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 * ONNX Runtime Web v1.18.0
 * Copyright (c) Microsoft Corporation. All rights reserved.
 * Licensed under the MIT License.
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zt;if(e.gt(this.shru(1)))return Cs;l=zt}else{if(this.eq(nt)){if(e.eq(Er)||e.eq(Ko))return nt;if(e.eq(nt))return Er;var n=this.shr(1);return a=n.div(e).shl(1),a.eq(It)?e.isNegative()?Er:Ko:(i=this.sub(e.mul(a)),l=a.add(i.div(e)),l)}else if(e.eq(nt))return this.unsigned?zt:It;if(this.isNegative())return e.isNegative()?this.neg().div(e.neg()):this.neg().div(e).neg();if(e.isNegative())return this.div(e.neg()).neg();l=It}for(i=this;i.gte(e);){a=Math.max(1,Math.floor(i.toNumber()/e.toNumber()));for(var o=Math.ceil(Math.log(a)/Math.LN2),p=o<=48?1:Un(2,o-48),c=ct(a),t=c.mul(e);t.isNegative()||t.gt(i);)a-=p,c=ct(a,this.unsigned),t=c.mul(e);c.isZero()&&(c=Er),l=l.add(c),i=i.sub(t)}return l},B.div=B.divide,B.modulo=function(e){if(Xe(e)||(e=St(e)),ft){var r=(this.unsigned?ft.rem_u:ft.rem_s)(this.low,this.high,e.low,e.high);return le(r,ft.get_high(),this.unsigned)}return this.sub(this.div(e).mul(e))},B.mod=B.modulo,B.rem=B.modulo,B.not=function(){return 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Xe(e)&&(e=e.toInt()),(e&=63)===0?this:e<32?le(this.low>>>e|this.high<<32-e,this.high>>>e,this.unsigned):e===32?le(this.high,0,this.unsigned):le(this.high>>>e-32,0,this.unsigned)},B.shru=B.shiftRightUnsigned,B.shr_u=B.shiftRightUnsigned,B.rotateLeft=function(e){var r;return Xe(e)&&(e=e.toInt()),(e&=63)===0?this:e===32?le(this.high,this.low,this.unsigned):e<32?(r=32-e,le(this.low<<e|this.high>>>r,this.high<<e|this.low>>>r,this.unsigned)):(e-=32,r=32-e,le(this.high<<e|this.low>>>r,this.low<<e|this.high>>>r,this.unsigned))},B.rotl=B.rotateLeft,B.rotateRight=function(e){var r;return Xe(e)&&(e=e.toInt()),(e&=63)===0?this:e===32?le(this.high,this.low,this.unsigned):e<32?(r=32-e,le(this.high<<r|this.low>>>e,this.low<<r|this.high>>>e,this.unsigned)):(e-=32,r=32-e,le(this.low<<r|this.high>>>e,this.high<<r|this.low>>>e,this.unsigned))},B.rotr=B.rotateRight,B.toSigned=function(){return this.unsigned?le(this.low,this.high,!1):this},B.toUnsigned=function(){return 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u=o.onnx.TensorProto.verify(t.t);if(u)return"t."+u}if(t.g!=null&&t.hasOwnProperty("g")){var u=o.onnx.GraphProto.verify(t.g);if(u)return"g."+u}if(t.sparseTensor!=null&&t.hasOwnProperty("sparseTensor")){var u=o.onnx.SparseTensorProto.verify(t.sparseTensor);if(u)return"sparseTensor."+u}if(t.tp!=null&&t.hasOwnProperty("tp")){var u=o.onnx.TypeProto.verify(t.tp);if(u)return"tp."+u}if(t.floats!=null&&t.hasOwnProperty("floats")){if(!Array.isArray(t.floats))return"floats: array expected";for(var s=0;s<t.floats.length;++s)if(typeof t.floats[s]!="number")return"floats: number[] expected"}if(t.ints!=null&&t.hasOwnProperty("ints")){if(!Array.isArray(t.ints))return"ints: array expected";for(var s=0;s<t.ints.length;++s)if(!n.isInteger(t.ints[s])&&!(t.ints[s]&&n.isInteger(t.ints[s].low)&&n.isInteger(t.ints[s].high)))return"ints: integer|Long[] expected"}if(t.strings!=null&&t.hasOwnProperty("strings")){if(!Array.isArray(t.strings))return"strings: array expected";for(var s=0;s<t.strings.length;++s)if(!(t.strings[s]&&typeof t.strings[s].length=="number"||n.isString(t.strings[s])))return"strings: buffer[] expected"}if(t.tensors!=null&&t.hasOwnProperty("tensors")){if(!Array.isArray(t.tensors))return"tensors: array expected";for(var s=0;s<t.tensors.length;++s){var u=o.onnx.TensorProto.verify(t.tensors[s]);if(u)return"tensors."+u}}if(t.graphs!=null&&t.hasOwnProperty("graphs")){if(!Array.isArray(t.graphs))return"graphs: array expected";for(var s=0;s<t.graphs.length;++s){var u=o.onnx.GraphProto.verify(t.graphs[s]);if(u)return"graphs."+u}}if(t.sparseTensors!=null&&t.hasOwnProperty("sparseTensors")){if(!Array.isArray(t.sparseTensors))return"sparseTensors: array expected";for(var s=0;s<t.sparseTensors.length;++s){var u=o.onnx.SparseTensorProto.verify(t.sparseTensors[s]);if(u)return"sparseTensors."+u}}if(t.typeProtos!=null&&t.hasOwnProperty("typeProtos")){if(!Array.isArray(t.typeProtos))return"typeProtos: array expected";for(var s=0;s<t.typeProtos.length;++s){var u=o.onnx.TypeProto.verify(t.typeProtos[s]);if(u)return"typeProtos."+u}}return null},c.fromObject=function(t){if(t instanceof o.onnx.AttributeProto)return t;var u=new o.onnx.AttributeProto;switch(t.name!=null&&(u.name=String(t.name)),t.refAttrName!=null&&(u.refAttrName=String(t.refAttrName)),t.docString!=null&&(u.docString=String(t.docString)),t.type){default:if(typeof t.type=="number"){u.type=t.type;break}break;case"UNDEFINED":case 0:u.type=0;break;case"FLOAT":case 1:u.type=1;break;case"INT":case 2:u.type=2;break;case"STRING":case 3:u.type=3;break;case"TENSOR":case 4:u.type=4;break;case"GRAPH":case 5:u.type=5;break;case"SPARSE_TENSOR":case 11:u.type=11;break;case"TYPE_PROTO":case 13:u.type=13;break;case"FLOATS":case 6:u.type=6;break;case"INTS":case 7:u.type=7;break;case"STRINGS":case 8:u.type=8;break;case"TENSORS":case 9:u.type=9;break;case"GRAPHS":case 10:u.type=10;break;case"SPARSE_TENSORS":case 12:u.type=12;break;case"TYPE_PROTOS":case 14:u.type=14;break}if(t.f!=null&&(u.f=Number(t.f)),t.i!=null&&(n.Long?(u.i=n.Long.fromValue(t.i)).unsigned=!1:typeof t.i=="string"?u.i=parseInt(t.i,10):typeof t.i=="number"?u.i=t.i:typeof t.i=="object"&&(u.i=new n.LongBits(t.i.low>>>0,t.i.high>>>0).toNumber())),t.s!=null&&(typeof t.s=="string"?n.base64.decode(t.s,u.s=n.newBuffer(n.base64.length(t.s)),0):t.s.length>=0&&(u.s=t.s)),t.t!=null){if(typeof t.t!="object")throw TypeError(".onnx.AttributeProto.t: object expected");u.t=o.onnx.TensorProto.fromObject(t.t)}if(t.g!=null){if(typeof t.g!="object")throw TypeError(".onnx.AttributeProto.g: object expected");u.g=o.onnx.GraphProto.fromObject(t.g)}if(t.sparseTensor!=null){if(typeof t.sparseTensor!="object")throw TypeError(".onnx.AttributeProto.sparseTensor: object expected");u.sparseTensor=o.onnx.SparseTensorProto.fromObject(t.sparseTensor)}if(t.tp!=null){if(typeof t.tp!="object")throw TypeError(".onnx.AttributeProto.tp: object 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t.strings[s]=="string"?n.base64.decode(t.strings[s],u.strings[s]=n.newBuffer(n.base64.length(t.strings[s])),0):t.strings[s].length>=0&&(u.strings[s]=t.strings[s])}if(t.tensors){if(!Array.isArray(t.tensors))throw TypeError(".onnx.AttributeProto.tensors: array expected");u.tensors=[];for(var s=0;s<t.tensors.length;++s){if(typeof t.tensors[s]!="object")throw TypeError(".onnx.AttributeProto.tensors: object expected");u.tensors[s]=o.onnx.TensorProto.fromObject(t.tensors[s])}}if(t.graphs){if(!Array.isArray(t.graphs))throw TypeError(".onnx.AttributeProto.graphs: array expected");u.graphs=[];for(var s=0;s<t.graphs.length;++s){if(typeof t.graphs[s]!="object")throw TypeError(".onnx.AttributeProto.graphs: object expected");u.graphs[s]=o.onnx.GraphProto.fromObject(t.graphs[s])}}if(t.sparseTensors){if(!Array.isArray(t.sparseTensors))throw TypeError(".onnx.AttributeProto.sparseTensors: array expected");u.sparseTensors=[];for(var s=0;s<t.sparseTensors.length;++s){if(typeof t.sparseTensors[s]!="object")throw TypeError(".onnx.AttributeProto.sparseTensors: object expected");u.sparseTensors[s]=o.onnx.SparseTensorProto.fromObject(t.sparseTensors[s])}}if(t.typeProtos){if(!Array.isArray(t.typeProtos))throw TypeError(".onnx.AttributeProto.typeProtos: array expected");u.typeProtos=[];for(var s=0;s<t.typeProtos.length;++s){if(typeof t.typeProtos[s]!="object")throw TypeError(".onnx.AttributeProto.typeProtos: object expected");u.typeProtos[s]=o.onnx.TypeProto.fromObject(t.typeProtos[s])}}return u},c.toObject=function(t,u){u||(u={});var s={};if((u.arrays||u.defaults)&&(s.floats=[],s.ints=[],s.strings=[],s.tensors=[],s.graphs=[],s.typeProtos=[],s.sparseTensors=[]),u.defaults){if(s.name="",s.f=0,n.Long){var d=new n.Long(0,0,!1);s.i=u.longs===String?d.toString():u.longs===Number?d.toNumber():d}else s.i=u.longs===String?"0":0;u.bytes===String?s.s="":(s.s=[],u.bytes!==Array&&(s.s=n.newBuffer(s.s))),s.t=null,s.g=null,s.docString="",s.tp=null,s.type=u.enums===String?"UNDEFINED":0,s.refAttrName="",s.sparseTensor=null}if(t.name!=null&&t.hasOwnProperty("name")&&(s.name=t.name),t.f!=null&&t.hasOwnProperty("f")&&(s.f=u.json&&!isFinite(t.f)?String(t.f):t.f),t.i!=null&&t.hasOwnProperty("i")&&(typeof t.i=="number"?s.i=u.longs===String?String(t.i):t.i:s.i=u.longs===String?n.Long.prototype.toString.call(t.i):u.longs===Number?new n.LongBits(t.i.low>>>0,t.i.high>>>0).toNumber():t.i),t.s!=null&&t.hasOwnProperty("s")&&(s.s=u.bytes===String?n.base64.encode(t.s,0,t.s.length):u.bytes===Array?Array.prototype.slice.call(t.s):t.s),t.t!=null&&t.hasOwnProperty("t")&&(s.t=o.onnx.TensorProto.toObject(t.t,u)),t.g!=null&&t.hasOwnProperty("g")&&(s.g=o.onnx.GraphProto.toObject(t.g,u)),t.floats&&t.floats.length){s.floats=[];for(var f=0;f<t.floats.length;++f)s.floats[f]=u.json&&!isFinite(t.floats[f])?String(t.floats[f]):t.floats[f]}if(t.ints&&t.ints.length){s.ints=[];for(var f=0;f<t.ints.length;++f)typeof t.ints[f]=="number"?s.ints[f]=u.longs===String?String(t.ints[f]):t.ints[f]:s.ints[f]=u.longs===String?n.Long.prototype.toString.call(t.ints[f]):u.longs===Number?new n.LongBits(t.ints[f].low>>>0,t.ints[f].high>>>0).toNumber():t.ints[f]}if(t.strings&&t.strings.length){s.strings=[];for(var f=0;f<t.strings.length;++f)s.strings[f]=u.bytes===String?n.base64.encode(t.strings[f],0,t.strings[f].length):u.bytes===Array?Array.prototype.slice.call(t.strings[f]):t.strings[f]}if(t.tensors&&t.tensors.length){s.tensors=[];for(var f=0;f<t.tensors.length;++f)s.tensors[f]=o.onnx.TensorProto.toObject(t.tensors[f],u)}if(t.graphs&&t.graphs.length){s.graphs=[];for(var f=0;f<t.graphs.length;++f)s.graphs[f]=o.onnx.GraphProto.toObject(t.graphs[f],u)}if(t.docString!=null&&t.hasOwnProperty("docString")&&(s.docString=t.docString),t.tp!=null&&t.hasOwnProperty("tp")&&(s.tp=o.onnx.TypeProto.toObject(t.tp,u)),t.typeProtos&&t.typeProtos.length){s.typeProtos=[];for(var f=0;f<t.typeProtos.length;++f)s.typeProtos[f]=o.onnx.TypeProto.toObject(t.typeProtos[f],u)}if(t.type!=null&&t.hasOwnProperty("type")&&(s.type=u.enums===String?o.onnx.AttributeProto.AttributeType[t.type]===void 0?t.type:o.onnx.AttributeProto.AttributeType[t.type]:t.type),t.refAttrName!=null&&t.hasOwnProperty("refAttrName")&&(s.refAttrName=t.refAttrName),t.sparseTensor!=null&&t.hasOwnProperty("sparseTensor")&&(s.sparseTensor=o.onnx.SparseTensorProto.toObject(t.sparseTensor,u)),t.sparseTensors&&t.sparseTensors.length){s.sparseTensors=[];for(var f=0;f<t.sparseTensors.length;++f)s.sparseTensors[f]=o.onnx.SparseTensorProto.toObject(t.sparseTensors[f],u)}return s},c.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},c.getTypeUrl=function(t){return t===void 0&&(t="type.googleapis.com"),t+"/onnx.AttributeProto"},c.AttributeType=function(){var t={},u=Object.create(t);return u[t[0]="UNDEFINED"]=0,u[t[1]="FLOAT"]=1,u[t[2]="INT"]=2,u[t[3]="STRING"]=3,u[t[4]="TENSOR"]=4,u[t[5]="GRAPH"]=5,u[t[11]="SPARSE_TENSOR"]=11,u[t[13]="TYPE_PROTO"]=13,u[t[6]="FLOATS"]=6,u[t[7]="INTS"]=7,u[t[8]="STRINGS"]=8,u[t[9]="TENSORS"]=9,u[t[10]="GRAPHS"]=10,u[t[12]="SPARSE_TENSORS"]=12,u[t[14]="TYPE_PROTOS"]=14,u}(),c}(),p.ValueInfoProto=function(){function c(t){if(t)for(var u=Object.keys(t),s=0;s<u.length;++s)t[u[s]]!=null&&(this[u[s]]=t[u[s]])}return c.prototype.name="",c.prototype.type=null,c.prototype.docString="",c.create=function(t){return new c(t)},c.encode=function(t,u){return u||(u=l.create()),t.name!=null&&Object.hasOwnProperty.call(t,"name")&&u.uint32(10).string(t.name),t.type!=null&&Object.hasOwnProperty.call(t,"type")&&o.onnx.TypeProto.encode(t.type,u.uint32(18).fork()).ldelim(),t.docString!=null&&Object.hasOwnProperty.call(t,"docString")&&u.uint32(26).string(t.docString),u},c.encodeDelimited=function(t,u){return this.encode(t,u).ldelim()},c.decode=function(t,u){t instanceof i||(t=i.create(t));for(var s=u===void 0?t.len:t.pos+u,d=new o.onnx.ValueInfoProto;t.pos<s;){var f=t.uint32();switch(f>>>3){case 1:{d.name=t.string();break}case 2:{d.type=o.onnx.TypeProto.decode(t,t.uint32());break}case 3:{d.docString=t.string();break}default:t.skipType(f&7);break}}return d},c.decodeDelimited=function(t){return t instanceof i||(t=new i(t)),this.decode(t,t.uint32())},c.verify=function(t){if(typeof t!="object"||t===null)return"object expected";if(t.name!=null&&t.hasOwnProperty("name")&&!n.isString(t.name))return"name: string 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this.constructor.toObject(this,a.util.toJSONOptions)},c.getTypeUrl=function(t){return t===void 0&&(t="type.googleapis.com"),t+"/onnx.ValueInfoProto"},c}(),p.NodeProto=function(){function c(t){if(this.input=[],this.output=[],this.attribute=[],t)for(var u=Object.keys(t),s=0;s<u.length;++s)t[u[s]]!=null&&(this[u[s]]=t[u[s]])}return c.prototype.input=n.emptyArray,c.prototype.output=n.emptyArray,c.prototype.name="",c.prototype.opType="",c.prototype.domain="",c.prototype.attribute=n.emptyArray,c.prototype.docString="",c.create=function(t){return new c(t)},c.encode=function(t,u){if(u||(u=l.create()),t.input!=null&&t.input.length)for(var s=0;s<t.input.length;++s)u.uint32(10).string(t.input[s]);if(t.output!=null&&t.output.length)for(var s=0;s<t.output.length;++s)u.uint32(18).string(t.output[s]);if(t.name!=null&&Object.hasOwnProperty.call(t,"name")&&u.uint32(26).string(t.name),t.opType!=null&&Object.hasOwnProperty.call(t,"opType")&&u.uint32(34).string(t.opType),t.attribute!=null&&t.attribute.length)for(var s=0;s<t.attribute.length;++s)o.onnx.AttributeProto.encode(t.attribute[s],u.uint32(42).fork()).ldelim();return t.docString!=null&&Object.hasOwnProperty.call(t,"docString")&&u.uint32(50).string(t.docString),t.domain!=null&&Object.hasOwnProperty.call(t,"domain")&&u.uint32(58).string(t.domain),u},c.encodeDelimited=function(t,u){return this.encode(t,u).ldelim()},c.decode=function(t,u){t instanceof i||(t=i.create(t));for(var s=u===void 0?t.len:t.pos+u,d=new o.onnx.NodeProto;t.pos<s;){var f=t.uint32();switch(f>>>3){case 1:{d.input&&d.input.length||(d.input=[]),d.input.push(t.string());break}case 2:{d.output&&d.output.length||(d.output=[]),d.output.push(t.string());break}case 3:{d.name=t.string();break}case 4:{d.opType=t.string();break}case 7:{d.domain=t.string();break}case 5:{d.attribute&&d.attribute.length||(d.attribute=[]),d.attribute.push(o.onnx.AttributeProto.decode(t,t.uint32()));break}case 6:{d.docString=t.string();break}default:t.skipType(f&7);break}}return d},c.decodeDelimited=function(t){return t instanceof i||(t=new i(t)),this.decode(t,t.uint32())},c.verify=function(t){if(typeof t!="object"||t===null)return"object expected";if(t.input!=null&&t.hasOwnProperty("input")){if(!Array.isArray(t.input))return"input: array expected";for(var u=0;u<t.input.length;++u)if(!n.isString(t.input[u]))return"input: string[] expected"}if(t.output!=null&&t.hasOwnProperty("output")){if(!Array.isArray(t.output))return"output: array expected";for(var u=0;u<t.output.length;++u)if(!n.isString(t.output[u]))return"output: string[] expected"}if(t.name!=null&&t.hasOwnProperty("name")&&!n.isString(t.name))return"name: string expected";if(t.opType!=null&&t.hasOwnProperty("opType")&&!n.isString(t.opType))return"opType: string expected";if(t.domain!=null&&t.hasOwnProperty("domain")&&!n.isString(t.domain))return"domain: string expected";if(t.attribute!=null&&t.hasOwnProperty("attribute")){if(!Array.isArray(t.attribute))return"attribute: array expected";for(var u=0;u<t.attribute.length;++u){var s=o.onnx.AttributeProto.verify(t.attribute[u]);if(s)return"attribute."+s}}return t.docString!=null&&t.hasOwnProperty("docString")&&!n.isString(t.docString)?"docString: string expected":null},c.fromObject=function(t){if(t instanceof o.onnx.NodeProto)return t;var u=new o.onnx.NodeProto;if(t.input){if(!Array.isArray(t.input))throw TypeError(".onnx.NodeProto.input: array expected");u.input=[];for(var s=0;s<t.input.length;++s)u.input[s]=String(t.input[s])}if(t.output){if(!Array.isArray(t.output))throw TypeError(".onnx.NodeProto.output: array expected");u.output=[];for(var s=0;s<t.output.length;++s)u.output[s]=String(t.output[s])}if(t.name!=null&&(u.name=String(t.name)),t.opType!=null&&(u.opType=String(t.opType)),t.domain!=null&&(u.domain=String(t.domain)),t.attribute){if(!Array.isArray(t.attribute))throw TypeError(".onnx.NodeProto.attribute: array expected");u.attribute=[];for(var s=0;s<t.attribute.length;++s){if(typeof t.attribute[s]!="object")throw TypeError(".onnx.NodeProto.attribute: object expected");u.attribute[s]=o.onnx.AttributeProto.fromObject(t.attribute[s])}}return t.docString!=null&&(u.docString=String(t.docString)),u},c.toObject=function(t,u){u||(u={});var s={};if((u.arrays||u.defaults)&&(s.input=[],s.output=[],s.attribute=[]),u.defaults&&(s.name="",s.opType="",s.docString="",s.domain=""),t.input&&t.input.length){s.input=[];for(var d=0;d<t.input.length;++d)s.input[d]=t.input[d]}if(t.output&&t.output.length){s.output=[];for(var d=0;d<t.output.length;++d)s.output[d]=t.output[d]}if(t.name!=null&&t.hasOwnProperty("name")&&(s.name=t.name),t.opType!=null&&t.hasOwnProperty("opType")&&(s.opType=t.opType),t.attribute&&t.attribute.length){s.attribute=[];for(var d=0;d<t.attribute.length;++d)s.attribute[d]=o.onnx.AttributeProto.toObject(t.attribute[d],u)}return t.docString!=null&&t.hasOwnProperty("docString")&&(s.docString=t.docString),t.domain!=null&&t.hasOwnProperty("domain")&&(s.domain=t.domain),s},c.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},c.getTypeUrl=function(t){return t===void 0&&(t="type.googleapis.com"),t+"/onnx.NodeProto"},c}(),p.TrainingInfoProto=function(){function c(t){if(this.initializationBinding=[],this.updateBinding=[],t)for(var u=Object.keys(t),s=0;s<u.length;++s)t[u[s]]!=null&&(this[u[s]]=t[u[s]])}return c.prototype.initialization=null,c.prototype.algorithm=null,c.prototype.initializationBinding=n.emptyArray,c.prototype.updateBinding=n.emptyArray,c.create=function(t){return new c(t)},c.encode=function(t,u){if(u||(u=l.create()),t.initialization!=null&&Object.hasOwnProperty.call(t,"initialization")&&o.onnx.GraphProto.encode(t.initialization,u.uint32(10).fork()).ldelim(),t.algorithm!=null&&Object.hasOwnProperty.call(t,"algorithm")&&o.onnx.GraphProto.encode(t.algorithm,u.uint32(18).fork()).ldelim(),t.initializationBinding!=null&&t.initializationBinding.length)for(var s=0;s<t.initializationBinding.length;++s)o.onnx.StringStringEntryProto.encode(t.initializationBinding[s],u.uint32(26).fork()).ldelim();if(t.updateBinding!=null&&t.updateBinding.length)for(var s=0;s<t.updateBinding.length;++s)o.onnx.StringStringEntryProto.encode(t.updateBinding[s],u.uint32(34).fork()).ldelim();return u},c.encodeDelimited=function(t,u){return this.encode(t,u).ldelim()},c.decode=function(t,u){t instanceof i||(t=i.create(t));for(var s=u===void 0?t.len:t.pos+u,d=new o.onnx.TrainingInfoProto;t.pos<s;){var f=t.uint32();switch(f>>>3){case 1:{d.initialization=o.onnx.GraphProto.decode(t,t.uint32());break}case 2:{d.algorithm=o.onnx.GraphProto.decode(t,t.uint32());break}case 3:{d.initializationBinding&&d.initializationBinding.length||(d.initializationBinding=[]),d.initializationBinding.push(o.onnx.StringStringEntryProto.decode(t,t.uint32()));break}case 4:{d.updateBinding&&d.updateBinding.length||(d.updateBinding=[]),d.updateBinding.push(o.onnx.StringStringEntryProto.decode(t,t.uint32()));break}default:t.skipType(f&7);break}}return d},c.decodeDelimited=function(t){return t instanceof i||(t=new i(t)),this.decode(t,t.uint32())},c.verify=function(t){if(typeof t!="object"||t===null)return"object expected";if(t.initialization!=null&&t.hasOwnProperty("initialization")){var u=o.onnx.GraphProto.verify(t.initialization);if(u)return"initialization."+u}if(t.algorithm!=null&&t.hasOwnProperty("algorithm")){var u=o.onnx.GraphProto.verify(t.algorithm);if(u)return"algorithm."+u}if(t.initializationBinding!=null&&t.hasOwnProperty("initializationBinding")){if(!Array.isArray(t.initializationBinding))return"initializationBinding: array expected";for(var s=0;s<t.initializationBinding.length;++s){var u=o.onnx.StringStringEntryProto.verify(t.initializationBinding[s]);if(u)return"initializationBinding."+u}}if(t.updateBinding!=null&&t.hasOwnProperty("updateBinding")){if(!Array.isArray(t.updateBinding))return"updateBinding: array expected";for(var s=0;s<t.updateBinding.length;++s){var u=o.onnx.StringStringEntryProto.verify(t.updateBinding[s]);if(u)return"updateBinding."+u}}return null},c.fromObject=function(t){if(t instanceof o.onnx.TrainingInfoProto)return t;var u=new o.onnx.TrainingInfoProto;if(t.initialization!=null){if(typeof t.initialization!="object")throw TypeError(".onnx.TrainingInfoProto.initialization: object expected");u.initialization=o.onnx.GraphProto.fromObject(t.initialization)}if(t.algorithm!=null){if(typeof t.algorithm!="object")throw TypeError(".onnx.TrainingInfoProto.algorithm: object expected");u.algorithm=o.onnx.GraphProto.fromObject(t.algorithm)}if(t.initializationBinding){if(!Array.isArray(t.initializationBinding))throw TypeError(".onnx.TrainingInfoProto.initializationBinding: array expected");u.initializationBinding=[];for(var s=0;s<t.initializationBinding.length;++s){if(typeof t.initializationBinding[s]!="object")throw TypeError(".onnx.TrainingInfoProto.initializationBinding: object expected");u.initializationBinding[s]=o.onnx.StringStringEntryProto.fromObject(t.initializationBinding[s])}}if(t.updateBinding){if(!Array.isArray(t.updateBinding))throw TypeError(".onnx.TrainingInfoProto.updateBinding: array expected");u.updateBinding=[];for(var s=0;s<t.updateBinding.length;++s){if(typeof t.updateBinding[s]!="object")throw TypeError(".onnx.TrainingInfoProto.updateBinding: object expected");u.updateBinding[s]=o.onnx.StringStringEntryProto.fromObject(t.updateBinding[s])}}return u},c.toObject=function(t,u){u||(u={});var s={};if((u.arrays||u.defaults)&&(s.initializationBinding=[],s.updateBinding=[]),u.defaults&&(s.initialization=null,s.algorithm=null),t.initialization!=null&&t.hasOwnProperty("initialization")&&(s.initialization=o.onnx.GraphProto.toObject(t.initialization,u)),t.algorithm!=null&&t.hasOwnProperty("algorithm")&&(s.algorithm=o.onnx.GraphProto.toObject(t.algorithm,u)),t.initializationBinding&&t.initializationBinding.length){s.initializationBinding=[];for(var d=0;d<t.initializationBinding.length;++d)s.initializationBinding[d]=o.onnx.StringStringEntryProto.toObject(t.initializationBinding[d],u)}if(t.updateBinding&&t.updateBinding.length){s.updateBinding=[];for(var d=0;d<t.updateBinding.length;++d)s.updateBinding[d]=o.onnx.StringStringEntryProto.toObject(t.updateBinding[d],u)}return s},c.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},c.getTypeUrl=function(t){return t===void 0&&(t="type.googleapis.com"),t+"/onnx.TrainingInfoProto"},c}(),p.ModelProto=function(){function c(t){if(this.opsetImport=[],this.metadataProps=[],this.trainingInfo=[],this.functions=[],t)for(var u=Object.keys(t),s=0;s<u.length;++s)t[u[s]]!=null&&(this[u[s]]=t[u[s]])}return c.prototype.irVersion=n.Long?n.Long.fromBits(0,0,!1):0,c.prototype.opsetImport=n.emptyArray,c.prototype.producerName="",c.prototype.producerVersion="",c.prototype.domain="",c.prototype.modelVersion=n.Long?n.Long.fromBits(0,0,!1):0,c.prototype.docString="",c.prototype.graph=null,c.prototype.metadataProps=n.emptyArray,c.prototype.trainingInfo=n.emptyArray,c.prototype.functions=n.emptyArray,c.create=function(t){return new c(t)},c.encode=function(t,u){if(u||(u=l.create()),t.irVersion!=null&&Object.hasOwnProperty.call(t,"irVersion")&&u.uint32(8).int64(t.irVersion),t.producerName!=null&&Object.hasOwnProperty.call(t,"producerName")&&u.uint32(18).string(t.producerName),t.producerVersion!=null&&Object.hasOwnProperty.call(t,"producerVersion")&&u.uint32(26).string(t.producerVersion),t.domain!=null&&Object.hasOwnProperty.call(t,"domain")&&u.uint32(34).string(t.domain),t.modelVersion!=null&&Object.hasOwnProperty.call(t,"modelVersion")&&u.uint32(40).int64(t.modelVersion),t.docString!=null&&Object.hasOwnProperty.call(t,"docString")&&u.uint32(50).string(t.docString),t.graph!=null&&Object.hasOwnProperty.call(t,"graph")&&o.onnx.GraphProto.encode(t.graph,u.uint32(58).fork()).ldelim(),t.opsetImport!=null&&t.opsetImport.length)for(var s=0;s<t.opsetImport.length;++s)o.onnx.OperatorSetIdProto.encode(t.opsetImport[s],u.uint32(66).fork()).ldelim();if(t.metadataProps!=null&&t.metadataProps.length)for(var s=0;s<t.metadataProps.length;++s)o.onnx.StringStringEntryProto.encode(t.metadataProps[s],u.uint32(114).fork()).ldelim();if(t.trainingInfo!=null&&t.trainingInfo.length)for(var s=0;s<t.trainingInfo.length;++s)o.onnx.TrainingInfoProto.encode(t.trainingInfo[s],u.uint32(162).fork()).ldelim();if(t.functions!=null&&t.functions.length)for(var s=0;s<t.functions.length;++s)o.onnx.FunctionProto.encode(t.functions[s],u.uint32(202).fork()).ldelim();return u},c.encodeDelimited=function(t,u){return this.encode(t,u).ldelim()},c.decode=function(t,u){t instanceof i||(t=i.create(t));for(var s=u===void 0?t.len:t.pos+u,d=new o.onnx.ModelProto;t.pos<s;){var f=t.uint32();switch(f>>>3){case 1:{d.irVersion=t.int64();break}case 8:{d.opsetImport&&d.opsetImport.length||(d.opsetImport=[]),d.opsetImport.push(o.onnx.OperatorSetIdProto.decode(t,t.uint32()));break}case 2:{d.producerName=t.string();break}case 3:{d.producerVersion=t.string();break}case 4:{d.domain=t.string();break}case 5:{d.modelVersion=t.int64();break}case 6:{d.docString=t.string();break}case 7:{d.graph=o.onnx.GraphProto.decode(t,t.uint32());break}case 14:{d.metadataProps&&d.metadataProps.length||(d.metadataProps=[]),d.metadataProps.push(o.onnx.StringStringEntryProto.decode(t,t.uint32()));break}case 20:{d.trainingInfo&&d.trainingInfo.length||(d.trainingInfo=[]),d.trainingInfo.push(o.onnx.TrainingInfoProto.decode(t,t.uint32()));break}case 25:{d.functions&&d.functions.length||(d.functions=[]),d.functions.push(o.onnx.FunctionProto.decode(t,t.uint32()));break}default:t.skipType(f&7);break}}return d},c.decodeDelimited=function(t){return t instanceof i||(t=new i(t)),this.decode(t,t.uint32())},c.verify=function(t){if(typeof t!="object"||t===null)return"object expected";if(t.irVersion!=null&&t.hasOwnProperty("irVersion")&&!n.isInteger(t.irVersion)&&!(t.irVersion&&n.isInteger(t.irVersion.low)&&n.isInteger(t.irVersion.high)))return"irVersion: integer|Long expected";if(t.opsetImport!=null&&t.hasOwnProperty("opsetImport")){if(!Array.isArray(t.opsetImport))return"opsetImport: array expected";for(var u=0;u<t.opsetImport.length;++u){var s=o.onnx.OperatorSetIdProto.verify(t.opsetImport[u]);if(s)return"opsetImport."+s}}if(t.producerName!=null&&t.hasOwnProperty("producerName")&&!n.isString(t.producerName))return"producerName: string expected";if(t.producerVersion!=null&&t.hasOwnProperty("producerVersion")&&!n.isString(t.producerVersion))return"producerVersion: string expected";if(t.domain!=null&&t.hasOwnProperty("domain")&&!n.isString(t.domain))return"domain: string expected";if(t.modelVersion!=null&&t.hasOwnProperty("modelVersion")&&!n.isInteger(t.modelVersion)&&!(t.modelVersion&&n.isInteger(t.modelVersion.low)&&n.isInteger(t.modelVersion.high)))return"modelVersion: integer|Long expected";if(t.docString!=null&&t.hasOwnProperty("docString")&&!n.isString(t.docString))return"docString: string expected";if(t.graph!=null&&t.hasOwnProperty("graph")){var s=o.onnx.GraphProto.verify(t.graph);if(s)return"graph."+s}if(t.metadataProps!=null&&t.hasOwnProperty("metadataProps")){if(!Array.isArray(t.metadataProps))return"metadataProps: array expected";for(var u=0;u<t.metadataProps.length;++u){var s=o.onnx.StringStringEntryProto.verify(t.metadataProps[u]);if(s)return"metadataProps."+s}}if(t.trainingInfo!=null&&t.hasOwnProperty("trainingInfo")){if(!Array.isArray(t.trainingInfo))return"trainingInfo: array expected";for(var u=0;u<t.trainingInfo.length;++u){var s=o.onnx.TrainingInfoProto.verify(t.trainingInfo[u]);if(s)return"trainingInfo."+s}}if(t.functions!=null&&t.hasOwnProperty("functions")){if(!Array.isArray(t.functions))return"functions: array expected";for(var u=0;u<t.functions.length;++u){var s=o.onnx.FunctionProto.verify(t.functions[u]);if(s)return"functions."+s}}return null},c.fromObject=function(t){if(t instanceof o.onnx.ModelProto)return t;var u=new o.onnx.ModelProto;if(t.irVersion!=null&&(n.Long?(u.irVersion=n.Long.fromValue(t.irVersion)).unsigned=!1:typeof t.irVersion=="string"?u.irVersion=parseInt(t.irVersion,10):typeof t.irVersion=="number"?u.irVersion=t.irVersion:typeof t.irVersion=="object"&&(u.irVersion=new n.LongBits(t.irVersion.low>>>0,t.irVersion.high>>>0).toNumber())),t.opsetImport){if(!Array.isArray(t.opsetImport))throw TypeError(".onnx.ModelProto.opsetImport: array expected");u.opsetImport=[];for(var s=0;s<t.opsetImport.length;++s){if(typeof t.opsetImport[s]!="object")throw TypeError(".onnx.ModelProto.opsetImport: object expected");u.opsetImport[s]=o.onnx.OperatorSetIdProto.fromObject(t.opsetImport[s])}}if(t.producerName!=null&&(u.producerName=String(t.producerName)),t.producerVersion!=null&&(u.producerVersion=String(t.producerVersion)),t.domain!=null&&(u.domain=String(t.domain)),t.modelVersion!=null&&(n.Long?(u.modelVersion=n.Long.fromValue(t.modelVersion)).unsigned=!1:typeof t.modelVersion=="string"?u.modelVersion=parseInt(t.modelVersion,10):typeof t.modelVersion=="number"?u.modelVersion=t.modelVersion:typeof t.modelVersion=="object"&&(u.modelVersion=new n.LongBits(t.modelVersion.low>>>0,t.modelVersion.high>>>0).toNumber())),t.docString!=null&&(u.docString=String(t.docString)),t.graph!=null){if(typeof t.graph!="object")throw TypeError(".onnx.ModelProto.graph: object expected");u.graph=o.onnx.GraphProto.fromObject(t.graph)}if(t.metadataProps){if(!Array.isArray(t.metadataProps))throw TypeError(".onnx.ModelProto.metadataProps: array expected");u.metadataProps=[];for(var s=0;s<t.metadataProps.length;++s){if(typeof t.metadataProps[s]!="object")throw TypeError(".onnx.ModelProto.metadataProps: object expected");u.metadataProps[s]=o.onnx.StringStringEntryProto.fromObject(t.metadataProps[s])}}if(t.trainingInfo){if(!Array.isArray(t.trainingInfo))throw TypeError(".onnx.ModelProto.trainingInfo: array expected");u.trainingInfo=[];for(var s=0;s<t.trainingInfo.length;++s){if(typeof t.trainingInfo[s]!="object")throw TypeError(".onnx.ModelProto.trainingInfo: object expected");u.trainingInfo[s]=o.onnx.TrainingInfoProto.fromObject(t.trainingInfo[s])}}if(t.functions){if(!Array.isArray(t.functions))throw TypeError(".onnx.ModelProto.functions: array expected");u.functions=[];for(var s=0;s<t.functions.length;++s){if(typeof t.functions[s]!="object")throw TypeError(".onnx.ModelProto.functions: object expected");u.functions[s]=o.onnx.FunctionProto.fromObject(t.functions[s])}}return u},c.toObject=function(t,u){u||(u={});var s={};if((u.arrays||u.defaults)&&(s.opsetImport=[],s.metadataProps=[],s.trainingInfo=[],s.functions=[]),u.defaults){if(n.Long){var d=new n.Long(0,0,!1);s.irVersion=u.longs===String?d.toString():u.longs===Number?d.toNumber():d}else s.irVersion=u.longs===String?"0":0;if(s.producerName="",s.producerVersion="",s.domain="",n.Long){var d=new n.Long(0,0,!1);s.modelVersion=u.longs===String?d.toString():u.longs===Number?d.toNumber():d}else s.modelVersion=u.longs===String?"0":0;s.docString="",s.graph=null}if(t.irVersion!=null&&t.hasOwnProperty("irVersion")&&(typeof t.irVersion=="number"?s.irVersion=u.longs===String?String(t.irVersion):t.irVersion:s.irVersion=u.longs===String?n.Long.prototype.toString.call(t.irVersion):u.longs===Number?new n.LongBits(t.irVersion.low>>>0,t.irVersion.high>>>0).toNumber():t.irVersion),t.producerName!=null&&t.hasOwnProperty("producerName")&&(s.producerName=t.producerName),t.producerVersion!=null&&t.hasOwnProperty("producerVersion")&&(s.producerVersion=t.producerVersion),t.domain!=null&&t.hasOwnProperty("domain")&&(s.domain=t.domain),t.modelVersion!=null&&t.hasOwnProperty("modelVersion")&&(typeof t.modelVersion=="number"?s.modelVersion=u.longs===String?String(t.modelVersion):t.modelVersion:s.modelVersion=u.longs===String?n.Long.prototype.toString.call(t.modelVersion):u.longs===Number?new n.LongBits(t.modelVersion.low>>>0,t.modelVersion.high>>>0).toNumber():t.modelVersion),t.docString!=null&&t.hasOwnProperty("docString")&&(s.docString=t.docString),t.graph!=null&&t.hasOwnProperty("graph")&&(s.graph=o.onnx.GraphProto.toObject(t.graph,u)),t.opsetImport&&t.opsetImport.length){s.opsetImport=[];for(var f=0;f<t.opsetImport.length;++f)s.opsetImport[f]=o.onnx.OperatorSetIdProto.toObject(t.opsetImport[f],u)}if(t.metadataProps&&t.metadataProps.length){s.metadataProps=[];for(var f=0;f<t.metadataProps.length;++f)s.metadataProps[f]=o.onnx.StringStringEntryProto.toObject(t.metadataProps[f],u)}if(t.trainingInfo&&t.trainingInfo.length){s.trainingInfo=[];for(var f=0;f<t.trainingInfo.length;++f)s.trainingInfo[f]=o.onnx.TrainingInfoProto.toObject(t.trainingInfo[f],u)}if(t.functions&&t.functions.length){s.functions=[];for(var f=0;f<t.functions.length;++f)s.functions[f]=o.onnx.FunctionProto.toObject(t.functions[f],u)}return s},c.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},c.getTypeUrl=function(t){return t===void 0&&(t="type.googleapis.com"),t+"/onnx.ModelProto"},c}(),p.StringStringEntryProto=function(){function c(t){if(t)for(var u=Object.keys(t),s=0;s<u.length;++s)t[u[s]]!=null&&(this[u[s]]=t[u[s]])}return c.prototype.key="",c.prototype.value="",c.create=function(t){return new c(t)},c.encode=function(t,u){return u||(u=l.create()),t.key!=null&&Object.hasOwnProperty.call(t,"key")&&u.uint32(10).string(t.key),t.value!=null&&Object.hasOwnProperty.call(t,"value")&&u.uint32(18).string(t.value),u},c.encodeDelimited=function(t,u){return this.encode(t,u).ldelim()},c.decode=function(t,u){t instanceof i||(t=i.create(t));for(var s=u===void 0?t.len:t.pos+u,d=new o.onnx.StringStringEntryProto;t.pos<s;){var f=t.uint32();switch(f>>>3){case 1:{d.key=t.string();break}case 2:{d.value=t.string();break}default:t.skipType(f&7);break}}return d},c.decodeDelimited=function(t){return t instanceof i||(t=new i(t)),this.decode(t,t.uint32())},c.verify=function(t){return typeof t!="object"||t===null?"object expected":t.key!=null&&t.hasOwnProperty("key")&&!n.isString(t.key)?"key: string expected":t.value!=null&&t.hasOwnProperty("value")&&!n.isString(t.value)?"value: string expected":null},c.fromObject=function(t){if(t instanceof o.onnx.StringStringEntryProto)return t;var u=new o.onnx.StringStringEntryProto;return t.key!=null&&(u.key=String(t.key)),t.value!=null&&(u.value=String(t.value)),u},c.toObject=function(t,u){u||(u={});var s={};return u.defaults&&(s.key="",s.value=""),t.key!=null&&t.hasOwnProperty("key")&&(s.key=t.key),t.value!=null&&t.hasOwnProperty("value")&&(s.value=t.value),s},c.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},c.getTypeUrl=function(t){return t===void 0&&(t="type.googleapis.com"),t+"/onnx.StringStringEntryProto"},c}(),p.TensorAnnotation=function(){function c(t){if(this.quantParameterTensorNames=[],t)for(var u=Object.keys(t),s=0;s<u.length;++s)t[u[s]]!=null&&(this[u[s]]=t[u[s]])}return c.prototype.tensorName="",c.prototype.quantParameterTensorNames=n.emptyArray,c.create=function(t){return new c(t)},c.encode=function(t,u){if(u||(u=l.create()),t.tensorName!=null&&Object.hasOwnProperty.call(t,"tensorName")&&u.uint32(10).string(t.tensorName),t.quantParameterTensorNames!=null&&t.quantParameterTensorNames.length)for(var s=0;s<t.quantParameterTensorNames.length;++s)o.onnx.StringStringEntryProto.encode(t.quantParameterTensorNames[s],u.uint32(18).fork()).ldelim();return u},c.encodeDelimited=function(t,u){return this.encode(t,u).ldelim()},c.decode=function(t,u){t instanceof i||(t=i.create(t));for(var s=u===void 0?t.len:t.pos+u,d=new o.onnx.TensorAnnotation;t.pos<s;){var f=t.uint32();switch(f>>>3){case 1:{d.tensorName=t.string();break}case 2:{d.quantParameterTensorNames&&d.quantParameterTensorNames.length||(d.quantParameterTensorNames=[]),d.quantParameterTensorNames.push(o.onnx.StringStringEntryProto.decode(t,t.uint32()));break}default:t.skipType(f&7);break}}return d},c.decodeDelimited=function(t){return t instanceof i||(t=new i(t)),this.decode(t,t.uint32())},c.verify=function(t){if(typeof t!="object"||t===null)return"object expected";if(t.tensorName!=null&&t.hasOwnProperty("tensorName")&&!n.isString(t.tensorName))return"tensorName: string expected";if(t.quantParameterTensorNames!=null&&t.hasOwnProperty("quantParameterTensorNames")){if(!Array.isArray(t.quantParameterTensorNames))return"quantParameterTensorNames: array expected";for(var u=0;u<t.quantParameterTensorNames.length;++u){var s=o.onnx.StringStringEntryProto.verify(t.quantParameterTensorNames[u]);if(s)return"quantParameterTensorNames."+s}}return null},c.fromObject=function(t){if(t instanceof o.onnx.TensorAnnotation)return t;var u=new o.onnx.TensorAnnotation;if(t.tensorName!=null&&(u.tensorName=String(t.tensorName)),t.quantParameterTensorNames){if(!Array.isArray(t.quantParameterTensorNames))throw TypeError(".onnx.TensorAnnotation.quantParameterTensorNames: array expected");u.quantParameterTensorNames=[];for(var s=0;s<t.quantParameterTensorNames.length;++s){if(typeof t.quantParameterTensorNames[s]!="object")throw TypeError(".onnx.TensorAnnotation.quantParameterTensorNames: object expected");u.quantParameterTensorNames[s]=o.onnx.StringStringEntryProto.fromObject(t.quantParameterTensorNames[s])}}return u},c.toObject=function(t,u){u||(u={});var s={};if((u.arrays||u.defaults)&&(s.quantParameterTensorNames=[]),u.defaults&&(s.tensorName=""),t.tensorName!=null&&t.hasOwnProperty("tensorName")&&(s.tensorName=t.tensorName),t.quantParameterTensorNames&&t.quantParameterTensorNames.length){s.quantParameterTensorNames=[];for(var d=0;d<t.quantParameterTensorNames.length;++d)s.quantParameterTensorNames[d]=o.onnx.StringStringEntryProto.toObject(t.quantParameterTensorNames[d],u)}return s},c.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},c.getTypeUrl=function(t){return t===void 0&&(t="type.googleapis.com"),t+"/onnx.TensorAnnotation"},c}(),p.GraphProto=function(){function c(t){if(this.node=[],this.initializer=[],this.sparseInitializer=[],this.input=[],this.output=[],this.valueInfo=[],this.quantizationAnnotation=[],t)for(var u=Object.keys(t),s=0;s<u.length;++s)t[u[s]]!=null&&(this[u[s]]=t[u[s]])}return c.prototype.node=n.emptyArray,c.prototype.name="",c.prototype.initializer=n.emptyArray,c.prototype.sparseInitializer=n.emptyArray,c.prototype.docString="",c.prototype.input=n.emptyArray,c.prototype.output=n.emptyArray,c.prototype.valueInfo=n.emptyArray,c.prototype.quantizationAnnotation=n.emptyArray,c.create=function(t){return new c(t)},c.encode=function(t,u){if(u||(u=l.create()),t.node!=null&&t.node.length)for(var s=0;s<t.node.length;++s)o.onnx.NodeProto.encode(t.node[s],u.uint32(10).fork()).ldelim();if(t.name!=null&&Object.hasOwnProperty.call(t,"name")&&u.uint32(18).string(t.name),t.initializer!=null&&t.initializer.length)for(var s=0;s<t.initializer.length;++s)o.onnx.TensorProto.encode(t.initializer[s],u.uint32(42).fork()).ldelim();if(t.docString!=null&&Object.hasOwnProperty.call(t,"docString")&&u.uint32(82).string(t.docString),t.input!=null&&t.input.length)for(var s=0;s<t.input.length;++s)o.onnx.ValueInfoProto.encode(t.input[s],u.uint32(90).fork()).ldelim();if(t.output!=null&&t.output.length)for(var s=0;s<t.output.length;++s)o.onnx.ValueInfoProto.encode(t.output[s],u.uint32(98).fork()).ldelim();if(t.valueInfo!=null&&t.valueInfo.length)for(var s=0;s<t.valueInfo.length;++s)o.onnx.ValueInfoProto.encode(t.valueInfo[s],u.uint32(106).fork()).ldelim();if(t.quantizationAnnotation!=null&&t.quantizationAnnotation.length)for(var s=0;s<t.quantizationAnnotation.length;++s)o.onnx.TensorAnnotation.encode(t.quantizationAnnotation[s],u.uint32(114).fork()).ldelim();if(t.sparseInitializer!=null&&t.sparseInitializer.length)for(var s=0;s<t.sparseInitializer.length;++s)o.onnx.SparseTensorProto.encode(t.sparseInitializer[s],u.uint32(122).fork()).ldelim();return u},c.encodeDelimited=function(t,u){return this.encode(t,u).ldelim()},c.decode=function(t,u){t instanceof i||(t=i.create(t));for(var s=u===void 0?t.len:t.pos+u,d=new o.onnx.GraphProto;t.pos<s;){var f=t.uint32();switch(f>>>3){case 1:{d.node&&d.node.length||(d.node=[]),d.node.push(o.onnx.NodeProto.decode(t,t.uint32()));break}case 2:{d.name=t.string();break}case 5:{d.initializer&&d.initializer.length||(d.initializer=[]),d.initializer.push(o.onnx.TensorProto.decode(t,t.uint32()));break}case 15:{d.sparseInitializer&&d.sparseInitializer.length||(d.sparseInitializer=[]),d.sparseInitializer.push(o.onnx.SparseTensorProto.decode(t,t.uint32()));break}case 10:{d.docString=t.string();break}case 11:{d.input&&d.input.length||(d.input=[]),d.input.push(o.onnx.ValueInfoProto.decode(t,t.uint32()));break}case 12:{d.output&&d.output.length||(d.output=[]),d.output.push(o.onnx.ValueInfoProto.decode(t,t.uint32()));break}case 13:{d.valueInfo&&d.valueInfo.length||(d.valueInfo=[]),d.valueInfo.push(o.onnx.ValueInfoProto.decode(t,t.uint32()));break}case 14:{d.quantizationAnnotation&&d.quantizationAnnotation.length||(d.quantizationAnnotation=[]),d.quantizationAnnotation.push(o.onnx.TensorAnnotation.decode(t,t.uint32()));break}default:t.skipType(f&7);break}}return d},c.decodeDelimited=function(t){return t instanceof i||(t=new i(t)),this.decode(t,t.uint32())},c.verify=function(t){if(typeof t!="object"||t===null)return"object expected";if(t.node!=null&&t.hasOwnProperty("node")){if(!Array.isArray(t.node))return"node: array expected";for(var u=0;u<t.node.length;++u){var s=o.onnx.NodeProto.verify(t.node[u]);if(s)return"node."+s}}if(t.name!=null&&t.hasOwnProperty("name")&&!n.isString(t.name))return"name: string expected";if(t.initializer!=null&&t.hasOwnProperty("initializer")){if(!Array.isArray(t.initializer))return"initializer: array expected";for(var u=0;u<t.initializer.length;++u){var s=o.onnx.TensorProto.verify(t.initializer[u]);if(s)return"initializer."+s}}if(t.sparseInitializer!=null&&t.hasOwnProperty("sparseInitializer")){if(!Array.isArray(t.sparseInitializer))return"sparseInitializer: array expected";for(var u=0;u<t.sparseInitializer.length;++u){var s=o.onnx.SparseTensorProto.verify(t.sparseInitializer[u]);if(s)return"sparseInitializer."+s}}if(t.docString!=null&&t.hasOwnProperty("docString")&&!n.isString(t.docString))return"docString: string expected";if(t.input!=null&&t.hasOwnProperty("input")){if(!Array.isArray(t.input))return"input: array expected";for(var u=0;u<t.input.length;++u){var s=o.onnx.ValueInfoProto.verify(t.input[u]);if(s)return"input."+s}}if(t.output!=null&&t.hasOwnProperty("output")){if(!Array.isArray(t.output))return"output: array expected";for(var u=0;u<t.output.length;++u){var s=o.onnx.ValueInfoProto.verify(t.output[u]);if(s)return"output."+s}}if(t.valueInfo!=null&&t.hasOwnProperty("valueInfo")){if(!Array.isArray(t.valueInfo))return"valueInfo: array expected";for(var u=0;u<t.valueInfo.length;++u){var s=o.onnx.ValueInfoProto.verify(t.valueInfo[u]);if(s)return"valueInfo."+s}}if(t.quantizationAnnotation!=null&&t.hasOwnProperty("quantizationAnnotation")){if(!Array.isArray(t.quantizationAnnotation))return"quantizationAnnotation: array expected";for(var u=0;u<t.quantizationAnnotation.length;++u){var s=o.onnx.TensorAnnotation.verify(t.quantizationAnnotation[u]);if(s)return"quantizationAnnotation."+s}}return null},c.fromObject=function(t){if(t instanceof o.onnx.GraphProto)return t;var u=new o.onnx.GraphProto;if(t.node){if(!Array.isArray(t.node))throw TypeError(".onnx.GraphProto.node: array expected");u.node=[];for(var s=0;s<t.node.length;++s){if(typeof t.node[s]!="object")throw TypeError(".onnx.GraphProto.node: object expected");u.node[s]=o.onnx.NodeProto.fromObject(t.node[s])}}if(t.name!=null&&(u.name=String(t.name)),t.initializer){if(!Array.isArray(t.initializer))throw TypeError(".onnx.GraphProto.initializer: array expected");u.initializer=[];for(var s=0;s<t.initializer.length;++s){if(typeof t.initializer[s]!="object")throw TypeError(".onnx.GraphProto.initializer: object expected");u.initializer[s]=o.onnx.TensorProto.fromObject(t.initializer[s])}}if(t.sparseInitializer){if(!Array.isArray(t.sparseInitializer))throw TypeError(".onnx.GraphProto.sparseInitializer: array expected");u.sparseInitializer=[];for(var s=0;s<t.sparseInitializer.length;++s){if(typeof t.sparseInitializer[s]!="object")throw TypeError(".onnx.GraphProto.sparseInitializer: object expected");u.sparseInitializer[s]=o.onnx.SparseTensorProto.fromObject(t.sparseInitializer[s])}}if(t.docString!=null&&(u.docString=String(t.docString)),t.input){if(!Array.isArray(t.input))throw TypeError(".onnx.GraphProto.input: array expected");u.input=[];for(var s=0;s<t.input.length;++s){if(typeof t.input[s]!="object")throw TypeError(".onnx.GraphProto.input: object expected");u.input[s]=o.onnx.ValueInfoProto.fromObject(t.input[s])}}if(t.output){if(!Array.isArray(t.output))throw TypeError(".onnx.GraphProto.output: array expected");u.output=[];for(var s=0;s<t.output.length;++s){if(typeof t.output[s]!="object")throw TypeError(".onnx.GraphProto.output: object expected");u.output[s]=o.onnx.ValueInfoProto.fromObject(t.output[s])}}if(t.valueInfo){if(!Array.isArray(t.valueInfo))throw TypeError(".onnx.GraphProto.valueInfo: array expected");u.valueInfo=[];for(var s=0;s<t.valueInfo.length;++s){if(typeof t.valueInfo[s]!="object")throw TypeError(".onnx.GraphProto.valueInfo: object expected");u.valueInfo[s]=o.onnx.ValueInfoProto.fromObject(t.valueInfo[s])}}if(t.quantizationAnnotation){if(!Array.isArray(t.quantizationAnnotation))throw TypeError(".onnx.GraphProto.quantizationAnnotation: array expected");u.quantizationAnnotation=[];for(var s=0;s<t.quantizationAnnotation.length;++s){if(typeof t.quantizationAnnotation[s]!="object")throw TypeError(".onnx.GraphProto.quantizationAnnotation: object expected");u.quantizationAnnotation[s]=o.onnx.TensorAnnotation.fromObject(t.quantizationAnnotation[s])}}return u},c.toObject=function(t,u){u||(u={});var s={};if((u.arrays||u.defaults)&&(s.node=[],s.initializer=[],s.input=[],s.output=[],s.valueInfo=[],s.quantizationAnnotation=[],s.sparseInitializer=[]),u.defaults&&(s.name="",s.docString=""),t.node&&t.node.length){s.node=[];for(var d=0;d<t.node.length;++d)s.node[d]=o.onnx.NodeProto.toObject(t.node[d],u)}if(t.name!=null&&t.hasOwnProperty("name")&&(s.name=t.name),t.initializer&&t.initializer.length){s.initializer=[];for(var d=0;d<t.initializer.length;++d)s.initializer[d]=o.onnx.TensorProto.toObject(t.initializer[d],u)}if(t.docString!=null&&t.hasOwnProperty("docString")&&(s.docString=t.docString),t.input&&t.input.length){s.input=[];for(var d=0;d<t.input.length;++d)s.input[d]=o.onnx.ValueInfoProto.toObject(t.input[d],u)}if(t.output&&t.output.length){s.output=[];for(var d=0;d<t.output.length;++d)s.output[d]=o.onnx.ValueInfoProto.toObject(t.output[d],u)}if(t.valueInfo&&t.valueInfo.length){s.valueInfo=[];for(var d=0;d<t.valueInfo.length;++d)s.valueInfo[d]=o.onnx.ValueInfoProto.toObject(t.valueInfo[d],u)}if(t.quantizationAnnotation&&t.quantizationAnnotation.length){s.quantizationAnnotation=[];for(var d=0;d<t.quantizationAnnotation.length;++d)s.quantizationAnnotation[d]=o.onnx.TensorAnnotation.toObject(t.quantizationAnnotation[d],u)}if(t.sparseInitializer&&t.sparseInitializer.length){s.sparseInitializer=[];for(var d=0;d<t.sparseInitializer.length;++d)s.sparseInitializer[d]=o.onnx.SparseTensorProto.toObject(t.sparseInitializer[d],u)}return s},c.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},c.getTypeUrl=function(t){return t===void 0&&(t="type.googleapis.com"),t+"/onnx.GraphProto"},c}(),p.TensorProto=function(){function c(t){if(this.dims=[],this.floatData=[],this.int32Data=[],this.stringData=[],this.int64Data=[],this.externalData=[],this.doubleData=[],this.uint64Data=[],t)for(var u=Object.keys(t),s=0;s<u.length;++s)t[u[s]]!=null&&(this[u[s]]=t[u[s]])}return c.prototype.dims=n.emptyArray,c.prototype.dataType=0,c.prototype.segment=null,c.prototype.floatData=n.emptyArray,c.prototype.int32Data=n.emptyArray,c.prototype.stringData=n.emptyArray,c.prototype.int64Data=n.emptyArray,c.prototype.name="",c.prototype.docString="",c.prototype.rawData=n.newBuffer([]),c.prototype.externalData=n.emptyArray,c.prototype.dataLocation=0,c.prototype.doubleData=n.emptyArray,c.prototype.uint64Data=n.emptyArray,c.create=function(t){return new c(t)},c.encode=function(t,u){if(u||(u=l.create()),t.dims!=null&&t.dims.length){u.uint32(10).fork();for(var s=0;s<t.dims.length;++s)u.int64(t.dims[s]);u.ldelim()}if(t.dataType!=null&&Object.hasOwnProperty.call(t,"dataType")&&u.uint32(16).int32(t.dataType),t.segment!=null&&Object.hasOwnProperty.call(t,"segment")&&o.onnx.TensorProto.Segment.encode(t.segment,u.uint32(26).fork()).ldelim(),t.floatData!=null&&t.floatData.length){u.uint32(34).fork();for(var s=0;s<t.floatData.length;++s)u.float(t.floatData[s]);u.ldelim()}if(t.int32Data!=null&&t.int32Data.length){u.uint32(42).fork();for(var s=0;s<t.int32Data.length;++s)u.int32(t.int32Data[s]);u.ldelim()}if(t.stringData!=null&&t.stringData.length)for(var s=0;s<t.stringData.length;++s)u.uint32(50).bytes(t.stringData[s]);if(t.int64Data!=null&&t.int64Data.length){u.uint32(58).fork();for(var s=0;s<t.int64Data.length;++s)u.int64(t.int64Data[s]);u.ldelim()}if(t.name!=null&&Object.hasOwnProperty.call(t,"name")&&u.uint32(66).string(t.name),t.rawData!=null&&Object.hasOwnProperty.call(t,"rawData")&&u.uint32(74).bytes(t.rawData),t.doubleData!=null&&t.doubleData.length){u.uint32(82).fork();for(var s=0;s<t.doubleData.length;++s)u.double(t.doubleData[s]);u.ldelim()}if(t.uint64Data!=null&&t.uint64Data.length){u.uint32(90).fork();for(var s=0;s<t.uint64Data.length;++s)u.uint64(t.uint64Data[s]);u.ldelim()}if(t.docString!=null&&Object.hasOwnProperty.call(t,"docString")&&u.uint32(98).string(t.docString),t.externalData!=null&&t.externalData.length)for(var s=0;s<t.externalData.length;++s)o.onnx.StringStringEntryProto.encode(t.externalData[s],u.uint32(106).fork()).ldelim();return t.dataLocation!=null&&Object.hasOwnProperty.call(t,"dataLocation")&&u.uint32(112).int32(t.dataLocation),u},c.encodeDelimited=function(t,u){return this.encode(t,u).ldelim()},c.decode=function(t,u){t instanceof i||(t=i.create(t));for(var s=u===void 0?t.len:t.pos+u,d=new o.onnx.TensorProto;t.pos<s;){var f=t.uint32();switch(f>>>3){case 1:{if(d.dims&&d.dims.length||(d.dims=[]),(f&7)===2)for(var b=t.uint32()+t.pos;t.pos<b;)d.dims.push(t.int64());else d.dims.push(t.int64());break}case 2:{d.dataType=t.int32();break}case 3:{d.segment=o.onnx.TensorProto.Segment.decode(t,t.uint32());break}case 4:{if(d.floatData&&d.floatData.length||(d.floatData=[]),(f&7)===2)for(var b=t.uint32()+t.pos;t.pos<b;)d.floatData.push(t.float());else d.floatData.push(t.float());break}case 5:{if(d.int32Data&&d.int32Data.length||(d.int32Data=[]),(f&7)===2)for(var b=t.uint32()+t.pos;t.pos<b;)d.int32Data.push(t.int32());else d.int32Data.push(t.int32());break}case 6:{d.stringData&&d.stringData.length||(d.stringData=[]),d.stringData.push(t.bytes());break}case 7:{if(d.int64Data&&d.int64Data.length||(d.int64Data=[]),(f&7)===2)for(var b=t.uint32()+t.pos;t.pos<b;)d.int64Data.push(t.int64());else d.int64Data.push(t.int64());break}case 8:{d.name=t.string();break}case 12:{d.docString=t.string();break}case 9:{d.rawData=t.bytes();break}case 13:{d.externalData&&d.externalData.length||(d.externalData=[]),d.externalData.push(o.onnx.StringStringEntryProto.decode(t,t.uint32()));break}case 14:{d.dataLocation=t.int32();break}case 10:{if(d.doubleData&&d.doubleData.length||(d.doubleData=[]),(f&7)===2)for(var b=t.uint32()+t.pos;t.pos<b;)d.doubleData.push(t.double());else d.doubleData.push(t.double());break}case 11:{if(d.uint64Data&&d.uint64Data.length||(d.uint64Data=[]),(f&7)===2)for(var b=t.uint32()+t.pos;t.pos<b;)d.uint64Data.push(t.uint64());else d.uint64Data.push(t.uint64());break}default:t.skipType(f&7);break}}return d},c.decodeDelimited=function(t){return t instanceof i||(t=new i(t)),this.decode(t,t.uint32())},c.verify=function(t){if(typeof t!="object"||t===null)return"object expected";if(t.dims!=null&&t.hasOwnProperty("dims")){if(!Array.isArray(t.dims))return"dims: array expected";for(var u=0;u<t.dims.length;++u)if(!n.isInteger(t.dims[u])&&!(t.dims[u]&&n.isInteger(t.dims[u].low)&&n.isInteger(t.dims[u].high)))return"dims: integer|Long[] expected"}if(t.dataType!=null&&t.hasOwnProperty("dataType")&&!n.isInteger(t.dataType))return"dataType: integer expected";if(t.segment!=null&&t.hasOwnProperty("segment")){var s=o.onnx.TensorProto.Segment.verify(t.segment);if(s)return"segment."+s}if(t.floatData!=null&&t.hasOwnProperty("floatData")){if(!Array.isArray(t.floatData))return"floatData: array expected";for(var u=0;u<t.floatData.length;++u)if(typeof t.floatData[u]!="number")return"floatData: number[] expected"}if(t.int32Data!=null&&t.hasOwnProperty("int32Data")){if(!Array.isArray(t.int32Data))return"int32Data: array expected";for(var u=0;u<t.int32Data.length;++u)if(!n.isInteger(t.int32Data[u]))return"int32Data: integer[] expected"}if(t.stringData!=null&&t.hasOwnProperty("stringData")){if(!Array.isArray(t.stringData))return"stringData: array expected";for(var u=0;u<t.stringData.length;++u)if(!(t.stringData[u]&&typeof t.stringData[u].length=="number"||n.isString(t.stringData[u])))return"stringData: buffer[] expected"}if(t.int64Data!=null&&t.hasOwnProperty("int64Data")){if(!Array.isArray(t.int64Data))return"int64Data: array expected";for(var u=0;u<t.int64Data.length;++u)if(!n.isInteger(t.int64Data[u])&&!(t.int64Data[u]&&n.isInteger(t.int64Data[u].low)&&n.isInteger(t.int64Data[u].high)))return"int64Data: integer|Long[] expected"}if(t.name!=null&&t.hasOwnProperty("name")&&!n.isString(t.name))return"name: string expected";if(t.docString!=null&&t.hasOwnProperty("docString")&&!n.isString(t.docString))return"docString: string expected";if(t.rawData!=null&&t.hasOwnProperty("rawData")&&!(t.rawData&&typeof t.rawData.length=="number"||n.isString(t.rawData)))return"rawData: buffer expected";if(t.externalData!=null&&t.hasOwnProperty("externalData")){if(!Array.isArray(t.externalData))return"externalData: array expected";for(var u=0;u<t.externalData.length;++u){var s=o.onnx.StringStringEntryProto.verify(t.externalData[u]);if(s)return"externalData."+s}}if(t.dataLocation!=null&&t.hasOwnProperty("dataLocation"))switch(t.dataLocation){default:return"dataLocation: enum value expected";case 0:case 1:break}if(t.doubleData!=null&&t.hasOwnProperty("doubleData")){if(!Array.isArray(t.doubleData))return"doubleData: array expected";for(var u=0;u<t.doubleData.length;++u)if(typeof t.doubleData[u]!="number")return"doubleData: number[] expected"}if(t.uint64Data!=null&&t.hasOwnProperty("uint64Data")){if(!Array.isArray(t.uint64Data))return"uint64Data: array expected";for(var u=0;u<t.uint64Data.length;++u)if(!n.isInteger(t.uint64Data[u])&&!(t.uint64Data[u]&&n.isInteger(t.uint64Data[u].low)&&n.isInteger(t.uint64Data[u].high)))return"uint64Data: integer|Long[] expected"}return null},c.fromObject=function(t){if(t instanceof o.onnx.TensorProto)return t;var u=new o.onnx.TensorProto;if(t.dims){if(!Array.isArray(t.dims))throw TypeError(".onnx.TensorProto.dims: array expected");u.dims=[];for(var s=0;s<t.dims.length;++s)n.Long?(u.dims[s]=n.Long.fromValue(t.dims[s])).unsigned=!1:typeof t.dims[s]=="string"?u.dims[s]=parseInt(t.dims[s],10):typeof t.dims[s]=="number"?u.dims[s]=t.dims[s]:typeof 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t={},u=Object.create(t);return u[t[0]="UNDEFINED"]=0,u[t[1]="FLOAT"]=1,u[t[2]="UINT8"]=2,u[t[3]="INT8"]=3,u[t[4]="UINT16"]=4,u[t[5]="INT16"]=5,u[t[6]="INT32"]=6,u[t[7]="INT64"]=7,u[t[8]="STRING"]=8,u[t[9]="BOOL"]=9,u[t[10]="FLOAT16"]=10,u[t[11]="DOUBLE"]=11,u[t[12]="UINT32"]=12,u[t[13]="UINT64"]=13,u[t[14]="COMPLEX64"]=14,u[t[15]="COMPLEX128"]=15,u[t[16]="BFLOAT16"]=16,u[t[17]="FLOAT8E4M3FN"]=17,u[t[18]="FLOAT8E4M3FNUZ"]=18,u[t[19]="FLOAT8E5M2"]=19,u[t[20]="FLOAT8E5M2FNUZ"]=20,u}(),c.Segment=function(){function t(u){if(u)for(var s=Object.keys(u),d=0;d<s.length;++d)u[s[d]]!=null&&(this[s[d]]=u[s[d]])}return t.prototype.begin=n.Long?n.Long.fromBits(0,0,!1):0,t.prototype.end=n.Long?n.Long.fromBits(0,0,!1):0,t.create=function(u){return new t(u)},t.encode=function(u,s){return s||(s=l.create()),u.begin!=null&&Object.hasOwnProperty.call(u,"begin")&&s.uint32(8).int64(u.begin),u.end!=null&&Object.hasOwnProperty.call(u,"end")&&s.uint32(16).int64(u.end),s},t.encodeDelimited=function(u,s){return 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this.constructor.toObject(this,a.util.toJSONOptions)},u.getTypeUrl=function(s){return s===void 0&&(s="type.googleapis.com"),s+"/onnx.TypeProto.Optional"},u}(),c.SparseTensor=function(){function u(s){if(s)for(var d=Object.keys(s),f=0;f<d.length;++f)s[d[f]]!=null&&(this[d[f]]=s[d[f]])}return u.prototype.elemType=0,u.prototype.shape=null,u.create=function(s){return new u(s)},u.encode=function(s,d){return d||(d=l.create()),s.elemType!=null&&Object.hasOwnProperty.call(s,"elemType")&&d.uint32(8).int32(s.elemType),s.shape!=null&&Object.hasOwnProperty.call(s,"shape")&&o.onnx.TensorShapeProto.encode(s.shape,d.uint32(18).fork()).ldelim(),d},u.encodeDelimited=function(s,d){return this.encode(s,d).ldelim()},u.decode=function(s,d){s instanceof i||(s=i.create(s));for(var f=d===void 0?s.len:s.pos+d,b=new o.onnx.TypeProto.SparseTensor;s.pos<f;){var y=s.uint32();switch(y>>>3){case 1:{b.elemType=s.int32();break}case 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t[c[0]="EXPERIMENTAL"]=0,t[c[1]="STABLE"]=1,t}(),p.FunctionProto=function(){function c(t){if(this.input=[],this.output=[],this.attribute=[],this.attributeProto=[],this.node=[],this.opsetImport=[],t)for(var u=Object.keys(t),s=0;s<u.length;++s)t[u[s]]!=null&&(this[u[s]]=t[u[s]])}return c.prototype.name="",c.prototype.input=n.emptyArray,c.prototype.output=n.emptyArray,c.prototype.attribute=n.emptyArray,c.prototype.attributeProto=n.emptyArray,c.prototype.node=n.emptyArray,c.prototype.docString="",c.prototype.opsetImport=n.emptyArray,c.prototype.domain="",c.create=function(t){return new c(t)},c.encode=function(t,u){if(u||(u=l.create()),t.name!=null&&Object.hasOwnProperty.call(t,"name")&&u.uint32(10).string(t.name),t.input!=null&&t.input.length)for(var s=0;s<t.input.length;++s)u.uint32(34).string(t.input[s]);if(t.output!=null&&t.output.length)for(var s=0;s<t.output.length;++s)u.uint32(42).string(t.output[s]);if(t.attribute!=null&&t.attribute.length)for(var 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4:{d.input&&d.input.length||(d.input=[]),d.input.push(t.string());break}case 5:{d.output&&d.output.length||(d.output=[]),d.output.push(t.string());break}case 6:{d.attribute&&d.attribute.length||(d.attribute=[]),d.attribute.push(t.string());break}case 11:{d.attributeProto&&d.attributeProto.length||(d.attributeProto=[]),d.attributeProto.push(o.onnx.AttributeProto.decode(t,t.uint32()));break}case 7:{d.node&&d.node.length||(d.node=[]),d.node.push(o.onnx.NodeProto.decode(t,t.uint32()));break}case 8:{d.docString=t.string();break}case 9:{d.opsetImport&&d.opsetImport.length||(d.opsetImport=[]),d.opsetImport.push(o.onnx.OperatorSetIdProto.decode(t,t.uint32()));break}case 10:{d.domain=t.string();break}default:t.skipType(f&7);break}}return d},c.decodeDelimited=function(t){return t instanceof i||(t=new i(t)),this.decode(t,t.uint32())},c.verify=function(t){if(typeof t!="object"||t===null)return"object expected";if(t.name!=null&&t.hasOwnProperty("name")&&!n.isString(t.name))return"name: string expected";if(t.input!=null&&t.hasOwnProperty("input")){if(!Array.isArray(t.input))return"input: array expected";for(var u=0;u<t.input.length;++u)if(!n.isString(t.input[u]))return"input: string[] expected"}if(t.output!=null&&t.hasOwnProperty("output")){if(!Array.isArray(t.output))return"output: array expected";for(var u=0;u<t.output.length;++u)if(!n.isString(t.output[u]))return"output: string[] expected"}if(t.attribute!=null&&t.hasOwnProperty("attribute")){if(!Array.isArray(t.attribute))return"attribute: array expected";for(var u=0;u<t.attribute.length;++u)if(!n.isString(t.attribute[u]))return"attribute: string[] expected"}if(t.attributeProto!=null&&t.hasOwnProperty("attributeProto")){if(!Array.isArray(t.attributeProto))return"attributeProto: array expected";for(var u=0;u<t.attributeProto.length;++u){var s=o.onnx.AttributeProto.verify(t.attributeProto[u]);if(s)return"attributeProto."+s}}if(t.node!=null&&t.hasOwnProperty("node")){if(!Array.isArray(t.node))return"node: array expected";for(var u=0;u<t.node.length;++u){var s=o.onnx.NodeProto.verify(t.node[u]);if(s)return"node."+s}}if(t.docString!=null&&t.hasOwnProperty("docString")&&!n.isString(t.docString))return"docString: string expected";if(t.opsetImport!=null&&t.hasOwnProperty("opsetImport")){if(!Array.isArray(t.opsetImport))return"opsetImport: array expected";for(var u=0;u<t.opsetImport.length;++u){var s=o.onnx.OperatorSetIdProto.verify(t.opsetImport[u]);if(s)return"opsetImport."+s}}return t.domain!=null&&t.hasOwnProperty("domain")&&!n.isString(t.domain)?"domain: string expected":null},c.fromObject=function(t){if(t instanceof o.onnx.FunctionProto)return t;var u=new o.onnx.FunctionProto;if(t.name!=null&&(u.name=String(t.name)),t.input){if(!Array.isArray(t.input))throw TypeError(".onnx.FunctionProto.input: array expected");u.input=[];for(var s=0;s<t.input.length;++s)u.input[s]=String(t.input[s])}if(t.output){if(!Array.isArray(t.output))throw TypeError(".onnx.FunctionProto.output: array 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d=0;d<t.output.length;++d)s.output[d]=t.output[d]}if(t.attribute&&t.attribute.length){s.attribute=[];for(var d=0;d<t.attribute.length;++d)s.attribute[d]=t.attribute[d]}if(t.node&&t.node.length){s.node=[];for(var d=0;d<t.node.length;++d)s.node[d]=o.onnx.NodeProto.toObject(t.node[d],u)}if(t.docString!=null&&t.hasOwnProperty("docString")&&(s.docString=t.docString),t.opsetImport&&t.opsetImport.length){s.opsetImport=[];for(var d=0;d<t.opsetImport.length;++d)s.opsetImport[d]=o.onnx.OperatorSetIdProto.toObject(t.opsetImport[d],u)}if(t.domain!=null&&t.hasOwnProperty("domain")&&(s.domain=t.domain),t.attributeProto&&t.attributeProto.length){s.attributeProto=[];for(var d=0;d<t.attributeProto.length;++d)s.attributeProto[d]=o.onnx.AttributeProto.toObject(t.attributeProto[d],u)}return s},c.prototype.toJSON=function(){return this.constructor.toObject(this,a.util.toJSONOptions)},c.getTypeUrl=function(t){return t===void 0&&(t="type.googleapis.com"),t+"/onnx.FunctionProto"},c}(),p}(),r.exports=o});function Fr(e,r){if(!e)throw new Error(typeof r=="string"?r:r())}function sn(e){return new TextDecoder().decode(e)}var ye,hr,pi,Ze,jn,We,it,U,an,mr,br,gr,fe=L(()=>{zn(),Zo(),ye=Ar(Cr()),yr(),hr=class{static arraysEqual(e,r){if(e.length!==r.length)return!1;for(let a=0;a<e.length;a++)if(e[a]!==r[a])return!1;return!0}},pi=class{static preprocessInputShapes(e,r){let a=e.length===1?[1,e[0]]:e,i=r.length===1?[r[0],1]:r;return[a,i]}static postprocessOutputShape(e,r,a){r===1&&e.splice(e.length-2,1),a===1&&e.pop()}static calcMatMulShape(e,r){return e[1]!==r[0]?void 0:[e[0],r[1]]}},Ze=class tr{static calcShape(r,a,i=!1){let l=r.length,n=a.length;if(l===0)return a;if(n===0)return r;let o=Math.max(r.length,a.length),p=new Array(o);if(i){if(l<2||n<2)return;let c=pi.calcMatMulShape([r[l-2],r[l-1]],[a[n-2],a[n-1]]);if(c===void 0)return;[p[o-2],p[o-1]]=c}for(let c=i?3:1;c<=o;c++){let t=l-c<0?1:r[l-c],u=n-c<0?1:a[n-c];if(t!==u&&t>1&&u>1)return;p[o-c]=Math.max(t,u)}return p}static index(r,a){let i=new Array(a.length);return tr.fillIndex(r,a,i),i}static fillIndex(r,a,i){let l=r.length-a.length;for(let n=0;n<a.length;n++)i[n]=r[l+n]%a[n]}static calc(r,a,i,l,n){let o=tr.calcShape(r.dims,a.dims);if(o){if(l&&!U.areEqual(o,r.dims))return;let p=U.size(o),c=l?r:new $e(o,n||r.type);if(o.length===0)c.set([],i(r.get([]),a.get([])));else{let t=new Array(o.length),u=new Array(r.dims.length),s=new Array(a.dims.length),d=0,f=0,b=!1,y=!1;r.dims.length===0&&(d=r.get([]),b=!0),a.dims.length===0&&(f=a.get([]),y=!0);let v;for(let E=0;E<p;E++){v=E;for(let T=o.length-1;T>=0;T--)t[T]=v%o[T],v=Math.floor(v/o[T]);b||(tr.fillIndex(t,r.dims,u),d=r.get(u)),y||(tr.fillIndex(t,a.dims,s),f=a.get(s)),c.set(t,i(d,f))}}return c}}static isValidBroadcast(r,a){let i=r.length,l=a.length;if(i>l)return!1;for(let n=1;n<=i;n++)if(r[i-n]!==1&&r[i-n]!==a[l-n])return!1;return!0}static getBroadcastDims(r,a){let i=r.length,l=[];for(let n=0;n<i;n++){let o=i-1-n,p=r[o]||1;(a[a.length-1-n]||1)>1&&p===1&&l.unshift(o)}return l}},jn=class{static getShapeOfGemmResult(e,r,a,i,l){if(e.length!==2||a.length!==2)throw new Error("shape need to be of size 2");let n,o,p;r?(n=e[1],o=e[0]):(n=e[0],o=e[1]);let c=-1;if(i?(p=a[0],c=1):(p=a[1],c=0),a[c]!==o)throw new Error("dimension mismatch");if(n<=0||p<=0||o<=0)throw new Error("invalid shape specified");if(l&&!Ze.isValidBroadcast(l,[n,p]))throw new Error("gemm: invalid bias shape for broadcast");return[n,p,o]}},We=class _n{static tensorDataTypeFromProto(r){switch(r){case ye.onnx.TensorProto.DataType.INT8:return"int8";case ye.onnx.TensorProto.DataType.UINT8:return"uint8";case ye.onnx.TensorProto.DataType.BOOL:return"bool";case ye.onnx.TensorProto.DataType.INT16:return"int16";case ye.onnx.TensorProto.DataType.UINT16:return"uint16";case ye.onnx.TensorProto.DataType.INT32:return"int32";case ye.onnx.TensorProto.DataType.UINT32:return"uint32";case ye.onnx.TensorProto.DataType.FLOAT:return"float32";case ye.onnx.TensorProto.DataType.DOUBLE:return"float64";case ye.onnx.TensorProto.DataType.STRING:return"string";case ye.onnx.TensorProto.DataType.INT64:return"int32";case ye.onnx.TensorProto.DataType.UINT64:return"uint32";default:throw new Error(`unsupported data type: ${ye.onnx.TensorProto.DataType[r]}`)}}static tensorDataTypeStringToEnum(r){switch(r){case"int8":return ye.onnx.TensorProto.DataType.INT8;case"uint8":return ye.onnx.TensorProto.DataType.UINT8;case"bool":return ye.onnx.TensorProto.DataType.BOOL;case"int16":return ye.onnx.TensorProto.DataType.INT16;case"uint16":return ye.onnx.TensorProto.DataType.UINT16;case"int32":return ye.onnx.TensorProto.DataType.INT32;case"uint32":return ye.onnx.TensorProto.DataType.UINT32;case"float32":return ye.onnx.TensorProto.DataType.FLOAT;case"float64":return ye.onnx.TensorProto.DataType.DOUBLE;case"string":return ye.onnx.TensorProto.DataType.STRING;case"int64":return ye.onnx.TensorProto.DataType.INT64;case"uint64":return ye.onnx.TensorProto.DataType.UINT64;default:throw new Error(`unsupported data type: ${r}`)}}static tensorDimsFromProto(r){return r.map(a=>Vt.isLong(a)?a.toNumber():a)}static tensorValueTypeFromProto(r){return{tensorType:_n.tensorDataTypeFromProto(r.elemType),shape:{dims:_n.tensorDimsFromProto(r.shape.dim.map(a=>a.dimValue))}}}static tensorDimsFromORTFormat(r){let a=[];for(let i=0;i<r.dimsLength();i++)a.push(it.longToNumber(r.dims(i)));return a}static tensorAttributesFromORTFormat(r){let a=[];for(let i=0;i<r.attributesLength();i++)a.push(r.attributes(i));return a}},it=class{static longToNumber(e,r){return Vt.isLong(e)?e.toNumber():e instanceof _.Long?Vt.fromValue({low:e.low,high:e.high,unsigned:r??!1}).toNumber():e}static isLong(e){return Vt.isLong(e)||e instanceof _.Long}},U=class Tt{static size(r){return Tt.getSizeFromDimensionRange(r,0,r.length)}static sizeFromDimension(r,a){if(a<0||a>r.length)throw new Error(`invalid dimension of ${a} for sizeFromDimension as Tensor has ${r.length} dimensions.`);return Tt.getSizeFromDimensionRange(r,a,r.length)}static sizeToDimension(r,a){if(a<0||a>r.length)throw new Error(`invalid dimension of ${a} for sizeToDimension as Tensor has ${r.length} dimensions.`);return Tt.getSizeFromDimensionRange(r,0,a)}static getSizeFromDimensionRange(r,a,i){let l=1;for(let n=a;n<i;n++){if(r[n]<=0)throw new Error("cannot get valid size from specified dimension range. Most likely the range contains 0 or negative values in them.");l*=r[n]}return l}static computeStrides(r){let a=r.length;if(a===0)return[];if(a===1)return[1];let i=new Array(a);i[a-1]=1,i[a-2]=r[a-1];for(let l=a-3;l>=0;--l)i[l]=i[l+1]*r[l+1];return i}static transpose(r){return r.slice().reverse()}static indicesToOffset(r,a,i){i===void 0&&(i=r.length);let l=0;for(let n=0;n<i;++n)l+=a[n]*r[n];return l}static offsetToIndices(r,a){let i=a.length;if(i===0)return[];if(i===1)return[r*a[0]];let l=new Array(a.length);for(let n=0;n<l.length-1;++n)l[n]=Math.floor(r/a[n]),r-=l[n]*a[n];return l[l.length-1]=r,l}static normalizeAxis(r,a){if(r<-a&&r>=a)throw new Error("unsupported axis for this operation.");return r<0?r+a:r}static normalizeAxes(r,a){return r.map(i=>this.normalizeAxis(i,a))}static incrementIndex(r,a,i){if(a.length===0||r.length===0)throw new Error("Index incrementing unsupported for scalar Tensor");if(i===void 0)i=a.length;else if(i<=0||i>a.length)throw new Error("Incorrect axis to increment on");for(let l=i-1;l>=0&&(r[l]++,!(r[l]<a[l]));--l)r[l]=0}static calculateReshapedDims(r,a){if(a.length===0){if(r.length===0||Tt.size(r)===1)return[];throw new Error("cannot reshape to a scalar Tensor")}let i=a.length,l=new Array(i),n=-1,o=1;for(let c=0;c<i;c++){if(a[c]<-1)throw new Error("a dimension in shape hints cannot be less than -1");if(a[c]===-1){if(n!==-1)throw new Error("at most one dimension in shape hints can be -1");n=c}else{if(a[c]===0){if(c>=r.length)throw new Error("the dimension with value zero exceeds the dimension size of the input tensor");l[c]=r[c]}else l[c]=a[c];o*=l[c]}}let p=Tt.size(r);if(n!==-1){if(p%o!==0)throw new Error(`the input tensor cannot be reshaped to the requested shape. Input shape: [${r}] Output shape: [${a}]`);l[n]=p/o}else if(o!==p)throw new Error("reshapedDims and originalDims don't have matching sizes");return l}static sortBasedOnPerm(r,a){return a?a.map(i=>r[i]):r.slice().reverse()}static padShape(r,a){let i=r.length;return r.map((l,n)=>l+a[n]+a[n+i])}static areEqual(r,a){return r.length!==a.length?!1:r.every((i,l)=>i===a[l])}static validateDimsAndCalcSize(r){if(r.length>6)throw new TypeError("Only rank 0 to 6 is supported for tensor shape.");let a=1;for(let i of r){if(!Number.isInteger(i))throw new TypeError(`Invalid shape: ${i} is not an integer`);if(i<0||i>2147483647)throw new TypeError(`Invalid shape: length ${i} is not allowed`);a*=i}return a}static flattenShape(r,a){a<0&&(a+=r.length);let i=r.reduce((n,o)=>n*o,1),l=r.slice(a).reduce((n,o)=>n*o,1);return[i/l,l]}static squeezeShape(r,a){let i=new Array;a=Tt.normalizeAxes(a,r.length);for(let l=0;l<r.length;l++){let n=a.indexOf(l)>=0;if(n&&r[l]!==1)throw new Error("squeeze an axis of size different than 1");(a.length===0&&r[l]>1||a.length>0&&!n)&&i.push(r[l])}return i}static unsqueezeShape(r,a){let i=new Array(r.length+a.length);i.fill(0);for(let n=0;n<a.length;n++){let o=Tt.normalizeAxis(a[n],i.length);if(o>=i.length)throw new Error("'axes' has an out of range axis");if(i[o]!==0)throw new Error("'axes' has a duplicate axis");i[o]=1}let l=0;for(let n=0;n<i.length;n++)i[n]===0&&(i[n]=r[l++]);if(l!==r.length)throw new Error("the unsqueezed dimension could not be established");return i}},an=class na{static splitShape(r,a,i,l){if(i.length===0){if(!l)throw new Error("need to know number of outputs when the 'split' attribute is not specified");na.determineSplit(r[a],l,i)}let n=[],o=[0];for(let p=0;p<i.length;++p){p!==0&&o.push(o[p-1]+i[p-1]);let c=r.slice();c[a]=i[p],n.push(c)}return[n,o]}static determineSplit(r,a,i){if(r%a!==0)throw new Error("cannot split tensor to equal sized parts");for(let l=0;l<a;++l)i.push(r/a)}},mr=class rr{static adjustPoolAttributes(r,a,i,l,n,o){if(!r&&i.length!==a.length-2)throw new Error("length of specified kernel shapes should be 2 less than length of input dimensions");if(r)for(let p=0;p<a.length-2;p++)p>=i.length?i.push(a[p+2]):i[p]=a[p+2];for(let p=0;p<i.length;p++)if(p<l.length){if(l[p]<0)throw new Error("strides should be greater than or equal to 1")}else l.push(1);for(let p=0;p<i.length;p++)if(p<n.length){if(n[p]<0)throw new Error("dilations should be greater than or equal to 1")}else n.push(1);for(let p=0;p<i.length*2;p++)if(p<o.length){if(o[p]<0)throw new Error("pad should be greater than or equal to 1")}else o.push(0);for(let p=0;p<i.length;p++){if(i[p]<=0)throw new Error("kernel shapes need to be greater than 0");if(o[p]>=i[p]||o[p+i.length]>=i[p])throw new Error("pads should be smaller than kernel")}}static adjustPadsBasedOnAutoPad(r,a,i,l,n,o){if(o){if(n.length!==2*(r.length-2))throw new Error("length of pads should be twice the length of data dimensions");if(a.length!==r.length-2)throw new Error("length of strides should be the length of data dimensions");if(l.length!==r.length-2)throw new Error("length of kernel shapes should be the length of data dimensions");for(let p=0;p<r.length-2;p++)rr.adjustPadAndReturnShape(r[p+2],a[p],i[p],l[p],n,p,p+r.length-2,o)}}static computePoolOutputShape(r,a,i,l,n,o,p){if(a.length<=0)throw new Error("input shape must be of size greater than 0");let c=[a[0],a[1]];return rr.computeShapeHelper(r,a,c,i,l,n,o,p),c}static computeConvOutputShape(r,a,i,l,n,o,p){if(r.length<=0||a.length<=0)throw new Error("invalid input tensor dims or invalid filter tensor dims");let c=[r[0],a[0]];return rr.computeShapeHelper(!1,r,c,i,l,n,o,p),c}static computeShapeHelper(r,a,i,l,n,o,p,c){if(r)for(let t=0;t<a.length-2;t++)i.push(1);else for(let t=0;t<a.length-2;t++)i.push(rr.adjustPadAndReturnShape(a[t+2],l[t],n[t],o[t],p,t,t+a.length-2,c))}static adjustPadAndReturnShape(r,a,i,l,n,o,p,c){let t=i*(l-1)+1;if(c&&c!=="NOTSET")switch(c){case"VALID":return n[o]=0,n[p]=0,Math.floor((r-t)/a+1);case"SAME_LOWER":case"SAME_UPPER":if(i!==1)throw new Error("Dilation not supported for SAME_UPPER or SAME_LOWER");{let u=((r+a-1)/a-1)*a+l-r;return n[o]=Math.floor(c==="SAME_LOWER"?(u+1)/2:u/2),n[p]=u-n[o],Math.floor((r+u-l)/a+1)}default:throw new Error("Unsupported AutoPad type")}else return Math.floor((r+n[o]+n[p]-t)/a+1)}},br=-34028234663852886e22,gr=34028234663852886e22});function Hd(e){switch(e){case"bool":case"int8":case"uint8":return 1;case"int16":case"uint16":return 2;case"int32":case"uint32":case"float32":return 4;case"float64":return 8;default:throw new Error(`cannot calculate sizeof() on type ${e}`)}}function Fu(e){switch(e){case ne.onnx.TensorProto.DataType.UINT8:case ne.onnx.TensorProto.DataType.INT8:case ne.onnx.TensorProto.DataType.BOOL:return 1;case ne.onnx.TensorProto.DataType.UINT16:case ne.onnx.TensorProto.DataType.INT16:return 2;case ne.onnx.TensorProto.DataType.FLOAT:case ne.onnx.TensorProto.DataType.INT32:case ne.onnx.TensorProto.DataType.UINT32:return 4;case ne.onnx.TensorProto.DataType.INT64:case ne.onnx.TensorProto.DataType.DOUBLE:case ne.onnx.TensorProto.DataType.UINT64:return 8;default:throw new Error(`cannot calculate sizeof() on type ${ne.onnx.TensorProto.DataType[e]}`)}}function qd(e,r){return new(Bu(r))(e)}function Bu(e){switch(e){case"bool":case"uint8":return Uint8Array;case"int8":return Int8Array;case"int16":return Int16Array;case"uint16":return Uint16Array;case"int32":return Int32Array;case"uint32":return Uint32Array;case"int64":return BigInt64Array;case"float32":return Float32Array;case"float64":return Float64Array;default:throw new Error("unspecified error")}}function hi(e,r){if(r===ne.onnx.TensorProto.DataType.INT64||r===di.TensorDataType.INT64){if(e.greaterThanOrEqual(2147483648)||e.lessThan(-2147483648))throw new TypeError("int64 is not supported")}else if(r===ne.onnx.TensorProto.DataType.UINT32||r===di.TensorDataType.UINT32||r===ne.onnx.TensorProto.DataType.UINT64||r===di.TensorDataType.UINT64){if(e.greaterThanOrEqual(4294967296)||e.lessThan(0))throw new TypeError("uint64 is not supported")}else throw new TypeError(`not a LONG type: ${ne.onnx.TensorProto.DataType[r]}`);return e.toNumber()}function $u(e,r,a){switch(r){case ne.onnx.TensorProto.DataType.BOOL:case ne.onnx.TensorProto.DataType.UINT8:return e.getUint8(a);case ne.onnx.TensorProto.DataType.INT8:return e.getInt8(a);case ne.onnx.TensorProto.DataType.UINT16:return e.getUint16(a,!0);case ne.onnx.TensorProto.DataType.INT16:return e.getInt16(a,!0);case ne.onnx.TensorProto.DataType.FLOAT:return e.getFloat32(a,!0);case ne.onnx.TensorProto.DataType.INT32:return e.getInt32(a,!0);case ne.onnx.TensorProto.DataType.UINT32:return e.getUint32(a,!0);case ne.onnx.TensorProto.DataType.INT64:return hi(Vt.fromBits(e.getUint32(a,!0),e.getUint32(a+4,!0),!1),r);case ne.onnx.TensorProto.DataType.DOUBLE:return e.getFloat64(a,!0);case ne.onnx.TensorProto.DataType.UINT64:return hi(Vt.fromBits(e.getUint32(a,!0),e.getUint32(a+4,!0),!0),r);default:throw new Error(`cannot read from DataView for type ${ne.onnx.TensorProto.DataType[r]}`)}}var ku,ne,di,$e,yr=L(()=>{ku=Ar(Os()),Zo(),tn(),ne=Ar(Cr()),fe(),di=V.experimental.fbs,$e=class qr{constructor(r,a,i,l,n,o=ku.Guid.create()){this.dims=r,this.type=a,this.dataProvider=i,this.asyncDataProvider=l,this.cache=n,this.dataId=o,this.size=U.validateDimsAndCalcSize(r);let p=this.size,c=i===void 0&&l===void 0&&n===void 0;if(n!==void 0&&n.length!==p)throw new RangeError("Input dims doesn't match data length.");if(a==="string"){if(n!==void 0&&(!Array.isArray(n)||!n.every(t=>typeof t=="string")))throw new TypeError("cache should be a string array");c&&(this.cache=new Array(p))}else{if(n!==void 0){let t=Bu(a);if(!(n instanceof t))throw new TypeError(`cache should be type ${t.name}`)}if(c){let t=new ArrayBuffer(p*Hd(a));this.cache=qd(t,a)}}}get data(){if(this.cache===void 0){let r=this.dataProvider(this.dataId);if(r.length!==this.size)throw new Error("Length of data provided by the Data Provider is inconsistent with the dims of this Tensor.");this.cache=r}return this.cache}get stringData(){if(this.type!=="string")throw new TypeError("data type is not string");return this.data}get integerData(){switch(this.type){case"uint8":case"int8":case"uint16":case"int16":case"int32":case"uint32":case"bool":return this.data;default:throw new TypeError("data type is not integer (uint8, int8, uint16, int16, int32, uint32, bool)")}}get floatData(){switch(this.type){case"float32":case"float64":return this.data;default:throw new TypeError("data type is not float (float32, float64)")}}get numberData(){if(this.type!=="string")return this.data;throw new TypeError("type cannot be non-number (string)")}get(r){return this.data[U.indicesToOffset(r,this.strides)]}set(r,a){this.data[U.indicesToOffset(r,this.strides)]=a}async getData(){return this.cache===void 0&&(this.cache=await this.asyncDataProvider(this.dataId)),this.cache}get strides(){return this._strides||(this._strides=U.computeStrides(this.dims)),this._strides}static fromProto(r){if(!r)throw new Error("cannot construct Value from an empty tensor");let a=We.tensorDataTypeFromProto(r.dataType),i=We.tensorDimsFromProto(r.dims),l=new qr(i,a);if(a==="string")r.stringData.forEach((n,o)=>{l.data[o]=sn(n)});else if(r.rawData&&typeof r.rawData.byteLength=="number"&&r.rawData.byteLength>0){let n=l.data,o=new DataView(r.rawData.buffer,r.rawData.byteOffset,r.rawData.byteLength),p=Fu(r.dataType),c=r.rawData.byteLength/p;if(r.rawData.byteLength%p!==0)throw new Error("invalid buffer length");if(n.length!==c)throw new Error("buffer length mismatch");for(let t=0;t<c;t++){let u=$u(o,r.dataType,t*p);n[t]=u}}else{let n;switch(r.dataType){case ne.onnx.TensorProto.DataType.FLOAT:n=r.floatData;break;case ne.onnx.TensorProto.DataType.INT32:case ne.onnx.TensorProto.DataType.INT16:case ne.onnx.TensorProto.DataType.UINT16:case ne.onnx.TensorProto.DataType.INT8:case ne.onnx.TensorProto.DataType.UINT8:case ne.onnx.TensorProto.DataType.BOOL:n=r.int32Data;break;case ne.onnx.TensorProto.DataType.INT64:n=r.int64Data;break;case ne.onnx.TensorProto.DataType.DOUBLE:n=r.doubleData;break;case ne.onnx.TensorProto.DataType.UINT32:case ne.onnx.TensorProto.DataType.UINT64:n=r.uint64Data;break;default:throw new Error("unspecific error")}if(n==null)throw new Error("failed to populate data from a tensorproto value");let o=l.data;if(o.length!==n.length)throw new Error("array length mismatch");for(let p=0;p<n.length;p++){let c=n[p];Vt.isLong(c)?o[p]=hi(c,r.dataType):o[p]=c}}return l}static fromData(r,a,i){return new qr(a,i,void 0,void 0,r)}static fromOrtTensor(r){if(!r)throw new Error("cannot construct Value from an empty tensor");let a=We.tensorDimsFromORTFormat(r),i=We.tensorDataTypeFromProto(r.dataType()),l=new qr(a,i);if(i==="string")for(let n=0;n<r.stringDataLength();n++)l.data[n]=r.stringData(n);else if(r.rawDataArray()&&typeof r.rawDataLength()=="number"&&r.rawDataLength()>0){let n=l.data,o=new DataView(r.rawDataArray().buffer,r.rawDataArray().byteOffset,r.rawDataLength()),p=Fu(r.dataType()),c=r.rawDataLength()/p;if(r.rawDataLength()%p!==0)throw new Error("invalid buffer length");if(n.length!==c)throw new Error("buffer length mismatch");for(let t=0;t<c;t++){let u=$u(o,r.dataType(),t*p);n[t]=u}}return l}}});function H(e){return e===1?jd:Yd}function Nu(e){let r=H(e);return`${r.version}
      precision highp float;
      ${r.attribute} vec3 position;
      ${r.attribute} vec2 textureCoord;

      ${r.varyingVertex} vec2 TexCoords;

      void main()
      {
          gl_Position = vec4(position, 1.0);
          TexCoords = textureCoord;
      }`}function Ru(e){let r=H(e);return`${r.version}
    precision highp float;
    precision highp int;
    precision highp sampler2D;
    ${r.varyingFrag} vec2 TexCoords;
    ${r.outputDeclaration}
    const vec2 halfCR = vec2(0.5, 0.5);

    // Custom vector types to handle higher dimenalities.
    struct ivec5
    {
      int x;
      int y;
      int z;
      int w;
      int u;
    };

    struct ivec6
    {
      int x;
      int y;
      int z;
      int w;
      int u;
      int v;
    };

    int imod(int x, int y) {
      return x - y * (x / y);
    }

    `}function Mu(e,r){let a=H(e);return`
  void main() {
    int indices[${r}];
    toVec(TexCoords, indices);
    vec4 result = vec4(process(indices));
    ${a.output} = result;
  }
  `}var jd,Yd,we=L(()=>{jd={version:"",attribute:"attribute",varyingVertex:"varying",varyingFrag:"varying",texture2D:"texture2D",output:"gl_FragColor",outputDeclaration:""},Yd={version:"#version 300 es",attribute:"in",varyingVertex:"out",varyingFrag:"in",texture2D:"texture",output:"outputColor",outputDeclaration:"out vec4 outputColor;"}}),ae=L(()=>{});async function mi(e,r=i=>0,a){return new Promise((i,l)=>{let n=0,o=()=>{if(e()){i();return}n++;let p=r(n);setTimeout(o,p)};o()})}function Yn(e){return Fr(typeof e<"u"&&e.length!==0,()=>"empty string found for sampler name"),"get"+e.charAt(0).toUpperCase()+e.slice(1)}function Gu(e){return Fr(typeof e<"u"&&e.length!==0,()=>"empty string found for sampler name"),"get"+e.charAt(0).toUpperCase()+e.slice(1)+"AtOutCoords"}function $r(e,r){let a=JSON.parse(JSON.stringify(e));return a=r,a}function kr(e,r){return r.map(a=>e[a]).join(", ")}function Qe(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function Dt(e=6){return["x","y","z","w","u","v"].slice(0,e)}var Bt=L(()=>{fe()});function Xd(e,r){return Dt(r).map(a=>`${e}.${a}`)}function Br(e,r){return r===1?[e]:Xd(e,r)}function Nt(){return`
    float getChannel(vec4 frag, int dim) {
      int modCoord = imod(dim, 2);
      return modCoord == 0 ? frag.r : frag.g;
    }

    float getChannel(vec4 frag, vec2 innerDims) {
      vec2 modCoord = mod(innerDims, 2.);
      return modCoord.x == 0. ?
        (modCoord.y == 0. ? frag.r : frag.g) :
        (modCoord.y == 0. ? frag.b : frag.a);
    }
  `}var Tr=L(()=>{Bt()});function Jd(e,r,a){if(e===0)return"false";if(e===1)return`rc > ${r[0]}`;let i="";for(let l=e-2;l<e;l++)i+=`${a[l]} >= ${r[l-e+2]}`,l<e-1&&(i+="||");return i}function Zd(e,r){let a=e.length;if(a===0)return"getA(), 0, 0, 0";if(a===1)return`getA(rc),
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            0, 0`;let i="r, c",l="r, cp1",n="rp1, c",o="rp1, cp1",p="";if(a>2)for(let c=0;c<a-2;++c)p=p+`${r[c]},`;return`getA(${p}${i}),
          rEdge ? 0. : getA(${p}${n}),
          cEdge ? 0. : getA(${p}${l}),
          rEdge || cEdge ? 0. : getA(${p}${o})`}function Qd(e,r,a,i){return e===0||e===1?"":`
    int r = ${r[e-2]};
    int c = ${r[e-1]};
    int rp1 = ${r[e-2]} + 1;
    int cp1 = ${r[e-1]} + 1;
    bool rEdge = rp1 >= ${i};
    bool cEdge = cp1 >= ${a};
    `}var Uu,Kd,zu,Vu=L(()=>{we(),ae(),Bt(),Tr(),Uu={name:"pack",inputNames:["A"],inputTypes:[1]},Kd=(e,r)=>{let a=H(e.session.backend.glContext.version),i=r.dims,l=i.length,n=r.dims.length,o=Qe(n),p=Br("rc",n),c=Qd(n,p,i[i.length-2],i[i.length-1]),t;l===0?t=[1,1]:l===1?t=[i[0],1]:t=[i[n-1],i[n-2]];let u=Jd(n,t,p),s=Zd(i,p),d=`
        void main() {
          ${o} rc = getOutputCoords();

          if(${u}) {
            ${a.output} = vec4(0);
          } else {
            ${c}

            ${a.output} = vec4(${s});
          }
        }
      `;return{...Uu,hasMain:!0,output:{dims:r.dims,type:r.type,textureType:2},shaderSource:d}},zu=(e,r)=>({...Uu,get:()=>Kd(e,r)})});function bi(e){if(e.length===0)return[1,1,1];let r=1;for(let a=0;a<e.length-2;++a)r*=e[a];return[r,e.length>1?e[e.length-2]:1,e[e.length-1]]}function Hu(e,r){let a=!1;return e.length===0||r.length===0?a=!0:e.length<2||r.length<2?a=e[e.length-1]===r[r.length-1]:a=e[e.length-1]===r[r.length-1]&&e[e.length-2]===r[r.length-2],a}function rh(e){let r=U.computeStrides(e),a=["b","r","c"],i="index";return`
    ivec3 inputCoordsFromReshapedOutCoords(int index) {
      ${r.map((l,n)=>{let o=`int ${a[n]} = ${i} / ${l}`,p=n===r.length-1?`int ${a[n+1]} = ${i} - ${a[n]} * ${l}`:`index -= ${a[n]} * ${l}`;return`${o}; ${p};`}).join("")}
      return ivec3(b, r, c);
    }
  `}function nh(e){let r=U.computeStrides(e);return`
  int getFlattenedIndex(ivec3 coords) {
    // reverse y, z order
    return coords.x * ${r[0]} + coords.z * ${r[1]} + coords.y;
  }
`}var eh,th,Wu,qu=L(()=>{fe(),we(),ae(),Tr(),eh=e=>({name:"Reshape (packed)",inputTypes:[2],inputNames:["A"],cacheHint:`${e}`}),th=(e,r,a,i)=>{let l=r.dims,n=i,o="";for(let t=0;t<4;t++){let u="";switch(t){case 0:u="outputCoords = rc;";break;case 1:u="outputCoords = ivec3(rc.x, rc.y+1, rc.z);";break;case 2:u="outputCoords = ivec3(rc.x, rc.y, rc.z+1);";break;case 3:u="outputCoords = ivec3(rc.x, rc.y+1, rc.z+1);";break;default:throw new Error}o+=`
        ${u}
        ${t>0?"if(outputCoords.y < rows && outputCoords.z < cols){":""}
          int flattenedIndex = getFlattenedIndex(outputCoords);

          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flattenedIndex);
          vec2 innerDims = vec2(float(inputRC.y),float(inputRC.z));

          result[${t}] = getChannel(getA(inputRC.x, inputRC.y, inputRC.z), innerDims);

        ${t>0?"}":""}
      `}let p=H(e.session.backend.glContext.version),c=`
      ${rh(l)}
      ${nh(n)}
      ${Nt()}

      void main() {
        ivec3 rc = getOutputCoords();

        vec4 result = vec4(0.0);

        ivec3 outputCoords;
        int rows = ${n[2]};
        int cols = ${n[1]};

        ${o}
        ${p.output} = result;
      }
    `;return{...a,output:{dims:n,type:r.type,textureType:2},shaderSource:c,hasMain:!0}},Wu=(e,r,a)=>{let i=eh(a);return{...i,get:()=>th(e,r,i,a)}}}),gi,ju=L(()=>{we(),ae(),gi=(e,r)=>{let a=r.shape,i=H(e.session.backend.glContext.version),l=`
    const float FLOAT_MAX = 1.70141184e38;
    const float FLOAT_MIN = 1.17549435e-38;

    bool isNaN(float val) {
      return (val < 1.0 || 0.0 < val || val == 0.0) ? false : true;
    }

    highp vec4 encodeAsUint8(highp float v) {
      if (isNaN(v)) {
        return vec4(255, 255, 255, 255);
      }

      highp float av = abs(v);

      if(av < FLOAT_MIN) {
        return vec4(0.0, 0.0, 0.0, 0.0);
      } else if(v > FLOAT_MAX) {
        return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;
      } else if(v < -FLOAT_MAX) {
        return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;
      }

      highp vec4 c = vec4(0,0,0,0);

      highp float e = floor(log2(av));
      highp float m = exp2(fract(log2(av))) - 1.0;

      c[2] = floor(128.0 * m);
      m -= c[2] / 128.0;
      c[1] = floor(32768.0 * m);
      m -= c[1] / 32768.0;
      c[0] = floor(8388608.0 * m);

      highp float ebias = e + 127.0;
      c[3] = floor(ebias / 2.0);
      ebias -= c[3] * 2.0;
      c[2] += floor(ebias) * 128.0;

      c[3] += 128.0 * step(0.0, -v);

      return c / 255.0;
    }

    void main() {
      float value = ${i.texture2D}(X,TexCoords).r;
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              result.g = getValue(${p});
            }

            ${p[o-2]} = ${p[o-2]} + 1;
            if (${p[o-2]} < ${n[o-2]}) {
              result.a = getValue(${p});
            }

            ${p[o-1]} = ${p[o-1]} - 1;
            if (${p[o-2]} < ${n[o-2]} &&
                ${p[o-1]} < ${n[o-1]}) {
              result.b = getValue(${p});
            }
            ${$.output} = result;
          }
        `;return{...r,output:{dims:n,type:a[0].type,textureType:2},shaderSource:F,hasMain:!0}},wl=(e,r,a)=>{let i=Ah(r.length,a.cacheKey);return{...i,get:()=>Ph(e,i,r,a.axis)}},eo=(e,r,a)=>{let i=e.indexOf(r);return e.map((l,n)=>n===i?`${l} - ${a}`:l).join()}}),_l,Eh,Dh,Lh,Ol,Ch,Fh,$h,Il,kh,Sl=L(()=>{Ue(),ae(),vl(),_l=(e,r,a)=>(kh(r),e.session.pack&&r[0].dims.length>1?[e.run(wl(e,r,a),r)]:[e.run(Lh(e,r,a),r)]),Eh=(e,r)=>({name:"Concat",inputNames:Array.from({length:e},(a,i)=>`X${i}`),inputTypes:Array(e).fill(0),cacheHint:r}),Dh=(e,r,a,i)=>{let l=a[0].dims.slice();if(i>=l.length||i<-1*l.length)throw new Error("axis specified for concat doesn't match input dimensionality");i<0&&(i=l.length+i);let n=l.slice(0);for(let f=1;f<a.length;f++){let b=a[f].dims.slice();for(let y=0;y<l.length;y++)if(y===i)n[i]+=b[y];else if(l[y]!==b[y])throw new Error("non concat dimensions must match")}let o=n.length,p=new Array(a.length),c=0;for(let f=0;f<p.length;++f)c+=a[f].dims[i],p[f]=c;let t="";a.length<5?t=Ol(p):t=Ch(p);let u=Fh(a.length,o),s=$h(p),d=`
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        ${s}
        ${t}
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          if(textureIndex != 0) {
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          }

          return fetchDataFromCorrectTexture(textureIndex, indices);
        }`;return{...r,output:{dims:n,type:a[0].type,textureType:0},shaderSource:d}},Lh=(e,r,a)=>{let i=Eh(r.length,a.cacheKey);return{...i,get:()=>Dh(e,i,r,a.axis)}},Ol=e=>`int getTextureWhereDataResides(int index) {
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`)},$h=e=>{let r=["int getSizeInConcatAxisValueFromIndex(int index) {"];for(let a=0;a<e.length;++a)a===0?r.push(`	if (index == ${a}) { return ${e[a]}; }`):a===e.length-1?r.push(`	else { return ${e[a]}; }`):r.push(`	else if (index == ${a}) { return ${e[a]}; }`);return r.push("	}"),r.join(`
`)},Il=e=>Q({axis:e.attributes.getInt("axis")}),kh=e=>{if(!e||e.length<1)throw new Error("too few inputs");let r=e[0].type,a=e[0].dims.length;if(r==="string")throw new Error("string tensor is not supported yet");for(let i of e){if(i.type!==r)throw new Error("input tensors should be one type");if(i.dims.length!==a)throw new Error("input tensors should have the same shape")}}});function Bh(){return mt("abs")}function Nh(){return mt("acos")}function Rh(){return mt("asin")}function Mh(){return mt("atan")}function Gh(){return mt("ceil")}function Uh(){return mt("cos")}function zh(e){let r="elu";return{body:`
  const float alpha = float(${e});

  float ${r}_(float a) {
    return a >= 0.0 ? a: (exp(a) - 1.0) * alpha;
  }
  vec4 ${r}_(vec4 v) {
    return vec4(${r}_(v.x), ${r}_(v.y), ${r}_(v.z), ${r}_(v.w));
  }
  `,name:r,type:0}}function Vh(){return mt("exp")}function Wh(){return mt("floor")}function xi(e,r){let a="clip";return{body:`
  const float min = float(${e});
  const float max = float(${r});

  float ${a}_(float a) {
    return clamp(a, min, max);
  }
  vec4 ${a}_(vec4 v) {
    return clamp(v, min, max);
  }
  `,name:a,type:0}}function Hh(){let e="indentity";return{body:`
  float ${e}_(float a) {
    return a;
  }
  vec4 ${e}_(vec4 v) {
    return v;
  }
  `,name:e,type:0}}function qh(e){let r="leakyRelu";return{body:`
  const float alpha = float(${e});

  float ${r}_(float a) {
    return a < 0.0 ? a * alpha : a;
  }
  vec4 ${r}_(vec4 v) {
    return vec4(${r}_(v.x), ${r}_(v.y), ${r}_(v.z), ${r}_(v.w));
  }
  `,name:r,type:0}}function jh(){return mt("log")}function Yh(){let e="neg";return{body:`
  float ${e}_(float a) {
    return -a;
  }
  vec4 ${e}_(vec4 v) {
    return -v;
  }
  `,name:e,type:0}}function Xh(){let e="not";return{body:`
  float ${e}_(float a) {
    return float( ! bool(a) );
  }
  bool ${e}_(bool a) {
    return !a;
  }
  vec4 ${e}_(vec4 v) {
    return vec4(!bool(v.x), !bool(v.y), !bool(v.z), !bool(v.w));
  }
  bvec4 ${e}_(bvec4 v) {
    return bvec4(!v.x, !v.y, !v.z, !v.w);
  }
  `,name:e,type:0}}function Kh(){return mt("sin")}function wi(){let e="relu";return{body:`
  float ${e}_(float a) {
    return max( a, 0.0 );
  }
  vec4 ${e}_(vec4 v) {
    return max( v, 0.0 );
  }
  `,name:e,type:0}}function vi(){let e="sigmoid";return{body:`
  float ${e}_(float a) {
    return 1.0 / (1.0 + exp(-a));
  }
  vec4 ${e}_(vec4 v) {
    return 1.0 / (1.0 + exp(-v));
  }
  `,name:e,type:0}}function Jh(){return mt("sqrt")}function Zh(){return mt("tan")}function Qh(){let e="tanh";return{body:`
  float ${e}_(float a) {
    a = clamp(a, -10., 10.);
    a = exp(2.*a);
    return (a - 1.) / (a + 1.);
  }
  vec4 ${e}_(vec4 v) {
    v = clamp(v, -10., 10.);
    v = exp(2.*v);
    return (v - 1.) / (v + 1.);
  }
  `,name:e,type:0}}function mt(e){return{body:`
  float ${e}_(float a) {
    return ${e}(a);
  }
  vec4 ${e}_(vec4 v) {
    return ${e}(v);
  }
  `,name:e,type:0}}var em,Ee,Al,Pl,El,Dl,_i,Ll,Cl,tm,Fl,$l,kl,Bl,Nl,Rl,Oi,Ml,Gl,Ul,zl,Vl,Wl,Hl,ql,jl,Yl,Xl,Ii=L(()=>{Ue(),fe(),Wt(),we(),ae(),em=(e,r,a,i)=>{let l=e.session.pack?2:0,n=H(e.session.backend.glContext.version);return{...r,output:{dims:a.dims,type:a.type,textureType:l},shaderSource:`
     ${i.body}
     void main() {
       vec4 v = ${n.texture2D}(A, TexCoords);
       v = ${i.name}_(v);
       ${n.output} = v;
     }
     `,hasMain:!0}},Ee=(e,r,a,i)=>{let l=e.session.pack?2:0,n={name:a.name,inputTypes:[l],inputNames:["A"],cacheHint:i};return{...n,get:()=>em(e,n,r,a)}},Al=(e,r)=>[e.run(Ee(e,r[0],Bh()),r)],Pl=(e,r)=>[e.run(Ee(e,r[0],Nh()),r)],El=(e,r)=>[e.run(Ee(e,r[0],Rh()),r)],Dl=(e,r)=>[e.run(Ee(e,r[0],Mh()),r)],_i=(e,r,a)=>[e.run(Ee(e,r[0],xi(a.min,a.max),a.cacheKey),r)],Ll=e=>Q({min:e.attributes.getFloat("min",br),max:e.attributes.getFloat("max",gr)}),Cl=(e,r)=>{let a=tm(e,r);return _i(e,[r[0]],a)},tm=(e,r)=>{if(r.length>=3&&(!e.session.isInitializer(r[1].dataId)||!e.session.isInitializer(r[2].dataId)))throw new Error("dynamic clip attributes are not allowed");let a=r.length>=3?r[1].numberData[0]:br,i=r.length>=3?r[2].numberData[0]:gr;return Q({min:a,max:i})},Fl=(e,r)=>[e.run(Ee(e,r[0],Gh()),r)],$l=(e,r)=>[e.run(Ee(e,r[0],Uh()),r)],kl=(e,r,a)=>[e.run(Ee(e,r[0],zh(a.alpha),a.cacheKey),r)],Bl=e=>Q({alpha:e.attributes.getFloat("alpha",1)}),Nl=(e,r)=>[e.run(Ee(e,r[0],Vh()),r)],Rl=(e,r)=>[e.run(Ee(e,r[0],Wh()),r)],Oi=(e,r)=>[e.run(Ee(e,r[0],Hh()),r)],Ml=(e,r,a)=>[e.run(Ee(e,r[0],qh(a.alpha),a.cacheKey),r)],Gl=e=>Q({alpha:e.attributes.getFloat("alpha",.01)}),Ul=(e,r)=>[e.run(Ee(e,r[0],jh()),r)],zl=(e,r)=>[e.run(Ee(e,r[0],Yh()),r)],Vl=(e,r)=>[e.run(Ee(e,r[0],Xh()),r)],Wl=(e,r)=>[e.run(Ee(e,r[0],wi()),r)],Hl=(e,r)=>[e.run(Ee(e,r[0],vi()),r)],ql=(e,r)=>[e.run(Ee(e,r[0],Kh()),r)],jl=(e,r)=>[e.run(Ee(e,r[0],Jh()),r)],Yl=(e,r)=>[e.run(Ee(e,r[0],Zh()),r)],Xl=(e,r)=>[e.run(Ee(e,r[0],Qh()),r)]});function Rt(e){let r;switch(e.activation){case"Relu":r=wi();break;case"Sigmoid":r=vi();break;case"Clip":r=xi(e.clipMin,e.clipMax);break;default:return{activationFunction:"",applyActivation:""}}let a=r.name,i=r.body,l=`value = ${a}_(value);`;return{activationFunction:i,applyActivation:l}}var Nr,xr=L(()=>{fe(),Ii(),Nr=e=>{let r=e.getString("activation","");if(r==="Clip"){let[a,i]=e.getFloats("activation_params",[br,gr]);return{activation:r,clipMax:i,clipMin:a,activationCacheKey:`${r}:${a},${i}`}}return{activation:r,activationCacheKey:r}}}),nm,om,Kl,Jl=L(()=>{lt(),we(),ae(),to(),xr(),nm=(e,r)=>({name:"GroupedConv",inputNames:e?["X","W","Bias"]:["X","W"],inputTypes:e?[0,0,0]:[0,0],cacheHint:r}),om=(e,r,a,i)=>{let l=r.length>2?"value += getBias(output_channel);":"",n=r[0].dims.slice(),o=r[1].dims.slice(),p=o[0]/i.group;ce.verbose("GroupedConv",`autpPad:${i.autoPad}, dilations:${i.dilations}, group:${i.group}, kernelShape:${i.kernelShape}, pads:${i.pads}, strides:${i.strides}`);let c=Rr(n,o,i.dilations,i.pads,i.strides),t=H(e.session.backend.glContext.version),{activationFunction:u,applyActivation:s}=Rt(i),d=`
  const ivec2 strides = ivec2(${i.strides[0]}, ${i.strides[1]});
  const ivec2 pads = ivec2(${i.pads[0]}, ${i.pads[1]});
  ${u}
  void main() {
    ivec4 coords = getOutputCoords();
    int batch = coords.x;
    int output_channel = coords.y;
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    int group_id = output_channel / ${p};

    float value = 0.0;
    for (int wInChannel = 0; wInChannel < ${o[1]}; wInChannel++) {
      int input_channel = group_id * ${o[1]} + wInChannel;
      for (int wHeight = 0; wHeight < ${o[2]}; wHeight++) {
        int xHeight = xRCCorner.x + wHeight * ${i.dilations[0]};

        if (xHeight < 0 || xHeight >= ${n[2]}) {
          continue;
        }

        for (int wWidth = 0; wWidth < ${o[3]}; wWidth++) {
          int xWidth = xRCCorner.y + wWidth * ${i.dilations[1]};
          if (xWidth < 0 || xWidth >= ${n[3]}) {
            continue;
          }

          float xVal = getX(batch, input_channel, xWidth, xHeight);
          float wVal = getW(output_channel, wInChannel, wWidth, wHeight);
          value += xVal*wVal;
        }
      }
    }
    ${l}
    ${s}
    ${t.output} = vec4(value, .0, .0, .0);
  }
`;return{...a,output:{dims:c,type:r[0].type,textureType:0},shaderSource:d,hasMain:!0}},Kl=(e,r,a)=>{let i=nm(r.length>2,a.cacheKey);return{...i,get:()=>om(e,r,i,a)}}}),im,am,Zl,Ql=L(()=>{we(),ae(),Tr(),im=e=>({name:"Im2Col (packed)",inputNames:["A"],inputTypes:[2],cacheHint:e}),am=(e,r,a,i,l,n)=>{let o=a.dims,p=i.dims,c=2,t=3,u=l.length,s=[p[1]*p[2]*p[3],l[2]*l[3]],d=p[2]*p[3],f=Nt(),b=H(e.session.backend.glContext.version),y="";for(let E=0;E<=1;E++)for(let T=0;T<=1;T++)y+=`
            blockIndex = rc.x + ${T};
            pos = rc.y + ${E};

            if(blockIndex < ${s[1]} && pos < ${s[0]}) {
              offsetY = int(blockIndex / (${l[u-1]})) * ${n.strides[0]} -
                ${n.pads[0]};
              d0 = offsetY + ${n.dilations[0]} * (imod(pos, ${d}) / ${p[2]});

              if(d0 < ${o[c]} && d0 >= 0) {
                offsetX = imod(blockIndex, ${l[u-1]}) * ${n.strides[1]} -
                  ${n.pads[1]};
                d1 = offsetX + ${n.dilations[1]} * imod(imod(pos, ${d}), ${p[2]});

                if(d1 < ${o[t]} && d1 >= 0) {

                  ch = int(float(pos)/ ${d}.);
                    innerDims = vec2(d0, d1);
                    result[${E*2+T}] = getChannel(
                      getA(0, ch, int(innerDims.x),
                      int(innerDims.y)), innerDims);
                }
              }
            }

          `;let v=`
      ${f}

      void main() {
        ivec2 rc = getOutputCoords();
          vec4 result = vec4(0.0);
          int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
          vec2 innerDims;
          ${y}
          ${b.output} = result;
      }
            `;return{...r,output:{dims:s,type:a.type,textureType:2},shaderSource:v,hasMain:!0}},Zl=(e,r,a,i,l)=>{let n=im(l.cacheKey);return{...n,get:()=>am(e,n,r,a,i,l)}}});function um(e,r,a){let i=r[0].dims,l=r[1].dims,n=Ze.calcShape(i,l,!0);if(!n)throw new Error("Can't use matmul on the given tensors");let o=Qe(n.length),p=Dt(),{activationFunction:c,applyActivation:t}=Rt(a),u=r.length>2,s=u?"value += getBiasForMatmul();":"",d=u?`${Ai(o,p,r[2].dims,n,!1)}`:"",f=n.length,b=i.length,y=l.length,v=i[i.length-1],E=`
    ${c}
    ${d}
    float process(int indices[${f}]) {
        int a[${b}];
        int b[${y}];
        bcastMatmulIndices_A(indices, a);
        bcastMatmulIndices_B(indices, b);

        float value;
        for (int k=0; k<${v}; ++k) {
            a[${b-1}] = k;
            b[${y-2}] = k;
            value += _A(a) * _B(b);
        }
        ${s}
        ${t}
        return value;
    }`;return{...e,output:{dims:n,type:r[0].type,textureType:0},shaderSource:E}}function Si(e,r){let a=sm(e.length>2,r.activationCacheKey);return{...a,get:()=>um(a,e,r)}}function Ai(e,r,a,i,l){let n="",o=a.length,p=i.length,c=p-o;p<2&&o>0?n="coords":n=a.map((d,f)=>`coords.${r[f+c]}`).join(", ");let t=Ze.getBroadcastDims(a,i).map(d=>`coords.${r[d+c]} = 0;`).join(`
`),u=U.size(a)===1,s="vec4(outputValue.xx, outputValue.yy)";return u&&(s="vec4(outputValue.x)"),l?`
vec4 getBiasForMatmul() {
  ${e} coords = getOutputCoords();
  ${t}
  vec4 outputValue = getBias(${n});
  return ${s};
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float getBiasForMatmul() {
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  ${t}
  return getBias(coords.x);
}`}var ef,tf,sm,lm,ro=L(()=>{fe(),ae(),Bt(),xr(),Pi(),ef=(e,r,a)=>(lm(r),e.session.pack?[e.run(no(e,r,a),r)]:[e.run(Si(r,a),r)]),tf=e=>Nr(e.attributes),sm=(e,r)=>({name:"MatMul",inputNames:e?["A","B","Bias"]:["A","B"],inputTypes:e?[0,0,0]:[0,0],cacheHint:r}),lm=e=>{if(!e||e.length!==2)throw new Error("MatMul requires 2 inputs.");if(e[0].dims[e[0].dims.length-1]!==e[1].dims[e[1].dims.length-2])throw new Error("shared dimension does not match.");if(e[0].type!=="float32"&&e[0].type!=="float64"||e[1].type!=="float32"&&e[1].type!=="float64")throw new Error("inputs should be float type");if(e[0].type!==e[1].type)throw new Error("inputs types should match")}});function pm(e,r,a,i){let l=[],n=[],o=a[0].dims,p=a[1].dims,c=o.length,t=p.length,u=i.length,s=u-c,d=u-t;l=o.map((T,$)=>`coords.${r[$+s]}`),l[c-1]="i*2",l.join(", "),n=p.map((T,$)=>`coords.${r[$+d]}`),n[t-2]="i*2",n.join(", ");let f=Ze.getBroadcastDims(o,i),b=Ze.getBroadcastDims(p,i),y=f.map(T=>`coords.${r[T+s]} = 0;`).join(`
`),v=b.map(T=>`coords.${r[T+d]} = 0;`).join(`
`),E=`int lastDim = coords.${r[u-1]};
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  coords.${r[u-2]} = lastDim;`;return`
vec4 getAAtOutCoordsMatmul(int i) {
  ${e} coords = getOutputCoords();
  ${E}
  ${y}
  vec4 outputValue = getA(${l});
  return outputValue;
}

vec4 getBAtOutCoordsMatmul(int i) {
  ${e} coords = getOutputCoords();
  ${E}
  ${v}
  vec4 outputValue = getB(${n});
  return outputValue;
}`}function dm(e,r){let a="";for(let i=0;i<r-2;i++)a+=`rc.${e[i]}, `;return a+=`rc.${e[r-2]}, i*2`,a}function hm(e,r){let a="";for(let i=0;i<r-2;i++)a+=`rc.${e[i]}, `;return a+=`i*2, rc.${e[r-1]}`,a}var fm,cm,no,Pi=L(()=>{fe(),we(),ae(),Bt(),xr(),ro(),fm=(e,r)=>({name:"MatMul (packed)",inputNames:e?["A","B","Bias"]:["A","B"],inputTypes:e?[2,2,2]:[2,2],cacheHint:r}),cm=(e,r,a,i)=>{let l=a.length>2,n=l?"value += getBiasForMatmul();":"",o=a[0].dims,p=a[1].dims,c=Ze.calcShape(o,p,!0),t=!U.areEqual(a[0].dims,a[1].dims);if(!c)throw new Error("Can't use matmul on the given tensors");let u=o[o.length-1],s=Math.ceil(u/2),d=o.length,f=p.length,b=H(e.session.backend.glContext.version),y=Qe(c.length),v=c.length,E=Dt(),{activationFunction:T,applyActivation:$}=Rt(i),F=l?`${Ai(y,E,a[2].dims,c,!0)}`:"",C=t?`${pm(y,E,a,c)}`:"",J=t?"getAAtOutCoordsMatmul(i)":`getA(${dm(E,d)})`,ge=t?"getBAtOutCoordsMatmul(i)":`getB(${hm(E,f)})`,ze=t?"":`${y} rc =
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      `,Fe=`
            ${C}
            ${F}
            ${T}
            void main() {
              ${ze}

              vec4 value = vec4(0);
              for (int i = 0; i < ${s}; i++) {
                vec4 a = ${J};
                vec4 b = ${ge};

                value += (a.rrbb * b.rgrg);
                value += (a.ggaa * b.baba);
              }
              ${n}
              ${$}
              ${b.output} = value;
            }`;return{...r,output:{dims:c,type:a[0].type,textureType:2},shaderSource:Fe,hasMain:!0}},no=(e,r,a)=>{let i=fm(r.length>2,a.activationCacheKey);return{...i,get:()=>cm(e,i,r,a)}}}),rf,nf=L(()=>{to(),Ql(),Pi(),rf=(e,r,a)=>{let i=r[0].dims,l=r[1].dims,n=Rr(i,l,a.dilations,a.pads,a.strides),o=e.run(Zl(e,r[0],r[1],n,a),[r[0]]),p=e.reshapePacked(r[1],[l[0],l[1]*l[2]*l[3]]),c=r.length===3?[p,o,r[2]]:[p,o],t=e.run(no(e,c,a),c);return e.reshapePacked(t,n)}}),mm,bm,of,Ei,Di=L(()=>{ae(),mm=e=>({name:"Im2Col",inputNames:["X"],inputTypes:[0],cacheHint:e}),bm=(e,r,a,i,l,n)=>{let o=a.dims,p=i.dims,c=l.length,t=Ei(o,p,l,4),u=`
        const int XC = ${o[1]};
        const int XH = ${o[2]};
        const int XW = ${o[3]};
        const int KH = ${n.kernelShape[0]};
        const int KW = ${n.kernelShape[1]};
        const int dilationH = ${n.dilations[0]};
        const int dilationW = ${n.dilations[1]};
        const int strideH = ${n.strides[0]};
        const int strideW = ${n.strides[1]};
        const int padH = ${n.pads[0]};
        const int padW = ${n.pads[1]};
        const int KHKW = KH*KW;
        const int XCKHKW = XC * KHKW;
        const int outputChannels = 4;
        vec4 process(int indices[${c}]) {
          int b  = indices[0]; // batch size
          int oh = indices[1] * strideH - padH; //output height
          int ow = indices[2] * strideW - padW; //output width
          int p = indices[3] * outputChannels; //patch
          vec4 value = vec4(0.0);
          for(int i=0; i < outputChannels; ++i) {
            if(p < XCKHKW) {
              int patchC = p / KHKW;
              int patchH = (p - patchC*KHKW) / KW;
              int patchW = (p - patchC*KHKW) - patchH * KW;
              int xh2 = oh + patchH * dilationH;
              int xw2 = ow + patchW * dilationW;
              int x[${o.length}];
              x[0] = b;
              x[1] = patchC;
              x[2] = xh2;
              x[3] = xw2;
              if(xh2 >= 0 &&
                  xh2 < XH &&
                  xw2 >= 0 &&
                  xw2 < XW) {
                value[i] = _X(x);
              }
            }
            ++p;
          }
          return value;
        }
        `;return{...r,output:{dims:t,type:a.type,textureType:4},shaderSource:u}},of=(e,r,a,i,l)=>{let n=mm(l.cacheKey);return{...n,get:()=>bm(e,n,r,a,i,l)}},Ei=(e,r,a,i=4)=>[a[0],a[2],a[3],Math.ceil(e[1]*r[2]*r[3]/i)]}),gm,ym,af,sf=L(()=>{fe(),we(),ae(),xr(),Di(),gm=(e,r)=>({name:"ConvDotProduct",inputNames:e?["Im2Col","K","B"]:["Im2Col","K"],inputTypes:e?[0,4,0]:[0,4],cacheKey:r.activationCacheKey}),ym=(e,r,a,i,l)=>{let n=a[0].dims,o=a[1].dims,p=[o[0],Math.ceil(n[1]*o[2]*o[3]/4)],c=Ei(n,o,i),[t,u]=e.calculateTextureWidthAndHeight(p,4),s=U.computeStrides(c),[d,f]=e.calculateTextureWidthAndHeight(c,4),b=i.length,y=a.length<3?"0.0":"_B(b)",v=Math.ceil(n[1]*o[2]*o[3]/4),{activationFunction:E,applyActivation:T}=Rt(l),$=H(e.session.backend.glContext.version),F=`
${E}
float process(int indices[${b}]) {
  int b[1];
  b[0] = indices[1];
  int im2col[4];
  im2col[0] = indices[0];
  im2col[1] = indices[2];
  im2col[2] = indices[3];
  int im2colOffset = im2col[0] * ${s[0]} + im2col[1] * ${s[1]} + im2col[2] * ${s[2]};
  int kernelOffset = indices[1] * ${p[1]};
  float value = ${y};
  for (int i = 0; i < ${v}; ++i) {
    vec2 im2colCoords = offsetToCoords(im2colOffset, ${d}, ${f});
    vec2 kernelCoords = offsetToCoords(kernelOffset, ${t}, ${u});
    value += dot(${$.texture2D}(Im2Col, im2colCoords), ${$.texture2D}(K, kernelCoords));
    ++im2colOffset;
    ++kernelOffset;
  }
  ${T}
  return value;
}`;return{...r,output:{dims:i,type:a[0].type,textureType:0},shaderSource:F}},af=(e,r,a,i)=>{let l=gm(r.length>2,i);return{...l,get:()=>ym(e,l,r,a,i)}}}),Rr,Li,Tm,xm,wm,vm,Ci,_m,to=L(()=>{Ue(),fe(),Jl(),nf(),sf(),xr(),Di(),ro(),Rr=(e,r,a,i,l)=>{let n=e[0],o=e.slice(2),p=o.length,c=r[0],t=r.slice(2).map((s,d)=>s+(s-1)*(a[d]-1)),u=o.map((s,d)=>s+i[d]+i[d+p]).map((s,d)=>Math.floor((s-t[d]+l[d])/l[d]));return[n,c].concat(...u)},Li=(e,r,a)=>(_m(r,a),Tm(e,r,a)),Tm=(e,r,a)=>{let i=vm(a,r),l=e.session.pack,n=i.kernelShape[0]===1&&i.kernelShape[1]===1;return i.group>1?[e.run(Kl(e,r,i),r)]:n&&l?[xm(e,r,i)]:l&&r[0].dims.length===4&&r[0].dims[0]===1&&!n?[rf(e,r,i)]:[wm(e,r,i)]},xm=(e,r,a)=>{let i=r[0].dims,l=r[1].dims,n=Rr(i,l,a.dilations,a.pads,a.strides),o=e.reshapeUnpacked(r[0],[i[1],i[2]*i[3]]),p=e.reshapeUnpacked(r[1],[l[0],l[1]]),c=r.length>2?[p,o,r[2]]:[p,o],t=e.run(Si(c,a),c);return e.reshapeUnpacked(t,n)},wm=(e,r,a)=>{let i=r[0].dims,l=r[1].dims,n=Rr(i,l,a.dilations,a.pads,a.strides),o=e.run(of(e,r[0],r[1],n,a),[r[0]]),p=r.length===3?[o,r[1],r[2]]:[o,r[1]];return e.run(af(e,r,n,a),p)},vm=(e,r)=>{let a=e.kernelShape.slice();if(e.kernelShape.length===0)for(let n=2;n<r[1].dims.length;++n)a.push(r[1].dims[n]);let i=e.pads.slice();mr.adjustPadsBasedOnAutoPad(r[0].dims,e.strides,e.dilations,a,i,e.autoPad);let l=Object.assign({},e);return Object.assign(l,{kernelShape:a,pads:i,cacheKey:e.cacheKey}),l},Ci=e=>{let r=e.attributes,a=Nr(r),i=r.getString("auto_pad","NOTSET"),l=r.getInts("dilations",[1,1]),n=r.getInt("group",1),o=r.getInts("kernel_shape",[]),p=r.getInts("pads",[0,0,0,0]),c=r.getInts("strides",[1,1]);return Q({autoPad:i,dilations:l,group:n,kernelShape:o,pads:p,strides:c,...a})},_m=(e,r)=>{if(!e||e.length!==2&&e.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(e[0].dims.length!==4||e[1].dims.length!==4)throw new Error("currently only support 2-dimensional conv");let a=e[0].dims[1],i=e[1].dims[1]*r.group;if(a!==i)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");if(e.length===3&&(e[2].dims.length!==1||e[1].dims[0]!==e[2].dims[0]))throw new Error("invalid bias");let l=e[0].dims.length-2;if(r.dilations.length!==l)throw new Error(`dilations should be ${l}D`);if(r.strides.length!==l)throw new Error(`strides should be ${l}D`);if(r.pads.length!==l*2)throw new Error(`pads should be ${l*2}D`);if(r.kernelShape.length!==0&&r.kernelShape.length!==e[1].dims.length-2)throw new Error("invalid kernel shape");if(e[0].type!=="float32"||e[1].type!=="float32")throw new Error("Conv input(X,W) should be float tensor");if(e.length===3&&e[2].type!=="float32")throw new Error("Conv input(bias) should be float tensor")}}),Om,Im,Sm,uf,Am,Pm,Em,Dm,Lm,Cm,lf,Fm,ff=L(()=>{Ue(),we(),ae(),xr(),Om=(e,r,a,i,l,n)=>(e-1)*r+a+(i-1)*l+1-n,Im=(e,r,a,i,l)=>{let n=Math.floor(e/2);r==="SAME_UPPER"?(a[i]=n,a[l]=e-n):r==="SAME_LOWER"&&(a[i]=e-n,a[l]=n)},Sm=(e,r,a,i,l,n,o,p)=>{let c=e.length-2,t=p.length===0;for(let u=0;u<c;++u){let s=t?e[u+2]*n[u]:p[u],d=Om(e[u+2],n[u],l[u],r[u],a[u],s);Im(d,i,l,u,u+c),t&&p.push(n[u]*(e[u+2]-1)+o[u]+(r[u]-1)*a[u]+1-l[u]-l[u+c])}},uf=(e,r,a)=>(Fm(r,a),Am(e,r,a)),Am=(e,r,a)=>{let i=Cm(a,r);return[Lm(e,r,i)]},Pm=(e,r)=>({name:"ConvTranspose",inputNames:e?["X","W","B"]:["X","W"],inputTypes:e?[0,0,0]:[0,0],cacheHint:r}),Em=(e,r,a,i)=>{let l=r.length>2?"getB(output_channel)":"0.0",n=r[0].dims,o=r[1].dims,p=o[1],c=o[0]/i.group,t=[r[0].dims[0],r[1].dims[1]*i.group,...i.outputShape],u=H(e.session.backend.glContext.version),{activationFunction:s,applyActivation:d}=Rt(i),f=`
  const ivec2 strides = ivec2(${i.strides[0]}, ${i.strides[1]});
  const ivec2 pads = ivec2(${i.pads[0]}, ${i.pads[1]});
  ${s}
  void main() {
    ivec4 coords = getOutputCoords();
    int batch = coords.x;
    int output_channel = coords.y;

    ivec2 loc = coords.zw + pads;

    int group_id = output_channel / ${p};
    int wOutChannel = output_channel - group_id * ${p};

    float value = ${l};
    for (int inChannelOffset = 0; inChannelOffset < ${c}; inChannelOffset++) {
      int input_channel = group_id * ${c} + inChannelOffset;
      for (int wWOff = 0; wWOff < ${o[2]}; wWOff++) {
        for (int wHOff = 0; wHOff < ${o[3]}; wHOff++) {
          ivec2 wOff = ivec2(wWOff * ${i.dilations[0]}, wHOff * ${i.dilations[1]});
          ivec2 wLoc = loc - wOff;
          ivec2 wLocIn = wLoc / strides;
          if (
            wLocIn * strides == wLoc &&
            wLocIn.x >= 0 && wLocIn.x < ${n[2]} &&
            wLocIn.y >= 0 && wLocIn.y < ${n[3]}
          ) {
            float xVal = getX(batch, input_channel, wLocIn.y, wLocIn.x);
            float wVal = getW(input_channel, wOutChannel, wHOff, wWOff);
            value += xVal * wVal;
          }
        }
      }
    }
    ${d}
    ${u.output} = vec4(value, .0, .0, .0);
  }
`;return{...a,output:{dims:t,type:r[0].type,textureType:0},shaderSource:f,hasMain:!0}},Dm=(e,r,a)=>{let i=Pm(r.length>2,a.cacheKey);return{...i,get:()=>Em(e,r,i,a)}},Lm=(e,r,a)=>e.run(Dm(e,r,a),r),Cm=(e,r)=>{let a=e.kernelShape.slice();if(e.kernelShape.length===0)for(let p=2;p<r[1].dims.length;++p)a.push(r[1].dims[p]);let i=e.pads.slice(),l=e.outputShape.slice(),n=r[0].dims;Sm(n,a,e.dilations,e.autoPad,i,e.strides,e.outputPadding,l);let o=Object.assign({},e);return Object.assign(o,{kernelShape:a,pads:i,outputShape:l,cacheKey:e.cacheKey}),o},lf=e=>{let r=e.attributes,a=Nr(r),i=r.getString("auto_pad","NOTSET"),l=r.getInts("dilations",[1,1]),n=r.getInt("group",1),o=r.getInts("kernel_shape",[]),p=r.getInts("output_padding",[0,0]),c=r.getInts("output_shape",[]),t=r.getInts("pads",[0,0,0,0]),u=r.getInts("strides",[1,1]);return Q({autoPad:i,dilations:l,group:n,kernelShape:o,outputPadding:p,outputShape:c,pads:t,strides:u,...a})},Fm=(e,r)=>{if(!e||e.length!==2&&e.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(e[0].dims.length!==4||e[1].dims.length!==4)throw new Error("currently only support 2-dimensional conv");let a=e[0].dims[1],i=e[1].dims[0];if(a!==i)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");let l=e[1].dims[1]*r.group;if(e.length===3&&(e[2].dims.length!==1||e[2].dims[0]!==l))throw new Error("invalid bias");let n=e[0].dims.length-2;if(r.dilations.length!==n)throw new Error(`dilations should be ${n}D`);if(r.strides.length!==n)throw new Error(`strides should be ${n}D`);if(r.pads.length!==n*2)throw new Error(`pads should be ${n*2}D`);if(r.outputPadding.length!==n)throw new Error(`output_padding should be ${n}D`);if(r.kernelShape.length!==0&&r.kernelShape.length!==e[1].dims.length-2)throw new Error("invalid kernel shape");if(r.outputShape.length!==0&&r.outputShape.length!==e[0].dims.length-2)throw new Error("invalid output shape");if(e[0].type!=="float32"||e[1].type!=="float32")throw new Error("ConvTranspose input(X,W) should be float tensor");if(e.length===3&&e[2].type!=="float32")throw new Error("ConvTranspose input(bias) should be float tensor")}}),cf,wr,pf,$m,df,km,Bm,Nm,oo=L(()=>{Ue(),fe(),ae(),cf={name:"Transpose",inputNames:["A"],inputTypes:[0]},wr=(e,r,a)=>(Nm(r),[e.run({...cf,cacheHint:a.cacheKey,get:()=>$m(e,r[0],a.perm)},r)]),pf=e=>Q({perm:e.attributes.getInts("perm",[])}),$m=(e,r,a)=>{let i=r.dims;a=df(i,a);let l=km(i,a),n=i.length,o=`
      ${Bm("perm",a,n)}
      float process(int indices[${n}]) {
        int a[${n}];
        perm(a, indices);
        return _A(a);
      }`;return{...cf,output:{dims:l,type:r.type,textureType:0},shaderSource:o}},df=(e,r)=>(r&&r.length!==e.length&&(r=[...e.keys()].reverse()),r),km=(e,r)=>(r=df(e,r),U.sortBasedOnPerm(e,r)),Bm=(e,r,a)=>{let i=[];i.push(`void ${e}(out int a[${a}], int src[${a}]) {`);for(let l=0;l<a;++l)i.push(`	a[${r[l]}]=src[${l}];`);return i.push("	}"),i.join(`
`)},Nm=e=>{if(!e||e.length!==1)throw new Error("Transpose requires 1 input.");if(e[0].type!=="float32"&&e[0].type!=="float64")throw new Error("input should be float tensor")}}),hf,mf,Rm,bf=L(()=>{oo(),hf=(e,r,a)=>{Rm(r);let i=a.blocksize,l=i*i,n=a.mode==="DCR"?[0,3,4,1,5,2]:[0,1,4,2,5,3],o=a.mode==="DCR"?[r[0].dims[0],i,i,r[0].dims[1]/l,r[0].dims[2],r[0].dims[3]]:[r[0].dims[0],r[0].dims[1]/l,i,i,r[0].dims[2],r[0].dims[3]],p=e.reshapeUnpacked(r[0],o),c={perm:n,cacheKey:`${n}`},[t]=wr(e,[p],c),u=[r[0].dims[0],r[0].dims[1]/l,r[0].dims[2]*i,r[0].dims[3]*i];return[e.reshapeUnpacked(t,u)]},mf=e=>{let r=e.attributes.getInt("blocksize");if(r<1)throw new Error(`blocksize must be >= 1, but got : ${r} for DepthToSpace`);let a=e.attributes.getString("mode","DCR");if(a!=="DCR"&&a!=="CRD")throw new Error(`unrecognized mode: ${a} for DepthToSpace`);return{mode:a,blocksize:r}},Rm=e=>{if(e.length!==1)throw new Error(`DepthToSpace expect 1 inputs, but got ${e.length}`);if(e[0].type==="string"||e[0].dims.length!==4)throw new TypeError("DepthToSpace input should be a 4-D numeric tensor")}}),gf,yf,Mm,Tf=L(()=>{fe(),gf=(e,r,a)=>{Mm(r,a);let i=U.flattenShape(r[0].dims,a);return[e.reshapeUnpacked(r[0],i)]},yf=e=>e.attributes.getInt("axis",1),Mm=(e,r)=>{if(!e||e.length!==1)throw new Error("Flatten requires 1 input.");let a=e[0].dims.length;if(a===0)throw new Error("scalar tensor is not supported.");if(r<-a||r>a)throw new Error("Invalid axis");if(e[0].type==="string")throw new Error("string tensor is not supported.")}}),Qt,pn=L(()=>{Qt=["float32","float64","int32","int16","int8","uint16","uint32","uint8"]}),xf,wf,Gm,Um,zm,Vm,vf=L(()=>{Ue(),pn(),fe(),ae(),xf=(e,r,a)=>(Vm(r,a.axis),[e.run(zm(e,r,a),r)]),wf=e=>Q({axis:e.attributes.getInt("axis",0)}),Gm={name:"Gather",inputNames:["A","B"],inputTypes:[0,0]},Um=(e,r,a,i)=>{let l=a[0].dims.slice(),n=a[1].dims.slice(),o=new Array(l.length+n.length-1);i=U.normalizeAxis(i,l.length);let p=[];for(let d=0;d<o.length;d++)d<i?(o[d]=l[d],p.push(`inputIdx[${d}] = outputIdx[${d}];`)):d<i+n.length?(o[d]=n[d-i],p.push(`indexDataIdx[${d-i}] = outputIdx[${d}];`)):(o[d]=l[d-n.length+1],p.push(`inputIdx[${d-n.length+1}] = outputIdx[${d}];`));let c=o.length||1,t=l.length,u=n.length||1,s=`
      float process(int outputIdx[${c}]) {
        int inputIdx[${t}];
        int indexDataIdx[${u}];
        indexDataIdx[0] = 0;
        ${p.join(`
        `)}
        int idx = int(_B(indexDataIdx));
        inputIdx[${i}] = idx < 0 ? idx + ${l[i]} : idx;
        return _A(inputIdx);
      }`;return{...r,output:{dims:o,type:a[0].type,textureType:0},shaderSource:s}},zm=(e,r,a)=>{let i={...Gm,cacheHint:a.cacheKey};return{...i,get:()=>Um(e,i,r,a.axis)}},Vm=(e,r)=>{if(!e||e.length!==2)throw new Error("Gather requires 2 inputs.");let a=e[0].dims.length;if(a<1)throw new Error("Invalid input shape.");if(r<-a||r>a-1)throw new Error("Invalid axis.");if(Qt.indexOf(e[0].type)===-1)throw new Error("Invaid input type.");if(e[1].type!=="int32"&&e[1].type!=="int16")throw new Error("Invaid input type.")}}),Fi,_f,Of,If,Wm,Hm,qm,Sf=L(()=>{Ue(),fe(),ae(),Fi=(e,r,a)=>(qm(r,a),[e.run(Wm(r,a),r)]),_f=(e,r)=>{let a=e.attributes.getInt("transA",0)!==0,i=e.attributes.getInt("transB",0)!==0,l=e.attributes.getFloat("alpha",1),n=e.attributes.getFloat("beta",1);return Q({transA:a,transB:i,alpha:l,beta:n,isOptionalC:r})},Of=e=>_f(e,!1),If=e=>_f(e,!0),Wm=(e,r)=>{let a={name:"Gemm",inputNames:e.length===3?["A","B","C"]:["A","B"],inputTypes:e.length===3?[0,0,0]:[0,0],key:r.cacheKey};return{...a,get:()=>Hm(a,e,r)}},Hm=(e,r,a)=>{let i=r[0].dims.slice(),l=r[1].dims.slice(),[n,o]=jn.getShapeOfGemmResult(i,a.transA,l,a.transB,r.length===3?r[2].dims:void 0),p=[n,o];if(!p)throw new Error("Can't use gemm on the given tensors");let c=i[i.length-1],t="";a.transA&&(c=i[0]),a.transA&&a.transB?t="value += _A_T(a) * _B_T(b);":a.transA&&!a.transB?t="value += _A_T(a) * _B(b);":!a.transA&&a.transB?t="value += _A(a) * _B_T(b);":!a.transA&&!a.transB&&(t="value += _A(a) * _B(b);");let u=p.length,s=r.length===3?`int c[${r[2].dims.length}];`:"",d=r.length===3?"bcastIndices_C(indices, c);":"",f=r.length===3?"value += beta * _C(c);":"",b=`
      float process(int indices[${u}]) {
          int a[${u}];
          int b[${u}];
          ${s}

          copyVec(indices, a);
          copyVec(indices, b);
          ${d}

          float value = 0.0;
          for (int k=0; k<${c}; ++k) {
              a[${u-1}] = k;
              b[${u-2}] = k;
              ${t}
          }

          value = value * alpha;
          ${f}
          return value;
      }`;return{...e,output:{dims:p,type:r[0].type,textureType:0},variables:[{name:"alpha",type:"float",data:a.alpha},{name:"beta",type:"float",data:a.beta}],shaderSource:b}},qm=(e,r)=>{if(!e)throw new Error("Input is missing");if(r.isOptionalC&&(e.length<2||e.length>3))throw new Error("Invaid input shape.");if(!r.isOptionalC&&e.length!==3)throw new Error("Gemm requires 3 inputs");if(e.length===3&&e[2].dims.length!==1&&e[2].dims.length!==2)throw new Error("Invalid input shape of C");if(e[0].type!=="float32"&&e[0].type!=="float64"||e[1].type!=="float32"&&e[1].type!=="float64"||e.length===3&&e[2].type!=="float32"&&e[2].type!=="float64")throw new Error("Invalid input type.");if(e[0].type!==e[1].type||e.length===3&&e[0].type!==e[2].type)throw new Error("Input types are mismatched")}}),Af,Pf,jm,Ym,Xm,Km,Jm,Ef=L(()=>{Ue(),ae(),Af=(e,r,a)=>(Jm(r),[e.run(Xm(e,r,a),r)]),Pf=e=>{let r=e.attributes.getFloat("scale"),a=e.attributes.getFloats("bias");return Q({scale:r,bias:a})},jm={name:"ImageScaler",inputNames:["X"],inputTypes:[0]},Ym=(e,r,a,i)=>{let l=a[0].dims.slice(),n=l.length,o=`
      ${Km(i.bias.length)}
      float process(int indices[${n}]) {
        return _X(indices) * scale + getBias(bias, indices[1]);
      }`;return{...r,output:{dims:l,type:a[0].type,textureType:0},variables:[{name:"bias",type:"float",arrayLength:i.bias.length,data:i.bias},{name:"scale",type:"float",data:i.scale}],shaderSource:o}},Xm=(e,r,a)=>{let i={...jm,cacheHint:a.cacheKey};return{...i,get:()=>Ym(e,i,r,a)}},Km=e=>{let r=[`float getBias(float bias[${e}], int channel) {`];for(let a=0;a<e;++a)a===0?r.push(`	if (channel == ${a}) { return bias[${a}]; }`):a===e-1?r.push(`	else { return bias[${a}]; }`):r.push(`	else if (channel == ${a}) { return bias[${a}]; }`);return r.push("	}"),r.join(`
`)},Jm=e=>{if(!e||e.length!==1)throw new Error("ImageScaler requires 1 input.");if(e[0].dims.length!==4)throw new Error("Invalid input shape.");if(e[0].type!=="float32"&&e[0].type!=="float64")throw new Error("Invalid input type.")}}),Lf,Cf,Df,Zm,Qm,eb,tb,rb,nb,Ff=L(()=>{we(),ae(),Lf=(e,r,a)=>{nb(r);let i=e.run(Qm(r[0]),r);return[e.run(rb(e,r[0],a,i.dims),[r[0],i,r[1],r[2]])]},Cf=e=>e.attributes.getFloat("epsilon",1e-5),Df={name:"InstanceNormalization_MeanAndVariance",inputNames:["X"],inputTypes:[0]},Zm=(e,r)=>{let a=r.dims.slice(),i=a[1],l=a[2]*a[3],n=[a[0],i],o=`
      vec4 process(int[2] indices) {
        vec4 v = vec4(0.0);
        int a[4];
        a[0] = indices[0];
        a[1] = indices[1];
        float temp = 0.0;
        for(int a2=0; a2<${a[2]}; a2++) {
          a[2] = a2;
          for(int a3=0; a3<${a[3]}; a3++) {
            a[3] = a3;
            float x = _X(a);
            temp += x;
          }
        }
        float mean = temp / float(${l});
        temp = 0.0;
        for(int a2=0; a2<${a[2]}; a2++) {
          a[2] = a2;
          for(int a3=0; a3<${a[3]}; a3++) {
            a[3] = a3;
            float x = _X(a);
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          }
        }
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        v.g = temp / float(${l});

        return v;
      }`;return{...e,output:{dims:n,type:r.type,textureType:4},shaderSource:o}},Qm=e=>({...Df,get:()=>Zm(Df,e)}),eb={name:"InstanceNormalization_ComputeOutput",inputNames:["X","MeanAndVariance","Scale","B"],inputTypes:[0,4,0,0]},tb=(e,r,a,i,l)=>{let n=H(e.session.backend.glContext.version),[o,p]=e.calculateTextureWidthAndHeight(l,4),[c,t]=[o/4,p],u=`
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      float process(int[4] indices) {
        int mv[2];
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        mv[1] = indices[1];
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        float mean = mean_and_variance.r;
        float variance = mean_and_variance.g;

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        return scale * (_X(indices) - mean) / sqrt(variance + epsilon) + b;
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    float process(int indices[${i}]) {
        int c = indices[1];
        float x = _X(indices);
        float square_sum = 0.0;

        for (int i = ${l}; i <= ${n}; i++) {
          int idx = c + i;
          if (c >= 0 && c < ${a}) {
            indices[1] = idx;
            float j = _X(indices);
            square_sum += j * j;
          }
        }
        return x / pow(${p} + ${o} * square_sum, ${c});
    }`;return{...Bf,cacheHint:r.cacheKey,output:{dims:e[0].dims,type:e[0].type,textureType:0},shaderSource:t}}function ib(e,r){return{...Bf,cacheHint:r.cacheKey,get:()=>ob(e,r)}}var $f,kf,Bf,ab,Nf=L(()=>{Ue(),ae(),$f=(e,r,a)=>(ab(r),[e.run(ib(r,a),r)]),kf=e=>{let r=e.attributes.getFloat("alpha",1e-4),a=e.attributes.getFloat("beta",.75),i=e.attributes.getFloat("bias",1),l=e.attributes.getInt("size");return Q({alpha:r,beta:a,bias:i,size:l})},Bf={name:"LRN",inputNames:["X"],inputTypes:[0]},ab=e=>{if(!e||e.length!==1)throw new Error("LRN requires 1 input.");if(e[0].dims.length!==4)throw new Error('currently only support LRN for input with "NCHW" format');if(e[0].type!=="float32")throw new Error("input should be float type")}}),sb,$i,Rf,Mf,Gf,ub,lb,fb,cb,pb,db,hb,mb,Uf=L(()=>{Ue(),fe(),we(),ae(),sb={name:"Pad",inputNames:["A"],inputTypes:[0]},$i=(e,r,a)=>(fb(r),[e.run({...sb,cacheHint:a.cacheKey,get:()=>lb(e,r[0],a)},r)]),Rf=e=>{let r=e.attributes.getString("mode","constant"),a=e.attributes.getFloat("value",0),i=e.attributes.getInts("pads");return Q({mode:r,value:a,pads:i})},Mf=(e,r,a)=>{cb(r);let i=ub(e,r,a);return $i(e,[r[0]],i)},Gf=e=>e.attributes.getString("mode","constant"),ub=(e,r,a)=>{if(!e.session.isInitializer(r[1].dataId)||r.length>=3&&!e.session.isInitializer(r[2].dataId))throw new Error("dynamic pad attributes are not allowed");let i=Array.from(r[1].integerData),l=r.length>=3?r[2].floatData[0]:0;return Q({mode:a,pads:i,value:l})},lb=(e,r,a)=>{let i=U.padShape(r.dims.slice(),a.pads),l=i.length,n=`
      ${pb(e,r,a)}
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        k = m[${t}] - ${n[t]};
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      float padA(int m[${p}]) {
        const float constant = float(${o});
        int offset = 0;
        int k = 0;
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        vec2 coords = offsetToCoords(offset, ${i}, ${l});
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        return value;
      }
      `},hb=(e,r,a,i,l,n)=>{let o=r.length,p="";for(let c=o-1;c>=0;--c)p+=`
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        {
          const int _2n_1 = ${2*(r[c]-1)};
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        }
        offset += k * ${a[c]};
        `;return`
      float padA(int m[${o}]) {
        int offset = 0;
        int k = 0;
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        vec2 coords = offsetToCoords(offset, ${i}, ${l});
        float value = getColorAsFloat(${e.texture2D}(A, coords));
        return value;
      }
      `},mb=(e,r,a,i,l,n)=>{let o=r.length,p="";for(let c=o-1;c>=0;--c)p+=`
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      float padA(int m[${o}]) {
        int offset = 0;
        int k = 0;
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      `;return{...r,output:{dims:n,type:e[0].type,textureType:0},shaderSource:t}},qf=(e,r,a)=>{ao(r);let i={name:"GlobalAveragePool",inputNames:["X"],inputTypes:[0],cacheHint:`${a.countIncludePad}`};return[e.run({...i,get:()=>Hf(r,i,!0,a)},r)]},jf=e=>{let r=e.attributes.getInt("count_include_pad",0)!==0;return Q({autoPad:"",ceilMode:0,countIncludePad:r,kernelShape:[],strides:[],pads:[]})},Yf=(e,r,a)=>{ao(r);let i={name:"MaxPool",inputNames:["X"],inputTypes:[0],cacheHint:a.cacheKey};return[e.run({...i,get:()=>Kf(r,i,!1,a)},r)]},Xf=e=>{let r=e.attributes.getString("auto_pad","NOTSET"),a=e.attributes.getInt("ceil_mode",0),i=e.attributes.getInts("kernel_shape"),l=e.attributes.getInts("strides",[]),n=e.attributes.getInts("pads",[]),o=e.attributes.getInt("storage_order",0),p=e.attributes.getInts("dilations",[]);if(o!==0)throw new Error("column major storage order is not yet supported for MaxPool");if(a!==0)throw new Error("using ceil() in shape computation is not yet supported for MaxPool");return Q({autoPad:r,ceilMode:a,countIncludePad:!1,kernelShape:i,strides:l,pads:n,storageOrder:o,dilations:p})},Kf=(e,r,a,i)=>{let[l,n]=Jf(e,i,a),o=`
      value = max(_X(x), value);
    `,p="",c=`
      ${Qf(e[0].dims,l,o,p,"-1e5")}
    `;return{...r,output:{dims:n,type:e[0].type,textureType:0},shaderSource:c}},Jf=(e,r,a)=>{let i=e[0].dims.slice(),l=Object.hasOwnProperty.call(r,"dilations"),n=r.kernelShape.slice(),o=r.strides.slice(),p=l?r.dilations.slice():[],c=r.pads.slice();mr.adjustPoolAttributes(a,i,n,o,p,c);let t=mr.computePoolOutputShape(a,i,o,p,n,c,r.autoPad),u=Object.assign({},r);return l?Object.assign(u,{kernelShape:n,strides:o,pads:c,dilations:p,cacheKey:r.cacheKey}):Object.assign(u,{kernelShape:n,strides:o,pads:c,cacheKey:r.cacheKey}),[u,t]},bb={autoPad:"",ceilMode:0,countIncludePad:!1,kernelShape:[],strides:[],pads:[],storageOrder:0,dilations:[],cacheKey:""},zf={name:"GlobalMaxPool",inputNames:["X"],inputTypes:[0]},Zf=(e,r)=>(ao(r),[e.run({...zf,get:()=>Kf(r,zf,!0,bb)},r)]),ao=e=>{if(!e||e.length!==1)throw new Error("Pool ops requires 1 input.");if(e[0].type!=="float32"&&e[0].type!=="float64")throw new Error("Invalid input type.")},Qf=(e,r,a,i,l)=>{let n=e.length;if(r.kernelShape.length<=2){let o=r.kernelShape[r.kernelShape.length-1],p=r.strides[r.strides.length-1],c=r.pads[r.pads.length/2-1],t=r.pads[r.pads.length-1],u=e[n-1],s="",d="",f="";if(c+t!==0?s=`
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            ${a}
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            for (int j = 0; j < ${b}; j++) {
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                continue;
              }
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            for (int j = 0; j < ${b}; j++) {
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            `,f=`
          }
        `}return`
        float process(int indices[${n}]) {
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          float value = ${l};
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          ${s}
          ${f}
          ${i}
          return value;
        }
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            if (x[j] >= inputDims[j] || x[j] < 0) {
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            }
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          if (!isPad) {
            ${a}
          }`:v=`
          }
          ${a}
        `,`
        ${u}
        float process(int indices[${n}]) {
          int x[${n}];
          copyVec(indices, x);
          int offset[${c}];
          int pads[${t}];
          int inputDims[${n}];
          int kernelStrides[${c}];
          int strides[${c}];
          ${d}
          ${s}
          ${b}
          ${f}

          float value = ${l};
          int pad = 0;
          bool isPad = false;
          for (int i = 0; i < ${o}; i++) {
            offsetToIndices(i, kernelStrides, offset);
            isPad = false;
            for (int j = ${n} - ${c}; j < ${n}; j++) {
              x[j] = indices[j] * strides[j - ${n} + ${c}]
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              ${v}
          }
          ${i}

          return value;
        }
      `}},io=(e,r)=>{let a="";for(let i=0;i<e.length;i++)a+=`
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    if (${e} == 0) {
      return;
    }
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      indices[i] = offset / strides[i];
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        float value;                 // final result
        int inputIdx[${p}];      // addressing input data
        ${c.join(`
`)}
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`)}
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      int output_pitches[${t}];
      int input_pitches[${t}];
      `;for(let y=t-1;y>=0;y--)u[y]=y===t-1?1:u[y+1]*o[y+1],s[y]=y===t-1?1:s[y+1]*r[0].dims[y+1],d+=`
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        input_pitches[${y}] = ${s[y]};
        `;let f=`
      float getInputFloat(int index) {
        vec2 coords = offsetToCoords(index, ${l}, ${n});
        float value = getColorAsFloat(${i.texture2D}(X, coords));
        return value;
      }
      `,b=a.mode==="nearest"?`
    ${f}
    float process(int indices[${t}]) {
      int input_index = 0;
      int output_index = coordsToOffset(TexCoords, ${p}, ${c});

      ${d}

      int d, m;
      for (int dim = 0; dim < ${t}; ++dim) {
        d = output_index / output_pitches[dim];
        m = output_index - d * output_pitches[dim];
        output_index = m;

        if (scales[dim] != 1 && d > 0) {
          int d2 = d / scales[dim];
          m = d - d2 * scales[dim];
          d = d2;
        }
        input_index += input_pitches[dim] * d;
      }

      return getInputFloat(input_index);
    }`:t===4?`
    ${f}
    float process(int indices[4]) {
      int input_index = 0;
      int output_index = coordsToOffset(TexCoords, ${p}, ${c});

      ${d}

      int m;
      int index_of_dim0, index_of_dim1, index_of_dim2, index_of_dim3;
      index_of_dim0 = output_index / output_pitches[0];
      m = output_index - index_of_dim0 * output_pitches[0];
      index_of_dim1 = m / output_pitches[1];
      m = m - index_of_dim1 * output_pitches[1];
      index_of_dim2 = m / output_pitches[2];
      m = m - index_of_dim2 * output_pitches[2];
      index_of_dim3 = m;

      int index_of_input_dim2, index_of_input_dim3, x_offset, y_offset;
      index_of_input_dim2 = index_of_dim2 / scales[2];
      y_offset = index_of_dim2 - index_of_input_dim2 * scales[2];
      index_of_input_dim3 = index_of_dim3 / scales[3];
      x_offset = index_of_dim3 - index_of_input_dim3 * scales[3];

      input_index = index_of_dim0 * input_pitches[0] +
            index_of_dim1 * input_pitches[1] +
            index_of_input_dim2 * input_pitches[2] +
            index_of_input_dim3;

      float x00 = getInputFloat(input_index);
      float x10, x01, x11;

      bool end_of_dim2 = false;
      if (index_of_input_dim2 == (${r[0].dims[2]} - 1)) {
        // It's the end in dimension 2
        x01 = x00;
        end_of_dim2 = true;
      } else {
        x01 = getInputFloat(input_index + input_pitches[2]);
      }

      if (index_of_input_dim3 == (input_pitches[2] - 1)) {
        // It's the end in dimension 3
        x10 = x00;
        x11 = x01;
      }
      else {
        x10 = getInputFloat(input_index + 1);
        x11 = end_of_dim2 ? x10 : getInputFloat(input_index + input_pitches[2] + 1);
      }

      float y0 = x00 + float(y_offset) * (x01 - x00) / float(scales[2]);
      float y1 = x10 + float(y_offset) * (x11 - x10) / float(scales[2]);
      return y0 + float(x_offset) * (y1 - y0) / float(scales[3]);
    }`:`
    ${f}
    float process(int indices[2]) {
      int input_index = 0;
      int output_index = coordsToOffset(TexCoords, ${p}, ${c});

      ${d}

      int m;
      int index_of_dim0, index_of_dim1;
      index_of_dim0 = output_index / output_pitches[0];
      m = output_index - index_of_dim0 * output_pitches[0];
      index_of_dim1 = m;

      int index_of_input_dim0, index_of_input_dim1, x_offset, y_offset;
      index_of_input_dim0 = index_of_dim0 / scales[0];
      y_offset = index_of_dim0 - index_of_input_dim0 * scales[0];
      index_of_input_dim1 = index_of_dim1 / scales[1];
      x_offset = index_of_dim1 - index_of_input_dim1 * scales[1];

      input_index = index_of_input_dim0 * input_pitches[0] + index_of_input_dim1;

      float x00 = getInputFloat(input_index);
      float x10, x01, x11;

      bool end_of_dim0 = false;
      if (index_of_input_dim0 == (${r[0].dims[0]} - 1)) {
        // It's the end in dimension 0
        x01 = x00;
        end_of_dim0 = true;
      } else {
        x01 = getInputFloat(input_index + input_pitches[0]);
      }

      if (index_of_input_dim1 == (input_pitches[0] - 1)) {
        // It's the end in dimension 1
        x10 = x00;
        x11 = x01;
      }
      else {
        x10 = getInputFloat(input_index + 1);
        x11 = end_of_dim0 ? x10 : getInputFloat(input_index + input_pitches[0] + 1);
      }

      float y0 = x00 + float(y_offset) * (x01 - x00) / float(scales[0]);
      float y1 = x10 + float(y_offset) * (x11 - x10) / float(scales[0]);
      return y0 + float(x_offset) * (y1 - y0) / float(scales[1]);
    }`;return{...cc,output:{dims:o,type:r[0].type,textureType:0},shaderSource:b,variables:[{name:"scales",type:"int",arrayLength:a.scales.length,data:a.scales.map(y=>Math.ceil(y))}]}},Bi=(e,r)=>{if(!e||r.opset<9&&e.length!==1||r.opset>=9&&r.opset<11&&e.length!==2||r.opset>=11&&e.length<2)throw new Error("invalid inputs.");if(r.scales.length>0&&e[0].dims.length!==r.scales.length)throw new Error("Invalid input shape.");if(e[0].type==="string")throw new Error("Invalid input tensor types.")},so=(e,r,a)=>{if(a){for(let i of e)if(i<=0)throw new Error("Scale value should be greater than 0.")}else for(let i of e)if(i<1)throw new Error("Scale value should be greater than or equal to 1.");if((r==="linear"||r==="cubic")&&e.length!==2&&(e.length!==4||e[0]!==1||e[1]!==1))throw new Error(`'Linear' mode and 'Cubic' mode only support 2-D inputs ('Bilinear', 'Bicubic')         or 4-D inputs with the corresponding outermost 2 scale values being 1         in the ${a?"Resize":"Upsample"} opeartor.`)}}),Ri,Mi,hc,mc,wb,vb,_b,Ob,bc=L(()=>{we(),ae(),Bt(),Tr(),Ni(),Ri={name:"Resize",inputNames:["A"],inputTypes:[2]},Mi=(e,r,a)=>(Bi(r,a),[e.run({...Ri,cacheHint:a.cacheKey,get:()=>wb(e,r,a)},r)]),hc=e=>dn(e,10),mc=e=>dn(e,11),wb=(e,r,a)=>{let i=H(e.session.backend.glContext.version),[l,n]=vb(r,a);if(l.every(T=>T===1)&&a.coordinateTransformMode!=="tf_crop_and_resize")return{...Ri,output:{dims:n,type:r[0].type,textureType:2},hasMain:!0,shaderSource:`void main() {
                    vec4 v = ${i.texture2D}(X, TexCoords);
                    ${i.output} = v;
                }`};let o=n.length;if(o<2)throw new Error(`output dimension should be at least 2, but got ${o}`);let p=n[o-2],c=n[o-1],t=r[0].dims;if(o!==t.length)throw new Error(`output dimension should match input ${t.length}, but got ${o}`);let u=t[o-2],s=t[o-1],d=l[o-2],f=l[o-1],b="";if(a.mode!=="linear")throw new Error(`resize (packed) does not support mode: '${a.mode}'`);switch(a.coordinateTransformMode){case"asymmetric":b=`
                    vec4 getSourceFracIndex(ivec4 coords) {
                        return vec4(coords) / scaleWHWH;
                    }
                `;break;case"half_pixel":b=`
                    vec4 getSourceFracIndex(ivec4 coords) {
                        return (vec4(coords) + 0.5) / scaleWHWH - 0.5;
                    }
                `;break;case"pytorch_half_pixel":b=`
                    vec4 getSourceFracIndex(ivec4 coords) {
                        vec4 fcoords = vec4(coords);
                        return vec4(
                            ${c}.0 > 1.0 ? (fcoords.x + 0.5) / scaleWHWH.x - 0.5 : 0.0,
                            ${p}.0 > 1.0 ? (fcoords.y + 0.5) / scaleWHWH.y - 0.5 : 0.0,
                            ${c}.0 > 1.0 ? (fcoords.z + 0.5) / scaleWHWH.z - 0.5 : 0.0,
                            ${p}.0 > 1.0 ? (fcoords.w + 0.5) / scaleWHWH.w - 0.5 : 0.0
                          );
                    }
                `;break;case"align_corners":b=`
                    vec4 getSourceFracIndex(ivec4 coords) {
                        vec4 resized = vec4(${c}.0 - 1.0, ${p}.0 - 1.0, ${c}.0 - 1.0,
                            ${p}.0 - 1.0);
                        vec4 original = vec4(${s}.0 - 1.0, ${u}.0 - 1.0, ${s}.0 - 1.0,
                            ${u}.0 - 1.0);
                        vec4 new_scale = original / resized;
                        return vec4(coords) * new_scale;
                    }
                `;break;default:throw new Error(`resize (packed) does not support coordinateTransformMode:                                 '${a.coordinateTransformMode}'`)}let y=Qe(o),v=Nt(),E=`
            const vec2 inputWH = vec2(${u}.0, ${s}.0);
            const vec4 scaleWHWH = vec4(float(${d}), float(${f}), float(${d}), float(${f}));
            ${v}
            ${b}
            float getAValue(int x10, int r, int c, int d) {
                return getChannel(getA(x10, r, c, d), vec2(c, d));
            }
            void main() {
                ${y} rc = getOutputCoords();

                int batch = rc[0];
                int depth = rc[1];

                // retrieve the 4 coordinates that is used in the 4 packed output values.
                ivec4 coords = ivec4(rc.wz, rc.w + 1, rc.z + 1);

                // calculate the source index in fraction
                vec4 sourceFrac = getSourceFracIndex(coords);

                // get the lower and upper bound of the 4 values that will be packed into one texel.
                ivec4 x00 = ivec4(max(sourceFrac.xy, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.xy)));
                ivec4 x01 = ivec4(max(sourceFrac.xw, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.xw)));
                ivec4 x10 = ivec4(max(sourceFrac.zy, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.zy)));
                ivec4 x11 = ivec4(max(sourceFrac.zw, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.zw)));

                bool hasNextRow = rc.w < ${p-1};
                bool hasNextCol = rc.z < ${c-1};

                // pack x00, x01, x10, x11's top-left corner into one vec4 structure
                vec4 topLeft = vec4(
                    getAValue(batch, depth, x00.x, x00.y),
                    hasNextCol ? getAValue(batch, depth, x01.x, x01.y) : 0.0,
                    hasNextRow ? getAValue(batch, depth, x10.x, x10.y) : 0.0,
                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.x, x11.y) : 0.0);

                // pack x00, x01, x10, x11's top-right corner into one vec4 structure
                vec4 topRight = vec4(
                    getAValue(batch, depth, x00.x, x00.w),
                    hasNextCol ? getAValue(batch, depth, x01.x, x01.w) : 0.0,
                    hasNextRow ? getAValue(batch, depth, x10.x, x10.w) : 0.0,
                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.x, x11.w) : 0.0);

                // pack x00, x01, x10, x11's bottom-left corner into one vec4 structure
                vec4 bottomLeft = vec4(
                    getAValue(batch, depth, x00.z, x00.y),
                    hasNextCol ? getAValue(batch, depth, x01.z, x01.y) : 0.0,
                    hasNextRow ? getAValue(batch, depth, x10.z, x10.y) : 0.0,
                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.z, x11.y) : 0.0);

                // pack x00, x01, x10, x11's bottom-right corner into one vec4 structure
                vec4 bottomRight = vec4(
                    getAValue(batch, depth, x00.z, x00.w),
                    hasNextCol ? getAValue(batch, depth, x01.z, x01.w) : 0.0,
                    hasNextRow ? getAValue(batch, depth, x10.z, x10.w) : 0.0,
                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.z, x11.w) : 0.0);

                // calculate the interpolation fraction on u and v direction
                vec4 frac = vec4(sourceFrac) - floor(sourceFrac);
                vec4 clampFrac = clamp(frac, vec4(0.0), vec4(1.0));

                vec4 top = mix(topLeft, topRight, clampFrac.ywyw);
                vec4 bottom = mix(bottomLeft, bottomRight, clampFrac.ywyw);
                vec4 newValue = mix(top, bottom, clampFrac.xxzz);

                ${i.output} = vec4(newValue);
            }
        `;return{...Ri,output:{dims:n,type:r[0].type,textureType:2},hasMain:!0,shaderSource:E}},vb=(e,r)=>{let a=e[0].dims,i=r.scales,l;if(i.length===0){let o=e[r.scalesInputIdx];if(o&&o.size!==0){if(e[r.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");i=_b(o,r.mode,r.isResize)}else{let p=e[r.sizesInputIdx];if(!p||p.size===0)throw new Error("Either scales or sizes MUST be provided as input.");l=Array.from(p.integerData),i=Ob(l,a,r.mode,r.isResize)}}else if(e[r.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");let n=l||a.map((o,p)=>Math.floor(o*i[p]));return[i,n]},_b=(e,r,a)=>{let i=Array.from(e.floatData);return so(i,r,a),i},Ob=(e,r,a,i)=>{let l=r.length,n=new Array(l);for(let o=0,p=l;o<p;o++)if(r[o]===0){if(e[o]!==0)throw new Error("Input dim is zero but required output dim is non-zero.");n[o]=1}else n[o]=e[o]/r[o];return so(n,a,i),n}}),gc,Ib,yc=L(()=>{yr(),gc=(e,r)=>(Ib(r),[new $e([r[0].dims.length],"int32",void 0,void 0,new Int32Array(r[0].dims))]),Ib=e=>{if(!e||e.length!==1)throw new Error("Shape requires 1 input.")}}),Gi,Tc,xc,wc,Sb,vc,Ab,Pb,_c=L(()=>{Ue(),pn(),fe(),ae(),Gi={name:"Slice",inputNames:["A"],inputTypes:[0]},Tc=(e,r,a)=>(Sb(r),[e.run({...Gi,cacheHint:a.cacheKey,get:()=>wc(e,r[0],a)},r)]),xc=e=>{let r=e.attributes.getInts("starts"),a=e.attributes.getInts("ends"),i=e.attributes.getInts("axes",[]);return Q({starts:r,ends:a,axes:i})},wc=(e,r,a)=>{let i=a.axes.length===0?r.dims.slice(0).map((u,s)=>s):a.axes,l=U.normalizeAxes(i,r.dims.length),n=a.starts.map((u,s)=>u>r.dims[l[s]]-1?r.dims[l[s]]:U.normalizeAxis(u,r.dims[l[s]])),o=a.ends.map((u,s)=>u>r.dims[l[s]]-1?r.dims[l[s]]:U.normalizeAxis(u,r.dims[l[s]])),p=r.dims.slice(),c=[];for(let u=0;u<l.length;u++)p[l[u]]=o[u]-n[u],n[u]>0&&c.push(`outputIdx[${l[u]}] += ${n[u]};`);let t=`
      float process(int outputIdx[${p.length}]) {
        ${c.join(`
      `)}
        return _A(outputIdx);
      }`;return{...Gi,output:{dims:p,type:r.type,textureType:0},shaderSource:t}},Sb=e=>{if(!e||e.length!==1)throw new Error("Slice requires 1 input.");if(Qt.indexOf(e[0].type)===-1)throw new Error("Invalid input type.")},vc=(e,r)=>{Pb(r);let a=Ab(e,r);return[e.run({...Gi,cacheHint:a.cacheKey,get:()=>wc(e,r[0],a)},[r[0]])]},Ab=(e,r)=>{if(!e.session.isInitializer(r[1].dataId)||!e.session.isInitializer(r[2].dataId)||r.length>=4&&!e.session.isInitializer(r[3].dataId)||r.length>=5&&!e.session.isInitializer(r[4].dataId))throw new Error("dynamic slice attributes are not allowed");if(r.length>=5&&r[4].integerData.some(o=>o!==1))throw new Error("currently non-1 steps is not supported for Slice");let a=Array.from(r[1].integerData),i=Array.from(r[2].integerData),l=r.length>=4?Array.from(r[3].integerData):[],n=`${l};${a};${i}`;return{starts:a,ends:i,axes:l,cacheKey:n}},Pb=e=>{if(!e||e.length<3||e.length>5)throw new Error("Invalid input number.");if(e[1].type!=="int32"||e[1].dims.length!==1)throw new Error("Invalid input type.");if(e[2].type!=="int32"||e[2].dims.length!==1)throw new Error("Invalid input type.");if(e.length>=4&&(e[3].type!=="int32"||e[3].dims.length!==1))throw new Error("Invalid input type.");if(e.length>=5&&(e[4].type!=="int32"||e[4].dims.length!==1))throw new Error("Invalid input type.")}}),Oc,Ic,Sc,Ac,Pc,Ec,Dc,Lc,Eb,Db,Lb,Cc,Fc=L(()=>{Ue(),fe(),we(),ae(),oo(),Oc={name:"SoftmaxComputeMax",inputNames:["A"],inputTypes:[0]},Ic={name:"SoftmaxComputeScale",inputNames:["A","Max"],inputTypes:[0,0]},Sc={name:"SoftMax",inputNames:["A","Max","Norm"],inputTypes:[0,0,0]},Ac=(e,r,a)=>{Cc(r);let i=r[0].dims.slice(),l=U.normalizeAxis(a.axis,i.length),n=U.sizeToDimension(i,l),o=U.sizeFromDimension(i,l);return Lc(e,r,a,n,o)},Pc=e=>Q({axis:e.attributes.getInt("axis",1)}),Ec=e=>Q({axis:e.attributes.getInt("axis",-1)}),Dc=(e,r,a)=>{Cc(r);let i=r[0].dims.slice(),l=U.normalizeAxis(a.axis,i.length),n=i.length,o=l!==n-1,p=[],c=[],t=[],u;o&&(c=Array.from({length:n}).map((b,y)=>y),c[l]=n-1,c[n-1]=l,c.map(b=>p.push(i[b])),u=Q({perm:c}),t=wr(e,r,u));let s=o?U.sizeToDimension(p,n-1):U.sizeToDimension(i,n-1),d=o?U.sizeFromDimension(p,n-1):U.sizeFromDimension(i,n-1),f=Lc(e,o?t:r,a,s,d);return o?wr(e,f,u):f},Lc=(e,r,a,i,l)=>{let n=Eb(e,r[0],i,l,[i]),o=e.run({...Oc,cacheHint:a.cacheKey,get:()=>n},r),p=Db(e,r[0],i,l,n.output.dims,[i]),c=e.run({...Ic,cacheHint:a.cacheKey,get:()=>p},[r[0],o]),t=Lb(e,r[0],i,l,n.output.dims,p.output.dims);return[e.run({...Sc,cacheHint:a.cacheKey,get:()=>t},[r[0],o,c])]},Eb=(e,r,a,i,l)=>{let[n,o]=e.calculateTextureWidthAndHeight(r.dims,0),p=l.length;if(a<1||i<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(l.length!==1)throw new Error("Dimensionality of the output should be 1");if(l[0]!==a)throw new Error("Shape of the output should be equal to logical row count");let c=H(e.session.backend.glContext.version),t=`
      float process(int[${p}] indices) {
        int logical_row_start_offset = indices[0] * ${i};

        float max = getColorAsFloat(${c.texture2D}(A, offsetToCoords(logical_row_start_offset, ${n},
        ${o} )));
        for(int i=1; i<${i}; ++i)
        {
          float current = getColorAsFloat(${c.texture2D}(A, offsetToCoords(logical_row_start_offset + i,
            ${n}, ${o})));
          if(current > max)
          max = current;
        }

        return max;
      }`;return{...Oc,output:{dims:l,type:r.type,textureType:0},shaderSource:t}},Db=(e,r,a,i,l,n)=>{let[o,p]=e.calculateTextureWidthAndHeight(r.dims,0),c=n.length;if(a<1||i<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(n.length!==1)throw new Error("Dimensionality of the output should be 1");if(n[0]!==a)throw new Error("Shape of the output should be equal to logical row count");if(l.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(l[0]!==a)throw new Error("Shape of the intermediate results should be equal to logical row count");let t=H(e.session.backend.glContext.version),u=`
      float process(int[${c}] indices) {
        int logical_row_start_offset = indices[0] * ${i};

        float norm_factor = 0.0;
        float max = _Max(indices);
        for(int i=0; i<${i}; ++i)
        {
          norm_factor += exp(getColorAsFloat(${t.texture2D}(A, offsetToCoords(logical_row_start_offset + i,
            ${o}, ${p}))) - max);
        }

        return norm_factor;
      }`;return{...Ic,output:{dims:n,type:r.type,textureType:0},shaderSource:u}},Lb=(e,r,a,i,l,n)=>{let[o,p]=e.calculateTextureWidthAndHeight(r.dims,0),c=r.dims.length;if(a<1||i<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(l.length!==1||n.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(l[0]!==a||n[0]!==a)throw new Error("Shape of the intermediate results should be equal to logical row count");let t=`
      float process(int[${c}] indices) {

      // get offset of current logical tensor index from the 2-D texture coordinates (TexCoords)
      int offset = coordsToOffset(TexCoords, ${o}, ${p});

      //determine the logical row for this index
      int logical_row_index[1];
      logical_row_index[0] = offset / ${i};

      float norm_factor = _Norm(logical_row_index);

      // avoid possible division by 0
      // if norm_facor is 0, all elements are zero
      // if so, return 0
      if(norm_factor == 0.0)
        return 0.0;

      return exp(_A(indices) - _Max(logical_row_index)) / norm_factor;
    }`;return{...Sc,output:{dims:r.dims,type:r.type,textureType:0},shaderSource:t}},Cc=e=>{if(!e||e.length!==1)throw new Error("Softmax requires 1 input.");if(e[0].type!=="float32"&&e[0].type!=="float64")throw new Error("Invalid input type")}}),$c,kc,Bc,Cb,Fb,$b,Nc=L(()=>{Ue(),fe(),ae(),$c={name:"Split",inputNames:["A"],inputTypes:[0]},kc=(e,r,a)=>{$b(r);let i=U.normalizeAxis(a.axis,r[0].dims.length),l=Cb(e,r,i,a),n=[];for(let o=0;o<l;++o)n.push(e.run({...$c,cacheHint:`${a.cacheKey};${o}`,get:()=>Fb(e,r[0],a,i,o)},r));return n},Bc=e=>{let r=e.attributes.getInt("axis",0),a=e.attributes.getInts("split",[]),i=e.outputs.length;return Q({axis:r,split:a,numOutputs:i})},Cb=(e,r,a,i)=>{let[,l]=an.splitShape(r[0].dims,a,i.split,i.numOutputs);return l.length},Fb=(e,r,a,i,l)=>{let[n,o]=an.splitShape(r.dims,i,a.split,a.numOutputs),p=o[l],c=n[l],t=`
      float process(int indices[${c.length}]) {
        indices[${i}] += ${p};
        return _A(indices);
      }
    `;return{...$c,cacheHint:`${a.cacheKey}:${l}`,output:{dims:c,type:r.type,textureType:0},shaderSource:t}},$b=e=>{if(!e||e.length!==1)throw new Error("Split requires one input.");if(e[0].type!=="int8"&&e[0].type!=="uint8"&&e[0].type!=="int16"&&e[0].type!=="uint16"&&e[0].type!=="int32"&&e[0].type!=="uint32"&&e[0].type!=="float32"&&e[0].type!=="float64"&&e[0].type!=="bool")throw new Error("Invalid input type.")}}),Ui,Rc,Mc,kb,Bb,Gc=L(()=>{fe(),Ui=(e,r,a)=>{kb(r);let i=U.squeezeShape(r[0].dims,a);return[e.reshapeUnpacked(r[0],i)]},Rc=(e,r)=>(Bb(r),Ui(e,[r[0]],Array.from(r[1].integerData))),Mc=e=>e.attributes.getInts("axes"),kb=e=>{if(!e||e.length!==1)throw new Error("Squeeze requires 1 input.");if(e[0].type==="string")throw new Error("invalid input tensor types.")},Bb=e=>{if(!e||e.length!==2)throw new Error("Squeeze requires 2 inputs.");if(e[1].type!=="int32")throw new Error("Invalid input type.")}}),Uc,Nb,Rb,zc=L(()=>{we(),ae(),Uc=(e,r)=>{Rb(r);let a={name:"Sum",inputNames:r.map((i,l)=>`X${l}`),inputTypes:new Array(r.length).fill(0)};return[e.run({...a,get:()=>Nb(e,r,a)},r)]},Nb=(e,r,a)=>{let i=H(e.session.backend.glContext.version),l=r[0].dims.slice(),n=`
      void main() {
        vec4 result = ${r.map((o,p)=>`${i.texture2D}(X${p},TexCoords)`).join(" + ")};
        ${i.output} = result;
      }
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        ivec3 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
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      ivec4 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
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          int index = resTexRC.y * ${r[0]} + resTexRC.x;
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        }
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      ivec5 getOutputCoords() {
          ivec2 resTexRC = ivec2(TexCoords.xy *
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          int index = resTexRC.y * ${r[0]} + resTexRC.x;
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        }
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     ivec6 getOutputCoords() {
         ivec2 resTexRC = ivec2(TexCoords.xy *
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         int index = resTexRC.y * ${r[0]} + resTexRC.x;
         ${o}
         return ivec6(r, c, d, d2, d3, d4);
       }
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      int texC = index / texNumR;
      int texR = index - texC * texNumR;
      // TODO: swap texR, texC order in following function so row is corresponding to u and column is corresponding to
      //       v.
      return (vec2(texR, texC) + halfCR) / vec2(texNumR, texNumC);
    }
    `),r="packedUVfrom1D",e[r]=new R(`
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        int texelIndex = index / 2;
        int texR = texelIndex / texNumC;
        int texC = texelIndex - texR * texNumC;
        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
      }
      `),r="packedUVfrom2D",e[r]=new R(`
      vec2 packedUVfrom2D(int texNumR, int texNumC, int texelsInLogicalRow, int row, int col) {
        int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
        int texR = texelIndex / texNumC;
        int texC = texelIndex - texR * texNumC;
        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
      }
      `),r="packedUVfrom3D",e[r]=new R(`
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        int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);
        int texR = index / texNumC;
        int texC = index - texR * texNumC;
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      }
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        return vec4(outputValue.xy, outputValue.xy);
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          return vec4(outputValue.x, outputValue.x, 0., 0.);
        `:y=`
          return vec4(outputValue.x);
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        int lastDim = coords.${f[c-1]};
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        coords.${f[c-2]} = lastDim;
      `,$=`
      vec4 ${e}() {
        ${u} coords = getOutputCoords();
        ${T}
        ${d}
        vec4 outputValue = ${o}(${b});
        ${y}
      }
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          float ${e}() {
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n=this._nodes[l],o=e.node[l];if(!o.output)throw new Error(`missing output for node: ${o.name}`);for(let p of o.output){let c=r.get(p);if(typeof c>"u"&&(c=this._allData.push(new Mt)-1,r.set(p,c)),n.outputs.push(c),this._allData[c]._from!==void 0)throw new Error(`multiple nodes output to one data value: ${c}`);if(this._allData[c]._from=l,o.opType==="Constant"){if(!o.attribute||o.attribute.length!==1||!o.attribute[0].t)throw new Error("missing attributes or missing tensor value in attributes for this Constant operator");if(!o.output||o.output.length!==1)throw new Error("missing output or incorrect number of outputs for this Constant operator");n.outputs.pop(),n.executeNode=!1,this._allData[c]._from=-1,this._allData[c].tensor=$e.fromProto(o.attribute[0].t)}}}for(let l=0;l<this._nodes.length;l++){let n=this._nodes[l],o=e.node[l];if(!o.input)throw new Error(`missing input for node: ${o.name}`);for(let p of o.input){let c=r.get(p);if(typeof c>"u"){if(p===""&&(o.input.length===3||o.input.length===4)&&o.opType==="Resize")continue;throw new Error(`unrecognized input '${p}' for node: ${o.name}`)}n.inputs.push(c),this._allData[c]._to.push(l)}}return!0}buildGraphFromOrtFormat(e){var l,n,o;let r=new Map;this._allData=[],this._allInputIndices=[],this._allInputNames=[],this._allOutputIndices=[],this._allOutputNames=[],this._nodes=[];let a=new Map,i=[];for(let p=0;p<e.inputsLength();p++){let c=e.inputs(p);if(r.has(c))throw new Error(`duplicated input name: ${c}`);for(let t=0;t<e.nodeArgsLength();t++)if(((l=e.nodeArgs(t))==null?void 0:l.name())===c){let u=new Mt;if(((o=(n=e.nodeArgs(t))==null?void 0:n.type())==null?void 0:o.valueType())!==wo.TypeInfoValue.tensor_type)throw new Error("Unexpected value type for the nodeArg.");let s=e.nodeArgs(t).type().value(new wo.TensorTypeAndShape),d=We.tensorDataTypeFromProto(s.elemType()),f=s.shape(),b=[];for(let v=0;v<f.dimLength();v++)b.push(it.longToNumber(f.dim(v).value().dimValue()));u.type={shape:{dims:b},tensorType:d};let y=this._allData.push(u)-1;r.set(c,y),i.push(c)}}for(let p=0;p<e.initializersLength();p++){let c=e.initializers(p),t=r.get(c.name());if(t===void 0){let u=new Mt,s=We.tensorDimsFromORTFormat(c),d=We.tensorDataTypeFromProto(c.dataType());u.type={shape:{dims:s},tensorType:d},t=this._allData.push(u)-1,r.set(c.name(),t)}this._allData[t]._from=-1,this._allData[t].tensor=$e.fromOrtTensor(c)}for(let p=0;p<this._allData.length;p++)this._allData[p].tensor||(this._allInputIndices.push(p),this._allInputNames.push(i[p]));for(let p=0;p<e.outputsLength();p++){let c=e.outputs(p);if(r.has(c))throw new Error(`duplicated output name: ${c}`);let t=this._allData.push(new Mt)-1;r.set(c,t),this._allOutputIndices.push(t),this._allOutputNames.push(c)}if(!e.nodes)throw new Error("missing information in graph: node");for(let p=0;p<e.nodesLength();p++){let c=e.nodes(p),t=c.name();if(!t)for(let s=0;t=`unnamed_${c.opType()}_${s}`,!!a.has(t);s++);if(a.has(t))throw new Error(`duplicated node name: ${t}`);let u=this._nodes.push(new vo(c,t))-1;a.set(t,u)}for(let p=0;p<this._nodes.length;p++){let c=this._nodes[p],t=e.nodes(p);if(t==null)throw new Error(`No node exists at index ${p}`);if((t==null?void 0:t.outputsLength())===0)throw new Error(`missing output for node: ${t.name}`);for(let u=0;u<(t==null?void 0:t.outputsLength());u++){let s=t==null?void 0:t.outputs(u),d=r.get(s);if(typeof d>"u"&&(d=this._allData.push(new Mt)-1,r.set(s,d)),c.outputs.push(d),this._allData[d]._from!==void 0)throw new Error(`multiple nodes output to one data value: ${d}`);if(this._allData[d]._from=p,t.opType()==="Constant"){if(t.attributesLength()!==1||!t.attributes(0).t())throw new Error("missing attributes or missing tensor value in attributes for this Constant operator");if(t.outputsLength()!==1)throw new Error("missing output or incorrect number of outputs for this Constant operator");c.outputs.pop(),c.executeNode=!1,this._allData[d]._from=-1,this._allData[d].tensor=$e.fromOrtTensor(t.attributes(0).t())}}}for(let p=0;p<this._nodes.length;p++){let c=this._nodes[p],t=e.nodes(p);if(t.inputsLength()===0)throw new Error(`missing input for node: ${t.name}`);for(let u=0;u<t.inputsLength();u++){let s=t.inputs(u),d=r.get(s);if(typeof d>"u")throw new Error(`unrecognized input '${s}' for node: ${t.name()}`);c.inputs.push(d),this._allData[d]._to.push(p)}}}checkIsAcyclic(){let e=new Set;this._allInputIndices.forEach(i=>{this._allData[i]._to.forEach(l=>{e.add(l)})});let r=Array.from(e),a=new Array(this._nodes.length).fill("white");for(;r.length>0;){let i=r.pop();a[i]==="gray"?a[i]="black":(r.push(i),a[i]="gray",this._nodes[i].outputs.forEach(l=>{let n=this._allData[l];if(typeof n.tensor<"u")throw new Error("node outputs should not be initialized");if(n._from!==i)throw new Error("from property of the Value object doesn't match index of Node being processed");n._to.forEach(o=>{if(a[o]==="gray")throw new Error("model graph is cyclic");a[o]==="white"&&r.push(o)})}))}}transformGraph(e){this.removeAllIdentityNodes(),this.removeAllDropoutNodes(),this.fuseConvActivationNodes(),e&&e.transformGraph(this),this.finalizeGraph()}finalizeGraph(){let e=0,r=new Array(this._nodes.length,0),a=0;for(let i=0;i<this._nodes.length;i++)r[i]=a,this._nodes[i].executeNode?(a!==i&&(this._nodes[a]=this._nodes[i]),a++):this._nodes[i].outputs.forEach(l=>{this._allData[l]._from=-2});this._nodes.splice(a,this._nodes.length-a);for(let i=0;i<this._allData.length;i++){let l=this._allData[i];l._from!==void 0&&l._from!==-1&&l._from!==-2&&(l._from=r[l._from]);for(let n=0;n<l._to.length;n++)if(l._to[n]>=0)l._to[n]=r[l._to[n]];else throw new Error("Trying to update a removed node")}e=0;for(let i=0;i<this._allData.length;i++){if(this._allData[i].from===-2&&this._allOutputIndices.indexOf(i+e)===-1){e++,this._allData.splice(i,1),i--;continue}if(e>0){let l=-1;this._allData[i].from!==void 0&&this._allData[i].from!==-1?(l=this._nodes[this._allData[i].from].outputs.indexOf(i+e),l!==-1&&(this._nodes[this._allData[i].from].outputs[l]=i)):(l=this._allInputIndices.indexOf(i+e),l!==-1&&(this._allInputIndices[l]=i)),this._allData[i].to.forEach(n=>{l=this._nodes[n].inputs.indexOf(i+e),l!==-1&&(this._nodes[n].inputs[l]=i)}),this._allData[i].to.length===0&&(l=this._allOutputIndices.indexOf(i+e),l!==-1&&(this._allOutputIndices[l]=i))}}}deleteNode(e){let r=this._nodes[e];if(r.outputs.length>1){for(let o=1;o<r.outputs.length;o++)if(this._allData[r.outputs[o]].to.length>0)throw new Error("Node deletion with more than one output connected to other nodes is not supported. 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Bundled license information:

long/index.js:
  (**
   * @license
   * Copyright 2009 The Closure Library Authors
   * Copyright 2020 Daniel Wirtz / The long.js Authors.
   *
   * 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.
   *
   * SPDX-License-Identifier: Apache-2.0
   *)
*/export{Pd as InferenceSession,ls as TRACE,lr as TRACE_FUNC_BEGIN,fr as TRACE_FUNC_END,Me as Tensor,Dd as TrainingSession,jO as default,Z as env,Pr as registerBackend};