:()=>Au,CoherePreTrainedModel:()=>Ta,ConvBertForMaskedLM:()=>R,ConvBertForQuestionAnswering:()=>ue,ConvBertForSequenceClassification:()=>ee,ConvBertForTokenClassification:()=>D,ConvBertModel:()=>ye,ConvBertPreTrainedModel:()=>re,ConvNextForImageClassification:()=>Fc,ConvNextModel:()=>Ic,ConvNextPreTrainedModel:()=>qa,ConvNextV2ForImageClassification:()=>Dc,ConvNextV2Model:()=>zc,ConvNextV2PreTrainedModel:()=>Oc,DPTForDepthEstimation:()=>Wa,DPTModel:()=>Va,DPTPreTrainedModel:()=>Ua,DebertaForMaskedLM:()=>Tt,DebertaForQuestionAnswering:()=>Lt,DebertaForSequenceClassification:()=>bt,DebertaForTokenClassification:()=>Et,DebertaModel:()=>ht,DebertaPreTrainedModel:()=>ft,DebertaV2ForMaskedLM:()=>Ut,DebertaV2ForQuestionAnswering:()=>rr,DebertaV2ForSequenceClassification:()=>Xt,DebertaV2ForTokenClassification:()=>Yt,DebertaV2Model:()=>Ot,DebertaV2PreTrainedModel:()=>at,DeiTForImageClassification:()=>bc,DeiTModel:()=>vc,DeiTPreTrainedModel:()=>La,DepthAnythingForDepthEstimation:()=>Cc,DepthAnythingPreTrainedModel:()=>Ec,DetrForObjectDetection:()=>pc,DetrForSegmentation:()=>fc,DetrModel:()=>dc,DetrObjectDetectionOutput:()=>za,DetrPreTrainedModel:()=>Ds,DetrSegmentationOutput:()=>hc,Dinov2ForImageClassification:()=>Rc,Dinov2Model:()=>Lc,Dinov2PreTrainedModel:()=>Zn,DistilBertForMaskedLM:()=>$t,DistilBertForQuestionAnswering:()=>mt,DistilBertForSequenceClassification:()=>Yr,DistilBertForTokenClassification:()=>$r,DistilBertModel:()=>Pr,DistilBertPreTrainedModel:()=>Ht,DonutSwinModel:()=>Ha,DonutSwinPreTrainedModel:()=>Ac,EfficientNetForImageClassification:()=>_d,EfficientNetModel:()=>gd,EfficientNetPreTrainedModel:()=>fl,ElectraForMaskedLM:()=>Ne,ElectraForQuestionAnswering:()=>Ve,ElectraForSequenceClassification:()=>dt,ElectraForTokenClassification:()=>Je,ElectraModel:()=>ke,ElectraPreTrainedModel:()=>le,EsmForMaskedLM:()=>Bi,EsmForSequenceClassification:()=>Mi,EsmForTokenClassification:()=>Gr,EsmModel:()=>un,EsmPreTrainedModel:()=>Bt,FalconForCausalLM:()=>ud,FalconModel:()=>ld,FalconPreTrainedModel:()=>ul,FastViTForImageClassification:()=>Zu,FastViTModel:()=>Yu,FastViTPreTrainedModel:()=>zs,Florence2ForConditionalGeneration:()=>_a,Florence2PreTrainedModel:()=>du,GLPNForDepthEstimation:()=>$c,GLPNModel:()=>Pc,GLPNPreTrainedModel:()=>Ga,GPT2LMHeadModel:()=>bu,GPT2Model:()=>vu,GPT2PreTrainedModel:()=>va,GPTBigCodeForCausalLM:()=>rf,GPTBigCodeMo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reTrainedModel:()=>sd,UniSpeechForCTC:()=>Xc,UniSpeechForSequenceClassification:()=>Qc,UniSpeechModel:()=>Ja,UniSpeechPreTrainedModel:()=>xo,UniSpeechSatForAudioFrameClassification:()=>Bs,UniSpeechSatForCTC:()=>el,UniSpeechSatForSequenceClassification:()=>Yc,UniSpeechSatModel:()=>Rs,UniSpeechSatPreTrainedModel:()=>qo,ViTForImageClassification:()=>Qu,ViTModel:()=>Xu,ViTPreTrainedModel:()=>vo,VisionEncoderDecoderModel:()=>ga,VitMatteForImageMatting:()=>ec,VitMattePreTrainedModel:()=>Ju,VitsModel:()=>cl,VitsModelOutput:()=>Sf,VitsPreTrainedModel:()=>df,Wav2Vec2BertForCTC:()=>js,Wav2Vec2BertForSequenceClassification:()=>Zc,Wav2Vec2BertModel:()=>tl,Wav2Vec2BertPreTrainedModel:()=>Ns,Wav2Vec2ForAudioFrameClassification:()=>Wi,Wav2Vec2ForCTC:()=>af,Wav2Vec2ForSequenceClassification:()=>Vi,Wav2Vec2Model:()=>Kc,Wav2Vec2PreTrainedModel:()=>Ui,WavLMForAudioFrameClassification:()=>nd,WavLMForCTC:()=>nl,WavLMForSequenceClassification:()=>td,WavLMForXVector:()=>rd,WavLMModel:()=>ed,WavLMPreTrainedModel:()=>Ci,WeSpeakerResNetModel:()=>Za,WeSpeakerResNetPreTrainedModel:()=>vn,WhisperForConditionalGeneration:()=>ma,WhisperModel:()=>Gt,WhisperPreTrainedModel:()=>_t,XLMForQuestionAnswering:()=>yn,XLMForSequenceClassification:()=>Jt,XLMForTokenClassification:()=>Un,XLMModel:()=>cn,XLMPreTrainedModel:()=>Tr,XLMRobertaForMaskedLM:()=>At,XLMRobertaForQuestionAnswering:()=>Xr,XLMRobertaForSequenceClassification:()=>vr,XLMRobertaForTokenClassification:()=>Lr,XLMRobertaModel:()=>Er,XLMRobertaPreTrainedModel:()=>Sr,XLMWithLMHeadModel:()=>On,XVectorOutput:()=>np,YolosForObjectDetection:()=>Nc,YolosModel:()=>Bc,YolosObjectDetectionOutput:()=>jc,YolosPreTrainedModel:()=>Ka});var o=r("./src/configs.js"),a=r("./src/backends/onnx.js"),l=r("./src/utils/dtypes.js"),p=r("./src/utils/generic.js"),_=r("./src/utils/core.js"),h=r("./src/utils/hub.js"),g=r("./src/generation/logits_process.js"),M=r("./src/generation/configuration_utils.js"),y=r("./src/utils/tensor.js"),E=r("./src/utils/maths.js"),T=r("./src/generation/stopping_criteria.js"),O=r("./src/generation/logits_sampler.js"),S=r("./src/env.js"),C=r("./src/models/whisper/generation_whisper.js"),w=r("./src/models/whisper/common_whisper.js");const b={EncoderOnly:0,EncoderDecoder:1,Seq2Seq:2,Vision2Seq:3,DecoderOnly:4,MaskGeneration:5,ImageTextToText:6,Musicgen:7},I=new Map,U=new Map,z=new Map;async function B(V,G,ne){let Ee=ne.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 wt=ne.dtype;typeof wt!="string"&&(wt&&wt.hasOwnProperty(G)?wt=wt[G]:(wt=l.DEFAULT_DEVICE_DTYPE_MAPPING[Ze]??l.DATA_TYPES.fp32,console.warn(`dtype not specified for "${G}". Using the default dtype (${wt}) for this device (${Ze}).`)));const Ct=wt;if(l.DEFAULT_DTYPE_SUFFIX_MAPPING.hasOwnProperty(Ct)){if(Ct===l.DATA_TYPES.fp16&&Ze==="webgpu"&&!await(0,l.isWebGpuFp16Supported)())throw new Error(`The device (${Ze}) does not support fp16.`)}else throw new Error(`Invalid dtype: ${Ct}. Should be one of: ${Object.keys(l.DATA_TYPES).join(", ")}`);const Wt=l.DEFAULT_DTYPE_SUFFIX_MAPPING[Ct],cr=`${ne.subfolder??""}/${G}${Wt}.onnx`,lr={...ne.session_options};lr.executionProviders??(lr.executionProviders=it);const Ir=(0,h.getModelFile)(V,cr,!0,ne);let dr=[];if(ne.use_external_data_format&&(ne.use_external_data_format===!0||typeof ne.use_external_data_format=="object"&&ne.use_external_data_format.hasOwnProperty(G)&&ne.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 pr=`${G}${Wt}.onnx_data`,mr=`${ne.subfolder??""}/${pr}`;dr.push(new Promise(async(xr,Nr)=>{const $n=await(0,h.getModelFile)(V,mr,!0,ne);xr({path:pr,data:$n})}))}else lr.externalData!==void 0&&(dr=lr.externalData.map(async pr=>{if(typeof pr.data=="string"){const mr=await(0,h.getModelFile)(V,pr.data,!0,ne);return{...pr,data:mr}}return pr}));if(dr.length>0&&(lr.externalData=await Promise.all(dr)),Ze==="webgpu"){const pr=(0,o.getKeyValueShapes)(ne.config,{prefix:"present"});if(Object.keys(pr).length>0&&!(0,a.isONNXProxy)()){const mr={};for(const xr in pr)mr[xr]="gpu-buffer";lr.preferredOutputLocation=mr}}return{buffer:await Ir,session_options:lr}}async function j(V,G,ne){return Object.fromEntries(await Promise.all(Object.keys(G).map(async Ee=>{const{buffer:Ze,session_options:it}=await B(V,G[Ee],ne),wt=await(0,a.createInferenceSession)(Ze,it);return[Ee,wt]})))}function N(V,G){const ne=Object.create(null),Ee=[];for(const wt of V.inputNames){const Ct=G[wt];if(!(Ct instanceof y.Tensor)){Ee.push(wt);continue}ne[wt]=(0,a.isONNXProxy)()?Ct.clone():Ct}if(Ee.length>0)throw new Error(`An error occurred during model execution: "Missing the following inputs: ${Ee.join(", ")}.`);const Ze=Object.keys(G).length,it=V.inputNames.length;if(Ze>it){let wt=Object.keys(G).filter(Ct=>!V.inputNames.includes(Ct));console.warn(`WARNING: Too many inputs were provided (${Ze} > ${it}). The following inputs will be ignored: "${wt.join(", ")}".`)}return ne}async function ae(V,G){const ne=N(V,G);try{const Ee=Object.fromEntries(Object.entries(ne).map(([it,wt])=>[it,wt.ort_tensor]));let Ze=await V.run(Ee);return Ze=ce(Ze),Ze}catch(Ee){throw console.error(`An error occurred during model execution: "${Ee}".`),console.error("Inputs given to model:",ne),Ee}}function ce(V){for(let G in V)(0,a.isONNXTensor)(V[G])?V[G]=new y.Tensor(V[G]):typeof V[G]=="object"&&ce(V[G]);return V}function xe(V){if(V instanceof y.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 y.Tensor("int64",BigInt64Array.from(V.flat().map(G=>BigInt(G))),[V.length,V[0].length])}else return new y.Tensor("int64",BigInt64Array.from(V.map(G=>BigInt(G))),[1,V.length])}function Y(V){return new y.Tensor("bool",[V],[1])}async function _e(V,G){let{encoder_outputs:ne,input_ids:Ee,decoder_input_ids:Ze,...it}=G;if(!ne){const Ct=(0,_.pick)(G,V.sessions.model.inputNames);ne=(await L(V,Ct)).last_hidden_state}return it.input_ids=Ze,it.encoder_hidden_states=ne,V.sessions.decoder_model_merged.inputNames.includes("encoder_attention_mask")&&(it.encoder_attention_mask=G.attention_mask),await Se(V,it,!0)}async function L(V,G){const ne=V.sessions.model,Ee=(0,_.pick)(G,ne.inputNames);if(ne.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 ne.inputNames.includes("token_type_ids")&&!Ee.token_type_ids&&(Ee.token_type_ids=new y.Tensor("int64",new BigInt64Array(Ee.input_ids.data.length),Ee.input_ids.dims)),await ae(ne,Ee)}async function Se(V,G,ne=!1){const Ee=V.sessions[ne?"decoder_model_merged":"model"],{past_key_values:Ze,...it}=G;Ee.inputNames.includes("use_cache_branch")&&(it.use_cache_branch=Y(!!Ze)),Ee.inputNames.includes("position_ids")&&it.attention_mask&&!it.position_ids&&(it.position_ids=me(it,Ze)),V.addPastKeyValues(it,Ze);const wt=(0,_.pick)(it,Ee.inputNames);return await ae(Ee,wt)}async function Xe(V,{input_ids:G=null,attention_mask:ne=null,pixel_values:Ee=null,position_ids:Ze=null,inputs_embeds:it=null,past_key_values:wt=null,generation_config:Ct=null,logits_processor:Wt=null,...cr}){if(!it){if(it=await V.encode_text({input_ids:G}),Ee&&G.dims[1]!==1){const Ir=await V.encode_image({pixel_values:Ee});({inputs_embeds:it,attention_mask:ne}=V._merge_input_ids_with_image_features({image_features:Ir,inputs_embeds:it,input_ids:G,attention_mask:ne}))}else if(wt&&Ee&&G.dims[1]===1){const Ir=G.dims[1],dr=Object.values(wt)[0].dims.at(-2);ne=(0,y.cat)([(0,y.ones)([G.dims[0],dr]),ne.slice(null,[ne.dims[1]-Ir,ne.dims[1]])],1)}}return await Se(V,{inputs_embeds:it,past_key_values:wt,attention_mask:ne,position_ids:Ze,generation_config:Ct,logits_processor:Wt},!0)}function me(V,G=null){const{input_ids:ne,inputs_embeds:Ee,attention_mask:Ze}=V,[it,wt]=Ze.dims,Ct=new BigInt64Array(Ze.data.length);for(let cr=0;cr<it;++cr){const lr=cr*wt;let Ir=BigInt(0);for(let dr=0;dr<wt;++dr){const wr=lr+dr;Ze.data[wr]===0n?Ct[wr]=BigInt(1):(Ct[wr]=Ir,Ir+=Ze.data[wr])}}let Wt=new y.Tensor("int64",Ct,Ze.dims);if(G){const cr=-(ne??Ee).dims.at(1);Wt=Wt.slice(null,[cr,null])}return Wt}function X(V,G,ne,Ee){if(ne.past_key_values){const Ze=Object.values(ne.past_key_values)[0].dims.at(-2),{input_ids:it,attention_mask:wt}=ne;if(!(wt&&wt.dims[1]>it.dims[1])){if(Ze<it.dims[1])ne.input_ids=it.slice(null,[Ze,null]);else if(V.config.image_token_index!=null&&it.data.some(Ct=>Ct==V.config.image_token_index)){const Ct=V.config.num_image_tokens;if(!Ct)throw new Error("`num_image_tokens` is missing in the model configuration.");const Wt=it.dims[1]-(Ze-Ct);ne.input_ids=it.slice(null,[-Wt,null]),ne.attention_mask=(0,y.ones)([1,Ze+Wt])}}}return ne}function ie(V,G,ne,Ee){return ne.past_key_values&&(G=G.map(Ze=>[Ze.at(-1)])),{...ne,decoder_input_ids:xe(G)}}function Me(V,...G){return V.config.is_encoder_decoder?ie(V,...G):X(V,...G)}class Q extends p.Callable{constructor(ne,Ee){super();He(this,"main_input_name","input_ids");He(this,"forward_params",["input_ids","attention_mask"]);this.config=ne,this.sessions=Ee;const Ze=z.get(this.constructor),it=I.get(Ze);switch(this.can_generate=!1,this._forward=null,this._prepare_inputs_for_generation=null,it){case b.DecoderOnly:this.can_generate=!0,this._forward=Se,this._prepare_inputs_for_generation=X;break;case b.Seq2Seq:case b.Vision2Seq:case b.Musicgen:this.can_generate=!0,this._forward=_e,this._prepare_inputs_for_generation=ie;break;case b.EncoderDecoder:this._forward=_e;break;case b.ImageTextToText:this.can_generate=!0,this._forward=Xe,this._prepare_inputs_for_generation=Me;break;default:this._forward=L;break}this.can_generate&&this.forward_params.push("past_key_values"),this.custom_config=this.config["transformers.js_config"]??{}}async dispose(){var Ee;const ne=[];for(const Ze of Object.values(this.sessions))(Ee=Ze==null?void 0:Ze.handler)!=null&&Ee.dispose&&ne.push(Ze.handler.dispose());return await Promise.all(ne)}static async from_pretrained(ne,{progress_callback:Ee=null,config:Ze=null,cache_dir:it=null,local_files_only:wt=!1,revision:Ct="main",model_file_name:Wt=null,subfolder:cr="onnx",device:lr=null,dtype:Ir=null,use_external_data_format:dr=null,session_options:wr={}}={}){let pr={progress_callback:Ee,config:Ze,cache_dir:it,local_files_only:wt,revision:Ct,model_file_name:Wt,subfolder:cr,device:lr,dtype:Ir,use_external_data_format:dr,session_options:wr};const mr=z.get(this),xr=I.get(mr);Ze=pr.config=await o.AutoConfig.from_pretrained(ne,pr);let Nr;if(xr===b.DecoderOnly)Nr=await Promise.all([j(ne,{model:pr.model_file_name??"model"},pr),(0,h.getModelJSON)(ne,"generation_config.json",!1,pr)]);else if(xr===b.Seq2Seq||xr===b.Vision2Seq)Nr=await Promise.all([j(ne,{model:"encoder_model",decoder_model_merged:"decoder_model_merged"},pr),(0,h.getModelJSON)(ne,"generation_config.json",!1,pr)]);else if(xr===b.MaskGeneration)Nr=await Promise.all([j(ne,{model:"vision_encoder",prompt_encoder_mask_decoder:"prompt_encoder_mask_decoder"},pr)]);else if(xr===b.EncoderDecoder)Nr=await Promise.all([j(ne,{model:"encoder_model",decoder_model_merged:"decoder_model_merged"},pr)]);else if(xr===b.ImageTextToText){const $n={embed_tokens:"embed_tokens",vision_encoder:"vision_encoder",decoder_model_merged:"decoder_model_merged"};Ze.is_encoder_decoder&&($n.model="encoder_model"),Nr=await Promise.all([j(ne,$n,pr),(0,h.getModelJSON)(ne,"generation_config.json",!1,pr)])}else xr===b.Musicgen?Nr=await Promise.all([j(ne,{model:"text_encoder",decoder_model_merged:"decoder_model_merged",encodec_decode:"encodec_decode"},pr),(0,h.getModelJSON)(ne,"generation_config.json",!1,pr)]):(xr!==b.EncoderOnly&&console.warn(`Model type for '${mr??(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.`),Nr=await Promise.all([j(ne,{model:pr.model_file_name??"model"},pr)]));return new this(Ze,...Nr)}async _call(ne){return await this.forward(ne)}async forward(ne){return await this._forward(this,ne)}_get_logits_warper(ne){const Ee=new g.LogitsProcessorList;return ne.temperature!==null&&ne.temperature!==1&&Ee.push(new g.TemperatureLogitsWarper(ne.temperature)),ne.top_k!==null&&ne.top_k!==0&&Ee.push(new g.TopKLogitsWarper(ne.top_k)),ne.top_p!==null&&ne.top_p<1&&Ee.push(new g.TopPLogitsWarper(ne.top_p)),Ee}_get_logits_processor(ne,Ee,Ze=null){const it=new g.LogitsProcessorList;if(ne.repetition_penalty!==null&&ne.repetition_penalty!==1&&it.push(new g.RepetitionPenaltyLogitsProcessor(ne.repetition_penalty)),ne.no_repeat_ngram_size!==null&&ne.no_repeat_ngram_size>0&&it.push(new g.NoRepeatNGramLogitsProcessor(ne.no_repeat_ngram_size)),ne.bad_words_ids!==null&&it.push(new g.NoBadWordsLogitsProcessor(ne.bad_words_ids,ne.eos_token_id)),ne.min_length!==null&&ne.eos_token_id!==null&&ne.min_length>0&&it.push(new g.MinLengthLogitsProcessor(ne.min_length,ne.eos_token_id)),ne.min_new_tokens!==null&&ne.eos_token_id!==null&&ne.min_new_tokens>0&&it.push(new g.MinNewTokensLengthLogitsProcessor(Ee,ne.min_new_tokens,ne.eos_token_id)),ne.forced_bos_token_id!==null&&it.push(new g.ForcedBOSTokenLogitsProcessor(ne.forced_bos_token_id)),ne.forced_eos_token_id!==null&&it.push(new g.ForcedEOSTokenLogitsProcessor(ne.max_length,ne.forced_eos_token_id)),ne.begin_suppress_tokens!==null){const wt=Ee>1||ne.forced_bos_token_id===null?Ee:Ee+1;it.push(new g.SuppressTokensAtBeginLogitsProcessor(ne.begin_suppress_tokens,wt))}return ne.guidance_scale!==null&&ne.guidance_scale>1&&it.push(new g.ClassifierFreeGuidanceLogitsProcessor(ne.guidance_scale)),Ze!==null&&it.extend(Ze),it}_prepare_generation_config(ne,Ee,Ze=M.GenerationConfig){const it={...this.config};for(const Ct of["decoder","generator","text_config"])Ct in it&&Object.assign(it,it[Ct]);const wt=new Ze(it);return"generation_config"in this&&Object.assign(wt,this.generation_config),ne&&Object.assign(wt,ne),Ee&&Object.assign(wt,(0,_.pick)(Ee,Object.getOwnPropertyNames(wt))),wt}_get_stopping_criteria(ne,Ee=null){const Ze=new T.StoppingCriteriaList;return ne.max_length!==null&&Ze.push(new T.MaxLengthCriteria(ne.max_length,this.config.max_position_embeddings??null)),ne.eos_token_id!==null&&Ze.push(new T.EosTokenCriteria(ne.eos_token_id)),Ee&&Ze.extend(Ee),Ze}_validate_model_class(){if(!this.can_generate){const ne=[Hs,bl,vl,Gs],Ee=z.get(this.constructor),Ze=new Set,it=this.config.model_type;for(const Ct of ne){const Wt=Ct.get(it);Wt&&Ze.add(Wt[0])}let wt=`The current model class (${Ee}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;throw Ze.size>0&&(wt+=` Please use the following class instead: ${[...Ze].join(", ")}`),Error(wt)}}prepare_inputs_for_generation(...ne){return this._prepare_inputs_for_generation(this,...ne)}_update_model_kwargs_for_generation({generated_input_ids:ne,outputs:Ee,model_inputs:Ze,is_encoder_decoder:it}){return Ze.past_key_values=this.getPastKeyValues(Ee,Ze.past_key_values),Ze.input_ids=new y.Tensor("int64",ne.flat(),[ne.length,1]),it||(Ze.attention_mask=(0,y.cat)([Ze.attention_mask,(0,y.ones)([Ze.attention_mask.dims[0],1])],1)),Ze.position_ids=null,Ze}_prepare_model_inputs({inputs:ne,bos_token_id:Ee,model_kwargs:Ze}){const it=(0,_.pick)(Ze,this.forward_params),wt=this.main_input_name;if(wt in it){if(ne)throw new Error("`inputs`: {inputs}` were passed alongside {input_name} which is not allowed. Make sure to either pass {inputs} or {input_name}=...")}else it[wt]=ne;return{inputs_tensor:it[wt],model_inputs:it,model_input_name:wt}}async _prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:ne,model_inputs:Ee,model_input_name:Ze,generation_config:it}){if(this.sessions.model.inputNames.includes("inputs_embeds")&&!Ee.inputs_embeds&&"_prepare_inputs_embeds"in this){const{input_ids:Ct,pixel_values:Wt,attention_mask:cr,...lr}=Ee,Ir=await this._prepare_inputs_embeds(Ee);Ee={...lr,...(0,_.pick)(Ir,["inputs_embeds","attention_mask"])}}let{last_hidden_state:wt}=await L(this,Ee);if(it.guidance_scale!==null&&it.guidance_scale>1)wt=(0,y.cat)([wt,(0,y.full_like)(wt,0)],0),"attention_mask"in Ee&&(Ee.attention_mask=(0,y.cat)([Ee.attention_mask,(0,y.zeros_like)(Ee.attention_mask)],0));else if(Ee.decoder_input_ids){const Ct=xe(Ee.decoder_input_ids).dims[0];if(Ct!==wt.dims[0]){if(wt.dims[0]!==1)throw new Error(`The encoder outputs have a different batch size (${wt.dims[0]}) than the decoder inputs (${Ct}).`);wt=(0,y.cat)(Array.from({length:Ct},()=>wt),0)}}return Ee.encoder_outputs=wt,Ee}_prepare_decoder_input_ids_for_generation({batch_size:ne,model_input_name:Ee,model_kwargs:Ze,decoder_start_token_id:it,bos_token_id:wt,generation_config:Ct}){let{decoder_input_ids:Wt,...cr}=Ze;if(Wt)Array.isArray(Wt[0])||(Wt=Array.from({length:ne},()=>Wt));else if(it??(it=wt),this.config.model_type==="musicgen")Wt=Array.from({length:ne*this.config.decoder.num_codebooks},()=>[it]);else if(Array.isArray(it)){if(it.length!==ne)throw new Error(`\`decoder_start_token_id\` expcted to have length ${ne} but got ${it.length}`);Wt=it}else Wt=Array.from({length:ne},()=>[it]);return Wt=xe(Wt),Ze.decoder_attention_mask=(0,y.ones_like)(Wt),{input_ids:Wt,model_inputs:cr}}async generate({inputs:ne=null,generation_config:Ee=null,logits_processor:Ze=null,stopping_criteria:it=null,streamer:wt=null,...Ct}){this._validate_model_class(),Ee=this._prepare_generation_config(Ee,Ct);let{inputs_tensor:Wt,model_inputs:cr,model_input_name:lr}=this._prepare_model_inputs({inputs:ne,model_kwargs:Ct});const Ir=this.config.is_encoder_decoder;Ir&&("encoder_outputs"in cr||(cr=await this._prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:Wt,model_inputs:cr,model_input_name:lr,generation_config:Ee})));let dr;Ir?{input_ids:dr,model_inputs:cr}=this._prepare_decoder_input_ids_for_generation({batch_size:cr[lr].dims.at(0),model_input_name:lr,model_kwargs:cr,decoder_start_token_id:Ee.decoder_start_token_id,bos_token_id:Ee.bos_token_id,generation_config:Ee}):dr=cr[lr];let wr=dr.dims.at(-1);Ee.max_new_tokens!==null&&(Ee.max_length=wr+Ee.max_new_tokens);const pr=this._get_logits_processor(Ee,wr,Ze),mr=this._get_stopping_criteria(Ee,it),xr=cr[lr].dims.at(0),Nr=O.LogitsSampler.getSampler(Ee),$n=new Array(xr).fill(0),zn=dr.tolist();wt&&wt.put(zn);let Pi=null,Mn={};for(;;){cr=this.prepare_inputs_for_generation(zn,cr,Ee);const Tn=await this.forward(cr);if(Ee.output_attentions&&Ee.return_dict_in_generate){const mi=this.getAttentions(Tn);for(const Jo in mi)Jo in Mn||(Mn[Jo]=[]),Mn[Jo].push(mi[Jo])}const qs=Tn.logits.slice(null,-1,null),Ks=pr(zn,qs),El=[];for(let mi=0;mi<Ks.dims.at(0);++mi){const Jo=Ks[mi],Ef=await Nr(Jo);for(const[Cf,Pf]of Ef){const $f=BigInt(Cf);$n[mi]+=Pf,zn[mi].push($f),El.push([$f]);break}}if(wt&&wt.put(El),mr(zn).every(mi=>mi)){Ee.return_dict_in_generate&&(Pi=this.getPastKeyValues(Tn,cr.past_key_values,!1));break}cr=this._update_model_kwargs_for_generation({generated_input_ids:El,outputs:Tn,model_inputs:cr,is_encoder_decoder:Ir})}wt&&wt.end();const dn=new y.Tensor("int64",zn.flat(),[zn.length,zn[0].length]);return Ee.return_dict_in_generate?{sequences:dn,past_key_values:Pi,...Mn}:dn}getPastKeyValues(ne,Ee,Ze=!0){const it=Object.create(null);for(const wt in ne)if(wt.startsWith("present")){const Ct=wt.replace("present","past_key_values");if(Ee&&wt.includes("encoder"))it[Ct]=Ee[Ct];else{if(Ze&&Ee){const Wt=Ee[Ct];Wt.location==="gpu-buffer"&&Wt.dispose()}it[Ct]=ne[wt]}}return it}getAttentions(ne){const Ee={};for(const Ze of["cross_attentions","encoder_attentions","decoder_attentions"])for(const it in ne)it.startsWith(Ze)&&(Ze in Ee||(Ee[Ze]=[]),Ee[Ze].push(ne[it]));return Ee}addPastKeyValues(ne,Ee){if(Ee)Object.assign(ne,Ee);else{const Ze=this.custom_config.kv_cache_dtype??"float32",it=Ze==="float16"?new Uint16Array:[],wt=(0,o.getKeyValueShapes)(this.config);for(const Ct in wt)ne[Ct]=new y.Tensor(Ze,it,wt[Ct])}}async encode_image({pixel_values:ne}){const Ee=(await ae(this.sessions.vision_encoder,{pixel_values:ne})).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:ne}){return(await ae(this.sessions.embed_tokens,{input_ids:ne})).inputs_embeds}}class ge{}class Ke extends ge{constructor({last_hidden_state:G,hidden_states:ne=null,attentions:Ee=null}){super(),this.last_hidden_state=G,this.hidden_states=ne,this.attentions=Ee}}class Le extends Q{}class Be extends Le{}class We extends Le{async _call(G){return new bn(await super._call(G))}}class st extends Le{async _call(G){return new ur(await super._call(G))}}class pt extends Le{async _call(G){return new hn(await super._call(G))}}class Ge extends Le{async _call(G){return new xn(await super._call(G))}}class Te extends Q{}class je extends Te{}class Ye extends Q{}class et extends Ye{}class A extends Ye{async _call(G){return new bn(await super._call(G))}}class $e extends Ye{async _call(G){return new ur(await super._call(G))}}class Pe extends Ye{async _call(G){return new hn(await super._call(G))}}class se extends Ye{async _call(G){return new xn(await super._call(G))}}class re extends Q{}class ye extends re{}class R extends re{async _call(G){return new bn(await super._call(G))}}class ee extends re{async _call(G){return new ur(await super._call(G))}}class D extends re{async _call(G){return new hn(await super._call(G))}}class ue extends re{async _call(G){return new xn(await super._call(G))}}class le extends Q{}class ke extends le{}class Ne extends le{async _call(G){return new bn(await super._call(G))}}class dt extends le{async _call(G){return new ur(await super._call(G))}}class Je extends le{async _call(G){return new hn(await super._call(G))}}class Ve extends le{async _call(G){return new xn(await super._call(G))}}class Z extends Q{}class ve extends Z{}class Re extends Z{async _call(G){return new bn(await super._call(G))}}class qe extends Z{async _call(G){return new ur(await super._call(G))}}class Qe extends Z{async _call(G){return new hn(await super._call(G))}}class tt extends Z{async _call(G){return new xn(await super._call(G))}}class ft extends Q{}class ht extends ft{}class Tt extends ft{async _call(G){return new bn(await super._call(G))}}class bt extends ft{async _call(G){return new ur(await super._call(G))}}class Et extends ft{async _call(G){return new hn(await super._call(G))}}class Lt extends ft{async _call(G){return new xn(await super._call(G))}}class at extends Q{}class Ot extends at{}class Ut extends at{async _call(G){return new bn(await super._call(G))}}class Xt extends at{async _call(G){return new ur(await super._call(G))}}class Yt extends at{async _call(G){return new hn(await super._call(G))}}class rr extends at{async _call(G){return new xn(await super._call(G))}}class Ht extends Q{}class Pr extends Ht{}class Yr extends Ht{async _call(G){return new ur(await super._call(G))}}class $r extends Ht{async _call(G){return new hn(await super._call(G))}}class mt extends Ht{async _call(G){return new xn(await super._call(G))}}class $t extends Ht{async _call(G){return new bn(await super._call(G))}}class Bt extends Q{}class un extends Bt{}class Bi extends Bt{async _call(G){return new bn(await super._call(G))}}class Mi extends Bt{async _call(G){return new ur(await super._call(G))}}class Gr extends Bt{async _call(G){return new hn(await super._call(G))}}class wn extends Q{}class Kr extends wn{}class pi extends wn{async _call(G){return new bn(await super._call(G))}}class Dr extends wn{async _call(G){return new ur(await super._call(G))}}class Ni extends wn{async _call(G){return new xn(await super._call(G))}}class Ti extends Q{}class Cs extends Ti{}class Lo extends Ti{async _call(G){return new bn(await super._call(G))}}class Ro extends Ti{async _call(G){return new ur(await super._call(G))}}class Bo extends Ti{async _call(G){return new hn(await super._call(G))}}class No extends Ti{async _call(G){return new xn(await super._call(G))}}class ji extends Q{}class Ps extends ji{}class fo extends ji{async _call(G){return new bn(await super._call(G))}}class fi extends ji{async _call(G){return new ur(await super._call(G))}}class ki extends ji{async _call(G){return new xn(await super._call(G))}}class Si extends Q{}class Ji extends Si{}class ho extends Si{async _call(G){return new ur(await super._call(G))}}class mo extends Si{async _call(G){return new xn(await super._call(G))}}class Zt extends Si{async _call(G){return new bn(await super._call(G))}}class eo extends Q{constructor(ne,Ee,Ze){super(ne,Ee);He(this,"forward_params",["input_ids","attention_mask","encoder_outputs","decoder_input_ids","decoder_attention_mask","past_key_values"]);this.generation_config=Ze}}class jo extends eo{}class Uo extends eo{}class go extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Vo extends go{}class Wo extends go{}class _o extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Go extends _o{}class Vr extends _o{}class jn extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Ue extends jn{}class W extends jn{}class pe extends jn{async _call(G){return new ur(await super._call(G))}}class Ce extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Fe extends Ce{}class Oe extends Ce{}class rt extends Ce{async _call(G){return new ur(await super._call(G))}}class Mt extends Ce{}class St extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class kt extends St{}class It extends St{}class tr extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Ar extends tr{}class or extends tr{}class qt extends Q{}class _r extends qt{}class Cn extends qt{async _call(G){return new bn(await super._call(G))}}class gn extends qt{async _call(G){return new ur(await super._call(G))}}class ct extends qt{async _call(G){return new hn(await super._call(G))}}class Kn extends qt{async _call(G){return new xn(await super._call(G))}}class Tr extends Q{}class cn extends Tr{}class On extends Tr{async _call(G){return new bn(await super._call(G))}}class Jt extends Tr{async _call(G){return new ur(await super._call(G))}}class Un extends Tr{async _call(G){return new hn(await super._call(G))}}class yn extends Tr{async _call(G){return new xn(await super._call(G))}}class Sr extends Q{}class Er extends Sr{}class At extends Sr{async _call(G){return new bn(await super._call(G))}}class vr extends Sr{async _call(G){return new ur(await super._call(G))}}class Lr extends Sr{async _call(G){return new hn(await super._call(G))}}class Xr extends Sr{async _call(G){return new xn(await super._call(G))}}class Vn extends Q{}class zt extends Vn{}class $s extends Vn{}class _t extends Q{constructor(ne,Ee,Ze){super(ne,Ee);He(this,"requires_attention_mask",!1);He(this,"main_input_name","input_features");He(this,"forward_params",["input_features","attention_mask","decoder_input_ids","decoder_attention_mask","past_key_values"]);this.generation_config=Ze}}class Gt extends _t{}class ma extends _t{_prepare_generation_config(G,ne){return super._prepare_generation_config(G,ne,C.WhisperGenerationConfig)}_retrieve_init_tokens(G){const ne=[G.decoder_start_token_id];let Ee=G.language;const Ze=G.task;if(G.is_multilingual){Ee||(console.warn("No language specified - defaulting to English (en)."),Ee="en");const wt=`<|${(0,w.whisper_language_to_code)(Ee)}|>`;ne.push(G.lang_to_id[wt]),ne.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&&ne.at(-1)!==G.no_timestamps_token_id?ne.push(G.no_timestamps_token_id):G.return_timestamps&&ne.at(-1)===G.no_timestamps_token_id&&(console.warn("<|notimestamps|> prompt token is removed from generation_config since `return_timestamps` is set to `true`."),ne.pop()),ne.filter(it=>it!=null)}async generate({inputs:G=null,generation_config:ne=null,logits_processor:Ee=null,stopping_criteria:Ze=null,...it}){ne=this._prepare_generation_config(ne,it);const wt=it.decoder_input_ids??this._retrieve_init_tokens(ne);if(ne.return_timestamps&&(Ee??(Ee=new g.LogitsProcessorList),Ee.push(new g.WhisperTimeStampLogitsProcessor(ne,wt))),ne.begin_suppress_tokens&&(Ee??(Ee=new g.LogitsProcessorList),Ee.push(new g.SuppressTokensAtBeginLogitsProcessor(ne.begin_suppress_tokens,wt.length))),ne.return_token_timestamps){if(!ne.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.");ne.task==="translate"&&console.warn("Token-level timestamps may not be reliable for task 'translate'."),ne.output_attentions=!0,ne.return_dict_in_generate=!0}const Ct=await super.generate({inputs:G,generation_config:ne,logits_processor:Ee,decoder_input_ids:wt,...it});return ne.return_token_timestamps&&(Ct.token_timestamps=this._extract_token_timestamps(Ct,ne.alignment_heads,ne.num_frames)),Ct}_extract_token_timestamps(G,ne,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 wt=G.cross_attentions,Ct=Array.from({length:this.config.decoder_layers},(mr,xr)=>(0,y.cat)(wt.map(Nr=>Nr[xr]),2)),Wt=(0,y.stack)(ne.map(([mr,xr])=>{if(mr>=Ct.length)throw new Error(`Layer index ${mr} is out of bounds for cross attentions (length ${Ct.length}).`);return Ee?Ct[mr].slice(null,xr,null,[0,Ee]):Ct[mr].slice(null,xr)})).transpose(1,0,2,3),[cr,lr]=(0,y.std_mean)(Wt,-2,0,!0),Ir=Wt.clone();for(let mr=0;mr<Ir.dims[0];++mr){const xr=Ir[mr];for(let Nr=0;Nr<xr.dims[0];++Nr){const $n=xr[Nr],zn=cr[mr][Nr][0].data,Pi=lr[mr][Nr][0].data;for(let Mn=0;Mn<$n.dims[0];++Mn){let dn=$n[Mn].data;for(let Tn=0;Tn<dn.length;++Tn)dn[Tn]=(dn[Tn]-Pi[Tn])/zn[Tn];dn.set((0,E.medianFilter)(dn,it))}}}const dr=[(0,y.mean)(Ir,1)],wr=G.sequences.dims,pr=new y.Tensor("float32",new Float32Array(wr[0]*wr[1]),wr);for(let mr=0;mr<wr[0];++mr){const xr=dr[mr].neg().squeeze_(0),[Nr,$n]=(0,E.dynamic_time_warping)(xr.tolist()),zn=Array.from({length:Nr.length-1},(dn,Tn)=>Nr[Tn+1]-Nr[Tn]),Pi=(0,_.mergeArrays)([1],zn).map(dn=>!!dn),Mn=[];for(let dn=0;dn<Pi.length;++dn)Pi[dn]&&Mn.push($n[dn]*Ze);pr[mr].data.set(Mn,1)}return pr}}class ga extends Q{constructor(ne,Ee,Ze){super(ne,Ee);He(this,"main_input_name","pixel_values");He(this,"forward_params",["pixel_values","input_ids","encoder_hidden_states","past_key_values"]);this.generation_config=Ze}}class cu extends Q{constructor(ne,Ee,Ze){super(ne,Ee);He(this,"forward_params",["input_ids","pixel_values","attention_mask","position_ids","past_key_values"]);this.generation_config=Ze}}class wo extends cu{_merge_input_ids_with_image_features({inputs_embeds:G,image_features:ne,input_ids:Ee,attention_mask:Ze}){const it=this.config.image_token_index,Ct=Ee.tolist().map(dr=>dr.findIndex(wr=>wr==it)),Wt=Ct.every(dr=>dr===-1),cr=Ct.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 lr=[],Ir=[];for(let dr=0;dr<Ct.length;++dr){const wr=Ct[dr],pr=G[dr],mr=ne[dr],xr=Ze[dr];lr.push((0,y.cat)([pr.slice([0,wr]),mr,pr.slice([wr+1,pr.dims[0]])],0)),Ir.push((0,y.cat)([xr.slice([0,wr]),(0,y.ones)([mr.dims[0]]),xr.slice([wr+1,xr.dims[0]])],0))}return{inputs_embeds:(0,y.stack)(lr,0),attention_mask:(0,y.stack)(Ir,0)}}}class ar extends wo{}class du extends Q{constructor(ne,Ee,Ze){super(ne,Ee);He(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"]);He(this,"main_input_name","inputs_embeds");this.generation_config=Ze}}class _a extends du{_merge_input_ids_with_image_features({inputs_embeds:G,image_features:ne,input_ids:Ee,attention_mask:Ze}){return{inputs_embeds:(0,y.cat)([ne,G],1),attention_mask:(0,y.cat)([(0,y.ones)(ne.dims.slice(0,2)),Ze],1)}}async _prepare_inputs_embeds({input_ids:G,pixel_values:ne,inputs_embeds:Ee,attention_mask:Ze}){if(!G&&!ne)throw new Error("Either `input_ids` or `pixel_values` should be provided.");let it,wt;return G&&(it=await this.encode_text({input_ids:G})),ne&&(wt=await this.encode_image({pixel_values:ne})),it&&wt?{inputs_embeds:Ee,attention_mask:Ze}=this._merge_input_ids_with_image_features({inputs_embeds:it,image_features:wt,input_ids:G,attention_mask:Ze}):Ee=it||wt,{inputs_embeds:Ee,attention_mask:Ze}}async forward({input_ids:G,pixel_values:ne,attention_mask:Ee,decoder_input_ids:Ze,decoder_attention_mask:it,encoder_outputs:wt,past_key_values:Ct,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:ne,inputs_embeds:Wt,attention_mask:Ee})),!wt){let{last_hidden_state:dr}=await L(this,{inputs_embeds:Wt,attention_mask:Ee});wt=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 Se(this,{inputs_embeds:cr,attention_mask:it,encoder_attention_mask:Ee,encoder_hidden_states:wt,past_key_values:Ct},!0)}}class Ho extends Q{}class pu extends Ho{}class hi extends Ho{static async from_pretrained(G,ne={}){return ne.model_file_name??(ne.model_file_name="text_model"),super.from_pretrained(G,ne)}}class fu extends Ho{static async from_pretrained(G,ne={}){return ne.model_file_name??(ne.model_file_name="vision_model"),super.from_pretrained(G,ne)}}class wa extends Q{}class yo extends wa{}class hu extends wa{static async from_pretrained(G,ne={}){return ne.model_file_name??(ne.model_file_name="text_model"),super.from_pretrained(G,ne)}}class mu extends Ho{static async from_pretrained(G,ne={}){return ne.model_file_name??(ne.model_file_name="vision_model"),super.from_pretrained(G,ne)}}class gu extends Q{}class _u extends gu{}class ya extends Q{}class wu extends ya{}class yu extends ya{}class va extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class vu extends va{}class bu extends va{}class Xn extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class xu extends Xn{}class Mu extends Xn{}class ba extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Tu extends ba{}class ku extends ba{}class xa extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Su extends xa{}class Eu extends xa{}class Ma extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Cu extends Ma{}class rf extends Ma{}class Qn extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Pu extends Qn{}class As extends Qn{}class Is extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class ii extends Is{}class $u extends Is{}class Ta extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Au extends Ta{}class Iu extends Ta{}class ka extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Fu extends ka{}class Ou extends ka{}class Sa extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class zu extends Sa{}class Du extends Sa{}class Yn extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Lu extends Yn{}class Ru extends Yn{}class Ea extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Bu extends Ea{}class Nu extends Ea{}class Ca extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class ju extends Ca{}class Uu extends Ca{}class Pa extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Vu extends Pa{}class $a extends Pa{}class Fs extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Wu extends Fs{}class Gu extends Fs{}class Os extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class nf extends Os{}class Hu extends Os{}class Aa extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class qu extends Aa{}class Ku extends Aa{}class vo extends Q{}class Xu extends vo{}class Qu extends vo{async _call(G){return new ur(await super._call(G))}}class zs extends Q{}class Yu extends zs{}class Zu extends zs{async _call(G){return new ur(await super._call(G))}}class Ju extends Q{}class ec extends Ju{async _call(G){return new ip(await super._call(G))}}class tc extends Q{}class rc extends tc{}class nc extends tc{async _call(G){return new ur(await super._call(G))}}class Ia extends Q{}class of extends Ia{}class ic extends Ia{async _call(G){return new ur(await super._call(G))}}class br extends Q{}class oc extends br{}class sc extends br{}class Fa extends Q{}class ac extends Fa{}class lc extends Fa{}class Oa extends Q{}class uc extends Oa{}class cc extends Oa{async _call(G){return new ur(await super._call(G))}}class Ds extends Q{}class dc extends Ds{}class pc extends Ds{async _call(G){return new za(await super._call(G))}}class fc extends Ds{async _call(G){return new hc(await super._call(G))}}class za extends ge{constructor({logits:G,pred_boxes:ne}){super(),this.logits=G,this.pred_boxes=ne}}class hc extends ge{constructor({logits:G,pred_boxes:ne,pred_masks:Ee}){super(),this.logits=G,this.pred_boxes=ne,this.pred_masks=Ee}}class bo extends Q{}class mc extends bo{}class Ls extends bo{async _call(G){return new gc(await super._call(G))}}class gc extends ge{constructor({logits:G,pred_boxes:ne}){super(),this.logits=G,this.pred_boxes=ne}}class Da extends Q{}class _c extends Da{}class wc extends Da{async _call(G){return new yc(await super._call(G))}}class yc extends za{}class La extends Q{}class vc extends La{}class bc extends La{async _call(G){return new ur(await super._call(G))}}class Ra extends Q{}class xc extends Ra{}class Mc extends Ra{async _call(G){return new ur(await super._call(G))}}class Ba extends Q{}class Tc extends Ba{}class kc extends Ba{async _call(G){return new ur(await super._call(G))}}class Na extends Q{}class Sc extends Na{}class ja extends Na{}class Ua extends Q{}class Va extends Ua{}class Wa extends Ua{}class Ec extends Q{}class Cc extends Ec{}class Ga extends Q{}class Pc extends Ga{}class $c extends Ga{}class Ac extends Q{}class Ha extends Ac{}class qa extends Q{}class Ic extends qa{}class Fc extends qa{async _call(G){return new ur(await super._call(G))}}class Oc extends Q{}class zc extends Oc{}class Dc extends Oc{async _call(G){return new ur(await super._call(G))}}class Zn extends Q{}class Lc extends Zn{}class Rc extends Zn{async _call(G){return new ur(await super._call(G))}}class Ka extends Q{}class Bc extends Ka{}class Nc extends Ka{async _call(G){return new jc(await super._call(G))}}class jc extends ge{constructor({logits:G,pred_boxes:ne}){super(),this.logits=G,this.pred_boxes=ne}}class Uc extends Q{}class Vc extends Uc{async get_image_embeddings({pixel_values:G}){return await L(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,wt)=>it*wt,1);G.input_labels=new y.Tensor("int64",new BigInt64Array(Ze).fill(1n),Ee)}const ne={image_embeddings:G.image_embeddings,image_positional_embeddings:G.image_positional_embeddings};return G.input_points&&(ne.input_points=G.input_points),G.input_labels&&(ne.input_labels=G.input_labels),G.input_boxes&&(ne.input_boxes=G.input_boxes),await ae(this.sessions.prompt_encoder_mask_decoder,ne)}async _call(G){return new Wc(await super._call(G))}}class Wc extends ge{constructor({iou_scores:G,pred_masks:ne}){super(),this.iou_scores=G,this.pred_masks=ne}}class Xa extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class sf extends Xa{}class Gc extends Xa{}class Qa extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Hc extends Qa{}class qc extends Qa{}class Ui extends Q{}class Kc extends Ui{}class af extends Ui{async _call(G){return new to(await super._call(G))}}class Vi extends Ui{async _call(G){return new ur(await super._call(G))}}class Wi extends Ui{async _call(G){return new hn(await super._call(G))}}class Ei extends Q{}class Ya extends Ei{}class Gi extends Ei{async _call(G){return new hn(await super._call(G))}}class vn extends Q{}class Za extends vn{}class xo extends Q{}class Ja extends xo{}class Xc extends xo{async _call(G){return new to(await super._call(G))}}class Qc extends xo{async _call(G){return new ur(await super._call(G))}}class qo extends Q{}class Rs extends qo{}class el extends qo{async _call(G){return new to(await super._call(G))}}class Yc extends qo{async _call(G){return new ur(await super._call(G))}}class Bs extends qo{async _call(G){return new hn(await super._call(G))}}class Ns extends Q{}class tl extends Ns{}class js extends Ns{async _call(G){return new to(await super._call(G))}}class Zc extends Ns{async _call(G){return new ur(await super._call(G))}}class lf extends Q{}class uf extends Ui{}class Jc extends Ui{async _call(G){return new to(await super._call(G))}}class rl extends Ui{async _call(G){return new ur(await super._call(G))}}class Ci extends Q{}class ed extends Ci{}class nl extends Ci{async _call(G){return new to(await super._call(G))}}class td extends Ci{async _call(G){return new ur(await super._call(G))}}class rd extends Ci{async _call(G){return new np(await super._call(G))}}class nd extends Ci{async _call(G){return new hn(await super._call(G))}}class il extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class id extends il{}class od extends il{}class cf extends il{async generate_speech(G,ne,{threshold:Ee=.5,minlenratio:Ze=0,maxlenratio:it=20,vocoder:wt=null}={}){const Ct={input_ids:G},{encoder_outputs:Wt,encoder_attention_mask:cr}=await L(this,Ct),lr=Wt.dims[1]/this.config.reduction_factor,Ir=Math.floor(lr*it),dr=Math.floor(lr*Ze),wr=this.config.num_mel_bins;let pr=[],mr=null,xr=null,Nr=0;for(;;){++Nr;const Pi=Y(!!xr);let Mn;xr?Mn=xr.output_sequence_out:Mn=new y.Tensor("float32",new Float32Array(wr),[1,1,wr]);let dn={use_cache_branch:Pi,output_sequence:Mn,encoder_attention_mask:cr,speaker_embeddings:ne,encoder_hidden_states:Wt};this.addPastKeyValues(dn,mr),xr=await ae(this.sessions.decoder_model_merged,dn),mr=this.getPastKeyValues(xr,mr);const{prob:Tn,spectrum:qs}=xr;if(pr.push(qs),Nr>=dr&&(Array.from(Tn.data).filter(Ks=>Ks>=Ee).length>0||Nr>=Ir))break}const $n=(0,y.cat)(pr),{waveform:zn}=await ae(wt.sessions.model,{spectrogram:$n});return{spectrogram:$n,waveform:zn}}}class ol extends Q{constructor(){super(...arguments);He(this,"main_input_name","spectrogram")}}class sd extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class ad extends sd{}class sl extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Us extends sl{}class Vs extends sl{}class al extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class Ws extends al{}class ll extends al{}class ul extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class ld extends ul{}class ud extends ul{}class Ko extends Q{}class cd extends Ko{}class dd extends Ko{static async from_pretrained(G,ne={}){return ne.model_file_name??(ne.model_file_name="text_model"),super.from_pretrained(G,ne)}}class pd extends Ko{static async from_pretrained(G,ne={}){return ne.model_file_name??(ne.model_file_name="audio_model"),super.from_pretrained(G,ne)}}class df extends Q{}class cl extends df{async _call(G){return new Sf(await super._call(G))}}class Xo extends Q{}class mm extends Xo{}class fd extends Xo{}class hd extends Xo{}class dl extends Q{constructor(G,ne,Ee){super(G,ne),this.generation_config=Ee}}class pl extends dl{}class md extends dl{}class fl extends Q{}class gd extends fl{}class _d extends fl{async _call(G){return new ur(await super._call(G))}}class hl extends Q{}class pf extends hl{}class gm extends hl{}class ml extends Q{constructor(ne,Ee,Ze){super(ne,Ee);He(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(ne){const[Ee,Ze]=ne.dims,it=this.config.decoder.num_codebooks,wt=Ze-it;let Ct=0;for(let lr=0;lr<ne.size;++lr){if(ne.data[lr]===this.config.decoder.pad_token_id)continue;const Ir=lr%Ze,dr=Math.floor(lr/Ze)%it,wr=Ir-dr;wr>0&&wr<=wt&&(ne.data[Ct++]=ne.data[lr])}const Wt=Math.floor(Ee/it),cr=Ct/(Wt*it);return new y.Tensor(ne.type,ne.data.slice(0,Ct),[Wt,it,cr])}prepare_inputs_for_generation(ne,Ee,Ze){let it=structuredClone(ne);for(let Ct=0;Ct<it.length;++Ct)for(let Wt=0;Wt<it[Ct].length;++Wt)Ct%this.config.decoder.num_codebooks>=Wt&&(it[Ct][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(ne){const Ee=await super.generate(ne),Ze=this._apply_and_filter_by_delay_pattern_mask(Ee).unsqueeze_(0),{audio_values:it}=await ae(this.sessions.encodec_decode,{audio_codes:Ze});return it}}class gl extends Q{}class wd extends gl{}class ff extends gl{async _call(G){return new ur(await super._call(G))}}class _l extends Q{}class yd extends _l{}class vd extends _l{async _call(G){return new ur(await super._call(G))}}class wl extends Q{}class bd extends wl{}class hf extends wl{async _call(G){return new ur(await super._call(G))}}class Qo extends Q{}class Yo extends Qo{}class yl extends Qo{async _call(G){return new ur(await super._call(G))}}class Rr{static async from_pretrained(G,{progress_callback:ne=null,config:Ee=null,cache_dir:Ze=null,local_files_only:it=!1,revision:wt="main",model_file_name:Ct=null,subfolder:Wt="onnx",device:cr=null,dtype:lr=null,use_external_data_format:Ir=null,session_options:dr={}}={}){let wr={progress_callback:ne,config:Ee,cache_dir:Ze,local_files_only:it,revision:wt,model_file_name:Ct,subfolder:Wt,device:cr,dtype:lr,use_external_data_format:Ir,session_options:dr};if(wr.config=await o.AutoConfig.from_pretrained(G,wr),!this.MODEL_CLASS_MAPPINGS)throw new Error("`MODEL_CLASS_MAPPINGS` not implemented for this type of `AutoClass`: "+this.name);for(let pr of this.MODEL_CLASS_MAPPINGS){const mr=pr.get(wr.config.model_type);if(mr)return await mr[1].from_pretrained(G,wr)}if(this.BASE_IF_FAIL)return console.warn(`Unknown model class "${wr.config.model_type}", attempting to construct from base class.`),await Q.from_pretrained(G,wr);throw Error(`Unsupported model type: ${wr.config.model_type}`)}}He(Rr,"MODEL_CLASS_MAPPINGS",null),He(Rr,"BASE_IF_FAIL",!1);const mf=new Map([["bert",["BertModel",Be]],["nomic_bert",["NomicBertModel",je]],["roformer",["RoFormerModel",et]],["electra",["ElectraModel",ke]],["esm",["EsmModel",un]],["convbert",["ConvBertModel",ye]],["camembert",["CamembertModel",ve]],["deberta",["DebertaModel",ht]],["deberta-v2",["DebertaV2Model",Ot]],["mpnet",["MPNetModel",Cs]],["albert",["AlbertModel",Ji]],["distilbert",["DistilBertModel",Pr]],["roberta",["RobertaModel",_r]],["xlm",["XLMModel",cn]],["xlm-roberta",["XLMRobertaModel",Er]],["clap",["ClapModel",cd]],["clip",["CLIPModel",pu]],["clipseg",["CLIPSegModel",wu]],["chinese_clip",["ChineseCLIPModel",_u]],["siglip",["SiglipModel",yo]],["mobilebert",["MobileBertModel",Kr]],["squeezebert",["SqueezeBertModel",Ps]],["wav2vec2",["Wav2Vec2Model",Kc]],["wav2vec2-bert",["Wav2Vec2BertModel",tl]],["unispeech",["UniSpeechModel",Ja]],["unispeech-sat",["UniSpeechSatModel",Rs]],["hubert",["HubertModel",uf]],["wavlm",["WavLMModel",ed]],["audio-spectrogram-transformer",["ASTModel",zt]],["vits",["VitsModel",cl]],["pyannote",["PyAnnoteModel",Ya]],["wespeaker-resnet",["WeSpeakerResNetModel",Za]],["detr",["DetrModel",dc]],["rt_detr",["RTDetrModel",mc]],["table-transformer",["TableTransformerModel",_c]],["vit",["ViTModel",Xu]],["fastvit",["FastViTModel",Yu]],["mobilevit",["MobileViTModel",rc]],["mobilevitv2",["MobileViTV2Model",of]],["owlvit",["OwlViTModel",oc]],["owlv2",["Owlv2Model",ac]],["beit",["BeitModel",uc]],["deit",["DeiTModel",vc]],["convnext",["ConvNextModel",Ic]],["convnextv2",["ConvNextV2Model",zc]],["dinov2",["Dinov2Model",Lc]],["resnet",["ResNetModel",xc]],["swin",["SwinModel",Tc]],["swin2sr",["Swin2SRModel",Sc]],["donut-swin",["DonutSwinModel",Ha]],["yolos",["YolosModel",Bc]],["dpt",["DPTModel",Va]],["glpn",["GLPNModel",Pc]],["hifigan",["SpeechT5HifiGan",ol]],["efficientnet",["EfficientNetModel",gd]],["mobilenet_v1",["MobileNetV1Model",wd]],["mobilenet_v2",["MobileNetV2Model",yd]],["mobilenet_v3",["MobileNetV3Model",bd]],["mobilenet_v4",["MobileNetV4Model",Yo]]]),gf=new Map([["t5",["T5Model",jo]],["longt5",["LongT5Model",Vo]],["mt5",["MT5Model",Go]],["bart",["BartModel",Ue]],["mbart",["MBartModel",Fe]],["marian",["MarianModel",sf]],["whisper",["WhisperModel",Gt]],["m2m_100",["M2M100Model",Hc]],["blenderbot",["BlenderbotModel",kt]],["blenderbot-small",["BlenderbotSmallModel",Ar]]]),_f=new Map([["bloom",["BloomModel",Wu]],["gpt2",["GPT2Model",vu]],["gptj",["GPTJModel",Su]],["gpt_bigcode",["GPTBigCodeModel",Cu]],["gpt_neo",["GPTNeoModel",xu]],["gpt_neox",["GPTNeoXModel",Tu]],["codegen",["CodeGenModel",Pu]],["llama",["LlamaModel",ii]],["cohere",["CohereModel",Au]],["gemma",["GemmaModel",Fu]],["gemma2",["Gemma2Model",zu]],["openelm",["OpenELMModel",Lu]],["qwen2",["Qwen2Model",Bu]],["phi",["PhiModel",ju]],["phi3",["Phi3Model",Vu]],["mpt",["MptModel",nf]],["opt",["OPTModel",qu]],["mistral",["MistralModel",Us]],["starcoder2",["Starcoder2Model",Ws]],["falcon",["FalconModel",ld]],["stablelm",["StableLmModel",pl]]]),Gs=new Map([["speecht5",["SpeechT5ForSpeechToText",od]],["whisper",["WhisperForConditionalGeneration",ma]]]),xd=new Map([["speecht5",["SpeechT5ForTextToSpeech",cf]]]),Md=new Map([["vits",["VitsModel",cl]],["musicgen",["MusicgenForConditionalGeneration",ml]]]),Td=new Map([["bert",["BertForSequenceClassification",st]],["roformer",["RoFormerForSequenceClassification",$e]],["electra",["ElectraForSequenceClassification",dt]],["esm",["EsmForSequenceClassification",Mi]],["convbert",["ConvBertForSequenceClassification",ee]],["camembert",["CamembertForSequenceClassification",qe]],["deberta",["DebertaForSequenceClassification",bt]],["deberta-v2",["DebertaV2ForSequenceClassification",Xt]],["mpnet",["MPNetForSequenceClassification",Ro]],["albert",["AlbertForSequenceClassification",ho]],["distilbert",["DistilBertForSequenceClassification",Yr]],["roberta",["RobertaForSequenceClassification",gn]],["xlm",["XLMForSequenceClassification",Jt]],["xlm-roberta",["XLMRobertaForSequenceClassification",vr]],["bart",["BartForSequenceClassification",pe]],["mbart",["MBartForSequenceClassification",rt]],["mobilebert",["MobileBertForSequenceClassification",Dr]],["squeezebert",["SqueezeBertForSequenceClassification",fi]]]),wf=new Map([["bert",["BertForTokenClassification",pt]],["roformer",["RoFormerForTokenClassification",Pe]],["electra",["ElectraForTokenClassification",Je]],["esm",["EsmForTokenClassification",Gr]],["convbert",["ConvBertForTokenClassification",D]],["camembert",["CamembertForTokenClassification",Qe]],["deberta",["DebertaForTokenClassification",Et]],["deberta-v2",["DebertaV2ForTokenClassification",Yt]],["mpnet",["MPNetForTokenClassification",Bo]],["distilbert",["DistilBertForTokenClassification",$r]],["roberta",["RobertaForTokenClassification",ct]],["xlm",["XLMForTokenClassification",Un]],["xlm-roberta",["XLMRobertaForTokenClassification",Lr]]]),vl=new Map([["t5",["T5ForConditionalGeneration",Uo]],["longt5",["LongT5ForConditionalGeneration",Wo]],["mt5",["MT5ForConditionalGeneration",Vr]],["bart",["BartForConditionalGeneration",W]],["mbart",["MBartForConditionalGeneration",Oe]],["marian",["MarianMTModel",Gc]],["m2m_100",["M2M100ForConditionalGeneration",qc]],["blenderbot",["BlenderbotForConditionalGeneration",It]],["blenderbot-small",["BlenderbotSmallForConditionalGeneration",or]]]),Hs=new Map([["bloom",["BloomForCausalLM",Gu]],["gpt2",["GPT2LMHeadModel",bu]],["gptj",["GPTJForCausalLM",Eu]],["gpt_bigcode",["GPTBigCodeForCausalLM",rf]],["gpt_neo",["GPTNeoForCausalLM",Mu]],["gpt_neox",["GPTNeoXForCausalLM",ku]],["codegen",["CodeGenForCausalLM",As]],["llama",["LlamaForCausalLM",$u]],["cohere",["CohereForCausalLM",Iu]],["gemma",["GemmaForCausalLM",Ou]],["gemma2",["Gemma2ForCausalLM",Du]],["openelm",["OpenELMForCausalLM",Ru]],["qwen2",["Qwen2ForCausalLM",Nu]],["phi",["PhiForCausalLM",Uu]],["phi3",["Phi3ForCausalLM",$a]],["mpt",["MptForCausalLM",Hu]],["opt",["OPTForCausalLM",Ku]],["mbart",["MBartForCausalLM",Mt]],["mistral",["MistralForCausalLM",Vs]],["starcoder2",["Starcoder2ForCausalLM",ll]],["falcon",["FalconForCausalLM",ud]],["trocr",["TrOCRForCausalLM",ad]],["stablelm",["StableLmForCausalLM",md]]]),kd=new Map([["bert",["BertForMaskedLM",We]],["roformer",["RoFormerForMaskedLM",A]],["electra",["ElectraForMaskedLM",Ne]],["esm",["EsmForMaskedLM",Bi]],["convbert",["ConvBertForMaskedLM",R]],["camembert",["CamembertForMaskedLM",Re]],["deberta",["DebertaForMaskedLM",Tt]],["deberta-v2",["DebertaV2ForMaskedLM",Ut]],["mpnet",["MPNetForMaskedLM",Lo]],["albert",["AlbertForMaskedLM",Zt]],["distilbert",["DistilBertForMaskedLM",$t]],["roberta",["RobertaForMaskedLM",Cn]],["xlm",["XLMWithLMHeadModel",On]],["xlm-roberta",["XLMRobertaForMaskedLM",At]],["mobilebert",["MobileBertForMaskedLM",pi]],["squeezebert",["SqueezeBertForMaskedLM",fo]]]),Sd=new Map([["bert",["BertForQuestionAnswering",Ge]],["roformer",["RoFormerForQuestionAnswering",se]],["electra",["ElectraForQuestionAnswering",Ve]],["convbert",["ConvBertForQuestionAnswering",ue]],["camembert",["CamembertForQuestionAnswering",tt]],["deberta",["DebertaForQuestionAnswering",Lt]],["deberta-v2",["DebertaV2ForQuestionAnswering",rr]],["mpnet",["MPNetForQuestionAnswering",No]],["albert",["AlbertForQuestionAnswering",mo]],["distilbert",["DistilBertForQuestionAnswering",mt]],["roberta",["RobertaForQuestionAnswering",Kn]],["xlm",["XLMForQuestionAnswering",yn]],["xlm-roberta",["XLMRobertaForQuestionAnswering",Xr]],["mobilebert",["MobileBertForQuestionAnswering",Ni]],["squeezebert",["SqueezeBertForQuestionAnswering",ki]]]),bl=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",ga]]]),_m=new Map([["llava",["LlavaForConditionalGeneration",wo]],["moondream1",["Moondream1ForConditionalGeneration",ar]],["florence2",["Florence2ForConditionalGeneration",_a]]]),yf=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",ga]]]),Ed=new Map([["vit",["ViTForImageClassification",Qu]],["fastvit",["FastViTForImageClassification",Zu]],["mobilevit",["MobileViTForImageClassification",nc]],["mobilevitv2",["MobileViTV2ForImageClassification",ic]],["beit",["BeitForImageClassification",cc]],["deit",["DeiTForImageClassification",bc]],["convnext",["ConvNextForImageClassification",Fc]],["convnextv2",["ConvNextV2ForImageClassification",Dc]],["dinov2",["Dinov2ForImageClassification",Rc]],["resnet",["ResNetForImageClassification",Mc]],["swin",["SwinForImageClassification",kc]],["segformer",["SegformerForImageClassification",fd]],["efficientnet",["EfficientNetForImageClassification",_d]],["mobilenet_v1",["MobileNetV1ForImageClassification",ff]],["mobilenet_v2",["MobileNetV2ForImageClassification",vd]],["mobilenet_v3",["MobileNetV3ForImageClassification",hf]],["mobilenet_v4",["MobileNetV4ForImageClassification",yl]]]),vf=new Map([["detr",["DetrForObjectDetection",pc]],["rt_detr",["RTDetrForObjectDetection",Ls]],["table-transformer",["TableTransformerForObjectDetection",wc]],["yolos",["YolosForObjectDetection",Nc]]]),Cd=new Map([["owlvit",["OwlViTForObjectDetection",sc]],["owlv2",["Owlv2ForObjectDetection",lc]]]),Pd=new Map([["detr",["DetrForSegmentation",fc]],["clipseg",["CLIPSegForImageSegmentation",yu]]]),$d=new Map([["segformer",["SegformerForSemanticSegmentation",hd]]]),Ad=new Map([["sam",["SamModel",Vc]]]),bf=new Map([["wav2vec2",["Wav2Vec2ForCTC",af]],["wav2vec2-bert",["Wav2Vec2BertForCTC",js]],["unispeech",["UniSpeechForCTC",Xc]],["unispeech-sat",["UniSpeechSatForCTC",el]],["wavlm",["WavLMForCTC",nl]],["hubert",["HubertForCTC",Jc]]]),Id=new Map([["wav2vec2",["Wav2Vec2ForSequenceClassification",Vi]],["wav2vec2-bert",["Wav2Vec2BertForSequenceClassification",Zc]],["unispeech",["UniSpeechForSequenceClassification",Qc]],["unispeech-sat",["UniSpeechSatForSequenceClassification",Yc]],["wavlm",["WavLMForSequenceClassification",td]],["hubert",["HubertForSequenceClassification",rl]],["audio-spectrogram-transformer",["ASTForAudioClassification",$s]]]),Fd=new Map([["wavlm",["WavLMForXVector",rd]]]),Od=new Map([["unispeech-sat",["UniSpeechSatForAudioFrameClassification",Bs]],["wavlm",["WavLMForAudioFrameClassification",nd]],["wav2vec2",["Wav2Vec2ForAudioFrameClassification",Wi]],["pyannote",["PyAnnoteForAudioFrameClassification",Gi]]]),zd=new Map([["vitmatte",["VitMatteForImageMatting",ec]]]),xf=new Map([["swin2sr",["Swin2SRForImageSuperResolution",ja]]]),Dd=new Map([["dpt",["DPTForDepthEstimation",Wa]],["depth_anything",["DepthAnythingForDepthEstimation",Cc]],["glpn",["GLPNForDepthEstimation",$c]]]),Ld=new Map([["clip",["CLIPVisionModelWithProjection",fu]],["siglip",["SiglipVisionModel",mu]]]),Rd=[[mf,b.EncoderOnly],[gf,b.EncoderDecoder],[_f,b.DecoderOnly],[Td,b.EncoderOnly],[wf,b.EncoderOnly],[vl,b.Seq2Seq],[Gs,b.Seq2Seq],[Hs,b.DecoderOnly],[kd,b.EncoderOnly],[Sd,b.EncoderOnly],[bl,b.Vision2Seq],[_m,b.ImageTextToText],[Ed,b.EncoderOnly],[Pd,b.EncoderOnly],[$d,b.EncoderOnly],[zd,b.EncoderOnly],[xf,b.EncoderOnly],[Dd,b.EncoderOnly],[vf,b.EncoderOnly],[Cd,b.EncoderOnly],[Ad,b.MaskGeneration],[bf,b.EncoderOnly],[Id,b.EncoderOnly],[xd,b.Seq2Seq],[Md,b.EncoderOnly],[Fd,b.EncoderOnly],[Od,b.EncoderOnly],[Ld,b.EncoderOnly]];for(const[V,G]of Rd)for(const[ne,Ee]of V.values())I.set(ne,G),z.set(Ee,ne),U.set(ne,Ee);const Mf=[["MusicgenForConditionalGeneration",ml,b.Musicgen],["CLIPTextModelWithProjection",hi,b.EncoderOnly],["SiglipTextModel",hu,b.EncoderOnly],["ClapTextModelWithProjection",dd,b.EncoderOnly],["ClapAudioModelWithProjection",pd,b.EncoderOnly]];for(const[V,G,ne]of Mf)I.set(V,ne),z.set(G,V),U.set(V,G);class Bd extends Rr{}He(Bd,"MODEL_CLASS_MAPPINGS",Rd.map(G=>G[0])),He(Bd,"BASE_IF_FAIL",!0);class Pn extends Rr{}He(Pn,"MODEL_CLASS_MAPPINGS",[Td]);class Nd extends Rr{}He(Nd,"MODEL_CLASS_MAPPINGS",[wf]);class jd extends Rr{}He(jd,"MODEL_CLASS_MAPPINGS",[vl]);class xl extends Rr{}He(xl,"MODEL_CLASS_MAPPINGS",[Gs]);class Ud extends Rr{}He(Ud,"MODEL_CLASS_MAPPINGS",[xd]);class Zo extends Rr{}He(Zo,"MODEL_CLASS_MAPPINGS",[Md]);class Vd extends Rr{}He(Vd,"MODEL_CLASS_MAPPINGS",[Hs]);class Wd extends Rr{}He(Wd,"MODEL_CLASS_MAPPINGS",[kd]);class Ml extends Rr{}He(Ml,"MODEL_CLASS_MAPPINGS",[Sd]);class Gd extends Rr{}He(Gd,"MODEL_CLASS_MAPPINGS",[bl]);class Hd extends Rr{}He(Hd,"MODEL_CLASS_MAPPINGS",[Ed]);class Tl extends Rr{}He(Tl,"MODEL_CLASS_MAPPINGS",[Pd]);class qd extends Rr{}He(qd,"MODEL_CLASS_MAPPINGS",[$d]);class Kd extends Rr{}He(Kd,"MODEL_CLASS_MAPPINGS",[vf]);class Xd extends Rr{}He(Xd,"MODEL_CLASS_MAPPINGS",[Cd]);class kl extends Rr{}He(kl,"MODEL_CLASS_MAPPINGS",[Ad]);class Qd extends Rr{}He(Qd,"MODEL_CLASS_MAPPINGS",[bf]);class Yd extends Rr{}He(Yd,"MODEL_CLASS_MAPPINGS",[Id]);class Sl extends Rr{}He(Sl,"MODEL_CLASS_MAPPINGS",[Fd]);class Zd extends Rr{}He(Zd,"MODEL_CLASS_MAPPINGS",[Od]);class Tf extends Rr{}He(Tf,"MODEL_CLASS_MAPPINGS",[yf]);class Jd extends Rr{}He(Jd,"MODEL_CLASS_MAPPINGS",[zd]);class ep extends Rr{}He(ep,"MODEL_CLASS_MAPPINGS",[xf]);class tp extends Rr{}He(tp,"MODEL_CLASS_MAPPINGS",[Dd]);class rp extends Rr{}He(rp,"MODEL_CLASS_MAPPINGS",[Ld]);class wm extends ge{constructor({logits:G,past_key_values:ne,encoder_outputs:Ee,decoder_attentions:Ze=null,cross_attentions:it=null}){super(),this.logits=G,this.past_key_values=ne,this.encoder_outputs=Ee,this.decoder_attentions=Ze,this.cross_attentions=it}}class ur extends ge{constructor({logits:G}){super(),this.logits=G}}class np extends ge{constructor({logits:G,embeddings:ne}){super(),this.logits=G,this.embeddings=ne}}class hn extends ge{constructor({logits:G}){super(),this.logits=G}}class bn extends ge{constructor({logits:G}){super(),this.logits=G}}class xn extends ge{constructor({start_logits:G,end_logits:ne}){super(),this.start_logits=G,this.end_logits=ne}}class to extends ge{constructor({logits:G}){super(),this.logits=G}}class kf extends ge{constructor({logits:G,past_key_values:ne}){super(),this.logits=G,this.past_key_values=ne}}class ip extends ge{constructor({alphas:G}){super(),this.alphas=G}}class Sf extends ge{constructor({waveform:G,spectrogram:ne}){super(),this.waveform=G,this.spectrogram=ne}}},"./src/models/whisper/common_whisper.js":(e,t,r)=>{r.r(t),r.d(t,{WHISPER_LANGUAGE_MAPPING:()=>a,WHISPER_TO_LANGUAGE_CODE_MAPPING:()=>l,whisper_language_to_code:()=>p});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 p(_){_=_.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,r)=>{r.r(t),r.d(t,{WhisperGenerationConfig:()=>a});var o=r("./src/generation/configuration_utils.js");class a extends o.GenerationConfig{constructor(){super(...arguments);He(this,"return_timestamps",null);He(this,"return_token_timestamps",null);He(this,"num_frames",null);He(this,"alignment_heads",null);He(this,"task",null);He(this,"language",null);He(this,"no_timestamps_token_id",null);He(this,"prompt_ids",null);He(this,"is_multilingual",null);He(this,"lang_to_id",null);He(this,"task_to_id",null);He(this,"max_initial_timestamp_index",1)}}},"./src/ops/registry.js":(e,t,r)=>{r.r(t),r.d(t,{TensorOpRegistry:()=>p});var o=r("./src/backends/onnx.js"),a=r("./src/utils/tensor.js");const l=async(_,h,g)=>{const M=await(0,o.createInferenceSession)(new Uint8Array(_),h);return async y=>{const E=Object.fromEntries(Object.entries(y).map(([O,S])=>[O,S.ort_tensor])),T=await M.run(E);return Array.isArray(g)?g.map(O=>new a.Tensor(T[O])):new a.Tensor(T[g])}};class p{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}}He(p,"session_options",{})},"./src/pipelines.js":(e,t,r)=>{r.r(t),r.d(t,{AudioClassificationPipeline:()=>Y,AutomaticSpeechRecognitionPipeline:()=>L,DepthEstimationPipeline:()=>Le,DocumentQuestionAnsweringPipeline:()=>Q,FeatureExtractionPipeline:()=>ce,FillMaskPipeline:()=>I,ImageClassificationPipeline:()=>Xe,ImageFeatureExtractionPipeline:()=>xe,ImageSegmentationPipeline:()=>me,ImageToImagePipeline:()=>Ke,ImageToTextPipeline:()=>Se,ObjectDetectionPipeline:()=>ie,Pipeline:()=>S,QuestionAnsweringPipeline:()=>b,SummarizationPipeline:()=>z,Text2TextGenerationPipeline:()=>U,TextClassificationPipeline:()=>C,TextGenerationPipeline:()=>N,TextToAudioPipeline:()=>ge,TokenClassificationPipeline:()=>w,TranslationPipeline:()=>B,ZeroShotAudioClassificationPipeline:()=>_e,ZeroShotClassificationPipeline:()=>ae,ZeroShotImageClassificationPipeline:()=>X,ZeroShotObjectDetectionPipeline:()=>Me,pipeline:()=>st});var o=r("./src/tokenizers.js"),a=r("./src/models.js"),l=r("./src/processors.js"),p=r("./src/utils/generic.js"),_=r("./src/utils/core.js"),h=r("./src/utils/maths.js"),g=r("./src/utils/audio.js"),M=r("./src/utils/tensor.js"),y=r("./src/utils/image.js");async function E(Ge){return Array.isArray(Ge)||(Ge=[Ge]),await Promise.all(Ge.map(Te=>y.RawImage.read(Te)))}async function T(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 O(Ge,Te){Te&&(Ge=Ge.map($e=>$e|0));const[je,Ye,et,A]=Ge;return{xmin:je,ymin:Ye,xmax:et,ymax:A}}class S extends p.Callable{constructor({task:Te,model:je,tokenizer:Ye=null,processor:et=null}){super(),this.task=Te,this.model=je,this.tokenizer=Ye,this.processor=et}async dispose(){await this.model.dispose()}}class C extends S{constructor(Te){super(Te)}async _call(Te,{top_k:je=1}={}){const Ye=this.tokenizer(Te,{padding:!0,truncation:!0}),et=await this.model(Ye),A=this.model.config.problem_type==="multi_label_classification"?se=>se.sigmoid():se=>new M.Tensor("float32",(0,h.softmax)(se.data),se.dims),$e=this.model.config.id2label,Pe=[];for(const se of et.logits){const re=A(se),ye=await(0,M.topk)(re,je),R=ye[0].tolist(),D=ye[1].tolist().map((ue,le)=>({label:$e?$e[ue]:`LABEL_${ue}`,score:R[le]}));je===1?Pe.push(...D):Pe.push(D)}return Array.isArray(Te)||je===1?Pe:Pe[0]}}class w extends S{constructor(Te){super(Te)}async _call(Te,{ignore_labels:je=["O"]}={}){const Ye=Array.isArray(Te),et=this.tokenizer(Ye?Te:[Te],{padding:!0,truncation:!0}),$e=(await this.model(et)).logits,Pe=this.model.config.id2label,se=[];for(let re=0;re<$e.dims[0];++re){const ye=et.input_ids[re],R=$e[re],ee=[];for(let D=0;D<R.dims[0];++D){const ue=R[D],le=(0,h.max)(ue.data)[1],ke=Pe?Pe[le]:`LABEL_${le}`;if(je.includes(ke))continue;const Ne=this.tokenizer.decode([ye[D].item()],{skip_special_tokens:!0});if(Ne==="")continue;const dt=(0,h.softmax)(ue.data);ee.push({entity:ke,score:dt[le],index:D,word:Ne})}se.push(ee)}return Ye?se:se[0]}}class b extends S{constructor(Te){super(Te)}async _call(Te,je,{top_k:Ye=1}={}){const et=this.tokenizer(Te,{text_pair:je,padding:!0,truncation:!0}),{start_logits:A,end_logits:$e}=await this.model(et),Pe=et.input_ids.tolist(),se=et.attention_mask.tolist(),re=this.tokenizer.all_special_ids,ye=[];for(let R=0;R<A.dims[0];++R){const ee=Pe[R],D=ee.findIndex(Je=>Je==this.tokenizer.sep_token_id);se[R].map((Je,Ve)=>Je==1&&(Ve===0||Ve>D&&re.findIndex(Z=>Z==ee[Ve])===-1));const ue=A[R].tolist(),le=$e[R].tolist();for(let Je=1;Je<ue.length;++Je)(se[R]==0||Je<=D||re.findIndex(Ve=>Ve==ee[Je])!==-1)&&(ue[Je]=-1/0,le[Je]=-1/0);const ke=(0,h.softmax)(ue).map((Je,Ve)=>[Je,Ve]),Ne=(0,h.softmax)(le).map((Je,Ve)=>[Je,Ve]);ke[0][0]=0,Ne[0][0]=0;const dt=(0,_.product)(ke,Ne).filter(Je=>Je[0][1]<=Je[1][1]).map(Je=>[Je[0][1],Je[1][1],Je[0][0]*Je[1][0]]).sort((Je,Ve)=>Ve[2]-Je[2]);for(let Je=0;Je<Math.min(dt.length,Ye);++Je){const[Ve,Z,ve]=dt[Je],Re=ee.slice(Ve,Z+1),qe=this.tokenizer.decode(Re,{skip_special_tokens:!0});ye.push({answer:qe,score:ve})}}return Ye===1?ye[0]:ye}}class I extends S{constructor(Te){super(Te)}async _call(Te,{top_k:je=5}={}){const Ye=this.tokenizer(Te,{padding:!0,truncation:!0}),{logits:et}=await this.model(Ye),A=[],$e=Ye.input_ids.tolist();for(let Pe=0;Pe<$e.length;++Pe){const se=$e[Pe],re=se.findIndex(ue=>ue==this.tokenizer.mask_token_id);if(re===-1)throw Error(`Mask token (${this.tokenizer.mask_token}) not found in text.`);const ye=et[Pe][re],R=await(0,M.topk)(new M.Tensor("float32",(0,h.softmax)(ye.data),ye.dims),je),ee=R[0].tolist(),D=R[1].tolist();A.push(D.map((ue,le)=>{const ke=se.slice();return ke[re]=ue,{score:ee[le],token:Number(ue),token_str:this.tokenizer.model.vocab[ue],sequence:this.tokenizer.decode(ke,{skip_special_tokens:!0})}}))}return Array.isArray(Te)?A:A[0]}}class U extends S{constructor(je){super(je);He(this,"_key","generated_text")}async _call(je,Ye={}){Array.isArray(je)||(je=[je]),this.model.config.prefix&&(je=je.map(re=>this.model.config.prefix+re));const et=this.model.config.task_specific_params;et&&et[this.task]&&et[this.task].prefix&&(je=je.map(re=>et[this.task].prefix+re));const A=this.tokenizer,$e={padding:!0,truncation:!0};let Pe;this instanceof B&&"_build_translation_inputs"in A?Pe=A._build_translation_inputs(je,$e,Ye):Pe=A(je,$e);const se=await this.model.generate({...Pe,...Ye});return A.batch_decode(se,{skip_special_tokens:!0}).map(re=>({[this._key]:re}))}}class z extends U{constructor(je){super(je);He(this,"_key","summary_text")}}class B extends U{constructor(je){super(je);He(this,"_key","translation_text")}}function j(Ge){return Array.isArray(Ge)&&Ge.every(Te=>"role"in Te&&"content"in Te)}class N extends S{constructor(Te){super(Te)}async _call(Te,je={}){let Ye=!1,et=!1,A;if(typeof Te=="string")A=Te=[Te];else if(Array.isArray(Te)&&Te.every(D=>typeof D=="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");et=!0,A=Te.map(D=>this.tokenizer.apply_chat_template(D,{tokenize:!1,add_generation_prompt:!0}))}const $e=je.add_special_tokens??!1,Pe=et?!1:je.return_full_text??!0;this.tokenizer.padding_side="left";const se=this.tokenizer(A,{add_special_tokens:$e,padding:!0,truncation:!0}),re=await this.model.generate({...se,...je}),ye=this.tokenizer.batch_decode(re,{skip_special_tokens:!0});let R;!Pe&&se.input_ids.dims.at(-1)>0&&(R=this.tokenizer.batch_decode(se.input_ids,{skip_special_tokens:!0}).map(D=>D.length));const ee=Array.from({length:Te.length},D=>[]);for(let D=0;D<ye.length;++D){const ue=Math.floor(D/re.dims[0]*Te.length);R&&(ye[D]=ye[D].slice(R[ue])),ee[ue].push({generated_text:et?[...Te[ue],{role:"assistant",content:ye[D]}]:ye[D]})}return!Ye&&ee.length===1?ee[0]:ee}}class ae 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:et=!1}={}){const A=Array.isArray(Te);A||(Te=[Te]),Array.isArray(je)||(je=[je]);const $e=je.map(re=>Ye.replace("{}",re)),Pe=et||je.length===1,se=[];for(const re of Te){const ye=[];for(const D of $e){const ue=this.tokenizer(re,{text_pair:D,padding:!0,truncation:!0}),le=await this.model(ue);Pe?ye.push([le.logits.data[this.contradiction_id],le.logits.data[this.entailment_id]]):ye.push(le.logits.data[this.entailment_id])}const ee=(Pe?ye.map(D=>(0,h.softmax)(D)[1]):(0,h.softmax)(ye)).map((D,ue)=>[D,ue]).sort((D,ue)=>ue[0]-D[0]);se.push({sequence:re,labels:ee.map(D=>je[D[1]]),scores:ee.map(D=>D[0])})}return A?se:se[0]}}class ce extends S{constructor(Te){super(Te)}async _call(Te,{pooling:je="none",normalize:Ye=!1,quantize:et=!1,precision:A="binary"}={}){const $e=this.tokenizer(Te,{padding:!0,truncation:!0}),Pe=await this.model($e);let se=Pe.last_hidden_state??Pe.logits??Pe.token_embeddings;if(je!=="none")if(je==="mean")se=(0,M.mean_pooling)(se,$e.attention_mask);else if(je==="cls")se=se.slice(null,0);else throw Error(`Pooling method '${je}' not supported.`);return Ye&&(se=se.normalize(2,-1)),et&&(se=(0,M.quantize_embeddings)(se,A)),se}}class xe extends S{constructor(Te){super(Te)}async _call(Te,{pool:je=null}={}){const Ye=await E(Te),{pixel_values:et}=await this.processor(Ye),A=await this.model({pixel_values:et});let $e;if(je){if(!("pooler_output"in A))throw Error("No pooled output was returned. Make sure the model has a 'pooler' layer when using the 'pool' option.");$e=A.pooler_output}else $e=A.last_hidden_state??A.logits??A.image_embeds;return $e}}class Y extends S{constructor(Te){super(Te)}async _call(Te,{top_k:je=5}={}){const Ye=this.processor.feature_extractor.config.sampling_rate,et=await T(Te,Ye),A=this.model.config.id2label,$e=[];for(const Pe of et){const se=await this.processor(Pe),ye=(await this.model(se)).logits[0],R=await(0,M.topk)(new M.Tensor("float32",(0,h.softmax)(ye.data),ye.dims),je),ee=R[0].tolist(),ue=R[1].tolist().map((le,ke)=>({label:A?A[le]:`LABEL_${le}`,score:ee[ke]}));$e.push(ue)}return Array.isArray(Te)?$e:$e[0]}}class _e extends S{constructor(Te){super(Te)}async _call(Te,je,{hypothesis_template:Ye="This is a sound of {}."}={}){const et=!Array.isArray(Te);et&&(Te=[Te]);const A=je.map(ye=>Ye.replace("{}",ye)),$e=this.tokenizer(A,{padding:!0,truncation:!0}),Pe=this.processor.feature_extractor.config.sampling_rate,se=await T(Te,Pe),re=[];for(const ye of se){const R=await this.processor(ye),ee=await this.model({...$e,...R}),D=(0,h.softmax)(ee.logits_per_audio.data);re.push([...D].map((ue,le)=>({score:ue,label:je[le]})))}return et?re[0]:re}}class L 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 '${this.model.config.model_type}'.`)}}async _call_wav2vec2(Te,je){je.language&&console.warn('`language` parameter is not yet supported for `wav2vec2` models, defaulting to "English".'),je.task&&console.warn('`task` parameter is not yet supported for `wav2vec2` models, defaulting to "transcribe".');const Ye=!Array.isArray(Te);Ye&&(Te=[Te]);const et=this.processor.feature_extractor.config.sampling_rate,A=await T(Te,et),$e=[];for(const Pe of A){const se=await this.processor(Pe),ye=(await this.model(se)).logits[0],R=[];for(const D of ye)R.push((0,h.max)(D.data)[1]);const ee=this.tokenizer.decode(R);$e.push({text:ee})}return Ye?$e[0]:$e}async _call_whisper(Te,je){const Ye=je.return_timestamps??!1,et=je.chunk_length_s??0,A=je.force_full_sequences??!1;let $e=je.stride_length_s??null;const Pe={...je};Ye==="word"&&(Pe.return_token_timestamps=!0,Pe.return_timestamps=!1);const se=!Array.isArray(Te);se&&(Te=[Te]);const re=this.processor.feature_extractor.config.chunk_length/this.model.config.max_source_positions,ye=this.processor.feature_extractor.config.hop_length,R=this.processor.feature_extractor.config.sampling_rate,ee=await T(Te,R),D=[];for(const ue of ee){let le=[];if(et>0){if($e===null)$e=et/6;else if(et<=$e)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");const dt=R*et,Je=R*$e,Ve=dt-2*Je;let Z=0;for(;;){const ve=Z+dt,Re=ue.subarray(Z,ve),qe=await this.processor(Re),Qe=Z===0,tt=ve>=ue.length;if(le.push({stride:[Re.length,Qe?0:Je,tt?0:Je],input_features:qe.input_features,is_last:tt}),tt)break;Z+=Ve}}else le=[{stride:[ue.length,0,0],input_features:(await this.processor(ue)).input_features,is_last:!0}];for(const dt of le){Pe.num_frames=Math.floor(dt.stride[0]/ye);const Je=await this.model.generate({inputs:dt.input_features,...Pe});Ye==="word"?(dt.tokens=Je.sequences.tolist()[0],dt.token_timestamps=Je.token_timestamps.tolist()[0].map(Ve=>(0,h.round)(Ve,2))):dt.tokens=Je[0].tolist(),dt.stride=dt.stride.map(Ve=>Ve/R)}const[ke,Ne]=this.tokenizer._decode_asr(le,{time_precision:re,return_timestamps:Ye,force_full_sequences:A});D.push({text:ke,...Ne})}return se?D[0]:D}}class Se extends S{constructor(Te){super(Te)}async _call(Te,je={}){const Ye=Array.isArray(Te),et=await E(Te),{pixel_values:A}=await this.processor(et),$e=[];for(const Pe of A){Pe.dims=[1,...Pe.dims];const se=await this.model.generate({inputs:Pe,...je}),re=this.tokenizer.batch_decode(se,{skip_special_tokens:!0}).map(ye=>({generated_text:ye.trim()}));$e.push(re)}return Ye?$e:$e[0]}}class Xe extends S{constructor(Te){super(Te)}async _call(Te,{top_k:je=5}={}){const Ye=await E(Te),{pixel_values:et}=await this.processor(Ye),A=await this.model({pixel_values:et}),$e=this.model.config.id2label,Pe=[];for(const se of A.logits){const re=await(0,M.topk)(new M.Tensor("float32",(0,h.softmax)(se.data),se.dims),je),ye=re[0].tolist(),ee=re[1].tolist().map((D,ue)=>({label:$e?$e[D]:`LABEL_${D}`,score:ye[ue]}));Pe.push(ee)}return Array.isArray(Te)?Pe:Pe[0]}}class me extends S{constructor(Te){super(Te),this.subtasks_mapping={panoptic:"post_process_panoptic_segmentation",instance:"post_process_instance_segmentation",semantic:"post_process_semantic_segmentation"}}async _call(Te,{threshold:je=.5,mask_threshold:Ye=.5,overlap_mask_area_threshold:et=.8,label_ids_to_fuse:A=null,target_sizes:$e=null,subtask:Pe=null}={}){if(Array.isArray(Te)&&Te.length!==1)throw Error("Image segmentation pipeline currently only supports a batch size of 1.");const re=await E(Te),ye=re.map(Ne=>[Ne.height,Ne.width]),{pixel_values:R,pixel_mask:ee}=await this.processor(re),D=await this.model({pixel_values:R,pixel_mask:ee});let ue=null;if(Pe!==null)ue=this.subtasks_mapping[Pe];else for(let[Ne,dt]of Object.entries(this.subtasks_mapping))if(dt in this.processor.feature_extractor){ue=this.processor.feature_extractor[dt].bind(this.processor.feature_extractor),Pe=Ne;break}const le=this.model.config.id2label,ke=[];if(Pe==="panoptic"||Pe==="instance"){const Ne=ue(D,je,Ye,et,A,$e??ye)[0],dt=Ne.segmentation;for(const Je of Ne.segments_info){const Ve=new Uint8ClampedArray(dt.data.length);for(let ve=0;ve<dt.data.length;++ve)dt.data[ve]===Je.id&&(Ve[ve]=255);const Z=new y.RawImage(Ve,dt.dims[1],dt.dims[0],1);ke.push({score:Je.score,label:le[Je.label_id],mask:Z})}}else if(Pe==="semantic"){const{segmentation:Ne,labels:dt}=ue(D,$e??ye)[0];for(const Je of dt){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 y.RawImage(Ve,Ne.dims[1],Ne.dims[0],1);ke.push({score:null,label:le[Je],mask:Z})}}else throw Error(`Subtask ${Pe} not supported.`);return ke}}class X extends S{constructor(Te){super(Te)}async _call(Te,je,{hypothesis_template:Ye="This is a photo of {}"}={}){const et=Array.isArray(Te),A=await E(Te),$e=je.map(ee=>Ye.replace("{}",ee)),Pe=this.tokenizer($e,{padding:this.model.config.model_type==="siglip"?"max_length":!0,truncation:!0}),{pixel_values:se}=await this.processor(A),re=await this.model({...Pe,pixel_values:se}),ye=this.model.config.model_type==="siglip"?ee=>ee.sigmoid().data:ee=>(0,h.softmax)(ee.data),R=[];for(const ee of re.logits_per_image){const ue=[...ye(ee)].map((le,ke)=>({score:le,label:je[ke]}));ue.sort((le,ke)=>ke.score-le.score),R.push(ue)}return et?R:R[0]}}class ie extends S{constructor(Te){super(Te)}async _call(Te,{threshold:je=.9,percentage:Ye=!1}={}){const et=Array.isArray(Te);if(et&&Te.length!==1)throw Error("Object detection pipeline currently only supports a batch size of 1.");const A=await E(Te),$e=Ye?null:A.map(D=>[D.height,D.width]),{pixel_values:Pe,pixel_mask:se}=await this.processor(A),re=await this.model({pixel_values:Pe,pixel_mask:se}),ye=this.processor.feature_extractor.post_process_object_detection(re,je,$e),R=this.model.config.id2label,ee=ye.map(D=>D.boxes.map((ue,le)=>({score:D.scores[le],label:R[D.classes[le]],box:O(ue,!Ye)})));return et?ee:ee[0]}}class Me extends S{constructor(Te){super(Te)}async _call(Te,je,{threshold:Ye=.1,top_k:et=null,percentage:A=!1}={}){const $e=Array.isArray(Te),Pe=await E(Te),se=this.tokenizer(je,{padding:!0,truncation:!0}),re=await this.processor(Pe),ye=[];for(let R=0;R<Pe.length;++R){const ee=Pe[R],D=A?null:[[ee.height,ee.width]],ue=re.pixel_values[R].unsqueeze_(0),le=await this.model({...se,pixel_values:ue}),ke=this.processor.feature_extractor.post_process_object_detection(le,Ye,D,!0)[0];let Ne=ke.boxes.map((dt,Je)=>({score:ke.scores[Je],label:je[ke.classes[Je]],box:O(dt,!A)})).sort((dt,Je)=>Je.score-dt.score);et!==null&&(Ne=Ne.slice(0,et)),ye.push(Ne)}return $e?ye:ye[0]}}class Q extends S{constructor(Te){super(Te)}async _call(Te,je,Ye={}){throw new Error("This pipeline is not yet supported in Transformers.js v3.")}}class ge extends S{constructor(je){super(je);He(this,"DEFAULT_VOCODER_ID","Xenova/speecht5_hifigan");this.vocoder=je.vocoder??null}async _call(je,{speaker_embeddings:Ye=null}={}){return this.processor?this._call_text_to_spectrogram(je,{speaker_embeddings:Ye}):this._call_text_to_waveform(je)}async _call_text_to_waveform(je){const Ye=this.tokenizer(je,{padding:!0,truncation:!0}),{waveform:et}=await this.model(Ye),A=this.model.config.sampling_rate;return{audio:et.data,sampling_rate:A}}async _call_text_to_spectrogram(je,{speaker_embeddings:Ye}){if(this.vocoder||(console.log("No vocoder specified, using default HifiGan vocoder."),this.vocoder=await a.AutoModel.from_pretrained(this.DEFAULT_VOCODER_ID,{dtype:"fp32"})),(typeof Ye=="string"||Ye instanceof URL)&&(Ye=new Float32Array(await(await fetch(Ye)).arrayBuffer())),Ye instanceof Float32Array)Ye=new M.Tensor("float32",Ye,[1,Ye.length]);else if(!(Ye instanceof M.Tensor))throw new Error("Speaker embeddings must be a `Tensor`, `Float32Array`, `string`, or `URL`.");const{input_ids:et}=this.tokenizer(je,{padding:!0,truncation:!0}),{waveform:A}=await this.model.generate_speech(et,Ye,{vocoder:this.vocoder}),$e=this.processor.feature_extractor.config.sampling_rate;return{audio:A.data,sampling_rate:$e}}}class Ke extends S{constructor(Te){super(Te)}async _call(Te){const je=await E(Te),Ye=await this.processor(je),et=await this.model(Ye),A=[];for(const $e of et.reconstruction){const Pe=$e.squeeze().clamp_(0,1).mul_(255).round_().to("uint8");A.push(y.RawImage.fromTensor(Pe))}return A.length>1?A:A[0]}}class Le extends S{constructor(Te){super(Te)}async _call(Te){const je=await E(Te),Ye=await this.processor(je),{predicted_depth:et}=await this.model(Ye),A=[];for(let $e=0;$e<je.length;++$e){const Pe=(0,M.interpolate)(et[$e],je[$e].size.reverse(),"bilinear",!1),se=Pe.mul_(255/(0,h.max)(Pe.data)[0]).to("uint8");A.push({predicted_depth:et[$e],depth:y.RawImage.fromTensor(se)})}return A.length>1?A:A[0]}}const Be=Object.freeze({"text-classification":{tokenizer:o.AutoTokenizer,pipeline:C,model:a.AutoModelForSequenceClassification,default:{model:"Xenova/distilbert-base-uncased-finetuned-sst-2-english"},type:"text"},"token-classification":{tokenizer:o.AutoTokenizer,pipeline:w,model:a.AutoModelForTokenClassification,default:{model:"Xenova/bert-base-multilingual-cased-ner-hrl"},type:"text"},"question-answering":{tokenizer:o.AutoTokenizer,pipeline:b,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:z,model:a.AutoModelForSeq2SeqLM,default:{model:"Xenova/distilbart-cnn-6-6"},type:"text"},translation:{tokenizer:o.AutoTokenizer,pipeline:B,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:N,model:a.AutoModelForCausalLM,default:{model:"Xenova/gpt2"},type:"text"},"zero-shot-classification":{tokenizer:o.AutoTokenizer,pipeline:ae,model:a.AutoModelForSequenceClassification,default:{model:"Xenova/distilbert-base-uncased-mnli"},type:"text"},"audio-classification":{pipeline:Y,model:a.AutoModelForAudioClassification,processor:l.AutoProcessor,default:{model:"Xenova/wav2vec2-base-superb-ks"},type:"audio"},"zero-shot-audio-classification":{tokenizer:o.AutoTokenizer,pipeline:_e,model:a.AutoModel,processor:l.AutoProcessor,default:{model:"Xenova/clap-htsat-unfused"},type:"multimodal"},"automatic-speech-recognition":{tokenizer:o.AutoTokenizer,pipeline:L,model:[a.AutoModelForSpeechSeq2Seq,a.AutoModelForCTC],processor:l.AutoProcessor,default:{model:"Xenova/whisper-tiny.en"},type:"multimodal"},"text-to-audio":{tokenizer:o.AutoTokenizer,pipeline:ge,model:[a.AutoModelForTextToWaveform,a.AutoModelForTextToSpectrogram],processor:[l.AutoProcessor,null],default:{model:"Xenova/speecht5_tts"},type:"text"},"image-to-text":{tokenizer:o.AutoTokenizer,pipeline:Se,model:a.AutoModelForVision2Seq,processor:l.AutoProcessor,default:{model:"Xenova/vit-gpt2-image-captioning"},type:"multimodal"},"image-classification":{pipeline:Xe,model:a.AutoModelForImageClassification,processor:l.AutoProcessor,default:{model:"Xenova/vit-base-patch16-224"},type:"multimodal"},"image-segmentation":{pipeline:me,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:X,model:a.AutoModel,processor:l.AutoProcessor,default:{model:"Xenova/clip-vit-base-patch32"},type:"multimodal"},"object-detection":{pipeline:ie,model:a.AutoModelForObjectDetection,processor:l.AutoProcessor,default:{model:"Xenova/detr-resnet-50"},type:"multimodal"},"zero-shot-object-detection":{tokenizer:o.AutoTokenizer,pipeline:Me,model:a.AutoModelForZeroShotObjectDetection,processor:l.AutoProcessor,default:{model:"Xenova/owlvit-base-patch32"},type:"multimodal"},"document-question-answering":{tokenizer:o.AutoTokenizer,pipeline:Q,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:Le,model:a.AutoModelForDepthEstimation,processor:l.AutoProcessor,default:{model:"Xenova/dpt-large"},type:"image"},"feature-extraction":{tokenizer:o.AutoTokenizer,pipeline:ce,model:a.AutoModel,default:{model:"Xenova/all-MiniLM-L6-v2"},type:"text"},"image-feature-extraction":{processor:l.AutoProcessor,pipeline:xe,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 st(Ge,Te=null,{progress_callback:je=null,config:Ye=null,cache_dir:et=null,local_files_only:A=!1,revision:$e="main",device:Pe=null,dtype:se=null,model_file_name:re=null,session_options:ye={}}={}){Ge=We[Ge]??Ge;const R=Be[Ge.split("_",1)[0]];if(!R)throw Error(`Unsupported pipeline: ${Ge}. Must be one of [${Object.keys(Be)}]`);Te||(Te=R.default.model,console.log(`No model specified. Using default model: "${Te}".`));const ee={progress_callback:je,config:Ye,cache_dir:et,local_files_only:A,revision:$e,device:Pe,dtype:se,model_file_name:re,session_options:ye},D=new Map([["tokenizer",R.tokenizer],["model",R.model],["processor",R.processor]]),ue=await pt(D,Te,ee);ue.task=Ge,(0,_.dispatchCallback)(je,{status:"ready",task:Ge,model:Te});const le=R.pipeline;return new le(ue)}async function pt(Ge,Te,je){const Ye=Object.create(null),et=[];for(let[A,$e]of Ge.entries()){if(!$e)continue;let Pe;Array.isArray($e)?Pe=new Promise(async(se,re)=>{var R,ee;let ye;for(let D of $e){if(D===null){se(null);return}try{se(await D.from_pretrained(Te,je));return}catch(ue){if((R=ue.message)!=null&&R.includes("Unsupported model type"))ye=ue;else if((ee=ue.message)!=null&&ee.includes("Could not locate file"))ye=ue;else{re(ue);return}}}re(ye)}):Pe=$e.from_pretrained(Te,je),Ye[A]=Pe,et.push(Pe)}await Promise.all(et);for(let[A,$e]of Object.entries(Ye))Ye[A]=await $e;return Ye}},"./src/processors.js":(e,t,r)=>{r.r(t),r.d(t,{ASTFeatureExtractor:()=>$e,AutoProcessor:()=>Je,BeitFeatureExtractor:()=>Le,BitImageProcessor:()=>I,CLIPFeatureExtractor:()=>z,CLIPImageProcessor:()=>B,ChineseCLIPFeatureExtractor:()=>j,ClapFeatureExtractor:()=>Pe,ConvNextFeatureExtractor:()=>ae,ConvNextImageProcessor:()=>ce,DPTFeatureExtractor:()=>w,DPTImageProcessor:()=>b,DeiTFeatureExtractor:()=>Ke,DetrFeatureExtractor:()=>st,DonutFeatureExtractor:()=>Be,EfficientNetImageProcessor:()=>_e,FeatureExtractor:()=>O,Florence2Processor:()=>dt,GLPNFeatureExtractor:()=>U,ImageFeatureExtractor:()=>S,MobileNetV1FeatureExtractor:()=>L,MobileNetV2FeatureExtractor:()=>Se,MobileNetV3FeatureExtractor:()=>Xe,MobileNetV4FeatureExtractor:()=>me,MobileViTFeatureExtractor:()=>X,MobileViTImageProcessor:()=>ie,NougatImageProcessor:()=>We,OwlViTFeatureExtractor:()=>Me,OwlViTProcessor:()=>Ne,Owlv2ImageProcessor:()=>Q,Processor:()=>R,PyAnnoteFeatureExtractor:()=>se,PyAnnoteProcessor:()=>le,RTDetrImageProcessor:()=>ge,SamImageProcessor:()=>Ge,SamProcessor:()=>ee,SeamlessM4TFeatureExtractor:()=>A,SegformerFeatureExtractor:()=>C,SiglipImageProcessor:()=>N,SpeechT5FeatureExtractor:()=>ye,SpeechT5Processor:()=>ke,Swin2SRImageProcessor:()=>Te,ViTFeatureExtractor:()=>xe,ViTImageProcessor:()=>Y,VitMatteImageProcessor:()=>je,Wav2Vec2FeatureExtractor:()=>et,Wav2Vec2ProcessorWithLM:()=>ue,WeSpeakerFeatureExtractor:()=>re,WhisperFeatureExtractor:()=>Ye,WhisperProcessor:()=>D,YolosFeatureExtractor:()=>pt});var o=r("./src/utils/generic.js"),a=r("./src/utils/core.js"),l=r("./src/utils/hub.js"),p=r("./src/utils/maths.js"),_=r("./src/utils/tensor.js");r("./src/utils/image.js");var h=r("./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 qe=Ve.logits,Qe=Ve.pred_boxes,[tt,ft,ht]=qe.dims;if(ve!==null&&ve.length!==tt)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let Tt=[];for(let bt=0;bt<tt;++bt){let Et=ve!==null?ve[bt]:null,Lt={boxes:[],classes:[],scores:[]},at=qe[bt],Ot=Qe[bt];for(let Ut=0;Ut<ft;++Ut){let Xt=at[Ut],Yt=[],rr;if(Re){rr=Xt.sigmoid().data;for(let Ht=0;Ht<rr.length;++Ht)rr[Ht]>Z&&Yt.push(Ht)}else{let Ht=(0,p.max)(Xt.data)[1];if(Ht===ht-1||(rr=(0,p.softmax)(Xt.data),rr[Ht]<Z))continue;Yt.push(Ht)}for(const Ht of Yt){let Pr=Ot[Ut].data;Pr=g(Pr),Et!==null&&(Pr=Pr.map((Yr,$r)=>Yr*Et[($r+1)%2])),Lt.boxes.push(Pr),Lt.classes.push(Ht),Lt.scores.push(rr[Ht])}}Tt.push(Lt)}return Tt}function y(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 E(Ve,Z,ve=0,Re=null){const qe=Ve/Z;let Qe=(0,p.bankers_round)(qe)*Z;return Re!==null&&Qe>Re&&(Qe=Math.floor(qe)*Z),Qe<ve&&(Qe=Math.ceil(qe)*Z),Qe}function T([Ve,Z],ve){return[Math.max(Math.floor(Ve/ve),1)*ve,Math.max(Math.floor(Z/ve),1)*ve]}class O extends o.Callable{constructor(Z){super(),this.config=Z}}class S extends O{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 qe=Z.height,Qe=Z.width,tt=ve.height,ft=ve.width;let ht=Math.min(qe,tt),Tt=Math.min(Qe,ft);return ht===qe&&Tt===Qe?Z:(qe>Qe?Tt=Math.floor(Qe*ht/qe):Qe>qe&&(ht=Math.floor(qe*Tt/Qe)),await Z.resize(Tt,ht,{resample:Re}))}async crop_margin(Z,ve=200){const Re=Z.clone().grayscale(),qe=(0,p.min)(Re.data)[0],tt=(0,p.max)(Re.data)[0]-qe;if(tt===0)return Z;const ft=ve/255;let ht=Re.width,Tt=Re.height,bt=0,Et=0;const Lt=Re.data;for(let at=0;at<Re.height;++at){const Ot=at*Re.width;for(let Ut=0;Ut<Re.width;++Ut)(Lt[Ot+Ut]-qe)/tt<ft&&(ht=Math.min(ht,Ut),Tt=Math.min(Tt,at),bt=Math.max(bt,Ut),Et=Math.max(Et,at))}return Z=await Z.crop([ht,Tt,bt,Et]),Z}pad_image(Z,ve,Re,{mode:qe="constant",center:Qe=!1,constant_values:tt=0}={}){const[ft,ht,Tt]=ve;let bt,Et;if(typeof Re=="number"?(bt=Re,Et=Re):(bt=Re.width,Et=Re.height),bt!==ht||Et!==ft){const Lt=new Float32Array(bt*Et*Tt);if(Array.isArray(tt))for(let Ut=0;Ut<Lt.length;++Ut)Lt[Ut]=tt[Ut%Tt];else tt!==0&&Lt.fill(tt);const[at,Ot]=Qe?[Math.floor((bt-ht)/2),Math.floor((Et-ft)/2)]:[0,0];for(let Ut=0;Ut<ft;++Ut){const Xt=(Ut+Ot)*bt,Yt=Ut*ht;for(let rr=0;rr<ht;++rr){const Ht=(Xt+rr+at)*Tt,Pr=(Yt+rr)*Tt;for(let Yr=0;Yr<Tt;++Yr)Lt[Ht+Yr]=Z[Pr+Yr]}}if(qe==="symmetric"){if(Qe)throw new Error("`center` padding is not supported when `mode` is set to `symmetric`.");const Ut=ft-1,Xt=ht-1;for(let Yt=0;Yt<Et;++Yt){const rr=Yt*bt,Ht=(0,a.calculateReflectOffset)(Yt,Ut)*ht;for(let Pr=0;Pr<bt;++Pr){if(Yt<ft&&Pr<ht)continue;const Yr=(rr+Pr)*Tt,$r=(Ht+(0,a.calculateReflectOffset)(Pr,Xt))*Tt;for(let mt=0;mt<Tt;++mt)Lt[Yr+mt]=Z[$r+mt]}}}Z=Lt,ve=[Et,bt,Tt]}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,qe]=Z.size;let Qe,tt;if(this.do_thumbnail){const{height:ft,width:ht}=ve;Qe=Math.min(ft,ht)}else Number.isInteger(ve)?(Qe=ve,tt=this.config.max_size??Qe):ve!==void 0&&(Qe=ve.shortest_edge,tt=ve.longest_edge);if(Qe!==void 0||tt!==void 0){const ft=Qe===void 0?1:Math.max(Qe/Re,Qe/qe),ht=Re*ft,Tt=qe*ft,bt=tt===void 0?1:Math.min(tt/ht,tt/Tt);let Et=Math.floor(Number((ht*bt).toFixed(2))),Lt=Math.floor(Number((Tt*bt).toFixed(2)));return this.size_divisibility!==void 0&&([Et,Lt]=T([Et,Lt],this.size_divisibility)),[Et,Lt]}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 Tt=ht/qe,bt=ft/Re;Math.abs(1-bt)<Math.abs(1-Tt)?Tt=bt:bt=Tt,ht=E(Tt*qe,this.config.ensure_multiple_of),ft=E(bt*Re,this.config.ensure_multiple_of)}return[ft,ht]}else{if(this.size_divisibility!==void 0)return T([Re,qe],this.size_divisibility);throw new Error(`Could not resize image due to unsupported \`this.size\` option in config: ${JSON.stringify(ve)}`)}}async resize(Z){const[ve,Re]=this.get_resize_output_image_size(Z,this.size);return await Z.resize(ve,Re,{resample:this.resample})}async preprocess(Z,{do_normalize:ve=null,do_pad:Re=null,do_convert_rgb:qe=null,do_convert_grayscale:Qe=null,do_flip_channel_order:tt=null}={}){this.do_crop_margin&&(Z=await this.crop_margin(Z));const[ft,ht]=Z.size;if(qe??this.do_convert_rgb?Z=Z.rgb():Qe&&(Z=Z.grayscale()),this.do_resize&&(Z=await this.resize(Z)),this.do_thumbnail&&(Z=await this.thumbnail(Z,this.size,this.resample)),this.do_center_crop){let at,Ot;Number.isInteger(this.crop_size)?(at=this.crop_size,Ot=this.crop_size):(at=this.crop_size.width,Ot=this.crop_size.height),Z=await Z.center_crop(at,Ot)}const Tt=[Z.height,Z.width];let bt=Float32Array.from(Z.data),Et=[Z.height,Z.width,Z.channels];if(this.do_rescale&&this.rescale(bt),ve??this.do_normalize){let at=this.image_mean;Array.isArray(this.image_mean)||(at=new Array(Z.channels).fill(at));let Ot=this.image_std;if(Array.isArray(this.image_std)||(Ot=new Array(Z.channels).fill(at)),at.length!==Z.channels||Ot.length!==Z.channels)throw new Error(`When set to arrays, the length of \`image_mean\` (${at.length}) and \`image_std\` (${Ot.length}) must match the number of channels in the image (${Z.channels}).`);for(let Ut=0;Ut<bt.length;Ut+=Z.channels)for(let Xt=0;Xt<Z.channels;++Xt)bt[Ut+Xt]=(bt[Ut+Xt]-at[Xt])/Ot[Xt]}if(Re??this.do_pad){if(this.pad_size)[bt,Et]=this.pad_image(bt,[Z.height,Z.width,Z.channels],this.pad_size);else if(this.size_divisibility){const[at,Ot]=T([Et[1],Et[0]],this.size_divisibility);[bt,Et]=this.pad_image(bt,Et,{width:at,height:Ot})}}if(tt??this.do_flip_channel_order){if(Et[2]!==3)throw new Error("Flipping channel order is only supported for RGB images.");for(let at=0;at<bt.length;at+=3){const Ot=bt[at];bt[at]=bt[at+2],bt[at+2]=Ot}}const Lt=new _.Tensor("float32",bt,Et).permute(2,0,1);return{original_size:[ht,ft],reshaped_input_size:Tt,pixel_values:Lt}}async _call(Z,...ve){Array.isArray(Z)||(Z=[Z]);const Re=await Promise.all(Z.map(Qe=>this.preprocess(Qe)));return{pixel_values:(0,_.stack)(Re.map(Qe=>Qe.pixel_values),0),original_sizes:Re.map(Qe=>Qe.original_size),reshaped_input_sizes:Re.map(Qe=>Qe.reshaped_input_size)}}}class C extends S{post_process_semantic_segmentation(Z,ve=null){const Re=Z.logits,qe=Re.dims[0];if(ve!==null&&ve.length!==qe)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");const Qe=[];for(let tt=0;tt<qe;++tt){const ft=ve!==null?ve[tt]:null;let ht=Re[tt];ft!==null&&(ht=(0,_.interpolate)(ht,ft,"bilinear",!1));const[Tt,bt]=ft??ht.dims.slice(-2),Et=new _.Tensor("int32",new Int32Array(Tt*bt),[Tt,bt]),Lt=ht[0].data,at=Et.data;for(let Yt=1;Yt<ht.dims[0];++Yt){const rr=ht[Yt].data;for(let Ht=0;Ht<rr.length;++Ht)rr[Ht]>Lt[Ht]&&(Lt[Ht]=rr[Ht],at[Ht]=Yt)}const Ot=new Array(ht.dims[0]),Ut=Et.data;for(let Yt=0;Yt<Ut.length;++Yt){const rr=Ut[Yt];Ot[rr]=rr}const Xt=Ot.filter(Yt=>Yt!==void 0);Qe.push({segmentation:Et,labels:Xt})}return Qe}}class w extends S{}class b extends w{}class I extends S{}class U extends S{}class z extends S{}class B extends z{}class j extends S{}class N extends S{}class ae 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 qe=Math.floor(ve/this.crop_pct),[Qe,tt]=this.get_resize_output_image_size(Z,{shortest_edge:qe});Z=await Z.resize(Qe,tt,{resample:this.resample}),Z=await Z.center_crop(ve,ve)}else Z=await Z.resize(ve,ve,{resample:this.resample});return Z}}class ce extends ae{}class xe extends S{}class Y extends S{}class _e 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 L extends S{}class Se extends S{}class Xe extends S{}class me extends S{}class X extends S{}class ie extends X{}class Me extends S{post_process_object_detection(...Z){return M(...Z)}}class Q extends Me{}class ge extends S{post_process_object_detection(...Z){return M(...Z)}}class Ke extends S{}class Le extends S{}class Be extends S{pad_image(Z,ve,Re,qe={}){const[Qe,tt,ft]=ve;let ht=this.image_mean;Array.isArray(this.image_mean)||(ht=new Array(ft).fill(ht));let Tt=this.image_std;Array.isArray(Tt)||(Tt=new Array(ft).fill(ht));const bt=ht.map((Et,Lt)=>-Et/Tt[Lt]);return super.pad_image(Z,ve,Re,{center:!0,constant_values:bt,...qe})}}class We extends Be{}class st extends S{async _call(Z){const ve=await super._call(Z),Re=[ve.pixel_values.dims[0],64,64],qe=new _.Tensor("int64",new BigInt64Array(Re.reduce((Qe,tt)=>Qe*tt)).fill(1n),Re);return{...ve,pixel_mask:qe}}post_process_object_detection(...Z){return M(...Z)}remove_low_and_no_objects(Z,ve,Re,qe){let Qe=[],tt=[],ft=[];for(let ht=0;ht<Z.dims[0];++ht){let Tt=Z[ht],bt=ve[ht],Et=(0,p.max)(Tt.data)[1];if(Et===qe)continue;let at=(0,p.softmax)(Tt.data)[Et];at>Re&&(Qe.push(bt),tt.push(at),ft.push(Et))}return[Qe,tt,ft]}check_segment_validity(Z,ve,Re,qe=.5,Qe=.8){let tt=[],ft=0,ht=0;const Tt=ve[Re].data;for(let Et=0;Et<Z.length;++Et)Z[Et]===Re&&(tt.push(Et),++ft),Tt[Et]>=qe&&++ht;let bt=ft>0&&ht>0;return bt&&(bt=ft/ht>Qe),[bt,tt]}compute_segments(Z,ve,Re,qe,Qe,tt=null,ft=null){let[ht,Tt]=ft??Z[0].dims,bt=new _.Tensor("int32",new Int32Array(ht*Tt),[ht,Tt]),Et=[];if(ft!==null)for(let Xt=0;Xt<Z.length;++Xt)Z[Xt]=(0,_.interpolate)(Z[Xt],ft,"bilinear",!1);let Lt=new Int32Array(Z[0].data.length),at=new Float32Array(Z[0].data.length);for(let Xt=0;Xt<Z.length;++Xt){let Yt=ve[Xt];const rr=Z[Xt].data;for(let Ht=0;Ht<rr.length;++Ht)rr[Ht]*=Yt,rr[Ht]>at[Ht]&&(Lt[Ht]=Xt,at[Ht]=rr[Ht])}let Ot=0;const Ut=bt.data;for(let Xt=0;Xt<Re.length;++Xt){let Yt=Re[Xt],[rr,Ht]=this.check_segment_validity(Lt,Z,Xt,qe,Qe);if(rr){++Ot;for(let Pr of Ht)Ut[Pr]=Ot;Et.push({id:Ot,label_id:Yt,score:ve[Xt]})}}return[bt,Et]}post_process_panoptic_segmentation(Z,ve=.5,Re=.5,qe=.8,Qe=null,tt=null){Qe===null&&(console.warn("`label_ids_to_fuse` unset. No instance will be fused."),Qe=new Set);const ft=Z.logits,Tt=Z.pred_masks.sigmoid();let[bt,Et,Lt]=ft.dims;if(Lt-=1,tt!==null&&tt.length!==bt)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<bt;++Ot){let Ut=tt!==null?tt[Ot]:null,Xt=ft[Ot],Yt=Tt[Ot],[rr,Ht,Pr]=this.remove_low_and_no_objects(Xt,Yt,ve,Lt);if(Pr.length===0){let[mt,$t]=Ut??Yt.dims.slice(-2),Bt=new _.Tensor("int32",new Int32Array(mt*$t).fill(-1),[mt,$t]);at.push({segmentation:Bt,segments_info:[]});continue}let[Yr,$r]=this.compute_segments(rr,Ht,Pr,Re,qe,Qe,Ut);at.push({segmentation:Yr,segments_info:$r})}return at}post_process_instance_segmentation(){throw Error("Not implemented yet")}}class pt extends S{post_process_object_detection(...Z){return M(...Z)}}class Ge extends S{reshape_input_points(Z,ve,Re,qe=!1){Z=structuredClone(Z);let Qe=(0,a.calculateDimensions)(Z);if(Qe.length===3)qe||(Qe=[1,...Qe]),Z=[Z];else if(Qe.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 tt=0;tt<Z.length;++tt){let ft=ve[tt],ht=Re[tt],Tt=[ht[0]/ft[0],ht[1]/ft[1]];for(let bt=0;bt<Z[tt].length;++bt)for(let Et=0;Et<Z[tt][bt].length;++Et)for(let Lt=0;Lt<Z[tt][bt][Et].length;++Lt)Z[tt][bt][Et][Lt]*=Tt[Lt%2]}return new _.Tensor("float32",Float32Array.from(Z.flat(1/0)),Qe)}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((qe,Qe)=>qe!==ve.dims[Qe]))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:qe=null}={}){const Qe=await super._call(Z);if(ve&&(Qe.input_points=this.reshape_input_points(ve,Qe.original_sizes,Qe.reshaped_input_sizes)),Re){if(!Qe.input_points)throw Error("`input_points` must be provided if `input_labels` are provided.");Qe.input_labels=this.add_input_labels(Re,Qe.input_points)}return qe&&(Qe.input_boxes=this.reshape_input_points(qe,Qe.original_sizes,Qe.reshaped_input_sizes,!0)),Qe}async post_process_masks(Z,ve,Re,{mask_threshold:qe=0,binarize:Qe=!0,pad_size:tt=null}={}){const ft=[];tt=tt??this.pad_size;const ht=[tt.height,tt.width];for(let Tt=0;Tt<ve.length;++Tt){const bt=ve[Tt],Et=Re[Tt];let Lt=await(0,_.interpolate_4d)(Z[Tt],{mode:"bilinear",size:ht});if(Lt=Lt.slice(null,null,[0,Et[0]],[0,Et[1]]),Lt=await(0,_.interpolate_4d)(Lt,{mode:"bilinear",size:bt}),Qe){const at=Lt.data,Ot=new Uint8Array(at.length);for(let Ut=0;Ut<at.length;++Ut)at[Ut]>qe&&(Ot[Ut]=1);Lt=new _.Tensor("bool",Ot,Lt.dims)}ft.push(Lt)}return ft}generate_crop_boxes(Z,ve,{crop_n_layers:Re=0,overlap_ratio:qe=512/1500,points_per_crop:Qe=32,crop_n_points_downscale_factor:tt=1}={}){}}class Te extends S{pad_image(Z,ve,Re,qe={}){const[Qe,tt,ft]=ve;return super.pad_image(Z,ve,{width:tt+(Re-tt%Re)%Re,height:Qe+(Re-Qe%Re)%Re},{mode:"symmetric",center:!1,constant_values:-1,...qe})}}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(tt=>this.preprocess(tt))),qe=await Promise.all(ve.map(tt=>this.preprocess(tt,{do_normalize:!1,do_convert_rgb:!1,do_convert_grayscale:!0})));return{pixel_values:(0,_.stack)(Re.map((tt,ft)=>(0,_.cat)([tt.pixel_values,qe[ft].pixel_values],0)),0),original_sizes:Re.map(tt=>tt.original_size),reshaped_input_sizes:Re.map(tt=>tt.reshaped_input_size)}}}class Ye extends O{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,qe=(0,p.max)(Re)[0];for(let Qe=0;Qe<Re.length;++Qe)Re[Qe]=(Math.max(Re[Qe],qe-8)+4)/4;return ve}async _call(Z){y(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 et extends O{_zero_mean_unit_var_norm(Z){const Re=Z.reduce((Qe,tt)=>Qe+tt,0)/Z.length,qe=Z.reduce((Qe,tt)=>Qe+(tt-Re)**2,0)/Z.length;return Z.map(Qe=>(Qe-Re)/Math.sqrt(qe+1e-7))}async _call(Z){y(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 O{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 qe=0;qe<Re.length;++qe)Re[qe].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:qe=!0,return_attention_mask:Qe=!0}={}){y(Z,"SeamlessM4TFeatureExtractor");let tt=await this._extract_fbank_features(Z,this.config.max_length);if(qe){const[Ot,Ut]=tt.dims,Xt=tt.data;for(let Yt=0;Yt<Ut;++Yt){let rr=0;for(let $r=0;$r<Ot;++$r)rr+=Xt[$r*Ut+Yt];const Ht=rr/Ot;let Pr=0;for(let $r=0;$r<Ot;++$r)Pr+=(Xt[$r*Ut+Yt]-Ht)**2;Pr/=Ot-1;const Yr=Math.sqrt(Pr+1e-7);for(let $r=0;$r<Ot;++$r){const mt=$r*Ut+Yt;Xt[mt]=(Xt[mt]-Ht)/Yr}}}let ft;if(ve){const[Ot,Ut]=tt.dims,Xt=tt.data,Yt=Ot%Re;if(Yt>0){const rr=new Float32Array(Ut*(Ot+Yt));rr.set(Xt),rr.fill(this.config.padding_value,Xt.length);const Ht=Ot+Yt;tt=new _.Tensor(tt.type,rr,[Ht,Ut]),Qe&&(ft=new _.Tensor("int64",new BigInt64Array(Ht),[1,Ht]),ft.data.fill(1n,0,Ot))}}const[ht,Tt]=tt.dims,bt=this.config.stride;if(ht%bt!==0)throw new Error(`The number of frames (${ht}) must be a multiple of the stride (${bt}).`);const Lt=tt.view(1,Math.floor(ht/bt),Tt*bt),at={input_features:Lt};if(Qe){const Ot=Lt.dims[1],Ut=new BigInt64Array(Ot);if(ft){const Xt=ft.data;for(let Yt=1,rr=0;Yt<ht;Yt+=bt,++rr)Ut[rr]=Xt[Yt]}else Ut.fill(1n);at.attention_mask=new _.Tensor("int64",Ut,[1,Ot])}return at}}class $e extends O{constructor(Z){super(Z);const ve=this.config.sampling_rate,Re=(0,h.mel_filter_bank)(256,this.config.num_mel_bins,20,Math.floor(ve/2),ve,null,"kaldi",!0);for(let qe=0;qe<Re.length;++qe)Re[qe].push(0);this.mel_filters=Re,this.window=(0,h.window_function)(400,"hann",{periodic:!1}),this.mean=this.config.mean,this.std=this.config.std}async _extract_fbank_features(Z,ve){return(0,h.spectrogram)(Z,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,max_num_frames:ve,transpose:!0})}async _call(Z){y(Z,"ASTFeatureExtractor");const ve=await this._extract_fbank_features(Z,this.config.max_length);if(this.config.do_normalize){const Re=this.std*2,qe=ve.data;for(let Qe=0;Qe<qe.length;++Qe)qe[Qe]=(qe[Qe]-this.mean)/Re}return{input_values:ve.unsqueeze_(0)}}}class Pe extends O{constructor(Z){super(Z),this.mel_filters=(0,h.mel_filter_bank)(this.config.nb_frequency_bins,this.config.feature_size,this.config.frequency_min,this.config.frequency_max,this.config.sampling_rate,null,"htk"),this.mel_filters_slaney=(0,h.mel_filter_bank)(this.config.nb_frequency_bins,this.config.feature_size,this.config.frequency_min,this.config.frequency_max,this.config.sampling_rate,"slaney","slaney"),this.window=(0,h.window_function)(this.config.fft_window_size,"hann")}async _get_input_mel(Z,ve,Re,qe){let Qe;const tt=Z.length-ve;if(tt>0)if(Re==="rand_trunc"){const ft=Math.floor(Math.random()*(tt+1));Z=Z.subarray(ft,ft+ve),Qe=await this._extract_fbank_features(Z,this.mel_filters_slaney,this.config.nb_max_samples)}else throw new Error(`Truncation strategy "${Re}" not implemented`);else{if(tt<0){let ft=new Float64Array(ve);if(ft.set(Z),qe==="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(qe==="repeatpad")for(let ht=Z.length;ht<-tt;ht+=Z.length)ft.set(Z,ht);Z=ft}if(Re==="fusion")throw new Error(`Truncation strategy "${Re}" not implemented`);Qe=await this._extract_fbank_features(Z,this.mel_filters_slaney,this.config.nb_max_samples)}return Qe.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 y(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 O{async _call(Z){y(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,qe=[];for(const Qe of Z.tolist()){const tt=[];let ft=-1;for(let ht=0;ht<Qe.length;++ht){const Tt=(0,p.softmax)(Qe[ht]),[bt,Et]=(0,p.max)(Tt),[Lt,at]=[ht,ht+1];Et!==ft?(ft=Et,tt.push({id:Et,start:Lt,end:at,score:bt})):(tt.at(-1).end=at,tt.at(-1).score+=bt)}qe.push(tt.map(({id:ht,start:Tt,end:bt,score:Et})=>({id:ht,start:Tt*Re,end:bt*Re,confidence:Et/(bt-Tt)})))}return qe}}class re extends O{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 qe=0;qe<Re.length;++qe)Re[qe].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){y(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,qe=ve.data,[Qe,tt,ft]=ve.dims;for(let ht=0;ht<Qe;++ht){const Tt=ht*tt*ft,bt=ht*ft;for(let Et=0;Et<tt;++Et){const Lt=Tt+Et*ft;for(let at=0;at<ft;++at)qe[Lt+at]-=Re[bt+at]}}}return{input_features:ve}}}class ye extends O{}class R extends o.Callable{constructor(Z){super(),this.feature_extractor=Z}async _call(Z,...ve){return await this.feature_extractor(Z,...ve)}}class ee extends R{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 D extends R{async _call(Z){return await this.feature_extractor(Z)}}class ue extends R{async _call(Z){return await this.feature_extractor(Z)}}class le extends R{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 R{async _call(Z){return await this.feature_extractor(Z)}}class Ne extends R{}class dt extends R{constructor(Z){super(Z);const{tasks_answer_post_processing_type:ve,task_prompts_without_inputs:Re,task_prompts_with_input:qe}=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(qe??{})),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[qe,Qe]of this.task_prompts_with_input)if(Re.includes(qe)){ve.push(Qe.replaceAll("{input}",Re).replaceAll(qe,""));break}ve.length!==Z.length&&ve.push(Re)}return ve}post_process_generation(Z,ve,Re){const qe=this.tasks_answer_post_processing_type.get(ve)??"pure_text";Z=Z.replaceAll("<s>","").replaceAll("</s>","");let Qe;switch(qe){case"pure_text":Qe=Z;break;case"description_with_bboxes":case"bboxes":case"phrase_grounding":case"ocr":const tt=qe==="ocr"?"quad_boxes":"bboxes",ft=Z.matchAll(this.regexes[tt]),ht=[],Tt=[];for(const[bt,Et,...Lt]of ft)ht.push(Et?Et.trim():ht.at(-1)??""),Tt.push(Lt.map((at,Ot)=>(Number(at)+.5)/this.size_per_bin*Re[Ot%2]));Qe={labels:ht,[tt]:Tt};break;default:throw new Error(`Task "${ve}" (of type "${qe}") not yet implemented.`)}return{[ve]:Qe}}}class Je{static async from_pretrained(Z,{progress_callback:ve=null,config:Re=null,cache_dir:qe=null,local_files_only:Qe=!1,revision:tt="main"}={}){let ft=Re??await(0,l.getModelJSON)(Z,"preprocessor_config.json",!0,{progress_callback:ve,config:Re,cache_dir:qe,local_files_only:Qe,revision:tt}),ht=ft.feature_extractor_type??ft.image_processor_type,Tt=this.FEATURE_EXTRACTOR_CLASS_MAPPING[ht];if(!Tt)if(ft.size!==void 0)console.warn(`Feature extractor type "${ht}" not found, assuming ImageFeatureExtractor due to size parameter in config.`),Tt=S;else throw new Error(`Unknown Feature Extractor type: ${ht}`);let bt=this.PROCESSOR_CLASS_MAPPING[ft.processor_class]??R,Et=new Tt(ft);return new bt(Et)}}He(Je,"FEATURE_EXTRACTOR_CLASS_MAPPING",{ImageFeatureExtractor:S,WhisperFeatureExtractor:Ye,ViTFeatureExtractor:xe,MobileViTFeatureExtractor:X,MobileViTImageProcessor:ie,MobileNetV1FeatureExtractor:L,MobileNetV2FeatureExtractor:Se,MobileNetV3FeatureExtractor:Xe,MobileNetV4FeatureExtractor:me,OwlViTFeatureExtractor:Me,Owlv2ImageProcessor:Q,CLIPFeatureExtractor:z,CLIPImageProcessor:B,Florence2Processor:dt,ChineseCLIPFeatureExtractor:j,SiglipImageProcessor:N,ConvNextFeatureExtractor:ae,ConvNextImageProcessor:ce,SegformerFeatureExtractor:C,BitImageProcessor:I,DPTImageProcessor:b,DPTFeatureExtractor:w,GLPNFeatureExtractor:U,BeitFeatureExtractor:Le,DeiTFeatureExtractor:Ke,DetrFeatureExtractor:st,RTDetrImageProcessor:ge,YolosFeatureExtractor:pt,DonutFeatureExtractor:Be,NougatImageProcessor:We,EfficientNetImageProcessor:_e,ViTImageProcessor:Y,VitMatteImageProcessor:je,SamImageProcessor:Ge,Swin2SRImageProcessor:Te,Wav2Vec2FeatureExtractor:et,SeamlessM4TFeatureExtractor:A,SpeechT5FeatureExtractor:ye,ASTFeatureExtractor:$e,ClapFeatureExtractor:Pe,PyAnnoteFeatureExtractor:se,WeSpeakerFeatureExtractor:re}),He(Je,"PROCESSOR_CLASS_MAPPING",{WhisperProcessor:D,Wav2Vec2ProcessorWithLM:ue,PyAnnoteProcessor:le,SamProcessor:ee,SpeechT5Processor:ke,OwlViTProcessor:Ne,Florence2Processor:dt})},"./src/tokenizers.js":(e,t,r)=>{r.r(t),r.d(t,{AlbertTokenizer:()=>Ut,AutoTokenizer:()=>jn,BartTokenizer:()=>Gr,BertTokenizer:()=>Ot,BlenderbotSmallTokenizer:()=>Vo,BlenderbotTokenizer:()=>go,BloomTokenizer:()=>Dr,CLIPTokenizer:()=>Zt,CamembertTokenizer:()=>$t,CodeGenTokenizer:()=>mo,CodeLlamaTokenizer:()=>Cs,CohereTokenizer:()=>Vr,ConvBertTokenizer:()=>Yr,DebertaTokenizer:()=>rr,DebertaV2Tokenizer:()=>Ht,DistilBertTokenizer:()=>mt,ElectraTokenizer:()=>un,EsmTokenizer:()=>ji,FalconTokenizer:()=>Bo,GPT2Tokenizer:()=>Mi,GPTNeoXTokenizer:()=>No,GemmaTokenizer:()=>fo,Grok1Tokenizer:()=>fi,HerbertTokenizer:()=>Pr,LlamaTokenizer:()=>Ti,M2M100Tokenizer:()=>Ji,MBart50Tokenizer:()=>Kr,MBartTokenizer:()=>wn,MPNetTokenizer:()=>Ro,MarianTokenizer:()=>jo,MobileBertTokenizer:()=>Xt,NllbTokenizer:()=>Si,NougatTokenizer:()=>_o,PreTrainedTokenizer:()=>at,Qwen2Tokenizer:()=>Ps,RoFormerTokenizer:()=>$r,RobertaTokenizer:()=>pi,SiglipTokenizer:()=>eo,SpeechT5Tokenizer:()=>Wo,SqueezeBertTokenizer:()=>Yt,T5Tokenizer:()=>Bi,TokenizerModel:()=>xe,VitsTokenizer:()=>Go,Wav2Vec2CTCTokenizer:()=>Uo,WhisperTokenizer:()=>ho,XLMRobertaTokenizer:()=>Lo,XLMTokenizer:()=>Bt,is_chinese_char:()=>U});var o=r("./src/utils/generic.js"),a=r("./src/utils/core.js"),l=r("./src/utils/hub.js"),p=r("./src/utils/maths.js"),_=r("./src/utils/tensor.js"),h=r("./src/utils/data-structures.js"),g=r("./node_modules/@huggingface/jinja/dist/index.js"),M=r("./src/models/whisper/common_whisper.js"),y=r("./src/utils/constants.js");async function E(Ue,W){const pe=await Promise.all([(0,l.getModelJSON)(Ue,"tokenizer.json",!0,W),(0,l.getModelJSON)(Ue,"tokenizer_config.json",!0,W)]);return W.legacy!==null&&(pe[1].legacy=W.legacy),pe}function T(Ue,W){const pe=[];let Ce=0;for(const Fe of Ue.matchAll(W)){const Oe=Fe[0];Ce<Fe.index&&pe.push(Ue.slice(Ce,Fe.index)),Oe.length>0&&pe.push(Oe),Ce=Fe.index+Oe.length}return Ce<Ue.length&&pe.push(Ue.slice(Ce)),pe}function O(Ue,W=!0){if(Ue.Regex!==void 0){let pe=Ue.Regex.replace(/\\([#&~])/g,"$1");for(const[Ce,Fe]of ae)pe=pe.replaceAll(Ce,Fe);return new RegExp(pe,"gu")}else if(Ue.String!==void 0){const pe=(0,a.escapeRegExp)(Ue.String);return new RegExp(W?pe:`(${pe})`,"gu")}else return console.warn("Unknown pattern type:",Ue),null}function S(Ue){return new Map(Object.entries(Ue))}function C(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 ${W.length}.`)}}function w(Ue){return Ue.replace(/ \./g,".").replace(/ \?/g,"?").replace(/ \!/g,"!").replace(/ ,/g,",").replace(/ \' /g,"'").replace(/ n\'t/g,"n't").replace(/ \'m/g,"'m").replace(/ \'s/g,"'s").replace(/ \'ve/g,"'ve").replace(/ \'re/g,"'re")}function b(Ue){return Ue.replace(/[\u0300-\u036f]/g,"")}function I(Ue){return b(Ue.toLowerCase())}function U(Ue){return Ue>=19968&&Ue<=40959||Ue>=13312&&Ue<=19903||Ue>=131072&&Ue<=173791||Ue>=173824&&Ue<=177983||Ue>=177984&&Ue<=178207||Ue>=178208&&Ue<=183983||Ue>=63744&&Ue<=64255||Ue>=194560&&Ue<=195103}function z(Ue,W,pe){const Ce=[];let Fe=0;for(;Fe<Ue.length;){if(Ce.push(Ue[Fe]),(pe.get(Ue[Fe])??W)!==W){++Fe;continue}for(;Fe<Ue.length&&(pe.get(Ue[Fe])??W)===W;)++Fe}return Ce}function B(Ue){return Ue.match(/\S+/g)||[]}const j="\\p{P}\\u0021-\\u002F\\u003A-\\u0040\\u005B-\\u0060\\u007B-\\u007E",N=new RegExp(`^[${j}]+$`,"gu"),ae=new Map([["(?i:'s|'t|'re|'ve|'m|'ll|'d)","(?:'([sS]|[tT]|[rR][eE]|[vV][eE]|[mM]|[lL][lL]|[dD]))"]]);class ce{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 xe 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,...pe){switch(W.type){case"WordPiece":return new Y(W);case"Unigram":return new _e(W,...pe);case"BPE":return new Xe(W);default:if(W.vocab)return new me(W,...pe);throw new Error(`Unknown TokenizerModel type: ${W.type}`)}}_call(W){let pe=this.encode(W);return this.fuse_unk&&(pe=z(pe,this.unk_token_id,this.tokens_to_ids)),pe}encode(W){throw Error("encode should be implemented in subclass.")}convert_tokens_to_ids(W){return W.map(pe=>this.tokens_to_ids.get(pe)??this.unk_token_id)}convert_ids_to_tokens(W){return W.map(pe=>this.vocab[pe]??this.unk_token)}}class Y extends xe{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[pe,Ce]of this.tokens_to_ids)this.vocab[Ce]=pe}encode(W){const pe=[];for(const Ce of W){const Fe=[...Ce];if(Fe.length>this.max_input_chars_per_word){pe.push(this.unk_token);continue}let Oe=!1,rt=0;const Mt=[];for(;rt<Fe.length;){let St=Fe.length,kt=null;for(;rt<St;){let It=Fe.slice(rt,St).join("");if(rt>0&&(It=this.config.continuing_subword_prefix+It),this.tokens_to_ids.has(It)){kt=It;break}--St}if(kt===null){Oe=!0;break}Mt.push(kt),rt=St}Oe?pe.push(this.unk_token):pe.push(...Mt)}return pe}}class _e extends xe{constructor(W,pe){super(W);const Ce=W.vocab.length;this.vocab=new Array(Ce),this.scores=new Array(Ce);for(let Fe=0;Fe<Ce;++Fe){const Oe=W.vocab[Fe];this.vocab[Fe]=Oe[0],this.scores[Fe]=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((Fe,Oe)=>[Fe,Oe])),this.bosToken=" ",this.bosTokenId=this.tokens_to_ids.get(this.bosToken),this.eosToken=pe.eos_token,this.eosTokenId=this.tokens_to_ids.get(this.eosToken),this.unkToken=this.vocab[this.unk_token_id],this.minScore=(0,p.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 pe=W.sentence,Ce=pe.length;let Fe=0;for(;Fe<Ce;){let rt=!1;for(let Mt of this.trie.commonPrefixSearch(pe.slice(Fe))){const St=this.tokens_to_ids.get(Mt),kt=this.scores[St],It=Mt.length;W.insert(Fe,It,kt,St),!rt&&It===1&&(rt=!0)}rt||W.insert(Fe,1,this.unkScore,this.unk_token_id),Fe+=1}}tokenize(W){const pe=new h.TokenLattice(W,this.bosTokenId,this.eosTokenId);return this.populateNodes(pe),pe.tokens()}encode(W){const pe=[];for(const Ce of W){const Fe=this.tokenize(Ce);pe.push(...Fe)}return pe}}const L=(()=>{const Ue=[...Array.from({length:94},(Fe,Oe)=>Oe+33),...Array.from({length:12},(Fe,Oe)=>Oe+161),...Array.from({length:82},(Fe,Oe)=>Oe+174)],W=Ue.slice();let pe=0;for(let Fe=0;Fe<256;++Fe)Ue.includes(Fe)||(Ue.push(Fe),W.push(256+pe),pe+=1);const Ce=W.map(Fe=>String.fromCharCode(Fe));return Object.fromEntries(Ue.map((Fe,Oe)=>[Fe,Ce[Oe]]))})(),Se=(0,a.reverseDictionary)(L);class Xe extends xe{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[pe,Ce]of this.tokens_to_ids)this.vocab[Ce]=pe;this.bpe_ranks=new Map(W.merges.map((pe,Ce)=>[pe,Ce])),this.merges=W.merges.map(pe=>pe.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 pe=this.cache.get(W);if(pe!==void 0)return pe;const Ce=Array.from(W);this.end_of_word_suffix&&(Ce[Ce.length-1]+=this.end_of_word_suffix);let Fe=[];if(Ce.length>1){const Oe=new h.PriorityQueue((St,kt)=>St.score<kt.score);let rt={token:Ce[0],bias:0,prev:null,next:null},Mt=rt;for(let St=1;St<Ce.length;++St){const kt={bias:St/Ce.length,token:Ce[St],prev:Mt,next:null};Mt.next=kt,this._add_node(Oe,Mt),Mt=kt}for(;!Oe.isEmpty();){const St=Oe.pop();if(St.deleted||!St.next||St.next.deleted)continue;if(St.deleted=!0,St.next.deleted=!0,St.prev){const It={...St.prev};St.prev.deleted=!0,St.prev=It,It.prev?It.prev.next=It:rt=It}const kt={token:St.token+St.next.token,bias:St.bias,prev:St.prev,next:St.next.next};kt.prev?(kt.prev.next=kt,this._add_node(Oe,kt.prev)):rt=kt,kt.next&&(kt.next.prev=kt,this._add_node(Oe,kt))}for(let St=rt;St!==null;St=St.next)Fe.push(St.token)}else Fe=Ce;if(this.continuing_subword_suffix)for(let Oe=0;Oe<Fe.length-1;++Oe)Fe[Oe]+=this.continuing_subword_suffix;return this.cache.set(W,Fe),Fe}_add_node(W,pe){const Ce=this.bpe_ranks.get(pe.token+this.BPE_SPLIT_TOKEN+pe.next.token);Ce!==void 0&&(pe.score=Ce+pe.bias,W.push(pe))}encode(W){const pe=[];for(const Ce of W){if(this.ignore_merges&&this.tokens_to_ids.has(Ce)){pe.push(Ce);continue}const Fe=this.bpe(Ce);for(const Oe of Fe)this.tokens_to_ids.has(Oe)?pe.push(Oe):this.byte_fallback?pe.push(...Array.from(this.text_encoder.encode(Oe)).map(rt=>`<0x${rt.toString(16).toUpperCase().padStart(2,"0")}>`)):pe.push(this.unk_token)}return pe}}class me extends xe{constructor(W,pe){super(W),this.tokens_to_ids=S(pe.target_lang?W.vocab[pe.target_lang]:W.vocab),this.bos_token=pe.bos_token,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=pe.eos_token,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.pad_token=pe.pad_token,this.pad_token_id=this.tokens_to_ids.get(this.pad_token),this.unk_token=pe.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[Ce,Fe]of this.tokens_to_ids)this.vocab[Fe]=Ce}encode(W){return W}}class X extends o.Callable{constructor(W){super(),this.config=W}static fromConfig(W){if(W===null)return null;switch(W.type){case"BertNormalizer":return new pt(W);case"Precompiled":return new Qe(W);case"Sequence":return new st(W);case"Replace":return new ie(W);case"NFC":return new Me(W);case"NFKC":return new Q(W);case"NFKD":return new ge(W);case"Strip":return new Ke(W);case"StripAccents":return new Le(W);case"Lowercase":return new Be(W);case"Prepend":return new We(W);default:throw new Error(`Unknown Normalizer type: ${W.type}`)}}normalize(W){throw Error("normalize should be implemented in subclass.")}_call(W){return this.normalize(W)}}class ie extends X{normalize(W){const pe=O(this.config.pattern);return pe===null?W:W.replaceAll(pe,this.config.content)}}class Me extends X{normalize(W){return W=W.normalize("NFC"),W}}class Q extends X{normalize(W){return W=W.normalize("NFKC"),W}}class ge extends X{normalize(W){return W=W.normalize("NFKD"),W}}class Ke extends X{normalize(W){return this.config.strip_left&&this.config.strip_right?W=W.trim():(this.config.strip_left&&(W=W.trimStart()),this.config.strip_right&&(W=W.trimEnd())),W}}class Le extends X{normalize(W){return W=b(W),W}}class Be extends X{normalize(W){return W=W.toLowerCase(),W}}class We extends X{normalize(W){return W=this.config.prepend+W,W}}class st extends X{constructor(W){super(W),this.normalizers=W.normalizers.map(pe=>X.fromConfig(pe))}normalize(W){return this.normalizers.reduce((pe,Ce)=>Ce.normalize(pe),W)}}class pt extends X{_tokenize_chinese_chars(W){const pe=[];for(let Ce=0;Ce<W.length;++Ce){const Fe=W[Ce],Oe=Fe.charCodeAt(0);U(Oe)?(pe.push(" "),pe.push(Fe),pe.push(" ")):pe.push(Fe)}return pe.join("")}stripAccents(W){return W.normalize("NFD").replace(/[\u0300-\u036f]/g,"")}_is_control(W){switch(W){case"	":case`
`:case"\r":return!1;default:return new RegExp("^\\p{Cc}|\\p{Cf}|\\p{Co}|\\p{Cs}$","u").test(W)}}_clean_text(W){const pe=[];for(const Ce of W){const Fe=Ce.charCodeAt(0);Fe===0||Fe===65533||this._is_control(Ce)||(/^\s$/.test(Ce)?pe.push(" "):pe.push(Ce))}return pe.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 tt(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 et(W);case"Digits":return new A(W);case"Replace":return new Tt(W);default:throw new Error(`Unknown PreTokenizer type: ${W.type}`)}}pre_tokenize_text(W,pe){throw Error("pre_tokenize_text should be implemented in subclass.")}pre_tokenize(W,pe){return(Array.isArray(W)?W.map(Ce=>this.pre_tokenize_text(Ce,pe)):this.pre_tokenize_text(W,pe)).flat()}_call(W,pe){return this.pre_tokenize(W,pe)}}class Te extends Ge{constructor(W){super(),this.pattern=new RegExp(`[^\\s${j}]+|[${j}]`,"gu")}pre_tokenize_text(W,pe){return W.trim().match(this.pattern)||[]}}class je extends Ge{constructor(W){super(),this.config=W,this.add_prefix_space=this.config.add_prefix_space,this.trim_offsets=this.config.trim_offsets,this.use_regex=this.config.use_regex??!0,this.pattern=new RegExp("'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)|\\s+","gu"),this.byte_encoder=L,this.text_encoder=new TextEncoder}pre_tokenize_text(W,pe){return this.add_prefix_space&&!W.startsWith(" ")&&(W=" "+W),(this.use_regex?W.match(this.pattern)||[]:[W]).map(Fe=>Array.from(this.text_encoder.encode(Fe),Oe=>this.byte_encoder[Oe]).join(""))}}class Ye extends Ge{constructor(W){super(),this.config=W,this.pattern=O(this.config.pattern,this.config.invert)}pre_tokenize_text(W,pe){return this.pattern===null?[]:this.config.invert?W.match(this.pattern)||[]:T(W,this.pattern)}}class et extends Ge{constructor(W){super(),this.config=W,this.pattern=new RegExp(`[^${j}]+|[${j}]+`,"gu")}pre_tokenize_text(W,pe){return W.match(this.pattern)||[]}}class A extends Ge{constructor(W){super(),this.config=W;const pe=`[^\\d]+|\\d${this.config.individual_digits?"":"+"}`;this.pattern=new RegExp(pe,"gu")}pre_tokenize_text(W,pe){return W.match(this.pattern)||[]}}class $e extends o.Callable{constructor(W){super(),this.config=W}static fromConfig(W){if(W===null)return null;switch(W.type){case"TemplateProcessing":return new re(W);case"ByteLevel":return new ye(W);case"RobertaProcessing":return new se(W);case"BertProcessing":return new Pe(W);case"Sequence":return new R(W);default:throw new Error(`Unknown PostProcessor type: ${W.type}`)}}post_process(W,...pe){throw Error("post_process should be implemented in subclass.")}_call(W,...pe){return this.post_process(W,...pe)}}class Pe extends $e{constructor(W){super(W),this.cls=W.cls[0],this.sep=W.sep[0]}post_process(W,pe=null,{add_special_tokens:Ce=!0}={}){Ce&&(W=(0,a.mergeArrays)([this.cls],W,[this.sep]));let Fe=new Array(W.length).fill(0);if(pe!==null){const Oe=Ce&&this instanceof se?[this.sep]:[],rt=Ce?[this.sep]:[];W=(0,a.mergeArrays)(W,Oe,pe,rt),Fe=(0,a.mergeArrays)(Fe,new Array(pe.length+Oe.length+rt.length).fill(1))}return{tokens:W,token_type_ids:Fe}}}class se extends Pe{}class re extends $e{constructor(W){super(W),this.single=W.single,this.pair=W.pair}post_process(W,pe=null,{add_special_tokens:Ce=!0}={}){const Fe=pe===null?this.single:this.pair;let Oe=[],rt=[];for(const Mt of Fe)"SpecialToken"in Mt?Ce&&(Oe.push(Mt.SpecialToken.id),rt.push(Mt.SpecialToken.type_id)):"Sequence"in Mt&&(Mt.Sequence.id==="A"?(Oe=(0,a.mergeArrays)(Oe,W),rt=(0,a.mergeArrays)(rt,new Array(W.length).fill(Mt.Sequence.type_id))):Mt.Sequence.id==="B"&&(Oe=(0,a.mergeArrays)(Oe,pe),rt=(0,a.mergeArrays)(rt,new Array(pe.length).fill(Mt.Sequence.type_id))));return{tokens:Oe,token_type_ids:rt}}}class ye extends $e{post_process(W,pe=null){return pe&&(W=(0,a.mergeArrays)(W,pe)),{tokens:W}}}class R extends $e{constructor(W){super(W),this.processors=W.processors.map(pe=>$e.fromConfig(pe))}post_process(W,pe=null,Ce={}){let Fe;for(const Oe of this.processors)if(Oe instanceof ye)W=Oe.post_process(W).tokens,pe&&(pe=Oe.post_process(pe).tokens);else{const rt=Oe.post_process(W,pe,Ce);W=rt.tokens,Fe=rt.token_type_ids}return{tokens:W,token_type_ids:Fe}}}class ee 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 qe(W);case"ByteLevel":return new dt(W);case"Replace":return new D(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 D extends ee{decode_chain(W){const pe=O(this.config.pattern);return pe===null?W:W.map(Ce=>Ce.replaceAll(pe,this.config.content))}}class ue extends ee{constructor(W){super(W),this.text_decoder=new TextDecoder}decode_chain(W){const pe=[];let Ce=[];for(const Fe of W){let Oe=null;if(Fe.length===6&&Fe.startsWith("<0x")&&Fe.endsWith(">")){const rt=parseInt(Fe.slice(3,5),16);isNaN(rt)||(Oe=rt)}if(Oe!==null)Ce.push(Oe);else{if(Ce.length>0){const rt=this.text_decoder.decode(Uint8Array.from(Ce));pe.push(rt),Ce=[]}pe.push(Fe)}}if(Ce.length>0){const Fe=this.text_decoder.decode(Uint8Array.from(Ce));pe.push(Fe),Ce=[]}return pe}}class le extends ee{decode_chain(W){return[W.join("")]}}class ke extends ee{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(pe=>{let Ce=0;for(let Oe=0;Oe<this.start&&pe[Oe]===this.content;++Oe){Ce=Oe+1;continue}let Fe=pe.length;for(let Oe=0;Oe<this.stop;++Oe){const rt=pe.length-Oe-1;if(pe[rt]===this.content){Fe=rt;continue}else break}return pe.slice(Ce,Fe)})}}class Ne extends ee{constructor(W){super(W),this.cleanup=W.cleanup}decode_chain(W){return W.map((pe,Ce)=>(Ce!==0&&(pe.startsWith(this.config.prefix)?pe=pe.replace(this.config.prefix,""):pe=" "+pe),this.cleanup&&(pe=w(pe)),pe))}}class dt extends ee{constructor(W){super(W),this.byte_decoder=Se,this.text_decoder=new TextDecoder("utf-8",{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(W){const pe=W.join(""),Ce=new Uint8Array([...pe].map(Oe=>this.byte_decoder[Oe]));return this.text_decoder.decode(Ce)}decode_chain(W){const pe=[];let Ce=[];for(const Fe of W)this.added_tokens.find(Oe=>Oe.content===Fe)!==void 0?(Ce.length>0&&(pe.push(this.convert_tokens_to_string(Ce)),Ce=[]),pe.push(Fe)):Ce.push(Fe);return Ce.length>0&&pe.push(this.convert_tokens_to_string(Ce)),pe}}class Je extends ee{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 pe=[W[0]];for(let Oe=1;Oe<W.length;++Oe)W[Oe]!==pe.at(-1)&&pe.push(W[Oe]);let Fe=pe.filter(Oe=>Oe!==this.pad_token).join("");return this.cleanup&&(Fe=w(Fe).replaceAll(this.word_delimiter_token," ").trim()),Fe}decode_chain(W){return[this.convert_tokens_to_string(W)]}}class Ve extends ee{constructor(W){super(W),this.decoders=W.decoders.map(pe=>ee.fromConfig(pe))}decode_chain(W){return this.decoders.reduce((pe,Ce)=>Ce.decode_chain(pe),W)}}class Z extends ee{constructor(W){super(W),this.suffix=this.config.suffix}decode_chain(W){return W.map((pe,Ce)=>pe.replaceAll(this.suffix,Ce===W.length-1?"":" "))}}class ve extends ee{decode_chain(W){let pe="";for(let Ce=1;Ce<W.length;Ce+=2)pe+=W[Ce];return[pe]}}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:pe=void 0}={}){let Ce=W.replaceAll(" ",this.strRep);return this.addPrefixSpace&&!Ce.startsWith(this.replacement)&&(this.prepend_scheme==="always"||this.prepend_scheme==="first"&&pe===0)&&(Ce=this.strRep+Ce),[Ce]}}class qe extends ee{constructor(W){super(W),this.addPrefixSpace=W.add_prefix_space,this.replacement=W.replacement}decode_chain(W){const pe=[];for(let Ce=0;Ce<W.length;++Ce){let Fe=W[Ce].replaceAll(this.replacement," ");this.addPrefixSpace&&Ce==0&&Fe.startsWith(" ")&&(Fe=Fe.substring(1)),pe.push(Fe)}return pe}}class Qe extends X{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(Ce=>Ce.normalize("NFKC")).join("～"):W=W.normalize("NFKC"),W}}class tt extends Ge{constructor(W){super(),this.tokenizers=W.pretokenizers.map(pe=>Ge.fromConfig(pe))}pre_tokenize_text(W,pe){return this.tokenizers.reduce((Ce,Fe)=>Fe.pre_tokenize(Ce,pe),[W])}}class ft extends Ge{constructor(W){super()}pre_tokenize_text(W,pe){return W.match(/\w+|[^\w\s]+/g)||[]}}class ht extends Ge{constructor(W){super()}pre_tokenize_text(W,pe){return B(W)}}class Tt extends Ge{constructor(W){super(),this.config=W,this.pattern=O(this.config.pattern),this.content=this.config.content}pre_tokenize_text(W,pe){return this.pattern===null?[W]:[W.replaceAll(this.pattern,this.config.content)]}}const bt=["bos_token","eos_token","unk_token","sep_token","pad_token","cls_token","mask_token"];function Et(Ue,W,pe,Ce){for(const Fe of Object.keys(Ue)){const Oe=W-Ue[Fe].length,rt=pe(Fe),Mt=new Array(Oe).fill(rt);Ue[Fe]=Ce==="right"?(0,a.mergeArrays)(Ue[Fe],Mt):(0,a.mergeArrays)(Mt,Ue[Fe])}}function Lt(Ue,W){for(const pe of Object.keys(Ue))Ue[pe].length=W}class at extends o.Callable{constructor(pe,Ce){super();He(this,"return_token_type_ids",!1);He(this,"padding_side","right");this._tokenizer_config=Ce,this.normalizer=X.fromConfig(pe.normalizer),this.pre_tokenizer=Ge.fromConfig(pe.pre_tokenizer),this.model=xe.fromConfig(pe.model,Ce),this.post_processor=$e.fromConfig(pe.post_processor),this.decoder=ee.fromConfig(pe.decoder),this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];for(const Fe of pe.added_tokens){const Oe=new ce(Fe);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=Ce.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((Fe,Oe)=>Oe.content.length-Fe.content.length).map(Fe=>`${Fe.lstrip?"\\s*":""}(${(0,a.escapeRegExp)(Fe.content)})${Fe.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=Ce.model_max_length,this.remove_space=Ce.remove_space,this.clean_up_tokenization_spaces=Ce.clean_up_tokenization_spaces??!0,this.do_lowercase_and_remove_accent=Ce.do_lowercase_and_remove_accent??!1,Ce.padding_side&&(this.padding_side=Ce.padding_side),this.legacy=!1,this.chat_template=Ce.chat_template??null,Array.isArray(this.chat_template)){const Fe=Object.create(null);for(const{name:Oe,template:rt}of this.chat_template){if(typeof Oe!="string"||typeof rt!="string")throw new Error('Chat template must be a list of objects with "name" and "template" properties');Fe[Oe]=rt}this.chat_template=Fe}this._compiled_template_cache=new Map}getToken(...pe){for(const Ce of pe){const Fe=this._tokenizer_config[Ce];if(Fe)if(typeof Fe=="object"){if(Fe.__type==="AddedToken")return Fe.content;throw Error(`Unknown token: ${Fe}`)}else return Fe}return null}static async from_pretrained(pe,{progress_callback:Ce=null,config:Fe=null,cache_dir:Oe=null,local_files_only:rt=!1,revision:Mt="main",legacy:St=null}={}){const kt=await E(pe,{progress_callback:Ce,config:Fe,cache_dir:Oe,local_files_only:rt,revision:Mt,legacy:St});return new this(...kt)}_call(pe,{text_pair:Ce=null,add_special_tokens:Fe=!0,padding:Oe=!1,truncation:rt=null,max_length:Mt=null,return_tensor:St=!0,return_token_type_ids:kt=null}={}){const It=Array.isArray(pe);let tr;if(It){if(pe.length===0)throw Error("text array must be non-empty");if(Ce!==null){if(Array.isArray(Ce)){if(pe.length!==Ce.length)throw Error("text and text_pair must have the same length")}else throw Error("text_pair must also be an array");tr=pe.map((or,qt)=>this._encode_plus(or,{text_pair:Ce[qt],add_special_tokens:Fe,return_token_type_ids:kt}))}else tr=pe.map(or=>this._encode_plus(or,{add_special_tokens:Fe,return_token_type_ids:kt}))}else{if(pe==null)throw Error("text may not be null or undefined");if(Array.isArray(Ce))throw Error("When specifying `text_pair`, since `text` is a string, `text_pair` must also be a string (i.e., not an array).");tr=[this._encode_plus(pe,{text_pair:Ce,add_special_tokens:Fe,return_token_type_ids:kt})]}if(Mt===null?Oe==="max_length"?Mt=this.model_max_length:Mt=(0,p.max)(tr.map(or=>or.input_ids.length))[0]:rt||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."),Mt=Math.min(Mt,this.model_max_length??1/0),Oe||rt)for(let or=0;or<tr.length;++or)tr[or].input_ids.length!==Mt&&(tr[or].input_ids.length>Mt?rt&&Lt(tr[or],Mt):Oe&&Et(tr[or],Mt,qt=>qt==="input_ids"?this.pad_token_id:0,this.padding_side));const Ar={};if(St){if(!(Oe&&rt)&&tr.some(qt=>{var _r;for(const Cn of Object.keys(qt))if(qt[Cn].length!==((_r=tr[0][Cn])==null?void 0:_r.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 or=[tr.length,tr[0].input_ids.length];for(const qt of Object.keys(tr[0]))Ar[qt]=new _.Tensor("int64",BigInt64Array.from(tr.flatMap(_r=>_r[qt]).map(BigInt)),or)}else{for(const or of Object.keys(tr[0]))Ar[or]=tr.map(qt=>qt[or]);if(!It)for(const or of Object.keys(Ar))Ar[or]=Ar[or][0]}return Ar}_encode_text(pe){return pe===null?null:(this.added_tokens_regex?pe.split(this.added_tokens_regex).filter(Oe=>Oe):[pe]).map((Oe,rt)=>{if(this.added_tokens.find(St=>St.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 St=this.pre_tokenizer!==null?this.pre_tokenizer(Oe,{section_index:rt}):[Oe];return this.model(St)}}).flat()}_encode_plus(pe,{text_pair:Ce=null,add_special_tokens:Fe=!0,return_token_type_ids:Oe=null}={}){const{tokens:rt,token_type_ids:Mt}=this._tokenize_helper(pe,{pair:Ce,add_special_tokens:Fe}),St=this.model.convert_tokens_to_ids(rt),kt={input_ids:St,attention_mask:new Array(St.length).fill(1)};return(Oe??this.return_token_type_ids)&&Mt&&(kt.token_type_ids=Mt),kt}_tokenize_helper(pe,{pair:Ce=null,add_special_tokens:Fe=!1}={}){const Oe=this._encode_text(pe),rt=this._encode_text(Ce);return this.post_processor?this.post_processor(Oe,rt,{add_special_tokens:Fe}):{tokens:(0,a.mergeArrays)(Oe??[],rt??[])}}tokenize(pe,{pair:Ce=null,add_special_tokens:Fe=!1}={}){return this._tokenize_helper(pe,{pair:Ce,add_special_tokens:Fe}).tokens}encode(pe,{text_pair:Ce=null,add_special_tokens:Fe=!0,return_token_type_ids:Oe=null}={}){return this._encode_plus(pe,{text_pair:Ce,add_special_tokens:Fe,return_token_type_ids:Oe}).input_ids}batch_decode(pe,Ce={}){return pe instanceof _.Tensor&&(pe=pe.tolist()),pe.map(Fe=>this.decode(Fe,Ce))}decode(pe,Ce={}){if(pe instanceof _.Tensor&&(pe=C(pe)),!Array.isArray(pe)||pe.length===0||!(0,a.isIntegralNumber)(pe[0]))throw Error("token_ids must be a non-empty array of integers.");return this.decode_single(pe,Ce)}decode_single(pe,{skip_special_tokens:Ce=!1,clean_up_tokenization_spaces:Fe=null}){let Oe=this.model.convert_ids_to_tokens(pe);Ce&&(Oe=Oe.filter(Mt=>!this.special_tokens.includes(Mt)));let rt=this.decoder?this.decoder(Oe):Oe.join(" ");return this.decoder&&this.decoder.end_of_word_suffix&&(rt=rt.replaceAll(this.decoder.end_of_word_suffix," "),Ce&&(rt=rt.trim())),(Fe??this.clean_up_tokenization_spaces)&&(rt=w(rt)),rt}apply_chat_template(pe,{tools:Ce=null,documents:Fe=null,chat_template:Oe=null,add_generation_prompt:rt=!1,tokenize:Mt=!0,padding:St=!1,truncation:kt=!1,max_length:It=null,return_tensor:tr=!0,return_dict:Ar=!1,tokenizer_kwargs:or={},...qt}={}){if(this.chat_template&&typeof this.chat_template=="object"||this.chat_template===null){const ct=this.chat_template;if(Oe!==null&&Object.hasOwn(ct,Oe))Oe=ct[Oe];else if(Oe===null&&"default"in ct)Oe=ct.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(ct).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 _r=this._compiled_template_cache.get(Oe);_r===void 0&&(_r=new g.Template(Oe),this._compiled_template_cache.set(Oe,_r));const Cn=Object.create(null);for(const ct of bt){const Kn=this.getToken(ct);Kn&&(Cn[ct]=Kn)}const gn=_r.render({messages:pe,add_generation_prompt:rt,tools:Ce,documents:Fe,...Cn,...qt});if(Mt){const ct=this._call(gn,{add_special_tokens:!1,padding:St,truncation:kt,max_length:It,return_tensor:tr,...or});return Ar?ct:ct.input_ids}return gn}}class Ot extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class Ut extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class Xt extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class Yt extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class rr extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class Ht extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class Pr extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class Yr extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class $r extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class mt extends at{}class $t extends at{}class Bt extends at{constructor(pe,Ce){super(pe,Ce);He(this,"return_token_type_ids",!0);console.warn('WARNING: `XLMTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}}class un extends at{constructor(){super(...arguments);He(this,"return_token_type_ids",!0)}}class Bi extends at{}class Mi extends at{}class Gr extends at{}class wn extends at{constructor(W,pe){super(W,pe),this.languageRegex=/^[a-z]{2}_[A-Z]{2}$/,this.language_codes=this.special_tokens.filter(Ce=>this.languageRegex.test(Ce)),this.lang_to_token=Ce=>Ce}_build_translation_inputs(W,pe,Ce){return ki(this,W,pe,Ce)}}class Kr extends wn{}class pi extends at{}class Dr extends at{constructor(W,pe){var Oe,rt;const Ce=".,!?…。，、।۔،",Fe=(rt=(Oe=W.pre_tokenizer)==null?void 0:Oe.pretokenizers[0])==null?void 0:rt.pattern;Fe&&Fe.Regex===` ?[^(\\s|[${Ce}])]+`&&(Fe.Regex=` ?[^\\s${Ce}]+`),super(W,pe)}}const Ni="▁";class Ti extends at{constructor(pe,Ce){super(pe,Ce);He(this,"padding_side","left");this.legacy=Ce.legacy??!0,this.legacy||(this.normalizer=null,this.pre_tokenizer=new Re({replacement:Ni,add_prefix_space:!0,prepend_scheme:"first"}))}_encode_text(pe){if(pe===null)return null;if(this.legacy||pe.length===0)return super._encode_text(pe);let Ce=super._encode_text(Ni+pe.replaceAll(Ni," "));return Ce.length>1&&Ce[0]===Ni&&this.special_tokens.includes(Ce[1])&&(Ce=Ce.slice(1)),Ce}}class Cs extends at{}class Lo extends at{}class Ro extends at{}class Bo extends at{}class No extends at{}class ji extends at{}class Ps extends at{}class fo extends at{}class fi extends at{}function ki(Ue,W,pe,Ce){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 Fe=Ce.src_lang,Oe=Ce.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(Fe!==void 0){if(!Ue.language_codes.includes(Fe))throw new Error(`Source language code "${Fe}" is not valid. Must be one of: {${Ue.language_codes.join(", ")}}`);for(const rt of Ue.post_processor.config.single)if("SpecialToken"in rt&&Ue.languageRegex.test(rt.SpecialToken.id)){rt.SpecialToken.id=Ue.lang_to_token(Fe);break}}return Ce.forced_bos_token_id=Ue.model.convert_tokens_to_ids([Ue.lang_to_token(Oe)])[0],Ue._call(W,pe)}class Si extends at{constructor(W,pe){super(W,pe),this.languageRegex=/^[a-z]{3}_[A-Z][a-z]{3}$/,this.language_codes=this.special_tokens.filter(Ce=>this.languageRegex.test(Ce)),this.lang_to_token=Ce=>Ce}_build_translation_inputs(W,pe,Ce){return ki(this,W,pe,Ce)}}class Ji extends at{constructor(W,pe){super(W,pe),this.languageRegex=/^__[a-z]{2,3}__$/,this.language_codes=this.special_tokens.filter(Ce=>this.languageRegex.test(Ce)).map(Ce=>Ce.slice(2,-2)),this.lang_to_token=Ce=>`__${Ce}__`}_build_translation_inputs(W,pe,Ce){return ki(this,W,pe,Ce)}}class ho extends at{get timestamp_begin(){return this.model.convert_tokens_to_ids(["<|notimestamps|>"])[0]+1}_decode_asr(W,{return_timestamps:pe=!1,return_language:Ce=!1,time_precision:Fe=null,force_full_sequences:Oe=!0}={}){if(Fe===null)throw Error("Must specify time_precision");let rt=null;const Mt=pe==="word";function St(){return{language:rt,timestamp:[null,null],text:""}}const kt=[];let It=St(),tr=0;const Ar=this.timestamp_begin;let or=[],qt=[],_r=!1,Cn=null;const gn=new Set(this.all_special_ids);for(const Tr of W){const cn=Tr.tokens,On=Mt?Tr.token_timestamps:null;let Jt=null,Un=Ar;if("stride"in Tr){const[Er,At,vr]=Tr.stride;if(tr-=At,Cn=Er-vr,At&&(Un=At/Fe+Ar),vr)for(let Lr=cn.length-1;Lr>=0;--Lr){const Xr=Number(cn[Lr]);if(Xr>=Ar){if(Jt!==null&&(Xr-Ar)*Fe<Cn)break;Jt=Xr}}}let yn=[],Sr=[];for(let Er=0;Er<cn.length;++Er){const At=Number(cn[Er]);if(gn.has(At)){const vr=this.decode([At]),Lr=M.WHISPER_LANGUAGE_MAPPING.get(vr.slice(2,-2));if(Lr!==void 0){if(rt!==null&&Lr!==rt&&!pe){or.push(yn);const Xr=this.findLongestCommonSequence(or)[0],Vn=this.decode(Xr);It.text=Vn,kt.push(It),or=[],yn=[],It=St()}rt=It.language=Lr}}else if(At>=Ar){const vr=(At-Ar)*Fe+tr,Lr=(0,p.round)(vr,2);if(Jt!==null&&At>=Jt)_r=!0;else if(_r||or.length>0&&At<Un)_r=!1;else if(It.timestamp[0]===null)It.timestamp[0]=Lr;else if(Lr!==It.timestamp[0]){It.timestamp[1]=Lr,or.push(yn),Mt&&qt.push(Sr);const[Xr,Vn]=this.findLongestCommonSequence(or,qt),zt=this.decode(Xr);It.text=zt,Mt&&(It.words=this.collateWordTimestamps(Xr,Vn,rt)),kt.push(It),or=[],yn=[],qt=[],Sr=[],It=St()}}else if(yn.push(At),Mt){let vr=(0,p.round)(On[Er]+tr,2),Lr;if(Er+1<On.length){Lr=(0,p.round)(On[Er+1]+tr,2);const Xr=this.decode([At]);N.test(Xr)&&(Lr=(0,p.round)(Math.min(vr+Fe,Lr),2))}else Lr=null;Sr.push([vr,Lr])}}if("stride"in Tr){const[Er,At,vr]=Tr.stride;tr+=Er-vr}yn.length>0?(or.push(yn),Mt&&qt.push(Sr)):or.every(Er=>Er.length===0)&&(It=St(),or=[],yn=[],qt=[],Sr=[])}if(or.length>0){if(Oe&&pe)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[Tr,cn]=this.findLongestCommonSequence(or,qt),On=this.decode(Tr);It.text=On,Mt&&(It.words=this.collateWordTimestamps(Tr,cn,rt)),kt.push(It)}let ct=Object.create(null);const Kn=kt.map(Tr=>Tr.text).join("");if(pe||Ce){for(let Tr=0;Tr<kt.length;++Tr){const cn=kt[Tr];pe||delete cn.timestamp,Ce||delete cn.language}if(Mt){const Tr=[];for(const cn of kt)for(const On of cn.words)Tr.push(On);ct={chunks:Tr}}else ct={chunks:kt}}return[Kn,ct]}findLongestCommonSequence(W,pe=null){let Ce=W[0],Fe=Ce.length,Oe=[];const rt=Array.isArray(pe)&&pe.length>0;let Mt=rt?[]:null,St=rt?pe[0]:null;for(let kt=1;kt<W.length;++kt){const It=W[kt];let tr=0,Ar=[Fe,Fe,0,0];const or=It.length;for(let Tr=1;Tr<Fe+or;++Tr){const cn=Math.max(0,Fe-Tr),On=Math.min(Fe,Fe+or-Tr),Jt=Ce.slice(cn,On),Un=Math.max(0,Tr-Fe),yn=Math.min(or,Tr),Sr=It.slice(Un,yn);if(Jt.length!==Sr.length)throw new Error("There is a bug within whisper `decode_asr` function, please report it. Dropping to prevent bad inference.");let Er;rt?Er=Jt.filter((Lr,Xr)=>Lr===Sr[Xr]&&St[cn+Xr]<=pe[kt][Un+Xr]).length:Er=Jt.filter((Lr,Xr)=>Lr===Sr[Xr]).length;const At=Tr/1e4,vr=Er/Tr+At;Er>1&&vr>tr&&(tr=vr,Ar=[cn,On,Un,yn])}const[qt,_r,Cn,gn]=Ar,ct=Math.floor((_r+qt)/2),Kn=Math.floor((gn+Cn)/2);Oe.push(...Ce.slice(0,ct)),Ce=It.slice(Kn),Fe=Ce.length,rt&&(Mt.push(...St.slice(0,ct)),St=pe[kt].slice(Kn))}return Oe.push(...Ce),rt?(Mt.push(...St),[Oe,Mt]):[Oe,[]]}collateWordTimestamps(W,pe,Ce){const[Fe,Oe,rt]=this.combineTokensIntoWords(W,Ce),Mt=[];for(let St=0;St<Fe.length;++St){const kt=rt[St];Mt.push({text:Fe[St],timestamp:[pe[kt.at(0)][0],pe[kt.at(-1)][1]]})}return Mt}combineTokensIntoWords(W,pe,Ce=`"'“¡¿([{-`,Fe=`"'.。,，!！?？:：”)]}、`){pe=pe??"english";let Oe,rt,Mt;return["chinese","japanese","thai","lao","myanmar"].includes(pe)?[Oe,rt,Mt]=this.splitTokensOnUnicode(W):[Oe,rt,Mt]=this.splitTokensOnSpaces(W),this.mergePunctuations(Oe,rt,Mt,Ce,Fe)}decode(W,pe){let Ce;return pe!=null&&pe.decode_with_timestamps?(W instanceof _.Tensor&&(W=C(W)),Ce=this.decodeWithTimestamps(W,pe)):Ce=super.decode(W,pe),Ce}decodeWithTimestamps(W,pe){const Ce=(pe==null?void 0:pe.time_precision)??.02,Fe=Array.from(this.all_special_ids).at(-1)+1;let Oe=[[]];for(let rt of W)if(rt=Number(rt),rt>=Fe){const Mt=((rt-Fe)*Ce).toFixed(2);Oe.push(`<|${Mt}|>`),Oe.push([])}else Oe[Oe.length-1].push(rt);return Oe=Oe.map(rt=>typeof rt=="string"?rt:super.decode(rt,pe)),Oe.join("")}splitTokensOnUnicode(W){const pe=this.decode(W,{decode_with_timestamps:!0}),Ce="�",Fe=[],Oe=[],rt=[];let Mt=[],St=[],kt=0;for(let It=0;It<W.length;++It){const tr=W[It];Mt.push(tr),St.push(It);const Ar=this.decode(Mt,{decode_with_timestamps:!0});(!Ar.includes(Ce)||pe[kt+Ar.indexOf(Ce)]===Ce)&&(Fe.push(Ar),Oe.push(Mt),rt.push(St),Mt=[],St=[],kt+=Ar.length)}return[Fe,Oe,rt]}splitTokensOnSpaces(W){const[pe,Ce,Fe]=this.splitTokensOnUnicode(W),Oe=[],rt=[],Mt=[],St=new RegExp(`^[${j}]$`,"gu");for(let kt=0;kt<pe.length;++kt){const It=pe[kt],tr=Ce[kt],Ar=Fe[kt],or=tr[0]>=this.model.tokens_to_ids.get("<|endoftext|>"),qt=It.startsWith(" "),_r=It.trim(),Cn=St.test(_r);if(or||qt||Cn||Oe.length===0)Oe.push(It),rt.push(tr),Mt.push(Ar);else{const gn=Oe.length-1;Oe[gn]+=It,rt[gn].push(...tr),Mt[gn].push(...Ar)}}return[Oe,rt,Mt]}mergePunctuations(W,pe,Ce,Fe,Oe){const rt=structuredClone(W),Mt=structuredClone(pe),St=structuredClone(Ce);let kt=rt.length-2,It=rt.length-1;for(;kt>=0;)rt[kt].startsWith(" ")&&Fe.includes(rt[kt].trim())?(rt[It]=rt[kt]+rt[It],Mt[It]=(0,a.mergeArrays)(Mt[kt],Mt[It]),St[It]=(0,a.mergeArrays)(St[kt],St[It]),rt[kt]="",Mt[kt]=[],St[kt]=[]):It=kt,--kt;for(kt=0,It=1;It<rt.length;)!rt[kt].endsWith(" ")&&Oe.includes(rt[It])?(rt[kt]+=rt[It],Mt[kt]=(0,a.mergeArrays)(Mt[kt],Mt[It]),St[kt]=(0,a.mergeArrays)(St[kt],St[It]),rt[It]="",Mt[It]=[],St[It]=[]):kt=It,++It;return[rt.filter(tr=>tr),Mt.filter(tr=>tr.length>0),St.filter(tr=>tr.length>0)]}get_decoder_prompt_ids({language:W=null,task:pe=null,no_timestamps:Ce=!0}={}){const Fe=[];if(W){const Oe=(0,M.whisper_language_to_code)(W),rt=this.model.tokens_to_ids.get(`<|${Oe}|>`);if(rt===void 0)throw new Error(`Unable to find language "${Oe}" in model vocabulary. Please report this issue at ${y.GITHUB_ISSUE_URL}.`);Fe.push(rt)}else Fe.push(null);if(pe){if(pe=pe.toLowerCase(),pe!=="transcribe"&&pe!=="translate")throw new Error(`Task "${pe}" is not supported. Must be one of: ["transcribe", "translate"]`);const Oe=this.model.tokens_to_ids.get(`<|${pe}|>`);if(Oe===void 0)throw new Error(`Unable to find task "${pe}" in model vocabulary. Please report this issue at ${y.GITHUB_ISSUE_URL}.`);Fe.push(Oe)}else Fe.push(null);if(Ce){const Oe=this.model.tokens_to_ids.get("<|notimestamps|>");if(Oe===void 0)throw new Error(`Unable to find "<|notimestamps|>" in model vocabulary. 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Using bilinear instead.`),I="bilinear");case"nearest":case"bilinear":case"bicubic":U=U.affine([C/this.width,0,0,w/this.height],{interpolator:I});break;case"lanczos":U=U.resize({width:C,height:w,fit:"fill",kernel:"lanczos3"});break;default:throw new Error(`Resampling method ${I} is not supported.`)}return await y(U)}}async pad([C,w,b,I]){if(C=Math.max(C,0),w=Math.max(w,0),b=Math.max(b,0),I=Math.max(I,0),C===0&&w===0&&b===0&&I===0)return this;if(_){const U=this.channels,z=this.toCanvas(),B=this.width+C+w,j=this.height+b+I,N=g(B,j).getContext("2d");return N.drawImage(z,0,0,this.width,this.height,C,b,B,j),new O(N.getImageData(0,0,B,j).data,B,j,4).convert(U)}else{const U=this.toSharp().extend({left:C,right:w,top:b,bottom:I});return await y(U)}}async crop([C,w,b,I]){if(C=Math.max(C,0),w=Math.max(w,0),b=Math.min(b,this.width-1),I=Math.min(I,this.height-1),C===0&&w===0&&b===this.width-1&&I===this.height-1)return this;const U=b-C+1,z=I-w+1;if(_){const B=this.channels,j=this.toCanvas(),N=g(U,z).getContext("2d");return N.drawImage(j,C,w,U,z,0,0,U,z),new O(N.getImageData(0,0,U,z).data,U,z,4).convert(B)}else{const B=this.toSharp().extract({left:C,top:w,width:U,height:z});return await y(B)}}async center_crop(C,w){if(this.width===C&&this.height===w)return this;const b=(this.width-C)/2,I=(this.height-w)/2;if(_){const U=this.channels,z=this.toCanvas(),B=g(C,w).getContext("2d");let j=0,N=0,ae=0,ce=0;return b>=0?j=b:ae=-b,I>=0?N=I:ce=-I,B.drawImage(z,j,N,C,w,ae,ce,C,w),new O(B.getImageData(0,0,C,w).data,C,w,4).convert(U)}else{let U=this.toSharp();if(b>=0&&I>=0)U=U.extract({left:Math.floor(b),top:Math.floor(I),width:C,height:w});else if(b<=0&&I<=0){const z=Math.floor(-I),B=Math.floor(-b);U=U.extend({top:z,left:B,right:C-this.width-B,bottom:w-this.height-z})}else{let z=[0,0],B=0;I<0?(z[0]=Math.floor(-I),z[1]=w-this.height-z[0]):B=Math.floor(I);let j=[0,0],N=0;b<0?(j[0]=Math.floor(-b),j[1]=C-this.width-j[0]):N=Math.floor(b),U=U.extend({top:z[0],bottom:z[1],left:j[0],right:j[1]}).extract({left:N,top:B,width:C,height:w})}return await y(U)}}async toBlob(C="image/png",w=1){if(!_)throw new Error("toBlob() is only supported in browser environments.");return await this.toCanvas().convertToBlob({type:C,quality:w})}toTensor(C="CHW"){let w=new l.Tensor("uint8",new Uint8Array(this.data),[this.height,this.width,this.channels]);if(C!=="HWC")if(C==="CHW")w=w.permute(2,0,1);else throw new Error(`Unsupported channel format: ${C}`);return w}toCanvas(){if(!_)throw new Error("toCanvas() is only supported in browser environments.");const C=this.clone().rgba(),w=g(C.width,C.height),b=new M(C.data,C.width,C.height);return w.getContext("2d").putImageData(b,0,0),w}_update(C,w,b,I=null){return this.data=C,this.width=w,this.height=b,I!==null&&(this.channels=I),this}clone(){return new O(this.data.slice(),this.width,this.height,this.channels)}convert(C){if(this.channels===C)return this;switch(C){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: ${this.channels}`)}return this}async save(C){if(_){if(h)throw new Error("Unable to save an image from a Web Worker.");const w=C.split(".").pop().toLowerCase(),b=T.get(w)??"image/png",I=await this.toBlob(b),U=URL.createObjectURL(I),z=document.createElement("a");z.href=U,z.download=C,z.click(),z.remove()}else{if(a.env.useFS)return await this.toSharp().toFile(C);throw new Error("Unable to save the image because filesystem is disabled in this environment.")}}toSharp(){if(_)throw new Error("toSharp() is only supported in server-side environments.");return p(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}})}}},"./src/utils/maths.js":(e,t,r)=>{r.r(t),r.d(t,{FFT:()=>S,bankers_round:()=>b,cos_sim:()=>h,dot:()=>_,dynamic_time_warping:()=>I,interpolate_data:()=>o,log_softmax:()=>p,magnitude:()=>g,max:()=>y,medianFilter:()=>C,min:()=>M,permute_data:()=>a,round:()=>w,softmax:()=>l});function o(U,[z,B,j],[N,ae],ce="bilinear",xe=!1){const Y=ae/j,_e=N/B,L=new U.constructor(N*ae*z),Se=B*j,Xe=N*ae;for(let me=0;me<N;++me)for(let X=0;X<ae;++X){const ie=me*ae+X,Me=(X+.5)/Y-.5,Q=(me+.5)/_e-.5;let ge=Math.floor(Me),Ke=Math.floor(Q);const Le=Math.min(ge+1,j-1),Be=Math.min(Ke+1,B-1);ge=Math.max(ge,0),Ke=Math.max(Ke,0);const We=Me-ge,st=Q-Ke,pt=(1-We)*(1-st),Ge=We*(1-st),Te=(1-We)*st,je=We*st,Ye=Ke*j,et=Be*j,A=Ye+ge,$e=Ye+Le,Pe=et+ge,se=et+Le;for(let re=0;re<z;++re){const ye=re*Se;L[re*Xe+ie]=pt*U[ye+A]+Ge*U[ye+$e]+Te*U[ye+Pe]+je*U[ye+se]}}return L}function a(U,z,B){const j=new Array(B.length),N=new Array(B.length);for(let 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Error("Input and output buffers must be different");this._realTransform4(z,B,1)}inverseTransform(z,B){if(z===B)throw new Error("Input and output buffers must be different");this._transform4(z,B,-1);for(let j=0;j<z.length;++j)z[j]/=this.size}_transform4(z,B,j){const N=this._csize;let ce=1<<this._width,xe=N/ce<<1,Y,_e;const L=this._bitrev;if(xe===4)for(Y=0,_e=0;Y<N;Y+=xe,++_e){const Xe=L[_e];this._singleTransform2(B,z,Y,Xe,ce)}else for(Y=0,_e=0;Y<N;Y+=xe,++_e){const Xe=L[_e];this._singleTransform4(B,z,Y,Xe,ce,j)}const Se=this.table;for(ce>>=2;ce>=2;ce>>=2){xe=N/ce<<1;const Xe=xe>>>2;for(Y=0;Y<N;Y+=xe){const me=Y+Xe-1;for(let X=Y,ie=0;X<me;X+=2,ie+=ce){const Me=X,Q=Me+Xe,ge=Q+Xe,Ke=ge+Xe,Le=z[Me],Be=z[Me+1],We=z[Q],st=z[Q+1],pt=z[ge],Ge=z[ge+1],Te=z[Ke],je=z[Ke+1],Ye=Se[ie],et=j*Se[ie+1],A=We*Ye-st*et,$e=We*et+st*Ye,Pe=Se[2*ie],se=j*Se[2*ie+1],re=pt*Pe-Ge*se,ye=pt*se+Ge*Pe,R=Se[3*ie],ee=j*Se[3*ie+1],D=Te*R-je*ee,ue=Te*ee+je*R,le=Le+re,ke=Be+ye,Ne=Le-re,dt=Be-ye,Je=A+D,Ve=$e+ue,Z=j*(A-D),ve=j*($e-ue);z[Me]=le+Je,z[Me+1]=ke+Ve,z[Q]=Ne+ve,z[Q+1]=dt-Z,z[ge]=le-Je,z[ge+1]=ke-Ve,z[Ke]=Ne-ve,z[Ke+1]=dt+Z}}}}_singleTransform2(z,B,j,N,ae){const ce=z[N],xe=z[N+1],Y=z[N+ae],_e=z[N+ae+1];B[j]=ce+Y,B[j+1]=xe+_e,B[j+2]=ce-Y,B[j+3]=xe-_e}_singleTransform4(z,B,j,N,ae,ce){const xe=ae*2,Y=ae*3,_e=z[N],L=z[N+1],Se=z[N+ae],Xe=z[N+ae+1],me=z[N+xe],X=z[N+xe+1],ie=z[N+Y],Me=z[N+Y+1],Q=_e+me,ge=L+X,Ke=_e-me,Le=L-X,Be=Se+ie,We=Xe+Me,st=ce*(Se-ie),pt=ce*(Xe-Me);B[j]=Q+Be,B[j+1]=ge+We,B[j+2]=Ke+pt,B[j+3]=Le-st,B[j+4]=Q-Be,B[j+5]=ge-We,B[j+6]=Ke-pt,B[j+7]=Le+st}_realTransform4(z,B,j){const N=this._csize;let ce=1<<this._width,xe=N/ce<<1,Y,_e;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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O=T.meta.percent||0,S=this.entriesCount,C=this._sources.length;this.accumulate?this.contentBuffer.push(T):(this.bytesWritten+=T.data.length,h.prototype.push.call(this,{data:T.data,meta:{currentFile:this.currentFile,percent:S?(O+100*(S-C-1))/S:100}}))},E.prototype.openedSource=function(T){this.currentSourceOffset=this.bytesWritten,this.currentFile=T.file.name;var O=this.streamFiles&&!T.file.dir;if(O){var S=p(T,O,!1,this.currentSourceOffset,this.zipPlatform,this.encodeFileName);this.push({data:S.fileRecord,meta:{percent:0}})}else this.accumulate=!0},E.prototype.closedSource=function(T){this.accumulate=!1;var O=this.streamFiles&&!T.file.dir,S=p(T,O,!0,this.currentSourceOffset,this.zipPlatform,this.encodeFileName);if(this.dirRecords.push(S.dirRecord),O)this.push({data:function(C){return y.DATA_DESCRIPTOR+l(C.crc32,4)+l(C.compressedSize,4)+l(C.uncompressedSize,4)}(T),meta:{percent:100}});else for(this.push({data:S.fileRecord,meta:{percent:0}});this.contentBuffer.length;)this.push(this.contentBuffer.shift());this.currentFile=null},E.prototype.flush=function(){for(var T=this.bytesWritten,O=0;O<this.dirRecords.length;O++)this.push({data:this.dirRecords[O],meta:{percent:100}});var S=this.bytesWritten-T,C=function(w,b,I,U,z){var B=_.transformTo("string",z(U));return y.CENTRAL_DIRECTORY_END+"\0\0\0\0"+l(w,2)+l(w,2)+l(b,4)+l(I,4)+l(B.length,2)+B}(this.dirRecords.length,S,T,this.zipComment,this.encodeFileName);this.push({data:C,meta:{percent:100}})},E.prototype.prepareNextSource=function(){this.previous=this._sources.shift(),this.openedSource(this.previous.streamInfo),this.isPaused?this.previous.pause():this.previous.resume()},E.prototype.registerPrevious=function(T){this._sources.push(T);var O=this;return T.on("data",function(S){O.processChunk(S)}),T.on("end",function(){O.closedSource(O.previous.streamInfo),O._sources.length?O.prepareNextSource():O.end()}),T.on("error",function(S){O.error(S)}),this},E.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))},E.prototype.error=function(T){var O=this._sources;if(!h.prototype.error.call(this,T))return!1;for(var S=0;S<O.length;S++)try{O[S].error(T)}catch{}return!0},E.prototype.lock=function(){h.prototype.lock.call(this);for(var T=this._sources,O=0;O<T.length;O++)T[O].lock()},o.exports=E},{"../crc32":4,"../signature":23,"../stream/GenericWorker":28,"../utf8":31,"../utils":32}],9:[function(r,o,a){var l=r("../compressions"),p=r("./ZipFileWorker");a.generateWorker=function(_,h,g){var M=new p(h.streamFiles,g,h.platform,h.encodeFileName),y=0;try{_.forEach(function(E,T){y++;var O=function(b,I){var U=b||I,z=l[U];if(!z)throw new Error(U+" is not a valid compression method !");return z}(T.options.compression,h.compression),S=T.options.compressionOptions||h.compressionOptions||{},C=T.dir,w=T.date;T._compressWorker(O,S).withStreamInfo("file",{name:E,dir:C,date:w,comment:T.comment||"",unixPermissions:T.unixPermissions,dosPermissions:T.dosPermissions}).pipe(M)}),M.entriesCount=y}catch(E){M.error(E)}return M}},{"../compressions":3,"./ZipFileWorker":8}],10:[function(r,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 p=new l;for(var _ in this)typeof this[_]!="function"&&(p[_]=this[_]);return p}}(l.prototype=r("./object")).loadAsync=r("./load"),l.support=r("./support"),l.defaults=r("./defaults"),l.version="3.10.1",l.loadAsync=function(p,_){return new l().loadAsync(p,_)},l.external=r("./external"),o.exports=l},{"./defaults":5,"./external":6,"./load":11,"./object":15,"./support":30}],11:[function(r,o,a){var l=r("./utils"),p=r("./external"),_=r("./utf8"),h=r("./zipEntries"),g=r("./stream/Crc32Probe"),M=r("./nodejsUtils");function y(E){return new p.Promise(function(T,O){var S=E.decompressed.getContentWorker().pipe(new g);S.on("error",function(C){O(C)}).on("end",function(){S.streamInfo.crc32!==E.decompressed.crc32?O(new Error("Corrupted zip : CRC32 mismatch")):T()}).resume()})}o.exports=function(E,T){var O=this;return T=l.extend(T||{},{base64:!1,checkCRC32:!1,optimizedBinaryString:!1,createFolders:!1,decodeFileName:_.utf8decode}),M.isNode&&M.isStream(E)?p.Promise.reject(new Error("JSZip can't accept a stream when loading a zip file.")):l.prepareContent("the loaded zip file",E,!0,T.optimizedBinaryString,T.base64).then(function(S){var C=new h(T);return C.load(S),C}).then(function(S){var C=[p.Promise.resolve(S)],w=S.files;if(T.checkCRC32)for(var b=0;b<w.length;b++)C.push(y(w[b]));return p.Promise.all(C)}).then(function(S){for(var C=S.shift(),w=C.files,b=0;b<w.length;b++){var I=w[b],U=I.fileNameStr,z=l.resolve(I.fileNameStr);O.file(z,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:T.createFolders}),I.dir||(O.file(z).unsafeOriginalName=U)}return C.zipComment.length&&(O.comment=C.zipComment),O})}},{"./external":6,"./nodejsUtils":14,"./stream/Crc32Probe":25,"./utf8":31,"./utils":32,"./zipEntries":33}],12:[function(r,o,a){var l=r("../utils"),p=r("../stream/GenericWorker");function _(h,g){p.call(this,"Nodejs stream input adapter for "+h),this._upstreamEnded=!1,this._bindStream(g)}l.inherits(_,p),_.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!!p.prototype.pause.call(this)&&(this._stream.pause(),!0)},_.prototype.resume=function(){return!!p.prototype.resume.call(this)&&(this._upstreamEnded?this.end():this._stream.resume(),!0)},o.exports=_},{"../stream/GenericWorker":28,"../utils":32}],13:[function(r,o,a){var l=r("readable-stream").Readable;function p(_,h,g){l.call(this,h),this._helper=_;var M=this;_.on("data",function(y,E){M.push(y)||M._helper.pause(),g&&g(E)}).on("error",function(y){M.emit("error",y)}).on("end",function(){M.push(null)})}r("../utils").inherits(p,l),p.prototype._read=function(){this._helper.resume()},o.exports=p},{"../utils":32,"readable-stream":16}],14:[function(r,o,a){o.exports={isNode:typeof 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0||(ce.binary=!xe),(B instanceof y&&B.uncompressedSize===0||ce.dir||!B||B.length===0)&&(ce.base64=!1,ce.binary=!0,B="",ce.compression="STORE",ae="string");var Y=null;Y=B instanceof y||B instanceof h?B:O.isNode&&O.isStream(B)?new S(z,B):_.prepareContent(z,B,ce.binary,ce.optimizedBinaryString,ce.base64);var _e=new E(z,Y,ce);this.files[z]=_e}var p=r("./utf8"),_=r("./utils"),h=r("./stream/GenericWorker"),g=r("./stream/StreamHelper"),M=r("./defaults"),y=r("./compressedObject"),E=r("./zipObject"),T=r("./generate"),O=r("./nodejsUtils"),S=r("./nodejs/NodejsStreamInputAdapter"),C=function(z){z.slice(-1)==="/"&&(z=z.substring(0,z.length-1));var B=z.lastIndexOf("/");return 0<B?z.substring(0,B):""},w=function(z){return z.slice(-1)!=="/"&&(z+="/"),z},b=function(z,B){return B=B!==void 0?B:M.createFolders,z=w(z),this.files[z]||l.call(this,z,null,{dir:!0,createFolders:B}),this.files[z]};function I(z){return Object.prototype.toString.call(z)==="[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(z){var B,j,N;for(B in this.files)N=this.files[B],(j=B.slice(this.root.length,B.length))&&B.slice(0,this.root.length)===this.root&&z(j,N)},filter:function(z){var B=[];return this.forEach(function(j,N){z(j,N)&&B.push(N)}),B},file:function(z,B,j){if(arguments.length!==1)return z=this.root+z,l.call(this,z,B,j),this;if(I(z)){var N=z;return this.filter(function(ce,xe){return!xe.dir&&N.test(ce)})}var ae=this.files[this.root+z];return ae&&!ae.dir?ae:null},folder:function(z){if(!z)return this;if(I(z))return this.filter(function(ae,ce){return ce.dir&&z.test(ae)});var B=this.root+z,j=b.call(this,B),N=this.clone();return N.root=j.name,N},remove:function(z){z=this.root+z;var B=this.files[z];if(B||(z.slice(-1)!=="/"&&(z+="/"),B=this.files[z]),B&&!B.dir)delete this.files[z];else for(var j=this.filter(function(ae,ce){return ce.name.slice(0,z.length)===z}),N=0;N<j.length;N++)delete this.files[j[N].name];return this},generate:function(){throw new Error("This method has been removed in JSZip 3.0, please check the upgrade guide.")},generateInternalStream:function(z){var B,j={};try{if((j=_.extend(z||{},{streamFiles:!1,compression:"STORE",compressionOptions:null,type:"",platform:"DOS",comment:null,mimeType:"application/zip",encodeFileName:p.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 N=j.comment||this.comment||"";B=T.generateWorker(this,j,N)}catch(ae){(B=new h("error")).error(ae)}return new g(B,j.type||"string",j.mimeType)},generateAsync:function(z,B){return this.generateInternalStream(z).accumulate(B)},generateNodeStream:function(z,B){return(z=z||{}).type||(z.type="nodebuffer"),this.generateInternalStream(z).toNodejsStream(B)}};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(r,o,a){o.exports=r("stream")},{stream:void 0}],17:[function(r,o,a){var l=r("./DataReader");function p(_){l.call(this,_);for(var h=0;h<this.data.length;h++)_[h]=255&_[h]}r("../utils").inherits(p,l),p.prototype.byteAt=function(_){return this.data[this.zero+_]},p.prototype.lastIndexOfSignature=function(_){for(var h=_.charCodeAt(0),g=_.charCodeAt(1),M=_.charCodeAt(2),y=_.charCodeAt(3),E=this.length-4;0<=E;--E)if(this.data[E]===h&&this.data[E+1]===g&&this.data[E+2]===M&&this.data[E+3]===y)return E-this.zero;return-1},p.prototype.readAndCheckSignature=function(_){var h=_.charCodeAt(0),g=_.charCodeAt(1),M=_.charCodeAt(2),y=_.charCodeAt(3),E=this.readData(4);return h===E[0]&&g===E[1]&&M===E[2]&&y===E[3]},p.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=p},{"../utils":32,"./DataReader":18}],18:[function(r,o,a){var l=r("../utils");function p(_){this.data=_,this.length=_.length,this.index=0,this.zero=0}p.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 = "+_+"). 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g=this.streamInfo[this.propName]||0;this.streamInfo[this.propName]=g+h.data.length}p.prototype.processChunk.call(this,h)},o.exports=_},{"../utils":32,"./GenericWorker":28}],27:[function(r,o,a){var l=r("../utils"),p=r("./GenericWorker");function _(h){p.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(_,p),_.prototype.cleanUp=function(){p.prototype.cleanUp.call(this),this.data=null},_.prototype.resume=function(){return!!p.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(r,o,a){function l(p){this.name=p||"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(p){this.emit("data",p)},end:function(){if(this.isFinished)return!1;this.flush();try{this.emit("end"),this.cleanUp(),this.isFinished=!0}catch(p){this.emit("error",p)}return!0},error:function(p){return!this.isFinished&&(this.isPaused?this.generatedError=p:(this.isFinished=!0,this.emit("error",p),this.previous&&this.previous.error(p),this.cleanUp()),!0)},on:function(p,_){return this._listeners[p].push(_),this},cleanUp:function(){this.streamInfo=this.generatedError=this.extraStreamInfo=null,this._listeners=[]},emit:function(p,_){if(this._listeners[p])for(var h=0;h<this._listeners[p].length;h++)this._listeners[p][h].call(this,_)},pipe:function(p){return p.registerPrevious(this)},registerPrevious:function(p){if(this.isLocked)throw new Error("The stream '"+this+"' has already been used.");this.streamInfo=p.streamInfo,this.mergeStreamInfo(),this.previous=p;var _=this;return p.on("data",function(h){_.processChunk(h)}),p.on("end",function(){_.end()}),p.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 p=this.isPaused=!1;return this.generatedError&&(this.error(this.generatedError),p=!0),this.previous&&this.previous.resume(),!p},flush:function(){},processChunk:function(p){this.push(p)},withStreamInfo:function(p,_){return this.extraStreamInfo[p]=_,this.mergeStreamInfo(),this},mergeStreamInfo:function(){for(var p in this.extraStreamInfo)Object.prototype.hasOwnProperty.call(this.extraStreamInfo,p)&&(this.streamInfo[p]=this.extraStreamInfo[p])},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 p="Worker "+this.name;return this.previous?this.previous+" -> "+p:p}},o.exports=l},{}],29:[function(r,o,a){var l=r("../utils"),p=r("./ConvertWorker"),_=r("./GenericWorker"),h=r("../base64"),g=r("../support"),M=r("../external"),y=null;if(g.nodestream)try{y=r("../nodejs/NodejsStreamOutputAdapter")}catch{}function E(O,S){return new M.Promise(function(C,w){var b=[],I=O._internalType,U=O._outputType,z=O._mimeType;O.on("data",function(B,j){b.push(B),S&&S(j)}).on("error",function(B){b=[],w(B)}).on("end",function(){try{var B=function(j,N,ae){switch(j){case"blob":return l.newBlob(l.transformTo("arraybuffer",N),ae);case"base64":return h.encode(N);default:return l.transformTo(j,N)}}(U,function(j,N){var ae,ce=0,xe=null,Y=0;for(ae=0;ae<N.length;ae++)Y+=N[ae].length;switch(j){case"string":return N.join("");case"array":return Array.prototype.concat.apply([],N);case"uint8array":for(xe=new Uint8Array(Y),ae=0;ae<N.length;ae++)xe.set(N[ae],ce),ce+=N[ae].length;return xe;case"nodebuffer":return Buffer.concat(N);default:throw new Error("concat : unsupported type '"+j+"'")}}(I,b),z);C(B)}catch(j){w(j)}b=[]}).resume()})}function T(O,S,C){var w=S;switch(S){case"blob":case"arraybuffer":w="uint8array";break;case"base64":w="string"}try{this._internalType=w,this._outputType=S,this._mimeType=C,l.checkSupport(w),this._worker=O.pipe(new p(w)),O.lock()}catch(b){this._worker=new _("error"),this._worker.error(b)}}T.prototype={accumulate:function(O){return E(this,O)},on:function(O,S){var C=this;return O==="data"?this._worker.on(O,function(w){S.call(C,w.data,w.meta)}):this._worker.on(O,function(){l.delay(S,arguments,C)}),this},resume:function(){return l.delay(this._worker.resume,[],this._worker),this},pause:function(){return this._worker.pause(),this},toNodejsStream:function(O){if(l.checkSupport("nodestream"),this._outputType!=="nodebuffer")throw new Error(this._outputType+" is not supported by this method");return new y(this,{objectMode:this._outputType!=="nodebuffer"},O)}},o.exports=T},{"../base64":1,"../external":6,"../nodejs/NodejsStreamOutputAdapter":13,"../support":30,"../utils":32,"./ConvertWorker":24,"./GenericWorker":28}],30:[function(r,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 p=new(self.BlobBuilder||self.WebKitBlobBuilder||self.MozBlobBuilder||self.MSBlobBuilder);p.append(l),a.blob=p.getBlob("application/zip").size===0}catch{a.blob=!1}}}try{a.nodestream=!!r("readable-stream").Readable}catch{a.nodestream=!1}},{"readable-stream":16}],31:[function(r,o,a){for(var l=r("./utils"),p=r("./support"),_=r("./nodejsUtils"),h=r("./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 y(){h.call(this,"utf-8 decode"),this.leftOver=null}function E(){h.call(this,"utf-8 encode")}a.utf8encode=function(T){return p.nodebuffer?_.newBufferFrom(T,"utf-8"):function(O){var S,C,w,b,I,U=O.length,z=0;for(b=0;b<U;b++)(64512&(C=O.charCodeAt(b)))==55296&&b+1<U&&(64512&(w=O.charCodeAt(b+1)))==56320&&(C=65536+(C-55296<<10)+(w-56320),b++),z+=C<128?1:C<2048?2:C<65536?3:4;for(S=p.uint8array?new Uint8Array(z):new Array(z),b=I=0;I<z;b++)(64512&(C=O.charCodeAt(b)))==55296&&b+1<U&&(64512&(w=O.charCodeAt(b+1)))==56320&&(C=65536+(C-55296<<10)+(w-56320),b++),C<128?S[I++]=C:(C<2048?S[I++]=192|C>>>6:(C<65536?S[I++]=224|C>>>12:(S[I++]=240|C>>>18,S[I++]=128|C>>>12&63),S[I++]=128|C>>>6&63),S[I++]=128|63&C);return S}(T)},a.utf8decode=function(T){return p.nodebuffer?l.transformTo("nodebuffer",T).toString("utf-8"):function(O){var S,C,w,b,I=O.length,U=new Array(2*I);for(S=C=0;S<I;)if((w=O[S++])<128)U[C++]=w;else if(4<(b=g[w]))U[C++]=65533,S+=b-1;else{for(w&=b===2?31:b===3?15:7;1<b&&S<I;)w=w<<6|63&O[S++],b--;1<b?U[C++]=65533:w<65536?U[C++]=w:(w-=65536,U[C++]=55296|w>>10&1023,U[C++]=56320|1023&w)}return U.length!==C&&(U.subarray?U=U.subarray(0,C):U.length=C),l.applyFromCharCode(U)}(T=l.transformTo(p.uint8array?"uint8array":"array",T))},l.inherits(y,h),y.prototype.processChunk=function(T){var O=l.transformTo(p.uint8array?"uint8array":"array",T.data);if(this.leftOver&&this.leftOver.length){if(p.uint8array){var S=O;(O=new Uint8Array(S.length+this.leftOver.length)).set(this.leftOver,0),O.set(S,this.leftOver.length)}else O=this.leftOver.concat(O);this.leftOver=null}var C=function(b,I){var U;for((I=I||b.length)>b.length&&(I=b.length),U=I-1;0<=U&&(192&b[U])==128;)U--;return U<0||U===0?I:U+g[b[U]]>I?U:I}(O),w=O;C!==O.length&&(p.uint8array?(w=O.subarray(0,C),this.leftOver=O.subarray(C,O.length)):(w=O.slice(0,C),this.leftOver=O.slice(C,O.length))),this.push({data:a.utf8decode(w),meta:T.meta})},y.prototype.flush=function(){this.leftOver&&this.leftOver.length&&(this.push({data:a.utf8decode(this.leftOver),meta:{}}),this.leftOver=null)},a.Utf8DecodeWorker=y,l.inherits(E,h),E.prototype.processChunk=function(T){this.push({data:a.utf8encode(T.data),meta:T.meta})},a.Utf8EncodeWorker=E},{"./nodejsUtils":14,"./stream/GenericWorker":28,"./support":30,"./utils":32}],32:[function(r,o,a){var l=r("./support"),p=r("./base64"),_=r("./nodejsUtils"),h=r("./external");function g(S){return S}function M(S,C){for(var w=0;w<S.length;++w)C[w]=255&S.charCodeAt(w);return C}r("setimmediate"),a.newBlob=function(S,C){a.checkSupport("blob");try{return new Blob([S],{type:C})}catch{try{var w=new(self.BlobBuilder||self.WebKitBlobBuilder||self.MozBlobBuilder||self.MSBlobBuilder);return w.append(S),w.getBlob(C)}catch{throw new Error("Bug : can't construct the Blob.")}}};var y={stringifyByChunk:function(S,C,w){var b=[],I=0,U=S.length;if(U<=w)return String.fromCharCode.apply(null,S);for(;I<U;)C==="array"||C==="nodebuffer"?b.push(String.fromCharCode.apply(null,S.slice(I,Math.min(I+w,U)))):b.push(String.fromCharCode.apply(null,S.subarray(I,Math.min(I+w,U)))),I+=w;return b.join("")},stringifyByChar:function(S){for(var C="",w=0;w<S.length;w++)C+=String.fromCharCode(S[w]);return C},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 E(S){var C=65536,w=a.getTypeOf(S),b=!0;if(w==="uint8array"?b=y.applyCanBeUsed.uint8array:w==="nodebuffer"&&(b=y.applyCanBeUsed.nodebuffer),b)for(;1<C;)try{return y.stringifyByChunk(S,w,C)}catch{C=Math.floor(C/2)}return y.stringifyByChar(S)}function T(S,C){for(var w=0;w<S.length;w++)C[w]=S[w];return C}a.applyFromCharCode=E;var O={};O.string={string:g,array:function(S){return M(S,new Array(S.length))},arraybuffer:function(S){return O.string.uint8array(S).buffer},uint8array:function(S){return M(S,new Uint8Array(S.length))},nodebuffer:function(S){return M(S,_.allocBuffer(S.length))}},O.array={string:E,array:g,arraybuffer:function(S){return new Uint8Array(S).buffer},uint8array:function(S){return new Uint8Array(S)},nodebuffer:function(S){return _.newBufferFrom(S)}},O.arraybuffer={string:function(S){return E(new Uint8Array(S))},array:function(S){return T(new Uint8Array(S),new Array(S.byteLength))},arraybuffer:g,uint8array:function(S){return new Uint8Array(S)},nodebuffer:function(S){return _.newBufferFrom(new Uint8Array(S))}},O.uint8array={string:E,array:function(S){return T(S,new Array(S.length))},arraybuffer:function(S){return S.buffer},uint8array:g,nodebuffer:function(S){return _.newBufferFrom(S)}},O.nodebuffer={string:E,array:function(S){return T(S,new Array(S.length))},arraybuffer:function(S){return O.nodebuffer.uint8array(S).buffer},uint8array:function(S){return T(S,new Uint8Array(S.length))},nodebuffer:g},a.transformTo=function(S,C){if(C=C||"",!S)return C;a.checkSupport(S);var w=a.getTypeOf(C);return O[w][S](C)},a.resolve=function(S){for(var C=S.split("/"),w=[],b=0;b<C.length;b++){var I=C[b];I==="."||I===""&&b!==0&&b!==C.length-1||(I===".."?w.pop():w.push(I))}return w.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 C,w,b="";for(w=0;w<(S||"").length;w++)b+="\\x"+((C=S.charCodeAt(w))<16?"0":"")+C.toString(16).toUpperCase();return b},a.delay=function(S,C,w){setImmediate(function(){S.apply(w||null,C||[])})},a.inherits=function(S,C){function w(){}w.prototype=C.prototype,S.prototype=new w},a.extend=function(){var S,C,w={};for(S=0;S<arguments.length;S++)for(C in arguments[S])Object.prototype.hasOwnProperty.call(arguments[S],C)&&w[C]===void 0&&(w[C]=arguments[S][C]);return w},a.prepareContent=function(S,C,w,b,I){return h.Promise.resolve(C).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(z,B){var j=new FileReader;j.onload=function(N){z(N.target.result)},j.onerror=function(N){B(N.target.error)},j.readAsArrayBuffer(U)}):U}).then(function(U){var z=a.getTypeOf(U);return z?(z==="arraybuffer"?U=a.transformTo("uint8array",U):z==="string"&&(I?U=p.decode(U):w&&b!==!0&&(U=function(B){return M(B,l.uint8array?new Uint8Array(B.length):new Array(B.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(r,o,a){var l=r("./reader/readerFor"),p=r("./utils"),_=r("./signature"),h=r("./zipEntry"),g=r("./support");function M(y){this.files=[],this.loadOptions=y}M.prototype={checkSignature:function(y){if(!this.reader.readAndCheckSignature(y)){this.reader.index-=4;var E=this.reader.readString(4);throw new Error("Corrupted zip or bug: unexpected signature ("+p.pretty(E)+", expected "+p.pretty(y)+")")}},isSignature:function(y,E){var T=this.reader.index;this.reader.setIndex(y);var O=this.reader.readString(4)===E;return this.reader.setIndex(T),O},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 y=this.reader.readData(this.zipCommentLength),E=g.uint8array?"uint8array":"array",T=p.transformTo(E,y);this.zipComment=this.loadOptions.decodeFileName(T)},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 y,E,T,O=this.zip64EndOfCentralSize-44;0<O;)y=this.reader.readInt(2),E=this.reader.readInt(4),T=this.reader.readData(E),this.zip64ExtensibleData[y]={id:y,length:E,value:T}},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 y,E;for(y=0;y<this.files.length;y++)E=this.files[y],this.reader.setIndex(E.localHeaderOffset),this.checkSignature(_.LOCAL_FILE_HEADER),E.readLocalPart(this.reader),E.handleUTF8(),E.processAttributes()},readCentralDir:function(){var y;for(this.reader.setIndex(this.centralDirOffset);this.reader.readAndCheckSignature(_.CENTRAL_FILE_HEADER);)(y=new h({zip64:this.zip64},this.loadOptions)).readCentralPart(this.reader),this.files.push(y);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 y=this.reader.lastIndexOfSignature(_.CENTRAL_DIRECTORY_END);if(y<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(y);var E=y;if(this.checkSignature(_.CENTRAL_DIRECTORY_END),this.readBlockEndOfCentral(),this.diskNumber===p.MAX_VALUE_16BITS||this.diskWithCentralDirStart===p.MAX_VALUE_16BITS||this.centralDirRecordsOnThisDisk===p.MAX_VALUE_16BITS||this.centralDirRecords===p.MAX_VALUE_16BITS||this.centralDirSize===p.MAX_VALUE_32BITS||this.centralDirOffset===p.MAX_VALUE_32BITS){if(this.zip64=!0,(y=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(y),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 T=this.centralDirOffset+this.centralDirSize;this.zip64&&(T+=20,T+=12+this.zip64EndOfCentralSize);var O=E-T;if(0<O)this.isSignature(E,_.CENTRAL_FILE_HEADER)||(this.reader.zero=O);else if(O<0)throw new Error("Corrupted zip: missing "+Math.abs(O)+" bytes.")},prepareReader:function(y){this.reader=l(y)},load:function(y){this.prepareReader(y),this.readEndOfCentral(),this.readCentralDir(),this.readLocalFiles()}},o.exports=M},{"./reader/readerFor":22,"./signature":23,"./support":30,"./utils":32,"./zipEntry":34}],34:[function(r,o,a){var l=r("./reader/readerFor"),p=r("./utils"),_=r("./compressedObject"),h=r("./crc32"),g=r("./utf8"),M=r("./compressions"),y=r("./support");function E(T,O){this.options=T,this.loadOptions=O}E.prototype={isEncrypted:function(){return(1&this.bitFlag)==1},useUTF8:function(){return(2048&this.bitFlag)==2048},readLocalPart:function(T){var O,S;if(T.skip(22),this.fileNameLength=T.readInt(2),S=T.readInt(2),this.fileName=T.readData(this.fileNameLength),T.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((O=function(C){for(var w in M)if(Object.prototype.hasOwnProperty.call(M,w)&&M[w].magic===C)return M[w];return null}(this.compressionMethod))===null)throw new Error("Corrupted zip : compression "+p.pretty(this.compressionMethod)+" unknown (inner file : "+p.transformTo("string",this.fileName)+")");this.decompressed=new _(this.compressedSize,this.uncompressedSize,this.crc32,O,T.readData(this.compressedSize))},readCentralPart:function(T){this.versionMadeBy=T.readInt(2),T.skip(2),this.bitFlag=T.readInt(2),this.compressionMethod=T.readString(2),this.date=T.readDate(),this.crc32=T.readInt(4),this.compressedSize=T.readInt(4),this.uncompressedSize=T.readInt(4);var O=T.readInt(2);if(this.extraFieldsLength=T.readInt(2),this.fileCommentLength=T.readInt(2),this.diskNumberStart=T.readInt(2),this.internalFileAttributes=T.readInt(2),this.externalFileAttributes=T.readInt(4),this.localHeaderOffset=T.readInt(4),this.isEncrypted())throw new Error("Encrypted zip are not 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O,S,C,w=T.index+this.extraFieldsLength;for(this.extraFields||(this.extraFields={});T.index+4<w;)O=T.readInt(2),S=T.readInt(2),C=T.readData(S),this.extraFields[O]={id:O,length:S,value:C};T.setIndex(w)},handleUTF8:function(){var T=y.uint8array?"uint8array":"array";if(this.useUTF8())this.fileNameStr=g.utf8decode(this.fileName),this.fileCommentStr=g.utf8decode(this.fileComment);else{var O=this.findExtraFieldUnicodePath();if(O!==null)this.fileNameStr=O;else{var S=p.transformTo(T,this.fileName);this.fileNameStr=this.loadOptions.decodeFileName(S)}var C=this.findExtraFieldUnicodeComment();if(C!==null)this.fileCommentStr=C;else{var w=p.transformTo(T,this.fileComment);this.fileCommentStr=this.loadOptions.decodeFileName(w)}}},findExtraFieldUnicodePath:function(){var T=this.extraFields[28789];if(T){var O=l(T.value);return O.readInt(1)!==1||h(this.fileName)!==O.readInt(4)?null:g.utf8decode(O.readData(T.length-5))}return null},findExtraFieldUnicodeComment:function(){var 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L;if(D.lookahead===0)break}if(D.match_length=0,D.lookahead>=ae&&0<D.strstart&&(ke=Je[Ne=D.strstart-1])===Je[++Ne]&&ke===Je[++Ne]&&ke===Je[++Ne]){dt=D.strstart+ce;do;while(ke===Je[++Ne]&&ke===Je[++Ne]&&ke===Je[++Ne]&&ke===Je[++Ne]&&ke===Je[++Ne]&&ke===Je[++Ne]&&ke===Je[++Ne]&&ke===Je[++Ne]&&Ne<dt);D.match_length=ce-(dt-Ne),D.match_length>D.lookahead&&(D.match_length=D.lookahead)}if(D.match_length>=ae?(le=_._tr_tally(D,1,D.match_length-ae),D.lookahead-=D.match_length,D.strstart+=D.match_length,D.match_length=0):(le=_._tr_tally(D,0,D.window[D.strstart]),D.lookahead--,D.strstart++),le&&(ge(D,!1),D.strm.avail_out===0))return L}return D.insert=0,ue===E?(ge(D,!0),D.strm.avail_out===0?Xe:me):D.last_lit&&(ge(D,!1),D.strm.avail_out===0)?L:Se}(se,$e):l[se.level].func(se,$e);if(ee!==Xe&&ee!==me||(se.status=666),ee===L||ee===Xe)return A.avail_out===0&&(se.last_flush=-1),T;if(ee===Se&&($e===1?_._tr_align(se):$e!==5&&(_._tr_stored_block(se,0,0,!1),$e===3&&(Me(se.head),se.lookahead===0&&(se.strstart=0,se.block_start=0,se.insert=0))),Q(A),A.avail_out===0))return se.last_flush=-1,T}return $e!==E?T:se.wrap<=0?1:(se.wrap===2?(Ke(se,255&A.adler),Ke(se,A.adler>>8&255),Ke(se,A.adler>>16&255),Ke(se,A.adler>>24&255),Ke(se,255&A.total_in),Ke(se,A.total_in>>8&255),Ke(se,A.total_in>>16&255),Ke(se,A.total_in>>24&255)):(Le(se,A.adler>>>16),Le(se,65535&A.adler)),Q(A),0<se.wrap&&(se.wrap=-se.wrap),se.pending!==0?T:1)},a.deflateEnd=function(A){var $e;return A&&A.state?($e=A.state.status)!==Y&&$e!==69&&$e!==73&&$e!==91&&$e!==103&&$e!==_e&&$e!==666?X(A,O):(A.state=null,$e===_e?X(A,-3):T):O},a.deflateSetDictionary=function(A,$e){var Pe,se,re,ye,R,ee,D,ue,le=$e.length;if(!A||!A.state||(ye=(Pe=A.state).wrap)===2||ye===1&&Pe.status!==Y||Pe.lookahead)return O;for(ye===1&&(A.adler=h(A.adler,$e,le,0)),Pe.wrap=0,le>=Pe.w_size&&(ye===0&&(Me(Pe.head),Pe.strstart=0,Pe.block_start=0,Pe.insert=0),ue=new p.Buf8(Pe.w_size),p.arraySet(ue,$e,le-Pe.w_size,Pe.w_size,0),$e=ue,le=Pe.w_size),R=A.avail_in,ee=A.next_in,D=A.input,A.avail_in=le,A.next_in=0,A.input=$e,We(Pe);Pe.lookahead>=ae;){for(se=Pe.strstart,re=Pe.lookahead-(ae-1);Pe.ins_h=(Pe.ins_h<<Pe.hash_shift^Pe.window[se+ae-1])&Pe.hash_mask,Pe.prev[se&Pe.w_mask]=Pe.head[Pe.ins_h],Pe.head[Pe.ins_h]=se,se++,--re;);Pe.strstart=se,Pe.lookahead=ae-1,We(Pe)}return Pe.strstart+=Pe.lookahead,Pe.block_start=Pe.strstart,Pe.insert=Pe.lookahead,Pe.lookahead=0,Pe.match_length=Pe.prev_length=ae-1,Pe.match_available=0,A.next_in=ee,A.input=D,A.avail_in=R,Pe.wrap=ye,T},a.deflateInfo="pako deflate (from Nodeca project)"},{"../utils/common":41,"./adler32":43,"./crc32":45,"./messages":51,"./trees":52}],47:[function(r,o,a){o.exports=function(){this.text=0,this.time=0,this.xflags=0,this.os=0,this.extra=null,this.extra_len=0,this.name="",this.comment="",this.hcrc=0,this.done=!1}},{}],48:[function(r,o,a){o.exports=function(l,p){var _,h,g,M,y,E,T,O,S,C,w,b,I,U,z,B,j,N,ae,ce,xe,Y,_e,L,Se;_=l.state,h=l.next_in,L=l.input,g=h+(l.avail_in-5),M=l.next_out,Se=l.output,y=M-(p-l.avail_out),E=M+(l.avail_out-257),T=_.dmax,O=_.wsize,S=_.whave,C=_.wnext,w=_.window,b=_.hold,I=_.bits,U=_.lencode,z=_.distcode,B=(1<<_.lenbits)-1,j=(1<<_.distbits)-1;e:do{I<15&&(b+=L[h++]<<I,I+=8,b+=L[h++]<<I,I+=8),N=U[b&B];t:for(;;){if(b>>>=ae=N>>>24,I-=ae,(ae=N>>>16&255)===0)Se[M++]=65535&N;else{if(!(16&ae)){if(!(64&ae)){N=U[(65535&N)+(b&(1<<ae)-1)];continue t}if(32&ae){_.mode=12;break e}l.msg="invalid literal/length code",_.mode=30;break 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e;for(Be=0;A=Se[me+Be++],L.head&&A&&L.length<65536&&(L.head.name+=String.fromCharCode(A)),A&&Be<ie;);if(512&L.flags&&(L.check=_(L.check,Se,Be,me)),ie-=Be,me+=Be,A)break e}else L.head&&(L.head.name=null);L.length=0,L.mode=8;case 8:if(4096&L.flags){if(ie===0)break e;for(Be=0;A=Se[me+Be++],L.head&&A&&L.length<65536&&(L.head.comment+=String.fromCharCode(A)),A&&Be<ie;);if(512&L.flags&&(L.check=_(L.check,Se,Be,me)),ie-=Be,me+=Be,A)break e}else L.head&&(L.head.comment=null);L.mode=9;case 9:if(512&L.flags){for(;ge<16;){if(ie===0)break e;ie--,Q+=Se[me++]<<ge,ge+=8}if(Q!==(65535&L.check)){Y.msg="header crc mismatch",L.mode=30;break}ge=Q=0}L.head&&(L.head.hcrc=L.flags>>9&1,L.head.done=!0),Y.adler=L.check=0,L.mode=12;break;case 10:for(;ge<32;){if(ie===0)break e;ie--,Q+=Se[me++]<<ge,ge+=8}Y.adler=L.check=w(Q),ge=Q=0,L.mode=11;case 11:if(L.havedict===0)return Y.next_out=X,Y.avail_out=Me,Y.next_in=me,Y.avail_in=ie,L.hold=Q,L.bits=ge,2;Y.adler=L.check=1,L.mode=12;case 12:if(_e===5||_e===6)break e;case 13:if(L.last){Q>>>=7&ge,ge-=7&ge,L.mode=27;break}for(;ge<3;){if(ie===0)break e;ie--,Q+=Se[me++]<<ge,ge+=8}switch(L.last=1&Q,ge-=1,3&(Q>>>=1)){case 0:L.mode=14;break;case 1:if(ce(L),L.mode=20,_e!==6)break;Q>>>=2,ge-=2;break e;case 2:L.mode=17;break;case 3:Y.msg="invalid block type",L.mode=30}Q>>>=2,ge-=2;break;case 14:for(Q>>>=7&ge,ge-=7&ge;ge<32;){if(ie===0)break e;ie--,Q+=Se[me++]<<ge,ge+=8}if((65535&Q)!=(Q>>>16^65535)){Y.msg="invalid stored block lengths",L.mode=30;break}if(L.length=65535&Q,ge=Q=0,L.mode=15,_e===6)break e;case 15:L.mode=16;case 16:if(Be=L.length){if(ie<Be&&(Be=ie),Me<Be&&(Be=Me),Be===0)break e;l.arraySet(Xe,Se,me,Be,X),ie-=Be,me+=Be,Me-=Be,X+=Be,L.length-=Be;break}L.mode=12;break;case 17:for(;ge<14;){if(ie===0)break e;ie--,Q+=Se[me++]<<ge,ge+=8}if(L.nlen=257+(31&Q),Q>>>=5,ge-=5,L.ndist=1+(31&Q),Q>>>=5,ge-=5,L.ncode=4+(15&Q),Q>>>=4,ge-=4,286<L.nlen||30<L.ndist){Y.msg="too many length or distance symbols",L.mode=30;break}L.have=0,L.mode=18;case 18:for(;L.have<L.ncode;){for(;ge<3;){if(ie===0)break e;ie--,Q+=Se[me++]<<ge,ge+=8}L.lens[R[L.have++]]=7&Q,Q>>>=3,ge-=3}for(;L.have<19;)L.lens[R[L.have++]]=0;if(L.lencode=L.lendyn,L.lenbits=7,Pe={bits:L.lenbits},$e=g(0,L.lens,0,19,L.lencode,0,L.work,Pe),L.lenbits=Pe.bits,$e){Y.msg="invalid code lengths set",L.mode=30;break}L.have=0,L.mode=19;case 19:for(;L.have<L.nlen+L.ndist;){for(;Ge=(re=L.lencode[Q&(1<<L.lenbits)-1])>>>16&255,Te=65535&re,!((pt=re>>>24)<=ge);){if(ie===0)break e;ie--,Q+=Se[me++]<<ge,ge+=8}if(Te<16)Q>>>=pt,ge-=pt,L.lens[L.have++]=Te;else{if(Te===16){for(se=pt+2;ge<se;){if(ie===0)break e;ie--,Q+=Se[me++]<<ge,ge+=8}if(Q>>>=pt,ge-=pt,L.have===0){Y.msg="invalid bit length repeat",L.mode=30;break}A=L.lens[L.have-1],Be=3+(3&Q),Q>>>=2,ge-=2}else if(Te===17){for(se=pt+3;ge<se;){if(ie===0)break e;ie--,Q+=Se[me++]<<ge,ge+=8}ge-=pt,A=0,Be=3+(7&(Q>>>=pt)),Q>>>=3,ge-=3}else{for(se=pt+7;ge<se;){if(ie===0)break 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23:for(;Ge=(re=L.distcode[Q&(1<<L.distbits)-1])>>>16&255,Te=65535&re,!((pt=re>>>24)<=ge);){if(ie===0)break e;ie--,Q+=Se[me++]<<ge,ge+=8}if(!(240&Ge)){for(je=pt,Ye=Ge,et=Te;Ge=(re=L.distcode[et+((Q&(1<<je+Ye)-1)>>je)])>>>16&255,Te=65535&re,!(je+(pt=re>>>24)<=ge);){if(ie===0)break e;ie--,Q+=Se[me++]<<ge,ge+=8}Q>>>=je,ge-=je,L.back+=je}if(Q>>>=pt,ge-=pt,L.back+=pt,64&Ge){Y.msg="invalid distance code",L.mode=30;break}L.offset=Te,L.extra=15&Ge,L.mode=24;case 24:if(L.extra){for(se=L.extra;ge<se;){if(ie===0)break e;ie--,Q+=Se[me++]<<ge,ge+=8}L.offset+=Q&(1<<L.extra)-1,Q>>>=L.extra,ge-=L.extra,L.back+=L.extra}if(L.offset>L.dmax){Y.msg="invalid distance too far back",L.mode=30;break}L.mode=25;case 25:if(Me===0)break e;if(Be=Le-Me,L.offset>Be){if((Be=L.offset-Be)>L.whave&&L.sane){Y.msg="invalid distance too far back",L.mode=30;break}We=Be>L.wnext?(Be-=L.wnext,L.wsize-Be):L.wnext-Be,Be>L.length&&(Be=L.length),st=L.window}else 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Y.next_out=X,Y.avail_out=Me,Y.next_in=me,Y.avail_in=ie,L.hold=Q,L.bits=ge,(L.wsize||Le!==Y.avail_out&&L.mode<30&&(L.mode<27||_e!==4))&&xe(Y,Y.output,Y.next_out,Le-Y.avail_out)?(L.mode=31,-4):(Ke-=Y.avail_in,Le-=Y.avail_out,Y.total_in+=Ke,Y.total_out+=Le,L.total+=Le,L.wrap&&Le&&(Y.adler=L.check=L.flags?_(L.check,Xe,Le,Y.next_out-Le):p(L.check,Xe,Le,Y.next_out-Le)),Y.data_type=L.bits+(L.last?64:0)+(L.mode===12?128:0)+(L.mode===20||L.mode===15?256:0),(Ke==0&&Le===0||_e===4)&&$e===E&&($e=-5),$e)},a.inflateEnd=function(Y){if(!Y||!Y.state)return T;var _e=Y.state;return _e.window&&(_e.window=null),Y.state=null,E},a.inflateGetHeader=function(Y,_e){var L;return Y&&Y.state&&2&(L=Y.state).wrap?((L.head=_e).done=!1,E):T},a.inflateSetDictionary=function(Y,_e){var L,Se=_e.length;return Y&&Y.state?(L=Y.state).wrap!==0&&L.mode!==11?T:L.mode===11&&p(1,_e,Se,0)!==L.check?-3:xe(Y,_e,Se,Se)?(L.mode=31,-4):(L.havedict=1,E):T},a.inflateInfo="pako inflate (from Nodeca 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R,ee,D,ue=ye.dyn_tree,le=ye.stat_desc.static_tree,ke=ye.stat_desc.has_stree,Ne=ye.stat_desc.elems,dt=-1;for(re.heap_len=0,re.heap_max=S,R=0;R<Ne;R++)ue[2*R]!==0?(re.heap[++re.heap_len]=dt=R,re.depth[R]=0):ue[2*R+1]=0;for(;re.heap_len<2;)ue[2*(D=re.heap[++re.heap_len]=dt<2?++dt:0)]=1,re.depth[D]=0,re.opt_len--,ke&&(re.static_len-=le[2*D+1]);for(ye.max_code=dt,R=re.heap_len>>1;1<=R;R--)je(re,ue,R);for(D=Ne;R=re.heap[1],re.heap[1]=re.heap[re.heap_len--],je(re,ue,1),ee=re.heap[1],re.heap[--re.heap_max]=R,re.heap[--re.heap_max]=ee,ue[2*D]=ue[2*R]+ue[2*ee],re.depth[D]=(re.depth[R]>=re.depth[ee]?re.depth[R]:re.depth[ee])+1,ue[2*R+1]=ue[2*ee+1]=D,re.heap[1]=D++,je(re,ue,1),2<=re.heap_len;);re.heap[--re.heap_max]=re.heap[1],function(Je,Ve){var Z,ve,Re,qe,Qe,tt,ft=Ve.dyn_tree,ht=Ve.max_code,Tt=Ve.stat_desc.static_tree,bt=Ve.stat_desc.has_stree,Et=Ve.stat_desc.extra_bits,Lt=Ve.stat_desc.extra_base,at=Ve.stat_desc.max_length,Ot=0;for(qe=0;qe<=C;qe++)Je.bl_count[qe]=0;for(ft[2*Je.heap[Je.heap_max]+1]=0,Z=Je.heap_max+1;Z<S;Z++)at<(qe=ft[2*ft[2*(ve=Je.heap[Z])+1]+1]+1)&&(qe=at,Ot++),ft[2*ve+1]=qe,ht<ve||(Je.bl_count[qe]++,Qe=0,Lt<=ve&&(Qe=Et[ve-Lt]),tt=ft[2*ve],Je.opt_len+=tt*(qe+Qe),bt&&(Je.static_len+=tt*(Tt[2*ve+1]+Qe)));if(Ot!==0){do{for(qe=at-1;Je.bl_count[qe]===0;)qe--;Je.bl_count[qe]--,Je.bl_count[qe+1]+=2,Je.bl_count[at]--,Ot-=2}while(0<Ot);for(qe=at;qe!==0;qe--)for(ve=Je.bl_count[qe];ve!==0;)ht<(Re=Je.heap[--Z])||(ft[2*Re+1]!==qe&&(Je.opt_len+=(qe-ft[2*Re+1])*ft[2*Re],ft[2*Re+1]=qe),ve--)}}(re,ye),st(ue,dt,re.bl_count)}function A(re,ye,R){var ee,D,ue=-1,le=ye[1],ke=0,Ne=7,dt=4;for(le===0&&(Ne=138,dt=3),ye[2*(R+1)+1]=65535,ee=0;ee<=R;ee++)D=le,le=ye[2*(ee+1)+1],++ke<Ne&&D===le||(ke<dt?re.bl_tree[2*D]+=ke:D!==0?(D!==ue&&re.bl_tree[2*D]++,re.bl_tree[2*U]++):ke<=10?re.bl_tree[2*z]++:re.bl_tree[2*B]++,ue=D,dt=(ke=0)===le?(Ne=138,3):D===le?(Ne=6,3):(Ne=7,4))}function $e(re,ye,R){var ee,D,ue=-1,le=ye[1],ke=0,Ne=7,dt=4;for(le===0&&(Ne=138,dt=3),ee=0;ee<=R;ee++)if(D=le,le=ye[2*(ee+1)+1],!(++ke<Ne&&D===le)){if(ke<dt)for(;Be(re,D,re.bl_tree),--ke!=0;);else D!==0?(D!==ue&&(Be(re,D,re.bl_tree),ke--),Be(re,U,re.bl_tree),Le(re,ke-3,2)):ke<=10?(Be(re,z,re.bl_tree),Le(re,ke-3,3)):(Be(re,B,re.bl_tree),Le(re,ke-11,7));ue=D,dt=(ke=0)===le?(Ne=138,3):D===le?(Ne=6,3):(Ne=7,4)}}h(ie);var Pe=!1;function se(re,ye,R,ee){Le(re,(g<<1)+(ee?1:0),3),function(D,ue,le,ke){Ge(D),Ke(D,le),Ke(D,~le),l.arraySet(D.pending_buf,D.window,ue,le,D.pending),D.pending+=le}(re,ye,R)}a._tr_init=function(re){Pe||(function(){var ye,R,ee,D,ue,le=new 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