/*! For license information please see ort.webgl.min.js.LICENSE.txt */
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expected";if(null!=t.t&&t.hasOwnProperty("t")&&(n=l.onnx.TensorProto.verify(t.t)))return"t."+n;if(null!=t.g&&t.hasOwnProperty("g")&&(n=l.onnx.GraphProto.verify(t.g)))return"g."+n;if(null!=t.sparseTensor&&t.hasOwnProperty("sparseTensor")&&(n=l.onnx.SparseTensorProto.verify(t.sparseTensor)))return"sparseTensor."+n;if(null!=t.tp&&t.hasOwnProperty("tp")&&(n=l.onnx.TypeProto.verify(t.tp)))return"tp."+n;if(null!=t.floats&&t.hasOwnProperty("floats")){if(!Array.isArray(t.floats))return"floats: array expected";for(var e=0;e<t.floats.length;++e)if("number"!=typeof t.floats[e])return"floats: number[] expected"}if(null!=t.ints&&t.hasOwnProperty("ints")){if(!Array.isArray(t.ints))return"ints: array expected";for(e=0;e<t.ints.length;++e)if(!(u.isInteger(t.ints[e])||t.ints[e]&&u.isInteger(t.ints[e].low)&&u.isInteger(t.ints[e].high)))return"ints: integer|Long[] expected"}if(null!=t.strings&&t.hasOwnProperty("strings")){if(!Array.isArray(t.strings))return"strings: array expected";for(e=0;e<t.strings.length;++e)if(!(t.strings[e]&&"number"==typeof t.strings[e].length||u.isString(t.strings[e])))return"strings: buffer[] expected"}if(null!=t.tensors&&t.hasOwnProperty("tensors")){if(!Array.isArray(t.tensors))return"tensors: array expected";for(e=0;e<t.tensors.length;++e)if(n=l.onnx.TensorProto.verify(t.tensors[e]))return"tensors."+n}if(null!=t.graphs&&t.hasOwnProperty("graphs")){if(!Array.isArray(t.graphs))return"graphs: array expected";for(e=0;e<t.graphs.length;++e)if(n=l.onnx.GraphProto.verify(t.graphs[e]))return"graphs."+n}if(null!=t.sparseTensors&&t.hasOwnProperty("sparseTensors")){if(!Array.isArray(t.sparseTensors))return"sparseTensors: array expected";for(e=0;e<t.sparseTensors.length;++e)if(n=l.onnx.SparseTensorProto.verify(t.sparseTensors[e]))return"sparseTensors."+n}if(null!=t.typeProtos&&t.hasOwnProperty("typeProtos")){if(!Array.isArray(t.typeProtos))return"typeProtos: array expected";for(e=0;e<t.typeProtos.length;++e){var n;if(n=l.onnx.TypeProto.verify(t.typeProtos[e]))return"typeProtos."+n}}return null},t.fromObject=function(t){if(t instanceof l.onnx.AttributeProto)return t;var e=new l.onnx.AttributeProto;switch(null!=t.name&&(e.name=String(t.name)),null!=t.refAttrName&&(e.refAttrName=String(t.refAttrName)),null!=t.docString&&(e.docString=String(t.docString)),t.type){default:if("number"==typeof t.type){e.type=t.type;break}break;case"UNDEFINED":case 0:e.type=0;break;case"FLOAT":case 1:e.type=1;break;case"INT":case 2:e.type=2;break;case"STRING":case 3:e.type=3;break;case"TENSOR":case 4:e.type=4;break;case"GRAPH":case 5:e.type=5;break;case"SPARSE_TENSOR":case 11:e.type=11;break;case"TYPE_PROTO":case 13:e.type=13;break;case"FLOATS":case 6:e.type=6;break;case"INTS":case 7:e.type=7;break;case"STRINGS":case 8:e.type=8;break;case"TENSORS":case 9:e.type=9;break;case"GRAPHS":case 10:e.type=10;break;case"SPARSE_TENSORS":case 12:e.type=12;break;case"TYPE_PROTOS":case 14:e.type=14}if(null!=t.f&&(e.f=Number(t.f)),null!=t.i&&(u.Long?(e.i=u.Long.fromValue(t.i)).unsigned=!1:"string"==typeof t.i?e.i=parseInt(t.i,10):"number"==typeof t.i?e.i=t.i:"object"==typeof t.i&&(e.i=new u.LongBits(t.i.low>>>0,t.i.high>>>0).toNumber())),null!=t.s&&("string"==typeof t.s?u.base64.decode(t.s,e.s=u.newBuffer(u.base64.length(t.s)),0):t.s.length>=0&&(e.s=t.s)),null!=t.t){if("object"!=typeof t.t)throw TypeError(".onnx.AttributeProto.t: object expected");e.t=l.onnx.TensorProto.fromObject(t.t)}if(null!=t.g){if("object"!=typeof t.g)throw TypeError(".onnx.AttributeProto.g: object expected");e.g=l.onnx.GraphProto.fromObject(t.g)}if(null!=t.sparseTensor){if("object"!=typeof t.sparseTensor)throw TypeError(".onnx.AttributeProto.sparseTensor: object expected");e.sparseTensor=l.onnx.SparseTensorProto.fromObject(t.sparseTensor)}if(null!=t.tp){if("object"!=typeof t.tp)throw TypeError(".onnx.AttributeProto.tp: object expected");e.tp=l.onnx.TypeProto.fromObject(t.tp)}if(t.floats){if(!Array.isArray(t.floats))throw TypeError(".onnx.AttributeProto.floats: array expected");e.floats=[];for(var n=0;n<t.floats.length;++n)e.floats[n]=Number(t.floats[n])}if(t.ints){if(!Array.isArray(t.ints))throw TypeError(".onnx.AttributeProto.ints: array expected");for(e.ints=[],n=0;n<t.ints.length;++n)u.Long?(e.ints[n]=u.Long.fromValue(t.ints[n])).unsigned=!1:"string"==typeof t.ints[n]?e.ints[n]=parseInt(t.ints[n],10):"number"==typeof t.ints[n]?e.ints[n]=t.ints[n]:"object"==typeof t.ints[n]&&(e.ints[n]=new u.LongBits(t.ints[n].low>>>0,t.ints[n].high>>>0).toNumber())}if(t.strings){if(!Array.isArray(t.strings))throw TypeError(".onnx.AttributeProto.strings: array expected");for(e.strings=[],n=0;n<t.strings.length;++n)"string"==typeof t.strings[n]?u.base64.decode(t.strings[n],e.strings[n]=u.newBuffer(u.base64.length(t.strings[n])),0):t.strings[n].length>=0&&(e.strings[n]=t.strings[n])}if(t.tensors){if(!Array.isArray(t.tensors))throw TypeError(".onnx.AttributeProto.tensors: array expected");for(e.tensors=[],n=0;n<t.tensors.length;++n){if("object"!=typeof t.tensors[n])throw TypeError(".onnx.AttributeProto.tensors: object expected");e.tensors[n]=l.onnx.TensorProto.fromObject(t.tensors[n])}}if(t.graphs){if(!Array.isArray(t.graphs))throw TypeError(".onnx.AttributeProto.graphs: array expected");for(e.graphs=[],n=0;n<t.graphs.length;++n){if("object"!=typeof t.graphs[n])throw TypeError(".onnx.AttributeProto.graphs: object expected");e.graphs[n]=l.onnx.GraphProto.fromObject(t.graphs[n])}}if(t.sparseTensors){if(!Array.isArray(t.sparseTensors))throw TypeError(".onnx.AttributeProto.sparseTensors: array expected");for(e.sparseTensors=[],n=0;n<t.sparseTensors.length;++n){if("object"!=typeof t.sparseTensors[n])throw TypeError(".onnx.AttributeProto.sparseTensors: object expected");e.sparseTensors[n]=l.onnx.SparseTensorProto.fromObject(t.sparseTensors[n])}}if(t.typeProtos){if(!Array.isArray(t.typeProtos))throw TypeError(".onnx.AttributeProto.typeProtos: array expected");for(e.typeProtos=[],n=0;n<t.typeProtos.length;++n){if("object"!=typeof t.typeProtos[n])throw TypeError(".onnx.AttributeProto.typeProtos: object expected");e.typeProtos[n]=l.onnx.TypeProto.fromObject(t.typeProtos[n])}}return e},t.toObject=function(t,e){e||(e={});var n={};if((e.arrays||e.defaults)&&(n.floats=[],n.ints=[],n.strings=[],n.tensors=[],n.graphs=[],n.typeProtos=[],n.sparseTensors=[]),e.defaults){if(n.name="",n.f=0,u.Long){var r=new u.Long(0,0,!1);n.i=e.longs===String?r.toString():e.longs===Number?r.toNumber():r}else n.i=e.longs===String?"0":0;e.bytes===String?n.s="":(n.s=[],e.bytes!==Array&&(n.s=u.newBuffer(n.s))),n.t=null,n.g=null,n.docString="",n.tp=null,n.type=e.enums===String?"UNDEFINED":0,n.refAttrName="",n.sparseTensor=null}if(null!=t.name&&t.hasOwnProperty("name")&&(n.name=t.name),null!=t.f&&t.hasOwnProperty("f")&&(n.f=e.json&&!isFinite(t.f)?String(t.f):t.f),null!=t.i&&t.hasOwnProperty("i")&&("number"==typeof t.i?n.i=e.longs===String?String(t.i):t.i:n.i=e.longs===String?u.Long.prototype.toString.call(t.i):e.longs===Number?new u.LongBits(t.i.low>>>0,t.i.high>>>0).toNumber():t.i),null!=t.s&&t.hasOwnProperty("s")&&(n.s=e.bytes===String?u.base64.encode(t.s,0,t.s.length):e.bytes===Array?Array.prototype.slice.call(t.s):t.s),null!=t.t&&t.hasOwnProperty("t")&&(n.t=l.onnx.TensorProto.toObject(t.t,e)),null!=t.g&&t.hasOwnProperty("g")&&(n.g=l.onnx.GraphProto.toObject(t.g,e)),t.floats&&t.floats.length){n.floats=[];for(var i=0;i<t.floats.length;++i)n.floats[i]=e.json&&!isFinite(t.floats[i])?String(t.floats[i]):t.floats[i]}if(t.ints&&t.ints.length)for(n.ints=[],i=0;i<t.ints.length;++i)"number"==typeof t.ints[i]?n.ints[i]=e.longs===String?String(t.ints[i]):t.ints[i]:n.ints[i]=e.longs===String?u.Long.prototype.toString.call(t.ints[i]):e.longs===Number?new u.LongBits(t.ints[i].low>>>0,t.ints[i].high>>>0).toNumber():t.ints[i];if(t.strings&&t.strings.length)for(n.strings=[],i=0;i<t.strings.length;++i)n.strings[i]=e.bytes===String?u.base64.encode(t.strings[i],0,t.strings[i].length):e.bytes===Array?Array.prototype.slice.call(t.strings[i]):t.strings[i];if(t.tensors&&t.tensors.length)for(n.tensors=[],i=0;i<t.tensors.length;++i)n.tensors[i]=l.onnx.TensorProto.toObject(t.tensors[i],e);if(t.graphs&&t.graphs.length)for(n.graphs=[],i=0;i<t.graphs.length;++i)n.graphs[i]=l.onnx.GraphProto.toObject(t.graphs[i],e);if(null!=t.docString&&t.hasOwnProperty("docString")&&(n.docString=t.docString),null!=t.tp&&t.hasOwnProperty("tp")&&(n.tp=l.onnx.TypeProto.toObject(t.tp,e)),t.typeProtos&&t.typeProtos.length)for(n.typeProtos=[],i=0;i<t.typeProtos.length;++i)n.typeProtos[i]=l.onnx.TypeProto.toObject(t.typeProtos[i],e);if(null!=t.type&&t.hasOwnProperty("type")&&(n.type=e.enums===String?void 0===l.onnx.AttributeProto.AttributeType[t.type]?t.type:l.onnx.AttributeProto.AttributeType[t.type]:t.type),null!=t.refAttrName&&t.hasOwnProperty("refAttrName")&&(n.refAttrName=t.refAttrName),null!=t.sparseTensor&&t.hasOwnProperty("sparseTensor")&&(n.sparseTensor=l.onnx.SparseTensorProto.toObject(t.sparseTensor,e)),t.sparseTensors&&t.sparseTensors.length)for(n.sparseTensors=[],i=0;i<t.sparseTensors.length;++i)n.sparseTensors[i]=l.onnx.SparseTensorProto.toObject(t.sparseTensors[i],e);return n},t.prototype.toJSON=function(){return this.constructor.toObject(this,o.util.toJSONOptions)},t.getTypeUrl=function(t){return void 0===t&&(t="type.googleapis.com"),t+"/onnx.AttributeProto"},t.AttributeType=function(){var t={},e=Object.create(t);return e[t[0]="UNDEFINED"]=0,e[t[1]="FLOAT"]=1,e[t[2]="INT"]=2,e[t[3]="STRING"]=3,e[t[4]="TENSOR"]=4,e[t[5]="GRAPH"]=5,e[t[11]="SPARSE_TENSOR"]=11,e[t[13]="TYPE_PROTO"]=13,e[t[6]="FLOATS"]=6,e[t[7]="INTS"]=7,e[t[8]="STRINGS"]=8,e[t[9]="TENSORS"]=9,e[t[10]="GRAPHS"]=10,e[t[12]="SPARSE_TENSORS"]=12,e[t[14]="TYPE_PROTOS"]=14,e}(),t}(),i.ValueInfoProto=function(){function t(t){if(t)for(var e=Object.keys(t),n=0;n<e.length;++n)null!=t[e[n]]&&(this[e[n]]=t[e[n]])}return t.prototype.name="",t.prototype.type=null,t.prototype.docString="",t.create=function(e){return new t(e)},t.encode=function(t,e){return e||(e=a.create()),null!=t.name&&Object.hasOwnProperty.call(t,"name")&&e.uint32(10).string(t.name),null!=t.type&&Object.hasOwnProperty.call(t,"type")&&l.onnx.TypeProto.encode(t.type,e.uint32(18).fork()).ldelim(),null!=t.docString&&Object.hasOwnProperty.call(t,"docString")&&e.uint32(26).string(t.docString),e},t.encodeDelimited=function(t,e){return this.encode(t,e).ldelim()},t.decode=function(t,e){t instanceof s||(t=s.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new l.onnx.ValueInfoProto;t.pos<n;){var i=t.uint32();switch(i>>>3){case 1:r.name=t.string();break;case 2:r.type=l.onnx.TypeProto.decode(t,t.uint32());break;case 3:r.docString=t.string();break;default:t.skipType(7&i)}}return r},t.decodeDelimited=function(t){return t instanceof s||(t=new s(t)),this.decode(t,t.uint32())},t.verify=function(t){if("object"!=typeof t||null===t)return"object expected";if(null!=t.name&&t.hasOwnProperty("name")&&!u.isString(t.name))return"name: string expected";if(null!=t.type&&t.hasOwnProperty("type")){var e=l.onnx.TypeProto.verify(t.type);if(e)return"type."+e}return null!=t.docString&&t.hasOwnProperty("docString")&&!u.isString(t.docString)?"docString: string expected":null},t.fromObject=function(t){if(t instanceof l.onnx.ValueInfoProto)return t;var e=new l.onnx.ValueInfoProto;if(null!=t.name&&(e.name=String(t.name)),null!=t.type){if("object"!=typeof t.type)throw TypeError(".onnx.ValueInfoProto.type: object expected");e.type=l.onnx.TypeProto.fromObject(t.type)}return null!=t.docString&&(e.docString=String(t.docString)),e},t.toObject=function(t,e){e||(e={});var n={};return e.defaults&&(n.name="",n.type=null,n.docString=""),null!=t.name&&t.hasOwnProperty("name")&&(n.name=t.name),null!=t.type&&t.hasOwnProperty("type")&&(n.type=l.onnx.TypeProto.toObject(t.type,e)),null!=t.docString&&t.hasOwnProperty("docString")&&(n.docString=t.docString),n},t.prototype.toJSON=function(){return this.constructor.toObject(this,o.util.toJSONOptions)},t.getTypeUrl=function(t){return void 0===t&&(t="type.googleapis.com"),t+"/onnx.ValueInfoProto"},t}(),i.NodeProto=function(){function t(t){if(this.input=[],this.output=[],this.attribute=[],t)for(var e=Object.keys(t),n=0;n<e.length;++n)null!=t[e[n]]&&(this[e[n]]=t[e[n]])}return t.prototype.input=u.emptyArray,t.prototype.output=u.emptyArray,t.prototype.name="",t.prototype.opType="",t.prototype.domain="",t.prototype.attribute=u.emptyArray,t.prototype.docString="",t.create=function(e){return new t(e)},t.encode=function(t,e){if(e||(e=a.create()),null!=t.input&&t.input.length)for(var n=0;n<t.input.length;++n)e.uint32(10).string(t.input[n]);if(null!=t.output&&t.output.length)for(n=0;n<t.output.length;++n)e.uint32(18).string(t.output[n]);if(null!=t.name&&Object.hasOwnProperty.call(t,"name")&&e.uint32(26).string(t.name),null!=t.opType&&Object.hasOwnProperty.call(t,"opType")&&e.uint32(34).string(t.opType),null!=t.attribute&&t.attribute.length)for(n=0;n<t.attribute.length;++n)l.onnx.AttributeProto.encode(t.attribute[n],e.uint32(42).fork()).ldelim();return null!=t.docString&&Object.hasOwnProperty.call(t,"docString")&&e.uint32(50).string(t.docString),null!=t.domain&&Object.hasOwnProperty.call(t,"domain")&&e.uint32(58).string(t.domain),e},t.encodeDelimited=function(t,e){return this.encode(t,e).ldelim()},t.decode=function(t,e){t instanceof s||(t=s.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new l.onnx.NodeProto;t.pos<n;){var i=t.uint32();switch(i>>>3){case 1:r.input&&r.input.length||(r.input=[]),r.input.push(t.string());break;case 2:r.output&&r.output.length||(r.output=[]),r.output.push(t.string());break;case 3:r.name=t.string();break;case 4:r.opType=t.string();break;case 7:r.domain=t.string();break;case 5:r.attribute&&r.attribute.length||(r.attribute=[]),r.attribute.push(l.onnx.AttributeProto.decode(t,t.uint32()));break;case 6:r.docString=t.string();break;default:t.skipType(7&i)}}return r},t.decodeDelimited=function(t){return t instanceof s||(t=new s(t)),this.decode(t,t.uint32())},t.verify=function(t){if("object"!=typeof t||null===t)return"object expected";if(null!=t.input&&t.hasOwnProperty("input")){if(!Array.isArray(t.input))return"input: array expected";for(var e=0;e<t.input.length;++e)if(!u.isString(t.input[e]))return"input: string[] expected"}if(null!=t.output&&t.hasOwnProperty("output")){if(!Array.isArray(t.output))return"output: array expected";for(e=0;e<t.output.length;++e)if(!u.isString(t.output[e]))return"output: string[] expected"}if(null!=t.name&&t.hasOwnProperty("name")&&!u.isString(t.name))return"name: string expected";if(null!=t.opType&&t.hasOwnProperty("opType")&&!u.isString(t.opType))return"opType: string expected";if(null!=t.domain&&t.hasOwnProperty("domain")&&!u.isString(t.domain))return"domain: string expected";if(null!=t.attribute&&t.hasOwnProperty("attribute")){if(!Array.isArray(t.attribute))return"attribute: array expected";for(e=0;e<t.attribute.length;++e){var n=l.onnx.AttributeProto.verify(t.attribute[e]);if(n)return"attribute."+n}}return null!=t.docString&&t.hasOwnProperty("docString")&&!u.isString(t.docString)?"docString: string expected":null},t.fromObject=function(t){if(t instanceof l.onnx.NodeProto)return t;var e=new l.onnx.NodeProto;if(t.input){if(!Array.isArray(t.input))throw TypeError(".onnx.NodeProto.input: array expected");e.input=[];for(var n=0;n<t.input.length;++n)e.input[n]=String(t.input[n])}if(t.output){if(!Array.isArray(t.output))throw TypeError(".onnx.NodeProto.output: array expected");for(e.output=[],n=0;n<t.output.length;++n)e.output[n]=String(t.output[n])}if(null!=t.name&&(e.name=String(t.name)),null!=t.opType&&(e.opType=String(t.opType)),null!=t.domain&&(e.domain=String(t.domain)),t.attribute){if(!Array.isArray(t.attribute))throw TypeError(".onnx.NodeProto.attribute: array expected");for(e.attribute=[],n=0;n<t.attribute.length;++n){if("object"!=typeof t.attribute[n])throw TypeError(".onnx.NodeProto.attribute: object expected");e.attribute[n]=l.onnx.AttributeProto.fromObject(t.attribute[n])}}return null!=t.docString&&(e.docString=String(t.docString)),e},t.toObject=function(t,e){e||(e={});var n={};if((e.arrays||e.defaults)&&(n.input=[],n.output=[],n.attribute=[]),e.defaults&&(n.name="",n.opType="",n.docString="",n.domain=""),t.input&&t.input.length){n.input=[];for(var r=0;r<t.input.length;++r)n.input[r]=t.input[r]}if(t.output&&t.output.length)for(n.output=[],r=0;r<t.output.length;++r)n.output[r]=t.output[r];if(null!=t.name&&t.hasOwnProperty("name")&&(n.name=t.name),null!=t.opType&&t.hasOwnProperty("opType")&&(n.opType=t.opType),t.attribute&&t.attribute.length)for(n.attribute=[],r=0;r<t.attribute.length;++r)n.attribute[r]=l.onnx.AttributeProto.toObject(t.attribute[r],e);return null!=t.docString&&t.hasOwnProperty("docString")&&(n.docString=t.docString),null!=t.domain&&t.hasOwnProperty("domain")&&(n.domain=t.domain),n},t.prototype.toJSON=function(){return this.constructor.toObject(this,o.util.toJSONOptions)},t.getTypeUrl=function(t){return void 0===t&&(t="type.googleapis.com"),t+"/onnx.NodeProto"},t}(),i.TrainingInfoProto=function(){function t(t){if(this.initializationBinding=[],this.updateBinding=[],t)for(var e=Object.keys(t),n=0;n<e.length;++n)null!=t[e[n]]&&(this[e[n]]=t[e[n]])}return t.prototype.initialization=null,t.prototype.algorithm=null,t.prototype.initializationBinding=u.emptyArray,t.prototype.updateBinding=u.emptyArray,t.create=function(e){return new t(e)},t.encode=function(t,e){if(e||(e=a.create()),null!=t.initialization&&Object.hasOwnProperty.call(t,"initialization")&&l.onnx.GraphProto.encode(t.initialization,e.uint32(10).fork()).ldelim(),null!=t.algorithm&&Object.hasOwnProperty.call(t,"algorithm")&&l.onnx.GraphProto.encode(t.algorithm,e.uint32(18).fork()).ldelim(),null!=t.initializationBinding&&t.initializationBinding.length)for(var n=0;n<t.initializationBinding.length;++n)l.onnx.StringStringEntryProto.encode(t.initializationBinding[n],e.uint32(26).fork()).ldelim();if(null!=t.updateBinding&&t.updateBinding.length)for(n=0;n<t.updateBinding.length;++n)l.onnx.StringStringEntryProto.encode(t.updateBinding[n],e.uint32(34).fork()).ldelim();return e},t.encodeDelimited=function(t,e){return this.encode(t,e).ldelim()},t.decode=function(t,e){t instanceof s||(t=s.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new l.onnx.TrainingInfoProto;t.pos<n;){var i=t.uint32();switch(i>>>3){case 1:r.initialization=l.onnx.GraphProto.decode(t,t.uint32());break;case 2:r.algorithm=l.onnx.GraphProto.decode(t,t.uint32());break;case 3:r.initializationBinding&&r.initializationBinding.length||(r.initializationBinding=[]),r.initializationBinding.push(l.onnx.StringStringEntryProto.decode(t,t.uint32()));break;case 4:r.updateBinding&&r.updateBinding.length||(r.updateBinding=[]),r.updateBinding.push(l.onnx.StringStringEntryProto.decode(t,t.uint32()));break;default:t.skipType(7&i)}}return r},t.decodeDelimited=function(t){return t instanceof s||(t=new s(t)),this.decode(t,t.uint32())},t.verify=function(t){if("object"!=typeof t||null===t)return"object expected";if(null!=t.initialization&&t.hasOwnProperty("initialization")&&(n=l.onnx.GraphProto.verify(t.initialization)))return"initialization."+n;if(null!=t.algorithm&&t.hasOwnProperty("algorithm")&&(n=l.onnx.GraphProto.verify(t.algorithm)))return"algorithm."+n;if(null!=t.initializationBinding&&t.hasOwnProperty("initializationBinding")){if(!Array.isArray(t.initializationBinding))return"initializationBinding: array expected";for(var e=0;e<t.initializationBinding.length;++e)if(n=l.onnx.StringStringEntryProto.verify(t.initializationBinding[e]))return"initializationBinding."+n}if(null!=t.updateBinding&&t.hasOwnProperty("updateBinding")){if(!Array.isArray(t.updateBinding))return"updateBinding: array expected";for(e=0;e<t.updateBinding.length;++e){var n;if(n=l.onnx.StringStringEntryProto.verify(t.updateBinding[e]))return"updateBinding."+n}}return null},t.fromObject=function(t){if(t instanceof l.onnx.TrainingInfoProto)return t;var e=new l.onnx.TrainingInfoProto;if(null!=t.initialization){if("object"!=typeof t.initialization)throw TypeError(".onnx.TrainingInfoProto.initialization: object expected");e.initialization=l.onnx.GraphProto.fromObject(t.initialization)}if(null!=t.algorithm){if("object"!=typeof t.algorithm)throw TypeError(".onnx.TrainingInfoProto.algorithm: object expected");e.algorithm=l.onnx.GraphProto.fromObject(t.algorithm)}if(t.initializationBinding){if(!Array.isArray(t.initializationBinding))throw TypeError(".onnx.TrainingInfoProto.initializationBinding: array expected");e.initializationBinding=[];for(var n=0;n<t.initializationBinding.length;++n){if("object"!=typeof t.initializationBinding[n])throw TypeError(".onnx.TrainingInfoProto.initializationBinding: object expected");e.initializationBinding[n]=l.onnx.StringStringEntryProto.fromObject(t.initializationBinding[n])}}if(t.updateBinding){if(!Array.isArray(t.updateBinding))throw TypeError(".onnx.TrainingInfoProto.updateBinding: array expected");for(e.updateBinding=[],n=0;n<t.updateBinding.length;++n){if("object"!=typeof t.updateBinding[n])throw TypeError(".onnx.TrainingInfoProto.updateBinding: object expected");e.updateBinding[n]=l.onnx.StringStringEntryProto.fromObject(t.updateBinding[n])}}return e},t.toObject=function(t,e){e||(e={});var n={};if((e.arrays||e.defaults)&&(n.initializationBinding=[],n.updateBinding=[]),e.defaults&&(n.initialization=null,n.algorithm=null),null!=t.initialization&&t.hasOwnProperty("initialization")&&(n.initialization=l.onnx.GraphProto.toObject(t.initialization,e)),null!=t.algorithm&&t.hasOwnProperty("algorithm")&&(n.algorithm=l.onnx.GraphProto.toObject(t.algorithm,e)),t.initializationBinding&&t.initializationBinding.length){n.initializationBinding=[];for(var r=0;r<t.initializationBinding.length;++r)n.initializationBinding[r]=l.onnx.StringStringEntryProto.toObject(t.initializationBinding[r],e)}if(t.updateBinding&&t.updateBinding.length)for(n.updateBinding=[],r=0;r<t.updateBinding.length;++r)n.updateBinding[r]=l.onnx.StringStringEntryProto.toObject(t.updateBinding[r],e);return n},t.prototype.toJSON=function(){return this.constructor.toObject(this,o.util.toJSONOptions)},t.getTypeUrl=function(t){return void 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n=0;n<t.opsetImport.length;++n)l.onnx.OperatorSetIdProto.encode(t.opsetImport[n],e.uint32(66).fork()).ldelim();if(null!=t.metadataProps&&t.metadataProps.length)for(n=0;n<t.metadataProps.length;++n)l.onnx.StringStringEntryProto.encode(t.metadataProps[n],e.uint32(114).fork()).ldelim();if(null!=t.trainingInfo&&t.trainingInfo.length)for(n=0;n<t.trainingInfo.length;++n)l.onnx.TrainingInfoProto.encode(t.trainingInfo[n],e.uint32(162).fork()).ldelim();if(null!=t.functions&&t.functions.length)for(n=0;n<t.functions.length;++n)l.onnx.FunctionProto.encode(t.functions[n],e.uint32(202).fork()).ldelim();return e},t.encodeDelimited=function(t,e){return this.encode(t,e).ldelim()},t.decode=function(t,e){t instanceof s||(t=s.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new l.onnx.ModelProto;t.pos<n;){var i=t.uint32();switch(i>>>3){case 1:r.irVersion=t.int64();break;case 8:r.opsetImport&&r.opsetImport.length||(r.opsetImport=[]),r.opsetImport.push(l.onnx.OperatorSetIdProto.decode(t,t.uint32()));break;case 2:r.producerName=t.string();break;case 3:r.producerVersion=t.string();break;case 4:r.domain=t.string();break;case 5:r.modelVersion=t.int64();break;case 6:r.docString=t.string();break;case 7:r.graph=l.onnx.GraphProto.decode(t,t.uint32());break;case 14:r.metadataProps&&r.metadataProps.length||(r.metadataProps=[]),r.metadataProps.push(l.onnx.StringStringEntryProto.decode(t,t.uint32()));break;case 20:r.trainingInfo&&r.trainingInfo.length||(r.trainingInfo=[]),r.trainingInfo.push(l.onnx.TrainingInfoProto.decode(t,t.uint32()));break;case 25:r.functions&&r.functions.length||(r.functions=[]),r.functions.push(l.onnx.FunctionProto.decode(t,t.uint32()));break;default:t.skipType(7&i)}}return r},t.decodeDelimited=function(t){return t instanceof s||(t=new s(t)),this.decode(t,t.uint32())},t.verify=function(t){if("object"!=typeof t||null===t)return"object 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expected";if(null!=t.modelVersion&&t.hasOwnProperty("modelVersion")&&!u.isInteger(t.modelVersion)&&!(t.modelVersion&&u.isInteger(t.modelVersion.low)&&u.isInteger(t.modelVersion.high)))return"modelVersion: integer|Long expected";if(null!=t.docString&&t.hasOwnProperty("docString")&&!u.isString(t.docString))return"docString: string expected";if(null!=t.graph&&t.hasOwnProperty("graph")&&(n=l.onnx.GraphProto.verify(t.graph)))return"graph."+n;if(null!=t.metadataProps&&t.hasOwnProperty("metadataProps")){if(!Array.isArray(t.metadataProps))return"metadataProps: array expected";for(e=0;e<t.metadataProps.length;++e)if(n=l.onnx.StringStringEntryProto.verify(t.metadataProps[e]))return"metadataProps."+n}if(null!=t.trainingInfo&&t.hasOwnProperty("trainingInfo")){if(!Array.isArray(t.trainingInfo))return"trainingInfo: array 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TypeError(".onnx.ModelProto.opsetImport: object expected");e.opsetImport[n]=l.onnx.OperatorSetIdProto.fromObject(t.opsetImport[n])}}if(null!=t.producerName&&(e.producerName=String(t.producerName)),null!=t.producerVersion&&(e.producerVersion=String(t.producerVersion)),null!=t.domain&&(e.domain=String(t.domain)),null!=t.modelVersion&&(u.Long?(e.modelVersion=u.Long.fromValue(t.modelVersion)).unsigned=!1:"string"==typeof t.modelVersion?e.modelVersion=parseInt(t.modelVersion,10):"number"==typeof t.modelVersion?e.modelVersion=t.modelVersion:"object"==typeof t.modelVersion&&(e.modelVersion=new u.LongBits(t.modelVersion.low>>>0,t.modelVersion.high>>>0).toNumber())),null!=t.docString&&(e.docString=String(t.docString)),null!=t.graph){if("object"!=typeof t.graph)throw TypeError(".onnx.ModelProto.graph: object expected");e.graph=l.onnx.GraphProto.fromObject(t.graph)}if(t.metadataProps){if(!Array.isArray(t.metadataProps))throw TypeError(".onnx.ModelProto.metadataProps: array 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n={};if((e.arrays||e.defaults)&&(n.opsetImport=[],n.metadataProps=[],n.trainingInfo=[],n.functions=[]),e.defaults){if(u.Long){var r=new u.Long(0,0,!1);n.irVersion=e.longs===String?r.toString():e.longs===Number?r.toNumber():r}else n.irVersion=e.longs===String?"0":0;n.producerName="",n.producerVersion="",n.domain="",u.Long?(r=new u.Long(0,0,!1),n.modelVersion=e.longs===String?r.toString():e.longs===Number?r.toNumber():r):n.modelVersion=e.longs===String?"0":0,n.docString="",n.graph=null}if(null!=t.irVersion&&t.hasOwnProperty("irVersion")&&("number"==typeof t.irVersion?n.irVersion=e.longs===String?String(t.irVersion):t.irVersion:n.irVersion=e.longs===String?u.Long.prototype.toString.call(t.irVersion):e.longs===Number?new u.LongBits(t.irVersion.low>>>0,t.irVersion.high>>>0).toNumber():t.irVersion),null!=t.producerName&&t.hasOwnProperty("producerName")&&(n.producerName=t.producerName),null!=t.producerVersion&&t.hasOwnProperty("producerVersion")&&(n.producerVersion=t.producerVersion),null!=t.domain&&t.hasOwnProperty("domain")&&(n.domain=t.domain),null!=t.modelVersion&&t.hasOwnProperty("modelVersion")&&("number"==typeof t.modelVersion?n.modelVersion=e.longs===String?String(t.modelVersion):t.modelVersion:n.modelVersion=e.longs===String?u.Long.prototype.toString.call(t.modelVersion):e.longs===Number?new u.LongBits(t.modelVersion.low>>>0,t.modelVersion.high>>>0).toNumber():t.modelVersion),null!=t.docString&&t.hasOwnProperty("docString")&&(n.docString=t.docString),null!=t.graph&&t.hasOwnProperty("graph")&&(n.graph=l.onnx.GraphProto.toObject(t.graph,e)),t.opsetImport&&t.opsetImport.length){n.opsetImport=[];for(var i=0;i<t.opsetImport.length;++i)n.opsetImport[i]=l.onnx.OperatorSetIdProto.toObject(t.opsetImport[i],e)}if(t.metadataProps&&t.metadataProps.length)for(n.metadataProps=[],i=0;i<t.metadataProps.length;++i)n.metadataProps[i]=l.onnx.StringStringEntryProto.toObject(t.metadataProps[i],e);if(t.trainingInfo&&t.trainingInfo.length)for(n.trainingInfo=[],i=0;i<t.trainingInfo.length;++i)n.trainingInfo[i]=l.onnx.TrainingInfoProto.toObject(t.trainingInfo[i],e);if(t.functions&&t.functions.length)for(n.functions=[],i=0;i<t.functions.length;++i)n.functions[i]=l.onnx.FunctionProto.toObject(t.functions[i],e);return n},t.prototype.toJSON=function(){return this.constructor.toObject(this,o.util.toJSONOptions)},t.getTypeUrl=function(t){return void 0===t&&(t="type.googleapis.com"),t+"/onnx.ModelProto"},t}(),i.StringStringEntryProto=function(){function t(t){if(t)for(var e=Object.keys(t),n=0;n<e.length;++n)null!=t[e[n]]&&(this[e[n]]=t[e[n]])}return t.prototype.key="",t.prototype.value="",t.create=function(e){return new t(e)},t.encode=function(t,e){return e||(e=a.create()),null!=t.key&&Object.hasOwnProperty.call(t,"key")&&e.uint32(10).string(t.key),null!=t.value&&Object.hasOwnProperty.call(t,"value")&&e.uint32(18).string(t.value),e},t.encodeDelimited=function(t,e){return this.encode(t,e).ldelim()},t.decode=function(t,e){t instanceof s||(t=s.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new l.onnx.StringStringEntryProto;t.pos<n;){var i=t.uint32();switch(i>>>3){case 1:r.key=t.string();break;case 2:r.value=t.string();break;default:t.skipType(7&i)}}return r},t.decodeDelimited=function(t){return t instanceof s||(t=new s(t)),this.decode(t,t.uint32())},t.verify=function(t){return"object"!=typeof t||null===t?"object expected":null!=t.key&&t.hasOwnProperty("key")&&!u.isString(t.key)?"key: string expected":null!=t.value&&t.hasOwnProperty("value")&&!u.isString(t.value)?"value: string expected":null},t.fromObject=function(t){if(t instanceof l.onnx.StringStringEntryProto)return t;var e=new l.onnx.StringStringEntryProto;return null!=t.key&&(e.key=String(t.key)),null!=t.value&&(e.value=String(t.value)),e},t.toObject=function(t,e){e||(e={});var n={};return e.defaults&&(n.key="",n.value=""),null!=t.key&&t.hasOwnProperty("key")&&(n.key=t.key),null!=t.value&&t.hasOwnProperty("value")&&(n.value=t.value),n},t.prototype.toJSON=function(){return this.constructor.toObject(this,o.util.toJSONOptions)},t.getTypeUrl=function(t){return void 0===t&&(t="type.googleapis.com"),t+"/onnx.StringStringEntryProto"},t}(),i.TensorAnnotation=function(){function t(t){if(this.quantParameterTensorNames=[],t)for(var e=Object.keys(t),n=0;n<e.length;++n)null!=t[e[n]]&&(this[e[n]]=t[e[n]])}return t.prototype.tensorName="",t.prototype.quantParameterTensorNames=u.emptyArray,t.create=function(e){return new t(e)},t.encode=function(t,e){if(e||(e=a.create()),null!=t.tensorName&&Object.hasOwnProperty.call(t,"tensorName")&&e.uint32(10).string(t.tensorName),null!=t.quantParameterTensorNames&&t.quantParameterTensorNames.length)for(var n=0;n<t.quantParameterTensorNames.length;++n)l.onnx.StringStringEntryProto.encode(t.quantParameterTensorNames[n],e.uint32(18).fork()).ldelim();return e},t.encodeDelimited=function(t,e){return this.encode(t,e).ldelim()},t.decode=function(t,e){t instanceof s||(t=s.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new l.onnx.TensorAnnotation;t.pos<n;){var i=t.uint32();switch(i>>>3){case 1:r.tensorName=t.string();break;case 2:r.quantParameterTensorNames&&r.quantParameterTensorNames.length||(r.quantParameterTensorNames=[]),r.quantParameterTensorNames.push(l.onnx.StringStringEntryProto.decode(t,t.uint32()));break;default:t.skipType(7&i)}}return r},t.decodeDelimited=function(t){return t instanceof s||(t=new s(t)),this.decode(t,t.uint32())},t.verify=function(t){if("object"!=typeof t||null===t)return"object expected";if(null!=t.tensorName&&t.hasOwnProperty("tensorName")&&!u.isString(t.tensorName))return"tensorName: string expected";if(null!=t.quantParameterTensorNames&&t.hasOwnProperty("quantParameterTensorNames")){if(!Array.isArray(t.quantParameterTensorNames))return"quantParameterTensorNames: array expected";for(var e=0;e<t.quantParameterTensorNames.length;++e){var n=l.onnx.StringStringEntryProto.verify(t.quantParameterTensorNames[e]);if(n)return"quantParameterTensorNames."+n}}return null},t.fromObject=function(t){if(t instanceof l.onnx.TensorAnnotation)return t;var e=new l.onnx.TensorAnnotation;if(null!=t.tensorName&&(e.tensorName=String(t.tensorName)),t.quantParameterTensorNames){if(!Array.isArray(t.quantParameterTensorNames))throw TypeError(".onnx.TensorAnnotation.quantParameterTensorNames: array expected");e.quantParameterTensorNames=[];for(var n=0;n<t.quantParameterTensorNames.length;++n){if("object"!=typeof t.quantParameterTensorNames[n])throw TypeError(".onnx.TensorAnnotation.quantParameterTensorNames: object expected");e.quantParameterTensorNames[n]=l.onnx.StringStringEntryProto.fromObject(t.quantParameterTensorNames[n])}}return e},t.toObject=function(t,e){e||(e={});var n={};if((e.arrays||e.defaults)&&(n.quantParameterTensorNames=[]),e.defaults&&(n.tensorName=""),null!=t.tensorName&&t.hasOwnProperty("tensorName")&&(n.tensorName=t.tensorName),t.quantParameterTensorNames&&t.quantParameterTensorNames.length){n.quantParameterTensorNames=[];for(var r=0;r<t.quantParameterTensorNames.length;++r)n.quantParameterTensorNames[r]=l.onnx.StringStringEntryProto.toObject(t.quantParameterTensorNames[r],e)}return n},t.prototype.toJSON=function(){return this.constructor.toObject(this,o.util.toJSONOptions)},t.getTypeUrl=function(t){return void 0===t&&(t="type.googleapis.com"),t+"/onnx.TensorAnnotation"},t}(),i.GraphProto=function(){function t(t){if(this.node=[],this.initializer=[],this.sparseInitializer=[],this.input=[],this.output=[],this.valueInfo=[],this.quantizationAnnotation=[],t)for(var e=Object.keys(t),n=0;n<e.length;++n)null!=t[e[n]]&&(this[e[n]]=t[e[n]])}return t.prototype.node=u.emptyArray,t.prototype.name="",t.prototype.initializer=u.emptyArray,t.prototype.sparseInitializer=u.emptyArray,t.prototype.docString="",t.prototype.input=u.emptyArray,t.prototype.output=u.emptyArray,t.prototype.valueInfo=u.emptyArray,t.prototype.quantizationAnnotation=u.emptyArray,t.create=function(e){return new t(e)},t.encode=function(t,e){if(e||(e=a.create()),null!=t.node&&t.node.length)for(var n=0;n<t.node.length;++n)l.onnx.NodeProto.encode(t.node[n],e.uint32(10).fork()).ldelim();if(null!=t.name&&Object.hasOwnProperty.call(t,"name")&&e.uint32(18).string(t.name),null!=t.initializer&&t.initializer.length)for(n=0;n<t.initializer.length;++n)l.onnx.TensorProto.encode(t.initializer[n],e.uint32(42).fork()).ldelim();if(null!=t.docString&&Object.hasOwnProperty.call(t,"docString")&&e.uint32(82).string(t.docString),null!=t.input&&t.input.length)for(n=0;n<t.input.length;++n)l.onnx.ValueInfoProto.encode(t.input[n],e.uint32(90).fork()).ldelim();if(null!=t.output&&t.output.length)for(n=0;n<t.output.length;++n)l.onnx.ValueInfoProto.encode(t.output[n],e.uint32(98).fork()).ldelim();if(null!=t.valueInfo&&t.valueInfo.length)for(n=0;n<t.valueInfo.length;++n)l.onnx.ValueInfoProto.encode(t.valueInfo[n],e.uint32(106).fork()).ldelim();if(null!=t.quantizationAnnotation&&t.quantizationAnnotation.length)for(n=0;n<t.quantizationAnnotation.length;++n)l.onnx.TensorAnnotation.encode(t.quantizationAnnotation[n],e.uint32(114).fork()).ldelim();if(null!=t.sparseInitializer&&t.sparseInitializer.length)for(n=0;n<t.sparseInitializer.length;++n)l.onnx.SparseTensorProto.encode(t.sparseInitializer[n],e.uint32(122).fork()).ldelim();return e},t.encodeDelimited=function(t,e){return this.encode(t,e).ldelim()},t.decode=function(t,e){t instanceof s||(t=s.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new l.onnx.GraphProto;t.pos<n;){var i=t.uint32();switch(i>>>3){case 1:r.node&&r.node.length||(r.node=[]),r.node.push(l.onnx.NodeProto.decode(t,t.uint32()));break;case 2:r.name=t.string();break;case 5:r.initializer&&r.initializer.length||(r.initializer=[]),r.initializer.push(l.onnx.TensorProto.decode(t,t.uint32()));break;case 15:r.sparseInitializer&&r.sparseInitializer.length||(r.sparseInitializer=[]),r.sparseInitializer.push(l.onnx.SparseTensorProto.decode(t,t.uint32()));break;case 10:r.docString=t.string();break;case 11:r.input&&r.input.length||(r.input=[]),r.input.push(l.onnx.ValueInfoProto.decode(t,t.uint32()));break;case 12:r.output&&r.output.length||(r.output=[]),r.output.push(l.onnx.ValueInfoProto.decode(t,t.uint32()));break;case 13:r.valueInfo&&r.valueInfo.length||(r.valueInfo=[]),r.valueInfo.push(l.onnx.ValueInfoProto.decode(t,t.uint32()));break;case 14:r.quantizationAnnotation&&r.quantizationAnnotation.length||(r.quantizationAnnotation=[]),r.quantizationAnnotation.push(l.onnx.TensorAnnotation.decode(t,t.uint32()));break;default:t.skipType(7&i)}}return r},t.decodeDelimited=function(t){return t instanceof s||(t=new s(t)),this.decode(t,t.uint32())},t.verify=function(t){if("object"!=typeof t||null===t)return"object expected";if(null!=t.node&&t.hasOwnProperty("node")){if(!Array.isArray(t.node))return"node: array expected";for(var e=0;e<t.node.length;++e)if(n=l.onnx.NodeProto.verify(t.node[e]))return"node."+n}if(null!=t.name&&t.hasOwnProperty("name")&&!u.isString(t.name))return"name: string expected";if(null!=t.initializer&&t.hasOwnProperty("initializer")){if(!Array.isArray(t.initializer))return"initializer: array expected";for(e=0;e<t.initializer.length;++e)if(n=l.onnx.TensorProto.verify(t.initializer[e]))return"initializer."+n}if(null!=t.sparseInitializer&&t.hasOwnProperty("sparseInitializer")){if(!Array.isArray(t.sparseInitializer))return"sparseInitializer: array expected";for(e=0;e<t.sparseInitializer.length;++e)if(n=l.onnx.SparseTensorProto.verify(t.sparseInitializer[e]))return"sparseInitializer."+n}if(null!=t.docString&&t.hasOwnProperty("docString")&&!u.isString(t.docString))return"docString: string expected";if(null!=t.input&&t.hasOwnProperty("input")){if(!Array.isArray(t.input))return"input: array expected";for(e=0;e<t.input.length;++e)if(n=l.onnx.ValueInfoProto.verify(t.input[e]))return"input."+n}if(null!=t.output&&t.hasOwnProperty("output")){if(!Array.isArray(t.output))return"output: array expected";for(e=0;e<t.output.length;++e)if(n=l.onnx.ValueInfoProto.verify(t.output[e]))return"output."+n}if(null!=t.valueInfo&&t.hasOwnProperty("valueInfo")){if(!Array.isArray(t.valueInfo))return"valueInfo: array expected";for(e=0;e<t.valueInfo.length;++e)if(n=l.onnx.ValueInfoProto.verify(t.valueInfo[e]))return"valueInfo."+n}if(null!=t.quantizationAnnotation&&t.hasOwnProperty("quantizationAnnotation")){if(!Array.isArray(t.quantizationAnnotation))return"quantizationAnnotation: array expected";for(e=0;e<t.quantizationAnnotation.length;++e){var n;if(n=l.onnx.TensorAnnotation.verify(t.quantizationAnnotation[e]))return"quantizationAnnotation."+n}}return null},t.fromObject=function(t){if(t instanceof l.onnx.GraphProto)return t;var e=new l.onnx.GraphProto;if(t.node){if(!Array.isArray(t.node))throw TypeError(".onnx.GraphProto.node: array expected");e.node=[];for(var n=0;n<t.node.length;++n){if("object"!=typeof t.node[n])throw TypeError(".onnx.GraphProto.node: object 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expected");for(e.quantizationAnnotation=[],n=0;n<t.quantizationAnnotation.length;++n){if("object"!=typeof t.quantizationAnnotation[n])throw TypeError(".onnx.GraphProto.quantizationAnnotation: object expected");e.quantizationAnnotation[n]=l.onnx.TensorAnnotation.fromObject(t.quantizationAnnotation[n])}}return e},t.toObject=function(t,e){e||(e={});var n={};if((e.arrays||e.defaults)&&(n.node=[],n.initializer=[],n.input=[],n.output=[],n.valueInfo=[],n.quantizationAnnotation=[],n.sparseInitializer=[]),e.defaults&&(n.name="",n.docString=""),t.node&&t.node.length){n.node=[];for(var r=0;r<t.node.length;++r)n.node[r]=l.onnx.NodeProto.toObject(t.node[r],e)}if(null!=t.name&&t.hasOwnProperty("name")&&(n.name=t.name),t.initializer&&t.initializer.length)for(n.initializer=[],r=0;r<t.initializer.length;++r)n.initializer[r]=l.onnx.TensorProto.toObject(t.initializer[r],e);if(null!=t.docString&&t.hasOwnProperty("docString")&&(n.docString=t.docString),t.input&&t.input.length)for(n.input=[],r=0;r<t.input.length;++r)n.input[r]=l.onnx.ValueInfoProto.toObject(t.input[r],e);if(t.output&&t.output.length)for(n.output=[],r=0;r<t.output.length;++r)n.output[r]=l.onnx.ValueInfoProto.toObject(t.output[r],e);if(t.valueInfo&&t.valueInfo.length)for(n.valueInfo=[],r=0;r<t.valueInfo.length;++r)n.valueInfo[r]=l.onnx.ValueInfoProto.toObject(t.valueInfo[r],e);if(t.quantizationAnnotation&&t.quantizationAnnotation.length)for(n.quantizationAnnotation=[],r=0;r<t.quantizationAnnotation.length;++r)n.quantizationAnnotation[r]=l.onnx.TensorAnnotation.toObject(t.quantizationAnnotation[r],e);if(t.sparseInitializer&&t.sparseInitializer.length)for(n.sparseInitializer=[],r=0;r<t.sparseInitializer.length;++r)n.sparseInitializer[r]=l.onnx.SparseTensorProto.toObject(t.sparseInitializer[r],e);return n},t.prototype.toJSON=function(){return this.constructor.toObject(this,o.util.toJSONOptions)},t.getTypeUrl=function(t){return void 0===t&&(t="type.googleapis.com"),t+"/onnx.GraphProto"},t}(),i.TensorProto=function(){function t(t){if(this.dims=[],this.floatData=[],this.int32Data=[],this.stringData=[],this.int64Data=[],this.externalData=[],this.doubleData=[],this.uint64Data=[],t)for(var e=Object.keys(t),n=0;n<e.length;++n)null!=t[e[n]]&&(this[e[n]]=t[e[n]])}return t.prototype.dims=u.emptyArray,t.prototype.dataType=0,t.prototype.segment=null,t.prototype.floatData=u.emptyArray,t.prototype.int32Data=u.emptyArray,t.prototype.stringData=u.emptyArray,t.prototype.int64Data=u.emptyArray,t.prototype.name="",t.prototype.docString="",t.prototype.rawData=u.newBuffer([]),t.prototype.externalData=u.emptyArray,t.prototype.dataLocation=0,t.prototype.doubleData=u.emptyArray,t.prototype.uint64Data=u.emptyArray,t.create=function(e){return new t(e)},t.encode=function(t,e){if(e||(e=a.create()),null!=t.dims&&t.dims.length){e.uint32(10).fork();for(var n=0;n<t.dims.length;++n)e.int64(t.dims[n]);e.ldelim()}if(null!=t.dataType&&Object.hasOwnProperty.call(t,"dataType")&&e.uint32(16).int32(t.dataType),null!=t.segment&&Object.hasOwnProperty.call(t,"segment")&&l.onnx.TensorProto.Segment.encode(t.segment,e.uint32(26).fork()).ldelim(),null!=t.floatData&&t.floatData.length){for(e.uint32(34).fork(),n=0;n<t.floatData.length;++n)e.float(t.floatData[n]);e.ldelim()}if(null!=t.int32Data&&t.int32Data.length){for(e.uint32(42).fork(),n=0;n<t.int32Data.length;++n)e.int32(t.int32Data[n]);e.ldelim()}if(null!=t.stringData&&t.stringData.length)for(n=0;n<t.stringData.length;++n)e.uint32(50).bytes(t.stringData[n]);if(null!=t.int64Data&&t.int64Data.length){for(e.uint32(58).fork(),n=0;n<t.int64Data.length;++n)e.int64(t.int64Data[n]);e.ldelim()}if(null!=t.name&&Object.hasOwnProperty.call(t,"name")&&e.uint32(66).string(t.name),null!=t.rawData&&Object.hasOwnProperty.call(t,"rawData")&&e.uint32(74).bytes(t.rawData),null!=t.doubleData&&t.doubleData.length){for(e.uint32(82).fork(),n=0;n<t.doubleData.length;++n)e.double(t.doubleData[n]);e.ldelim()}if(null!=t.uint64Data&&t.uint64Data.length){for(e.uint32(90).fork(),n=0;n<t.uint64Data.length;++n)e.uint64(t.uint64Data[n]);e.ldelim()}if(null!=t.docString&&Object.hasOwnProperty.call(t,"docString")&&e.uint32(98).string(t.docString),null!=t.externalData&&t.externalData.length)for(n=0;n<t.externalData.length;++n)l.onnx.StringStringEntryProto.encode(t.externalData[n],e.uint32(106).fork()).ldelim();return null!=t.dataLocation&&Object.hasOwnProperty.call(t,"dataLocation")&&e.uint32(112).int32(t.dataLocation),e},t.encodeDelimited=function(t,e){return this.encode(t,e).ldelim()},t.decode=function(t,e){t instanceof s||(t=s.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new l.onnx.TensorProto;t.pos<n;){var i=t.uint32();switch(i>>>3){case 1:if(r.dims&&r.dims.length||(r.dims=[]),2==(7&i))for(var o=t.uint32()+t.pos;t.pos<o;)r.dims.push(t.int64());else r.dims.push(t.int64());break;case 2:r.dataType=t.int32();break;case 3:r.segment=l.onnx.TensorProto.Segment.decode(t,t.uint32());break;case 4:if(r.floatData&&r.floatData.length||(r.floatData=[]),2==(7&i))for(o=t.uint32()+t.pos;t.pos<o;)r.floatData.push(t.float());else r.floatData.push(t.float());break;case 5:if(r.int32Data&&r.int32Data.length||(r.int32Data=[]),2==(7&i))for(o=t.uint32()+t.pos;t.pos<o;)r.int32Data.push(t.int32());else r.int32Data.push(t.int32());break;case 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s(t)),this.decode(t,t.uint32())},t.verify=function(t){if("object"!=typeof t||null===t)return"object expected";if(null!=t.dims&&t.hasOwnProperty("dims")){if(!Array.isArray(t.dims))return"dims: array expected";for(var e=0;e<t.dims.length;++e)if(!(u.isInteger(t.dims[e])||t.dims[e]&&u.isInteger(t.dims[e].low)&&u.isInteger(t.dims[e].high)))return"dims: integer|Long[] expected"}if(null!=t.dataType&&t.hasOwnProperty("dataType")&&!u.isInteger(t.dataType))return"dataType: integer expected";if(null!=t.segment&&t.hasOwnProperty("segment")&&(n=l.onnx.TensorProto.Segment.verify(t.segment)))return"segment."+n;if(null!=t.floatData&&t.hasOwnProperty("floatData")){if(!Array.isArray(t.floatData))return"floatData: array expected";for(e=0;e<t.floatData.length;++e)if("number"!=typeof t.floatData[e])return"floatData: number[] expected"}if(null!=t.int32Data&&t.hasOwnProperty("int32Data")){if(!Array.isArray(t.int32Data))return"int32Data: array expected";for(e=0;e<t.int32Data.length;++e)if(!u.isInteger(t.int32Data[e]))return"int32Data: integer[] expected"}if(null!=t.stringData&&t.hasOwnProperty("stringData")){if(!Array.isArray(t.stringData))return"stringData: array expected";for(e=0;e<t.stringData.length;++e)if(!(t.stringData[e]&&"number"==typeof t.stringData[e].length||u.isString(t.stringData[e])))return"stringData: buffer[] expected"}if(null!=t.int64Data&&t.hasOwnProperty("int64Data")){if(!Array.isArray(t.int64Data))return"int64Data: array expected";for(e=0;e<t.int64Data.length;++e)if(!(u.isInteger(t.int64Data[e])||t.int64Data[e]&&u.isInteger(t.int64Data[e].low)&&u.isInteger(t.int64Data[e].high)))return"int64Data: integer|Long[] expected"}if(null!=t.name&&t.hasOwnProperty("name")&&!u.isString(t.name))return"name: string expected";if(null!=t.docString&&t.hasOwnProperty("docString")&&!u.isString(t.docString))return"docString: string expected";if(null!=t.rawData&&t.hasOwnProperty("rawData")&&!(t.rawData&&"number"==typeof t.rawData.length||u.isString(t.rawData)))return"rawData: buffer expected";if(null!=t.externalData&&t.hasOwnProperty("externalData")){if(!Array.isArray(t.externalData))return"externalData: array expected";for(e=0;e<t.externalData.length;++e){var n;if(n=l.onnx.StringStringEntryProto.verify(t.externalData[e]))return"externalData."+n}}if(null!=t.dataLocation&&t.hasOwnProperty("dataLocation"))switch(t.dataLocation){default:return"dataLocation: enum value expected";case 0:case 1:}if(null!=t.doubleData&&t.hasOwnProperty("doubleData")){if(!Array.isArray(t.doubleData))return"doubleData: array expected";for(e=0;e<t.doubleData.length;++e)if("number"!=typeof t.doubleData[e])return"doubleData: number[] expected"}if(null!=t.uint64Data&&t.hasOwnProperty("uint64Data")){if(!Array.isArray(t.uint64Data))return"uint64Data: array expected";for(e=0;e<t.uint64Data.length;++e)if(!(u.isInteger(t.uint64Data[e])||t.uint64Data[e]&&u.isInteger(t.uint64Data[e].low)&&u.isInteger(t.uint64Data[e].high)))return"uint64Data: integer|Long[] expected"}return null},t.fromObject=function(t){if(t instanceof l.onnx.TensorProto)return t;var e=new l.onnx.TensorProto;if(t.dims){if(!Array.isArray(t.dims))throw TypeError(".onnx.TensorProto.dims: array expected");e.dims=[];for(var n=0;n<t.dims.length;++n)u.Long?(e.dims[n]=u.Long.fromValue(t.dims[n])).unsigned=!1:"string"==typeof t.dims[n]?e.dims[n]=parseInt(t.dims[n],10):"number"==typeof t.dims[n]?e.dims[n]=t.dims[n]:"object"==typeof t.dims[n]&&(e.dims[n]=new u.LongBits(t.dims[n].low>>>0,t.dims[n].high>>>0).toNumber())}if(null!=t.dataType&&(e.dataType=0|t.dataType),null!=t.segment){if("object"!=typeof t.segment)throw TypeError(".onnx.TensorProto.segment: object expected");e.segment=l.onnx.TensorProto.Segment.fromObject(t.segment)}if(t.floatData){if(!Array.isArray(t.floatData))throw TypeError(".onnx.TensorProto.floatData: array expected");for(e.floatData=[],n=0;n<t.floatData.length;++n)e.floatData[n]=Number(t.floatData[n])}if(t.int32Data){if(!Array.isArray(t.int32Data))throw TypeError(".onnx.TensorProto.int32Data: array expected");for(e.int32Data=[],n=0;n<t.int32Data.length;++n)e.int32Data[n]=0|t.int32Data[n]}if(t.stringData){if(!Array.isArray(t.stringData))throw TypeError(".onnx.TensorProto.stringData: array expected");for(e.stringData=[],n=0;n<t.stringData.length;++n)"string"==typeof t.stringData[n]?u.base64.decode(t.stringData[n],e.stringData[n]=u.newBuffer(u.base64.length(t.stringData[n])),0):t.stringData[n].length>=0&&(e.stringData[n]=t.stringData[n])}if(t.int64Data){if(!Array.isArray(t.int64Data))throw TypeError(".onnx.TensorProto.int64Data: array expected");for(e.int64Data=[],n=0;n<t.int64Data.length;++n)u.Long?(e.int64Data[n]=u.Long.fromValue(t.int64Data[n])).unsigned=!1:"string"==typeof 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e={};if(null!=t.dimValue&&t.hasOwnProperty("dimValue")&&(e.value=1,!(u.isInteger(t.dimValue)||t.dimValue&&u.isInteger(t.dimValue.low)&&u.isInteger(t.dimValue.high))))return"dimValue: integer|Long expected";if(null!=t.dimParam&&t.hasOwnProperty("dimParam")){if(1===e.value)return"value: multiple values";if(e.value=1,!u.isString(t.dimParam))return"dimParam: string expected"}return null!=t.denotation&&t.hasOwnProperty("denotation")&&!u.isString(t.denotation)?"denotation: string expected":null},t.fromObject=function(t){if(t instanceof l.onnx.TensorShapeProto.Dimension)return t;var e=new l.onnx.TensorShapeProto.Dimension;return null!=t.dimValue&&(u.Long?(e.dimValue=u.Long.fromValue(t.dimValue)).unsigned=!1:"string"==typeof t.dimValue?e.dimValue=parseInt(t.dimValue,10):"number"==typeof t.dimValue?e.dimValue=t.dimValue:"object"==typeof t.dimValue&&(e.dimValue=new 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instanceof s||(t=s.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new l.onnx.FunctionProto;t.pos<n;){var i=t.uint32();switch(i>>>3){case 1:r.name=t.string();break;case 4:r.input&&r.input.length||(r.input=[]),r.input.push(t.string());break;case 5:r.output&&r.output.length||(r.output=[]),r.output.push(t.string());break;case 6:r.attribute&&r.attribute.length||(r.attribute=[]),r.attribute.push(t.string());break;case 11:r.attributeProto&&r.attributeProto.length||(r.attributeProto=[]),r.attributeProto.push(l.onnx.AttributeProto.decode(t,t.uint32()));break;case 7:r.node&&r.node.length||(r.node=[]),r.node.push(l.onnx.NodeProto.decode(t,t.uint32()));break;case 8:r.docString=t.string();break;case 9:r.opsetImport&&r.opsetImport.length||(r.opsetImport=[]),r.opsetImport.push(l.onnx.OperatorSetIdProto.decode(t,t.uint32()));break;case 10:r.domain=t.string();break;default:t.skipType(7&i)}}return r},t.decodeDelimited=function(t){return t instanceof s||(t=new s(t)),this.decode(t,t.uint32())},t.verify=function(t){if("object"!=typeof t||null===t)return"object expected";if(null!=t.name&&t.hasOwnProperty("name")&&!u.isString(t.name))return"name: string expected";if(null!=t.input&&t.hasOwnProperty("input")){if(!Array.isArray(t.input))return"input: array expected";for(var e=0;e<t.input.length;++e)if(!u.isString(t.input[e]))return"input: string[] expected"}if(null!=t.output&&t.hasOwnProperty("output")){if(!Array.isArray(t.output))return"output: array expected";for(e=0;e<t.output.length;++e)if(!u.isString(t.output[e]))return"output: string[] expected"}if(null!=t.attribute&&t.hasOwnProperty("attribute")){if(!Array.isArray(t.attribute))return"attribute: array expected";for(e=0;e<t.attribute.length;++e)if(!u.isString(t.attribute[e]))return"attribute: string[] expected"}if(null!=t.attributeProto&&t.hasOwnProperty("attributeProto")){if(!Array.isArray(t.attributeProto))return"attributeProto: array expected";for(e=0;e<t.attributeProto.length;++e)if(n=l.onnx.AttributeProto.verify(t.attributeProto[e]))return"attributeProto."+n}if(null!=t.node&&t.hasOwnProperty("node")){if(!Array.isArray(t.node))return"node: array expected";for(e=0;e<t.node.length;++e)if(n=l.onnx.NodeProto.verify(t.node[e]))return"node."+n}if(null!=t.docString&&t.hasOwnProperty("docString")&&!u.isString(t.docString))return"docString: string expected";if(null!=t.opsetImport&&t.hasOwnProperty("opsetImport")){if(!Array.isArray(t.opsetImport))return"opsetImport: array expected";for(e=0;e<t.opsetImport.length;++e){var n;if(n=l.onnx.OperatorSetIdProto.verify(t.opsetImport[e]))return"opsetImport."+n}}return null!=t.domain&&t.hasOwnProperty("domain")&&!u.isString(t.domain)?"domain: string expected":null},t.fromObject=function(t){if(t instanceof l.onnx.FunctionProto)return t;var e=new l.onnx.FunctionProto;if(null!=t.name&&(e.name=String(t.name)),t.input){if(!Array.isArray(t.input))throw TypeError(".onnx.FunctionProto.input: 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t.node[n])throw TypeError(".onnx.FunctionProto.node: object expected");e.node[n]=l.onnx.NodeProto.fromObject(t.node[n])}}if(null!=t.docString&&(e.docString=String(t.docString)),t.opsetImport){if(!Array.isArray(t.opsetImport))throw TypeError(".onnx.FunctionProto.opsetImport: array expected");for(e.opsetImport=[],n=0;n<t.opsetImport.length;++n){if("object"!=typeof t.opsetImport[n])throw TypeError(".onnx.FunctionProto.opsetImport: object expected");e.opsetImport[n]=l.onnx.OperatorSetIdProto.fromObject(t.opsetImport[n])}}return null!=t.domain&&(e.domain=String(t.domain)),e},t.toObject=function(t,e){e||(e={});var n={};if((e.arrays||e.defaults)&&(n.input=[],n.output=[],n.attribute=[],n.node=[],n.opsetImport=[],n.attributeProto=[]),e.defaults&&(n.name="",n.docString="",n.domain=""),null!=t.name&&t.hasOwnProperty("name")&&(n.name=t.name),t.input&&t.input.length){n.input=[];for(var r=0;r<t.input.length;++r)n.input[r]=t.input[r]}if(t.output&&t.output.length)for(n.output=[],r=0;r<t.output.length;++r)n.output[r]=t.output[r];if(t.attribute&&t.attribute.length)for(n.attribute=[],r=0;r<t.attribute.length;++r)n.attribute[r]=t.attribute[r];if(t.node&&t.node.length)for(n.node=[],r=0;r<t.node.length;++r)n.node[r]=l.onnx.NodeProto.toObject(t.node[r],e);if(null!=t.docString&&t.hasOwnProperty("docString")&&(n.docString=t.docString),t.opsetImport&&t.opsetImport.length)for(n.opsetImport=[],r=0;r<t.opsetImport.length;++r)n.opsetImport[r]=l.onnx.OperatorSetIdProto.toObject(t.opsetImport[r],e);if(null!=t.domain&&t.hasOwnProperty("domain")&&(n.domain=t.domain),t.attributeProto&&t.attributeProto.length)for(n.attributeProto=[],r=0;r<t.attributeProto.length;++r)n.attributeProto[r]=l.onnx.AttributeProto.toObject(t.attributeProto[r],e);return n},t.prototype.toJSON=function(){return this.constructor.toObject(this,o.util.toJSONOptions)},t.getTypeUrl=function(t){return void 0===t&&(t="type.googleapis.com"),t+"/onnx.FunctionProto"},t}(),i),e.exports=l}));function se(t,e){if(!t)throw new Error("string"==typeof e?e:e())}function Se(t){return(new TextDecoder).decode(t)}var H,jt,an,it,er,et,ft,A,_e,Kt,Xt,Jt,z=x((()=>{Je(),Hr(),H=re(ae()),Zt(),jt=class{static arraysEqual(t,e){if(t.length!==e.length)return!1;for(let n=0;n<t.length;n++)if(t[n]!==e[n])return!1;return!0}},an=class{static preprocessInputShapes(t,e){return[1===t.length?[1,t[0]]:t,1===e.length?[e[0],1]:e]}static postprocessOutputShape(t,e,n){1===e&&t.splice(t.length-2,1),1===n&&t.pop()}static calcMatMulShape(t,e){return t[1]!==e[0]?void 0:[t[0],e[1]]}},it=class t{static calcShape(t,e,n=!1){let r=t.length,i=e.length;if(0===r)return e;if(0===i)return t;let o=Math.max(t.length,e.length),s=new Array(o);if(n){if(r<2||i<2)return;let n=an.calcMatMulShape([t[r-2],t[r-1]],[e[i-2],e[i-1]]);if(void 0===n)return;[s[o-2],s[o-1]]=n}for(let a=n?3:1;a<=o;a++){let n=r-a<0?1:t[r-a],u=i-a<0?1:e[i-a];if(n!==u&&n>1&&u>1)return;s[o-a]=Math.max(n,u)}return s}static index(e,n){let r=new Array(n.length);return t.fillIndex(e,n,r),r}static fillIndex(t,e,n){let r=t.length-e.length;for(let i=0;i<e.length;i++)n[i]=t[r+i]%e[i]}static calc(e,n,r,i,o){let s=t.calcShape(e.dims,n.dims);if(s){if(i&&!A.areEqual(s,e.dims))return;let a=A.size(s),u=i?e:new Y(s,o||e.type);if(0===s.length)u.set([],r(e.get([]),n.get([])));else{let i,o=new Array(s.length),l=new Array(e.dims.length),p=new Array(n.dims.length),c=0,d=0,h=!1,f=!1;0===e.dims.length&&(c=e.get([]),h=!0),0===n.dims.length&&(d=n.get([]),f=!0);for(let g=0;g<a;g++){i=g;for(let t=s.length-1;t>=0;t--)o[t]=i%s[t],i=Math.floor(i/s[t]);h||(t.fillIndex(o,e.dims,l),c=e.get(l)),f||(t.fillIndex(o,n.dims,p),d=n.get(p)),u.set(o,r(c,d))}}return u}}static isValidBroadcast(t,e){let n=t.length,r=e.length;if(n>r)return!1;for(let i=1;i<=n;i++)if(1!==t[n-i]&&t[n-i]!==e[r-i])return!1;return!0}static getBroadcastDims(t,e){let n=t.length,r=[];for(let i=0;i<n;i++){let o=n-1-i,s=t[o]||1;(e[e.length-1-i]||1)>1&&1===s&&r.unshift(o)}return r}},er=class{static getShapeOfGemmResult(t,e,n,r,i){if(2!==t.length||2!==n.length)throw new Error("shape need to be of size 2");let o,s,a;e?(o=t[1],s=t[0]):(o=t[0],s=t[1]);let u=-1;if(r?(a=n[0],u=1):(a=n[1],u=0),n[u]!==s)throw new Error("dimension mismatch");if(o<=0||a<=0||s<=0)throw new Error("invalid shape specified");if(i&&!it.isValidBroadcast(i,[o,a]))throw new Error("gemm: invalid bias shape for broadcast");return[o,a,s]}},et=class t{static tensorDataTypeFromProto(t){switch(t){case H.onnx.TensorProto.DataType.INT8:return"int8";case H.onnx.TensorProto.DataType.UINT8:return"uint8";case H.onnx.TensorProto.DataType.BOOL:return"bool";case H.onnx.TensorProto.DataType.INT16:return"int16";case H.onnx.TensorProto.DataType.UINT16:return"uint16";case H.onnx.TensorProto.DataType.INT32:return"int32";case H.onnx.TensorProto.DataType.UINT32:return"uint32";case H.onnx.TensorProto.DataType.FLOAT:return"float32";case H.onnx.TensorProto.DataType.DOUBLE:return"float64";case H.onnx.TensorProto.DataType.STRING:return"string";case H.onnx.TensorProto.DataType.INT64:return"int32";case H.onnx.TensorProto.DataType.UINT64:return"uint32";default:throw new Error(`unsupported data type: ${H.onnx.TensorProto.DataType[t]}`)}}static tensorDataTypeStringToEnum(t){switch(t){case"int8":return H.onnx.TensorProto.DataType.INT8;case"uint8":return H.onnx.TensorProto.DataType.UINT8;case"bool":return H.onnx.TensorProto.DataType.BOOL;case"int16":return H.onnx.TensorProto.DataType.INT16;case"uint16":return H.onnx.TensorProto.DataType.UINT16;case"int32":return H.onnx.TensorProto.DataType.INT32;case"uint32":return H.onnx.TensorProto.DataType.UINT32;case"float32":return H.onnx.TensorProto.DataType.FLOAT;case"float64":return H.onnx.TensorProto.DataType.DOUBLE;case"string":return H.onnx.TensorProto.DataType.STRING;case"int64":return H.onnx.TensorProto.DataType.INT64;case"uint64":return H.onnx.TensorProto.DataType.UINT64;default:throw new Error(`unsupported data type: ${t}`)}}static tensorDimsFromProto(t){return t.map((t=>$t.isLong(t)?t.toNumber():t))}static tensorValueTypeFromProto(e){return{tensorType:t.tensorDataTypeFromProto(e.elemType),shape:{dims:t.tensorDimsFromProto(e.shape.dim.map((t=>t.dimValue)))}}}static tensorDimsFromORTFormat(t){let e=[];for(let n=0;n<t.dimsLength();n++)e.push(ft.longToNumber(t.dims(n)));return e}static tensorAttributesFromORTFormat(t){let e=[];for(let n=0;n<t.attributesLength();n++)e.push(t.attributes(n));return e}},ft=class{static longToNumber(t,e){return $t.isLong(t)?t.toNumber():t instanceof b.Long?$t.fromValue({low:t.low,high:t.high,unsigned:e??!1}).toNumber():t}static isLong(t){return $t.isLong(t)||t instanceof b.Long}},A=class t{static size(e){return t.getSizeFromDimensionRange(e,0,e.length)}static sizeFromDimension(e,n){if(n<0||n>e.length)throw new Error(`invalid dimension of ${n} for sizeFromDimension as Tensor has ${e.length} dimensions.`);return t.getSizeFromDimensionRange(e,n,e.length)}static sizeToDimension(e,n){if(n<0||n>e.length)throw new Error(`invalid dimension of ${n} for sizeToDimension as Tensor has ${e.length} dimensions.`);return t.getSizeFromDimensionRange(e,0,n)}static getSizeFromDimensionRange(t,e,n){let r=1;for(let i=e;i<n;i++){if(t[i]<=0)throw new Error("cannot get valid size from specified dimension range. Most likely the range contains 0 or negative values in them.");r*=t[i]}return r}static computeStrides(t){let e=t.length;if(0===e)return[];if(1===e)return[1];let n=new Array(e);n[e-1]=1,n[e-2]=t[e-1];for(let r=e-3;r>=0;--r)n[r]=n[r+1]*t[r+1];return n}static transpose(t){return t.slice().reverse()}static indicesToOffset(t,e,n){void 0===n&&(n=t.length);let r=0;for(let i=0;i<n;++i)r+=e[i]*t[i];return r}static offsetToIndices(t,e){let n=e.length;if(0===n)return[];if(1===n)return[t*e[0]];let r=new Array(e.length);for(let n=0;n<r.length-1;++n)r[n]=Math.floor(t/e[n]),t-=r[n]*e[n];return r[r.length-1]=t,r}static normalizeAxis(t,e){if(t<-e&&t>=e)throw new Error("unsupported axis for this operation.");return t<0?t+e:t}static normalizeAxes(t,e){return t.map((t=>this.normalizeAxis(t,e)))}static incrementIndex(t,e,n){if(0===e.length||0===t.length)throw new Error("Index incrementing unsupported for scalar Tensor");if(void 0===n)n=e.length;else if(n<=0||n>e.length)throw new Error("Incorrect axis to increment on");for(let r=n-1;r>=0&&(t[r]++,!(t[r]<e[r]));--r)t[r]=0}static calculateReshapedDims(e,n){if(0===n.length){if(0===e.length||1===t.size(e))return[];throw new Error("cannot reshape to a scalar Tensor")}let r=n.length,i=new Array(r),o=-1,s=1;for(let t=0;t<r;t++){if(n[t]<-1)throw new Error("a dimension in shape hints cannot be less than -1");if(-1===n[t]){if(-1!==o)throw new Error("at most one dimension in shape hints can be -1");o=t}else{if(0===n[t]){if(t>=e.length)throw new Error("the dimension with value zero exceeds the dimension size of the input tensor");i[t]=e[t]}else i[t]=n[t];s*=i[t]}}let a=t.size(e);if(-1!==o){if(a%s!=0)throw new Error(`the input tensor cannot be reshaped to the requested shape. Input shape: [${e}] Output shape: [${n}]`);i[o]=a/s}else if(s!==a)throw new Error("reshapedDims and originalDims don't have matching sizes");return i}static sortBasedOnPerm(t,e){return e?e.map((e=>t[e])):t.slice().reverse()}static padShape(t,e){let n=t.length;return t.map(((t,r)=>t+e[r]+e[r+n]))}static areEqual(t,e){return t.length===e.length&&t.every(((t,n)=>t===e[n]))}static validateDimsAndCalcSize(t){if(t.length>6)throw new TypeError("Only rank 0 to 6 is supported for tensor shape.");let e=1;for(let n of t){if(!Number.isInteger(n))throw new TypeError(`Invalid shape: ${n} is not an integer`);if(n<0||n>2147483647)throw new TypeError(`Invalid shape: length ${n} is not allowed`);e*=n}return e}static flattenShape(t,e){e<0&&(e+=t.length);let n=t.reduce(((t,e)=>t*e),1),r=t.slice(e).reduce(((t,e)=>t*e),1);return[n/r,r]}static squeezeShape(e,n){let r=new Array;n=t.normalizeAxes(n,e.length);for(let t=0;t<e.length;t++){let i=n.indexOf(t)>=0;if(i&&1!==e[t])throw new Error("squeeze an axis of size different than 1");(0===n.length&&e[t]>1||n.length>0&&!i)&&r.push(e[t])}return r}static unsqueezeShape(e,n){let r=new Array(e.length+n.length);r.fill(0);for(let e=0;e<n.length;e++){let i=t.normalizeAxis(n[e],r.length);if(i>=r.length)throw new Error("'axes' has an out of range axis");if(0!==r[i])throw new Error("'axes' has a duplicate axis");r[i]=1}let i=0;for(let t=0;t<r.length;t++)0===r[t]&&(r[t]=e[i++]);if(i!==e.length)throw new Error("the unsqueezed dimension could not be established");return r}},_e=class t{static splitShape(e,n,r,i){if(0===r.length){if(!i)throw new Error("need to know number of outputs when the 'split' attribute is not specified");t.determineSplit(e[n],i,r)}let o=[],s=[0];for(let t=0;t<r.length;++t){0!==t&&s.push(s[t-1]+r[t-1]);let i=e.slice();i[n]=r[t],o.push(i)}return[o,s]}static determineSplit(t,e,n){if(t%e!=0)throw new Error("cannot split tensor to equal sized parts");for(let r=0;r<e;++r)n.push(t/e)}},Kt=class t{static adjustPoolAttributes(t,e,n,r,i,o){if(!t&&n.length!==e.length-2)throw new Error("length of specified kernel shapes should be 2 less than length of input dimensions");if(t)for(let t=0;t<e.length-2;t++)t>=n.length?n.push(e[t+2]):n[t]=e[t+2];for(let t=0;t<n.length;t++)if(t<r.length){if(r[t]<0)throw new Error("strides should be greater than or equal to 1")}else r.push(1);for(let t=0;t<n.length;t++)if(t<i.length){if(i[t]<0)throw new Error("dilations should be greater than or equal to 1")}else i.push(1);for(let t=0;t<2*n.length;t++)if(t<o.length){if(o[t]<0)throw new Error("pad should be greater than or equal to 1")}else o.push(0);for(let t=0;t<n.length;t++){if(n[t]<=0)throw new Error("kernel shapes need to be greater than 0");if(o[t]>=n[t]||o[t+n.length]>=n[t])throw new Error("pads should be smaller than kernel")}}static adjustPadsBasedOnAutoPad(e,n,r,i,o,s){if(s){if(o.length!==2*(e.length-2))throw new Error("length of pads should be twice the length of data 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u=n*(r-1)+1;if(!a||"NOTSET"===a)return Math.floor((t+i[o]+i[s]-u)/e+1);switch(a){case"VALID":return i[o]=0,i[s]=0,Math.floor((t-u)/e+1);case"SAME_LOWER":case"SAME_UPPER":if(1!==n)throw new Error("Dilation not supported for SAME_UPPER or SAME_LOWER");{let n=((t+e-1)/e-1)*e+r-t;return i[o]=Math.floor("SAME_LOWER"===a?(n+1)/2:n/2),i[s]=n-i[o],Math.floor((t+n-r)/e+1)}default:throw new Error("Unsupported AutoPad type")}}},Xt=-34028234663852886e22,Jt=34028234663852886e22}));function jl(t){switch(t){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 ${t}`)}}function Ni(t){switch(t){case k.onnx.TensorProto.DataType.UINT8:case k.onnx.TensorProto.DataType.INT8:case k.onnx.TensorProto.DataType.BOOL:return 1;case k.onnx.TensorProto.DataType.UINT16:case k.onnx.TensorProto.DataType.INT16:return 2;case k.onnx.TensorProto.DataType.FLOAT:case 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const int XH = ${s[2]};\n        const int XW = ${s[3]};\n        const int KH = ${o.kernelShape[0]};\n        const int KW = ${o.kernelShape[1]};\n        const int dilationH = ${o.dilations[0]};\n        const int dilationW = ${o.dilations[1]};\n        const int strideH = ${o.strides[0]};\n        const int strideW = ${o.strides[1]};\n        const int padH = ${o.pads[0]};\n        const int padW = ${o.pads[1]};\n        const int KHKW = KH*KW;\n        const int XCKHKW = XC * KHKW;\n        const int outputChannels = 4;\n        vec4 process(int indices[${u}]) {\n          int b  = indices[0]; // batch size\n          int oh = indices[1] * strideH - padH; //output height\n          int ow = indices[2] * strideW - padW; //output width\n          int p = indices[3] * outputChannels; //patch\n          vec4 value = vec4(0.0);\n          for(int i=0; i < outputChannels; ++i) {\n            if(p < XCKHKW) {\n              int patchC = p / KHKW;\n              int patchH = (p - 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${i};\n          int pad = 0;\n          ${d}\n          ${c}\n          ${h}\n          ${r}\n          return value;\n        }\n      `}{let s=A.size(e.kernelShape),a=A.computeStrides(e.kernelShape),u=a.length,l=e.pads.length,p=Tp(u),c=dr(t,"inputDims"),d=dr(e.pads,"pads"),h=dr(a,"kernelStrides"),f=dr(e.strides,"strides"),g="";return g=e.pads.reduce(((t,e)=>t+e))?`\n            if (x[j] >= inputDims[j] || x[j] < 0) {\n              pad++;\n              isPad = true;\n              break;\n            }\n          }\n          if (!isPad) {\n            ${n}\n          }`:`\n          }\n          ${n}\n        `,`\n        ${p}\n        float process(int indices[${o}]) {\n          int x[${o}];\n          copyVec(indices, x);\n          int offset[${u}];\n          int pads[${l}];\n          int inputDims[${o}];\n          int kernelStrides[${u}];\n          int strides[${u}];\n          ${d}\n          ${c}\n          ${f}\n          ${h}\n\n          float value = ${i};\n          int pad = 0;\n          bool isPad = false;\n          for (int i = 0; i < ${s}; i++) {\n            offsetToIndices(i, kernelStrides, offset);\n            isPad = false;\n            for (int j = ${o} - ${u}; j < ${o}; j++) {\n              x[j] = indices[j] * strides[j - ${o} + ${u}]\n                + offset[j - ${o} + ${u}] - pads[j - 2];\n              ${g}\n          }\n          ${r}\n\n          return value;\n        }\n      `}},dr=(t,e)=>{let n="";for(let r=0;r<t.length;r++)n+=`\n      ${e}[${r}] = ${t[r]};\n    `;return n},Tp=t=>`\n  void offsetToIndices(int offset, int[${t}] strides, out int[${t}] indices) {\n    if (${t} == 0) {\n      return;\n    }\n    for (int i = 0; i < ${t} - 1; ++i) {\n      indices[i] = offset / strides[i];\n      offset -= indices[i] * strides[i];\n    }\n    indices[${t} - 1] = offset;\n  }`})),ee,Vt,vp,wp,nu,ou,iu,au,su,uu,lu,fu=x((()=>{tt(),De(),z(),N(),ee=(t,e,n,r,i)=>{wp(e);let o={name:r,inputNames:["A"],inputTypes:[0]};return[t.run({...o,cacheHint:n.cacheKey,get:()=>vp(t,e,n,r,i,o)},e)]},Vt=t=>{let e=t.attributes.getInts("axes",[]),n=1===t.attributes.getInt("keepdims",1);return $({axes:e,keepDims:n})},vp=(t,e,n,r,i,o)=>{let s=[],a=e[0].dims.length||1,u=[],l=A.normalizeAxes(n.axes,e[0].dims.length),p=i(e,l),c=p[1];for(let t=0;t<e[0].dims.length;t++)l.indexOf(t)>=0||0===l.length?(n.keepDims&&s.push(1),c=`\n          for(int j${t} = 0; j${t} < ${e[0].dims[t]}; j${t}++) {\n            inputIdx[${t}] = j${t};\n            ${c}\n          }`):(u.push(`inputIdx[${t}] = outputIdx[${s.length}];`),s.push(e[0].dims[t]));let d=`\n      float process(int outputIdx[${s.length||1}]) {\n        float value;                 // final result\n        int inputIdx[${a}];      // addressing input data\n        ${u.join("\n")}\n        ${p[0]}       // init ops for reduce max/min\n        ${c}\n        ${p[2]}       // final computation for reduce mean\n        return value;\n      }`;return{...o,output:{dims:s,type:e[0].type,textureType:0},shaderSource:d}},wp=t=>{if(!t||1!==t.length)throw new Error("Reduce op requires 1 input.");if(-1===Rt.indexOf(t[0].type))throw new Error("Invalid input type.")},nu=(t,e,n)=>ee(t,e,n,"ReduceSum",(()=>["value = 0.0;","value += _A(inputIdx);",""])),ou=(t,e,n)=>ee(t,e,n,"ReduceMean",((t,e)=>{let n=1;for(let r=0;r<t[0].dims.length;r++)(e.indexOf(r)>=0||0===e.length)&&(n*=t[0].dims[r]);return["value = 0.0;","value += _A(inputIdx);",`value /= ${n}.;`]})),iu=(t,e,n)=>ee(t,e,n,"ReduceMax",((t,e)=>{let n=[];for(let r=0;r<t[0].dims.length;r++)(e.indexOf(r)>=0||0===e.length)&&n.push(`inputIdx[${r}] = 0;`);return[`${n.join("\n")}\nvalue = _A(inputIdx);`,"value = max(value, _A(inputIdx));",""]})),au=(t,e,n)=>ee(t,e,n,"ReduceMin",((t,e)=>{let n=[];for(let r=0;r<t[0].dims.length;r++)(e.indexOf(r)>=0||0===e.length)&&n.push(`inputIdx[${r}] = 0;`);return[`${n.join("\n")}\nvalue = _A(inputIdx);`,"value = min(value, _A(inputIdx));",""]})),su=(t,e,n)=>ee(t,e,n,"ReduceProd",(()=>["value = 1.0;","value *= _A(inputIdx);",""])),uu=(t,e,n)=>ee(t,e,n,"ReduceLogSum",(()=>["value = 0.0;","value += _A(inputIdx);","value = log(value);"])),lu=(t,e,n)=>ee(t,e,n,"ReduceLogSumSquare",(()=>["float t; value = 0.0;","t = _A(inputIdx); value += t * t;",""]))})),cu,pu=x((()=>{z(),cu=(t,e)=>{let n=A.calculateReshapedDims(e[0].dims,e[1].integerData);return t.session.pack?[t.reshapePacked(e[0],n)]:[t.reshapeUnpacked(e[0],n)]}})),du,En,hu,mu,Le,Ip,Dn,mr,Ln=x((()=>{tt(),q(),N(),du={name:"Upsample",inputNames:["X"],inputTypes:[0]},En=(t,e,n)=>(Dn(e,n),[t.run({...du,cacheHint:n.cacheKey,get:()=>Ip(t,e,n)},e)]),hu=t=>Le(t,7),mu=t=>Le(t,9),Le=(t,e)=>{let n=e>=10,r=t.attributes.getString("mode","nearest");if("nearest"!==r&&"linear"!==r&&(e<11||"cubic"!==r))throw new Error(`unrecognized mode: ${r}`);let i=[];e<9&&(i=t.attributes.getFloats("scales"),mr(i,r,n));let o=t.attributes.getFloat("extrapolation_value",0),s=e>10?t.attributes.getString("coordinate_transformation_mode","half_pixel"):"asymmetric";if(-1===["asymmetric","pytorch_half_pixel","tf_half_pixel_for_nn","align_corners","tf_crop_and_resize","half_pixel"].indexOf(s))throw new Error(`coordinate_transform_mode '${s}' is not supported`);let a="tf_crop_and_resize"===s,u=a,l="nearest"===r&&e>=11?t.attributes.getString("nearest_mode","round_prefer_floor"):"";if(-1===["round_prefer_floor","round_prefer_ceil","floor","ceil",""].indexOf(l))throw new Error(`nearest_mode '${l}' is not supported`);let p=t.attributes.getFloat("cubic_coeff_a",-.75),c=0!==t.attributes.getInt("exclude_outside",0);if(c&&"cubic"!==r)throw new Error("exclude_outside can be set to 1 only when mode is CUBIC.");let d=e<11||"nearest"===r&&"asymmetric"===s&&"floor"===l,h=0,f=0,g=0;return e>10?t.inputs.length>2?(h=1,f=2,g=3):(f=1,g=2):9===e&&(f=1),$({opset:e,isResize:n,mode:r,scales:i,extrapolationValue:o,coordinateTransformMode:s,useExtrapolation:u,needRoiInput:a,nearestMode:l,cubicCoefficientA:p,excludeOutside:c,useNearest2xOptimization:d,roiInputIdx:h,scalesInputIdx:f,sizesInputIdx:g})},Ip=(t,e,n)=>{let r=D(t.session.backend.glContext.version),[i,o]=t.calculateTextureWidthAndHeight(e[0].dims,0),s=e[0].dims.map(((t,e)=>Math.floor(t*n.scales[e]))),[a,u]=t.calculateTextureWidthAndHeight(s,0),l=s.length,p=new Array(l),c=new Array(l),d=`\n      int output_pitches[${l}];\n      int input_pitches[${l}];\n      `;for(let t=l-1;t>=0;t--)p[t]=t===l-1?1:p[t+1]*s[t+1],c[t]=t===l-1?1:c[t+1]*e[0].dims[t+1],d+=`\n        output_pitches[${t}] = ${p[t]};\n        input_pitches[${t}] = ${c[t]};\n        `;let h=`\n      float getInputFloat(int index) {\n        vec2 coords = offsetToCoords(index, ${i}, ${o});\n        float value = getColorAsFloat(${r.texture2D}(X, coords));\n        return value;\n      }\n      `,f="nearest"===n.mode?`\n    ${h}\n    float process(int indices[${l}]) {\n      int input_index = 0;\n      int output_index = coordsToOffset(TexCoords, ${a}, ${u});\n\n      ${d}\n\n      int d, m;\n      for (int dim = 0; dim < ${l}; ++dim) {\n        d = output_index / output_pitches[dim];\n        m = output_index - d * output_pitches[dim];\n        output_index = m;\n\n        if (scales[dim] != 1 && d > 0) {\n          int d2 = d / scales[dim];\n          m = d - d2 * scales[dim];\n          d = d2;\n        }\n        input_index += input_pitches[dim] * d;\n      }\n\n      return getInputFloat(input_index);\n    }`:4===l?`\n    ${h}\n    float process(int indices[4]) {\n      int input_index = 0;\n      int output_index = coordsToOffset(TexCoords, ${a}, ${u});\n\n      ${d}\n\n      int m;\n      int index_of_dim0, index_of_dim1, index_of_dim2, index_of_dim3;\n      index_of_dim0 = output_index / output_pitches[0];\n      m = output_index - index_of_dim0 * output_pitches[0];\n      index_of_dim1 = m / output_pitches[1];\n      m = m - index_of_dim1 * output_pitches[1];\n      index_of_dim2 = m / output_pitches[2];\n      m = m - index_of_dim2 * output_pitches[2];\n      index_of_dim3 = m;\n\n      int index_of_input_dim2, index_of_input_dim3, x_offset, y_offset;\n      index_of_input_dim2 = index_of_dim2 / scales[2];\n      y_offset = index_of_dim2 - index_of_input_dim2 * scales[2];\n      index_of_input_dim3 = index_of_dim3 / scales[3];\n      x_offset = index_of_dim3 - index_of_input_dim3 * scales[3];\n\n      input_index = index_of_dim0 * input_pitches[0] +\n            index_of_dim1 * input_pitches[1] +\n            index_of_input_dim2 * input_pitches[2] +\n            index_of_input_dim3;\n\n      float x00 = getInputFloat(input_index);\n      float x10, x01, x11;\n\n      bool end_of_dim2 = false;\n      if (index_of_input_dim2 == (${e[0].dims[2]} - 1)) {\n        // It's the end in dimension 2\n        x01 = x00;\n        end_of_dim2 = true;\n      } else {\n        x01 = getInputFloat(input_index + input_pitches[2]);\n      }\n\n      if (index_of_input_dim3 == (input_pitches[2] - 1)) {\n        // It's the end in dimension 3\n        x10 = x00;\n        x11 = x01;\n      }\n      else {\n        x10 = getInputFloat(input_index + 1);\n        x11 = end_of_dim2 ? x10 : getInputFloat(input_index + input_pitches[2] + 1);\n      }\n\n      float y0 = x00 + float(y_offset) * (x01 - x00) / float(scales[2]);\n      float y1 = x10 + float(y_offset) * (x11 - x10) / float(scales[2]);\n      return y0 + float(x_offset) * (y1 - y0) / float(scales[3]);\n    }`:`\n    ${h}\n    float process(int indices[2]) {\n      int input_index = 0;\n      int output_index = coordsToOffset(TexCoords, ${a}, ${u});\n\n      ${d}\n\n      int m;\n      int index_of_dim0, index_of_dim1;\n      index_of_dim0 = output_index / output_pitches[0];\n      m = output_index - index_of_dim0 * output_pitches[0];\n      index_of_dim1 = m;\n\n      int index_of_input_dim0, index_of_input_dim1, x_offset, y_offset;\n      index_of_input_dim0 = index_of_dim0 / scales[0];\n      y_offset = index_of_dim0 - index_of_input_dim0 * scales[0];\n      index_of_input_dim1 = index_of_dim1 / scales[1];\n      x_offset = index_of_dim1 - index_of_input_dim1 * scales[1];\n\n      input_index = index_of_input_dim0 * input_pitches[0] + index_of_input_dim1;\n\n      float x00 = getInputFloat(input_index);\n      float x10, x01, x11;\n\n      bool end_of_dim0 = false;\n      if (index_of_input_dim0 == (${e[0].dims[0]} - 1)) {\n        // It's the end in dimension 0\n        x01 = x00;\n        end_of_dim0 = true;\n      } else {\n        x01 = getInputFloat(input_index + input_pitches[0]);\n      }\n\n      if (index_of_input_dim1 == (input_pitches[0] - 1)) {\n        // It's the end in dimension 1\n        x10 = x00;\n        x11 = x01;\n      }\n      else {\n        x10 = getInputFloat(input_index + 1);\n        x11 = end_of_dim0 ? x10 : getInputFloat(input_index + input_pitches[0] + 1);\n      }\n\n      float y0 = x00 + float(y_offset) * (x01 - x00) / float(scales[0]);\n      float y1 = x10 + float(y_offset) * (x11 - x10) / float(scales[0]);\n      return y0 + float(x_offset) * (y1 - y0) / float(scales[1]);\n    }`;return{...du,output:{dims:s,type:e[0].type,textureType:0},shaderSource:f,variables:[{name:"scales",type:"int",arrayLength:n.scales.length,data:n.scales.map((t=>Math.ceil(t)))}]}},Dn=(t,e)=>{if(!t||e.opset<9&&1!==t.length||e.opset>=9&&e.opset<11&&2!==t.length||e.opset>=11&&t.length<2)throw new Error("invalid inputs.");if(e.scales.length>0&&t[0].dims.length!==e.scales.length)throw new Error("Invalid input shape.");if("string"===t[0].type)throw new Error("Invalid input tensor types.")},mr=(t,e,n)=>{if(n){for(let e of t)if(e<=0)throw new Error("Scale value should be greater than 0.")}else for(let e of t)if(e<1)throw new Error("Scale value should be greater than or equal to 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a=o[s-2],u=o[s-1],l=e[0].dims;if(s!==l.length)throw new Error(`output dimension should match input ${l.length}, but got ${s}`);let p=l[s-2],c=l[s-1],d=i[s-2],h=i[s-1],f="";if("linear"!==n.mode)throw new Error(`resize (packed) does not support mode: '${n.mode}'`);switch(n.coordinateTransformMode){case"asymmetric":f="\n                    vec4 getSourceFracIndex(ivec4 coords) {\n                        return vec4(coords) / scaleWHWH;\n                    }\n                ";break;case"half_pixel":f="\n                    vec4 getSourceFracIndex(ivec4 coords) {\n                        return (vec4(coords) + 0.5) / scaleWHWH - 0.5;\n                    }\n                ";break;case"pytorch_half_pixel":f=`\n                    vec4 getSourceFracIndex(ivec4 coords) {\n                        vec4 fcoords = vec4(coords);\n                        return vec4(\n                            ${u}.0 > 1.0 ? (fcoords.x + 0.5) / scaleWHWH.x - 0.5 : 0.0,\n                            ${a}.0 > 1.0 ? (fcoords.y + 0.5) / scaleWHWH.y - 0.5 : 0.0,\n                            ${u}.0 > 1.0 ? (fcoords.z + 0.5) / scaleWHWH.z - 0.5 : 0.0,\n                            ${a}.0 > 1.0 ? (fcoords.w + 0.5) / scaleWHWH.w - 0.5 : 0.0\n                          );\n                    }\n                `;break;case"align_corners":f=`\n                    vec4 getSourceFracIndex(ivec4 coords) {\n                        vec4 resized = vec4(${u}.0 - 1.0, ${a}.0 - 1.0, ${u}.0 - 1.0,\n                            ${a}.0 - 1.0);\n                        vec4 original = vec4(${c}.0 - 1.0, ${p}.0 - 1.0, ${c}.0 - 1.0,\n                            ${p}.0 - 1.0);\n                        vec4 new_scale = original / resized;\n                        return vec4(coords) * new_scale;\n                    }\n                `;break;default:throw new Error(`resize (packed) does not support coordinateTransformMode:                                 '${n.coordinateTransformMode}'`)}let g=at(s),b=`\n            const vec2 inputWH = vec2(${p}.0, ${c}.0);\n            const vec4 scaleWHWH = vec4(float(${d}), float(${h}), float(${d}), float(${h}));\n            ${Pt()}\n            ${f}\n            float getAValue(int x10, int r, int c, int d) {\n                return getChannel(getA(x10, r, c, d), vec2(c, d));\n            }\n            void main() {\n                ${g} rc = getOutputCoords();\n\n                int batch = rc[0];\n                int depth = rc[1];\n\n                // retrieve the 4 coordinates that is used in the 4 packed output values.\n                ivec4 coords = ivec4(rc.wz, rc.w + 1, rc.z + 1);\n\n                // calculate the source index in fraction\n                vec4 sourceFrac = getSourceFracIndex(coords);\n\n                // get the lower and upper bound of the 4 values that will be packed into one texel.\n                ivec4 x00 = ivec4(max(sourceFrac.xy, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.xy)));\n                ivec4 x01 = ivec4(max(sourceFrac.xw, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.xw)));\n                ivec4 x10 = ivec4(max(sourceFrac.zy, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.zy)));\n                ivec4 x11 = ivec4(max(sourceFrac.zw, vec2(0.0)), min(inputWH - 1.0, ceil(sourceFrac.zw)));\n\n                bool hasNextRow = rc.w < ${a-1};\n                bool hasNextCol = rc.z < ${u-1};\n\n                // pack x00, x01, x10, x11's top-left corner into one vec4 structure\n                vec4 topLeft = vec4(\n                    getAValue(batch, depth, x00.x, x00.y),\n                    hasNextCol ? getAValue(batch, depth, x01.x, x01.y) : 0.0,\n                    hasNextRow ? getAValue(batch, depth, x10.x, x10.y) : 0.0,\n                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.x, x11.y) : 0.0);\n\n                // pack x00, x01, x10, x11's top-right corner into one vec4 structure\n                vec4 topRight = vec4(\n                    getAValue(batch, depth, x00.x, x00.w),\n                    hasNextCol ? getAValue(batch, depth, x01.x, x01.w) : 0.0,\n                    hasNextRow ? getAValue(batch, depth, x10.x, x10.w) : 0.0,\n                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.x, x11.w) : 0.0);\n\n                // pack x00, x01, x10, x11's bottom-left corner into one vec4 structure\n                vec4 bottomLeft = vec4(\n                    getAValue(batch, depth, x00.z, x00.y),\n                    hasNextCol ? getAValue(batch, depth, x01.z, x01.y) : 0.0,\n                    hasNextRow ? getAValue(batch, depth, x10.z, x10.y) : 0.0,\n                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.z, x11.y) : 0.0);\n\n                // pack x00, x01, x10, x11's bottom-right corner into one vec4 structure\n                vec4 bottomRight = vec4(\n                    getAValue(batch, depth, x00.z, x00.w),\n                    hasNextCol ? getAValue(batch, depth, x01.z, x01.w) : 0.0,\n                    hasNextRow ? getAValue(batch, depth, x10.z, x10.w) : 0.0,\n                    (hasNextRow && hasNextCol) ? getAValue(batch, depth, x11.z, x11.w) : 0.0);\n\n                // calculate the interpolation fraction on u and v direction\n                vec4 frac = vec4(sourceFrac) - floor(sourceFrac);\n                vec4 clampFrac = clamp(frac, vec4(0.0), vec4(1.0));\n\n                vec4 top = mix(topLeft, topRight, clampFrac.ywyw);\n                vec4 bottom = mix(bottomLeft, bottomRight, clampFrac.ywyw);\n                vec4 newValue = mix(top, bottom, clampFrac.xxzz);\n\n                ${r.output} = vec4(newValue);\n            }\n        `;return{...$n,output:{dims:o,type:e[0].type,textureType:2},hasMain:!0,shaderSource:b}},Sp=(t,e)=>{let n,r=t[0].dims,i=e.scales;if(0===i.length){let o=t[e.scalesInputIdx];if(o&&0!==o.size){if(t[e.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");i=Op(o,e.mode,e.isResize)}else{let o=t[e.sizesInputIdx];if(!o||0===o.size)throw new Error("Either scales or sizes MUST be provided as input.");n=Array.from(o.integerData),i=Ap(n,r,e.mode,e.isResize)}}else if(t[e.sizesInputIdx])throw 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mt{constructor(t){super(t)}getFunctions(){return{...this.offsetToCoords(),...this.coordsToOffset(),...this.toVec(),...this.valueFrom(),...this.getCommonUtilFuncs(),...this.getInputsSamplingSnippets(),...this.getOutputSamplingSnippet()}}getCustomTypes(){return{}}offsetToCoords(){return{offsetToCoords:new I("\n      vec2 offsetToCoords(int offset, int width, int height) {\n        int t = offset / width;\n        int s = offset - t*width;\n        vec2 coords = (vec2(s,t) + vec2(0.5,0.5)) / vec2(width, height);\n        return coords;\n      }\n      ")}}coordsToOffset(){return{coordsToOffset:new I("\n      int coordsToOffset(vec2 coords, int width, int height) {\n        float s = coords.s * float(width);\n        float t = coords.t * float(height);\n        int offset = int(t) * width + int(s);\n        return offset;\n      }\n      ")}}getOutputSamplingSnippet(){let t=this.context.outputTextureLayout;return t.isPacked?this.getPackedOutputSamplingSnippet(t):this.getUnpackedOutputSamplingSnippet(t)}getPackedOutputSamplingSnippet(t){let e=t.unpackedShape,n=[t.width,t.height],r={},i="getOutputCoords";switch(e.length){case 0:r[i]=this.getOutputScalarCoords();break;case 1:r[i]=this.getOutputPacked1DCoords(e,n);break;case 2:r[i]=this.getOutputPacked2DCoords(e,n);break;case 3:r[i]=this.getOutputPacked3DCoords(e,n);break;default:r[i]=this.getOutputPackedNDCoords(e,n)}let o=`\n      void setOutput(vec4 val) {\n        ${D(this.context.glContext.version).output} = val;\n      }\n    `;return r.floatTextureSetRGBA=new I(o),r}getUnpackedOutputSamplingSnippet(t){let e=t.unpackedShape,n=[t.width,t.height],r={},i="getOutputCoords";switch(e.length){case 0:r[i]=this.getOutputScalarCoords();break;case 1:r[i]=this.getOutputUnpacked1DCoords(e,n);break;case 2:r[i]=this.getOutputUnpacked2DCoords(e,n);break;case 3:r[i]=this.getOutputUnpacked3DCoords(e,n);break;case 4:r[i]=this.getOutputUnpacked4DCoords(e,n);break;case 5:r[i]=this.getOutputUnpacked5DCoords(e,n);break;case 6:r[i]=this.getOutputUnpacked6DCoords(e,n);break;default:throw new Error(`Unsupported output dimensionality: ${e.length}`)}let o=`\n        void setOutput(float val) {\n          ${D(this.context.glContext.version).output} = vec4(val, 0, 0, 0);\n        }\n    `;return r.floatTextureSetR=new I(o),r}getOutputScalarCoords(){return new I("\n      int getOutputCoords() {\n        return 0;\n      }\n    ")}getOutputPacked1DCoords(t,e){let n=e,r="";return 1===n[0]?(r=`\n          int getOutputCoords() {\n            return 2 * int(TexCoords.y * ${n[1]}.0);\n          }\n        `,new I(r)):1===n[1]?(r=`\n          int getOutputCoords() {\n            return 2 * int(TexCoords.x * ${n[0]}.0);\n          }\n        `,new I(r)):(r=`\n        int getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                 vec2(${n[0]}, ${n[1]}));\n          return 2 * (resTexRC.y * ${n[0]} + resTexRC.x);\n        }\n      `,new I(r))}getOutputPacked2DCoords(t,e){let n="";if(jt.arraysEqual(t,e))return n=`\n        ivec2 getOutputCoords() {\n          return 2 * ivec2(TexCoords.xy * vec2(${e[0]}, ${e[1]}));\n        }\n      `,new I(n);let r=e,i=Math.ceil(t[1]/2);return n=`\n        ivec2 getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                vec2(${r[0]}, ${r[1]}));\n\n          int index = resTexRC.y * ${r[0]} + resTexRC.x;\n\n          // reverse r and c order for packed texture\n          int r = imod(index, ${i}) * 2;\n          int c = 2 * (index / ${i});\n\n          return ivec2(r, c);\n        }\n      `,new I(n)}getOutputPacked3DCoords(t,e){let n=[e[0],e[1]],r=Math.ceil(t[2]/2),i=r*Math.ceil(t[1]/2);return new I(`\n        ivec3 getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                vec2(${n[0]}, ${n[1]}));\n          int index = resTexRC.y * ${n[0]} + resTexRC.x;\n\n          int b = index / ${i};\n          index -= b * ${i};\n\n          // reverse r and c order for packed texture\n          int r = imod(index, ${r}) * 2;\n          int c = 2 * (index / ${r});\n\n          return ivec3(b, r, c);\n        }\n      `)}getOutputPackedNDCoords(t,e){let n=[e[0],e[1]],r=Math.ceil(t[t.length-1]/2),i=r*Math.ceil(t[t.length-2]/2),o=i,s="",a="b, r, c";for(let e=2;e<t.length-1;e++)o*=t[t.length-e-1],s=`\n      int b${e} = index / ${o};\n      index -= b${e} * ${o};\n    `+s,a=`b${e}, `+a;let u=`\n      ivec${t.length} getOutputCoords() {\n        ivec2 resTexRC = ivec2(TexCoords.xy *\n                              vec2(${n[0]}, ${n[1]}));\n        int index = resTexRC.y * ${n[0]} + resTexRC.x;\n\n        ${s}\n\n        int b = index / ${i};\n        index -= b * ${i};\n\n        // reverse r and c order for packed texture\n        int r = imod(index, ${r}) * 2;\n        int c = 2 * (index / ${r});\n\n        return ivec${t.length}(${a});\n      }\n    `;return new I(u)}getOutputUnpacked1DCoords(t,e){let n=`\n        int getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                vec2(${e[0]}, ${e[1]}));\n          return resTexRC.y * ${e[0]} + resTexRC.x;\n        }\n      `;return new I(n)}getOutputUnpacked2DCoords(t,e){let n=`\n        ivec2 getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                vec2(${e[0]}, ${e[1]}));\n          int index = resTexRC.y * ${e[0]} + resTexRC.x;\n          int r = index / ${t[1]};\n          int c = index - r * ${t[1]};\n          return ivec2(r, c);\n        }\n      `;return new I(n)}getOutputUnpacked3DCoords(t,e){let n="",r=t.length,i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=t[r-1];for(let e=r-3;e>=0;--e)i[e]=i[e+1]*t[e+1];let o=["r","c","d"],s=i.map(((t,e)=>`${`int ${o[e]} = index / ${t}`}; ${e===i.length-1?`int ${o[e+1]} = index - ${o[e]} * ${t}`:`index -= ${o[e]} * ${t}`};`)).join("");return n=`\n        ivec3 getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                vec2(${e[0]}, ${e[1]}));\n          int index = resTexRC.y * ${e[0]} + resTexRC.x;\n          ${s}\n          return ivec3(r, c, d);\n        }\n      `,new I(n)}getOutputUnpacked4DCoords(t,e){let n="",r=t.length,i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=t[r-1];for(let e=r-3;e>=0;--e)i[e]=i[e+1]*t[e+1];let o=["r","c","d","d2"],s=i.map(((t,e)=>`${`int ${o[e]} = index / ${t}`}; ${e===i.length-1?`int ${o[e+1]} = index - ${o[e]} * ${t}`:`index -= ${o[e]} * ${t}`};`)).join("");return n=`\n      ivec4 getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                vec2(${e[0]}, ${e[1]}));\n          int index = resTexRC.y * ${e[0]} + resTexRC.x;\n          ${s}\n          return ivec4(r, c, d, d2);\n        }\n      `,new I(n)}getOutputUnpacked5DCoords(t,e){let n="",r=t.length,i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=t[r-1];for(let e=r-3;e>=0;--e)i[e]=i[e+1]*t[e+1];let o=["r","c","d","d2","d3"],s=i.map(((t,e)=>`${`int ${o[e]} = index / ${t}`}; ${e===i.length-1?`int ${o[e+1]} = index - ${o[e]} * ${t}`:`index -= ${o[e]} * ${t}`};`)).join("");return n=`\n      ivec5 getOutputCoords() {\n          ivec2 resTexRC = ivec2(TexCoords.xy *\n                                vec2(${e[0]}, ${e[1]}));\n          int index = resTexRC.y * ${e[0]} + resTexRC.x;\n          ${s}\n          return ivec5(r, c, d, d2, d3);\n        }\n      `,new I(n)}getOutputUnpacked6DCoords(t,e){let n="",r=t.length,i=null;r<2&&(i=[]),i=new Array(r-1),i[r-2]=t[r-1];for(let e=r-3;e>=0;--e)i[e]=i[e+1]*t[e+1];let o=["r","c","d","d2","d3","d4"],s=i.map(((t,e)=>`${`int ${o[e]} = index / ${t}`}; ${e===i.length-1?`int ${o[e+1]} = index - ${o[e]} * ${t}`:`index -= ${o[e]} * ${t}`};`)).join("");return n=`\n     ivec6 getOutputCoords() {\n         ivec2 resTexRC = ivec2(TexCoords.xy *\n                               vec2(${e[0]}, ${e[1]}));\n         int index = resTexRC.y * ${e[0]} + resTexRC.x;\n         ${s}\n         return ivec6(r, c, d, d2, d3, d4);\n       }\n     `,new I(n)}getCommonUtilFuncs(){let t={},e="uvFromFlat";t[e]=new I("\n    vec2 uvFromFlat(int texNumR, int texNumC, int index) {\n      int texC = index / texNumR;\n      int texR = index - texC * texNumR;\n      // TODO: swap texR, texC order in following function so row is corresponding to u and column is corresponding to\n      //       v.\n      return (vec2(texR, texC) + halfCR) / vec2(texNumR, texNumC);\n    }\n    "),e="packedUVfrom1D",t[e]=new I("\n      vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\n        int texelIndex = index / 2;\n        int texR = texelIndex / texNumC;\n        int texC = texelIndex - texR * texNumC;\n        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n      }\n      "),e="packedUVfrom2D",t[e]=new I("\n      vec2 packedUVfrom2D(int texNumR, int texNumC, int texelsInLogicalRow, int row, int col) {\n        int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);\n        int texR = texelIndex / texNumC;\n        int texC = texelIndex - texR * texNumC;\n        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n      }\n      "),e="packedUVfrom3D",t[e]=new I("\n      vec2 packedUVfrom3D(int texNumR, int texNumC,\n          int texelsInBatch, int texelsInLogicalRow, int b,\n          int row, int col) {\n        int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);\n        int texR = index / texNumC;\n        int texC = index - texR * texNumC;\n        return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n      }\n      "),e="sampleTexture";let n=D(this.context.glContext.version);return t[e]=new I(`\n        float sampleTexture(sampler2D textureSampler, vec2 uv) {\n            return ${n.texture2D}(textureSampler, uv).r;\n        }`),t}getInputsSamplingSnippets(){let t={},e=this.context.outputTextureLayout;return this.context.programInfo.inputNames.forEach(((n,r)=>{let i=this.context.inputTextureLayouts[r],o=rr(n);i.isPacked?t[o]=this.getPackedSamplerFromInput(o,n,i):t[o]=this.getUnpackedSamplerFromInput(o,n,i);let s=Ui(n);i.unpackedShape.length<=e.unpackedShape.length&&(i.isPacked?t[s]=this.getPackedSamplerAtOutputCoords(s,i,e,n):t[s]=this.getUnpackedSamplerAtOutputCoords(s,i,e,n))})),t}getPackedSamplerAtOutputCoords(t,e,n,r){let i,o=e.unpackedShape,s=n.unpackedShape,a=rr(r),u=o.length,l=s.length,p=it.getBroadcastDims(o,s),c=at(l),d=l-u,h=It();i=0===u?"":l<2&&p.length>=1?"coords = 0;":p.map((t=>`coords.${h[t+d]} = 0;`)).join("\n");let f="";f=l<2&&u>0?"coords":o.map(((t,e)=>`coords.${h[e+d]}`)).join(", ");let g="return outputValue;",b=1===A.size(o),m=1===A.size(s);if(1!==u||b||m){if(b&&!m)g=1===l?"\n          return vec4(outputValue.x, outputValue.x, 0., 0.);\n        ":"\n          return vec4(outputValue.x);\n        ";else if(p.length){let t=u-2,e=u-1;p.indexOf(t)>-1&&p.indexOf(e)>-1?g="return vec4(outputValue.x);":p.indexOf(t)>-1?g="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":p.indexOf(e)>-1&&(g="return vec4(outputValue.xx, outputValue.zz);")}}else g="\n        return vec4(outputValue.xy, outputValue.xy);\n      ";let y=`\n        int lastDim = coords.${h[l-1]};\n        coords.${h[l-1]} = coords.${h[l-2]};\n        coords.${h[l-2]} = lastDim;\n      `;return new I(`\n      vec4 ${t}() {\n        ${c} coords = getOutputCoords();\n        ${y}\n        ${i}\n        vec4 outputValue = ${a}(${f});\n        ${g}\n      }\n    `,["coordinates.getOutputCoords"])}getUnpackedSamplerAtOutputCoords(t,e,n,r){let i=[n.width,n.height],o=[e.width,e.height],s=e.unpackedShape.length,a=n.unpackedShape.length,u=e.unpackedShape,l=n.unpackedShape,p=rr(r);if(s===a&&jt.arraysEqual(o,i)){return new I(`\n          float ${t}() {\n            return sampleTexture(${r}, TexCoords);\n          }\n        `,["coordinates.sampleTexture"])}let c,d=at(a),h=it.getBroadcastDims(u,l),f=a-s,g=It();c=0===s?"":a<2&&h.length>=1?"coords = 0;":h.map((t=>`coords.${g[t+f]} = 0;`)).join("\n");let b="";return b=a<2&&s>0?"coords":e.unpackedShape.map(((t,e)=>`coords.${g[e+f]}`)).join(", "),new I(`\n        float ${t}() {\n          ${d} coords = getOutputCoords();\n          ${c}\n          return ${p}(${b});\n        }\n      `,["coordinates.getOutputCoords"])}getPackedSamplerFromInput(t,e,n){switch(n.unpackedShape.length){case 0:return this.getPackedSamplerScalar(t,e);case 1:return this.getPackedSampler1D(t,e,n);case 2:return this.getPackedSampler2D(t,e,n);case 3:return this.getPackedSampler3D(t,e,n);default:return this.getPackedSamplerND(t,e,n)}}getUnpackedSamplerFromInput(t,e,n){let r=n.unpackedShape;switch(r.length){case 0:return this.getUnpackedSamplerScalar(t,e,n);case 1:return this.getUnpackedSampler1D(t,e,n);case 2:return this.getUnpackedSampler2D(t,e,n);case 3:return this.getUnpackedSampler3D(t,e,n);case 4:return this.getUnpackedSampler4D(t,e,n);case 5:return this.getUnpackedSampler5D(t,e,n);case 6:return this.getUnpackedSampler6D(t,e,n);default:throw new Error(`Unsupported dimension ${r.length}-D`)}}getPackedSamplerScalar(t,e){let n=`\n          vec4 ${t}() {\n            return ${D(this.context.glContext.version).texture2D}(${e}, halfCR);\n          }\n        `;return new I(n)}getPackedSampler1D(t,e,n){let r=[n.width,n.height],i=[r[1],r[0]],o=D(this.context.glContext.version),s=`vec4 ${t}(int index) {\n      vec2 uv = packedUVfrom1D(\n      ${i[0]}, ${i[1]}, index);\n      return ${o.texture2D}(${e}, uv);\n    }`;return new I(s,["coordinates.packedUVfrom1D"])}getPackedSampler2D(t,e,n){let r=n.unpackedShape,i=[n.width,n.height],o=D(this.context.glContext.version),s=i[0],a=i[1];if(null!=i&&jt.arraysEqual(r,i)){let n=`vec4 ${t}(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(${a}.0, ${s}.0);\n        return ${o.texture2D}(${e}, uv);\n      }`;return new I(n)}let u=i,l=Math.ceil(r[1]/2),p=`vec4 ${t}(int row, int col) {\n      vec2 uv = packedUVfrom2D(${u[1]}, ${u[0]}, ${l}, row, col);\n      return ${o.texture2D}(${e}, uv);\n    }`;return new I(p,["coordinates.packedUVfrom2D"])}getPackedSampler3D(t,e,n){let r=n.unpackedShape,i=[n.width,n.height],o=[i[0],i[1]],s=D(this.context.glContext.version);if(1===r[0]){let i=r.slice(1),o=[1,2],s=ue(r,i),a=["b","row","col"],u=JSON.parse(JSON.stringify(n));u.unpackedShape=s;let l=this.getPackedSamplerFromInput(t,e,u),p=`${l.routineBody}\n      vec4 ${t}(int b, int row, int col) {\n        return ${t}(${le(a,o)});\n      } `;return new I(p,l.dependencies)}let a=o[0],u=o[1],l=Math.ceil(r[2]/2),p=`vec4 ${t}(int b, int row, int col) {\n      vec2 uv = packedUVfrom3D(\n        ${u}, ${a}, ${l*Math.ceil(r[1]/2)}, ${l}, b, row, col);\n      return ${s.texture2D}(${e}, uv);}`;return new I(p,["coordinates.packedUVfrom3D"])}getPackedSamplerND(t,e,n){let r=n.unpackedShape,i=r.length,o=[n.width,n.height],s=D(this.context.glContext.version),a=[o[0],o[1]],u=a[1],l=a[0],p=Math.ceil(r[i-1]/2),c=p*Math.ceil(r[i-2]/2),d="int b, int row, int col",h=`b * ${c} + (row / 2) * ${p} + (col / 2)`;for(let t=2;t<i-1;t++)d=`int b${t}, `+d,c*=r[i-t-1],h=`b${t} * ${c} + `+h;let f=`vec4 ${t}(${d}) {\n      int index = ${h};\n      int texR = index / ${l};\n      int texC = index - texR * ${l};\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${l}, ${u});\n      return ${s.texture2D}(${e}, uv);\n    }`;return new I(f)}getUnpackedSamplerScalar(t,e,n){let[r,i]=[n.width,n.height];if(1===r&&1===i){return new I(`\n          float ${t}() {\n            return sampleTexture(${e}, halfCR);\n          }\n        `,["coordinates.sampleTexture"])}return new I(`\n        float ${t}() {\n          int offset_${e} = coordsToOffset(TexCoords, ${r}, ${i});\n          vec2 uv = uvFromFlat(${r}, ${i}, offset_${e});\n          return sampleTexture(${e}, uv);\n        }\n      `,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}getUnpackedSampler1D(t,e,n){let r=n.width,i=n.height;if(1===i&&1===r){return new I(`\n        float ${t}(int index) {\n          return sampleTexture(${e}, halfCR);\n        }\n      `,["coordinates.sampleTexture"])}if(1===i){return new I(`\n          float ${t}(int index) {\n            vec2 uv = vec2((float(index) + 0.5) / ${r}.0, 0.5);\n            return sampleTexture(${e}, uv);\n          }\n        `,["coordinates.sampleTexture"])}if(1===r){return new I(`\n          float ${t}(int index) {\n            vec2 uv = vec2(0.5, (float(index) + 0.5) / ${i}.0);\n            return sampleTexture(${e}, uv);\n          }\n        `,["coordinates.sampleTexture"])}return new I(`\n        float ${t}(int index) {\n          vec2 uv = uvFromFlat(${r}, ${i}, index);\n          return sampleTexture(${e}, uv);\n        }\n      `,["coordinates.uvFromFlat","coordinates.sampleTexture"])}getUnpackedSampler2D(t,e,n){let r=n.unpackedShape,i=[n.height,n.width];if(null!=i&&jt.arraysEqual(r,i)){return new I(`\n          float ${t}(int row, int col) {\n            vec2 uv = (vec2(row, col) + halfCR) / vec2(${i[1]}.0, ${i[0]}.0);\n            return sampleTexture(${e}, uv);\n          }\n        `,["coordinates.sampleTexture"])}let{newShape:o,keptDims:s}=de(r),a=o;if(a.length<r.length){let i=ue(r,a),o=JSON.parse(JSON.stringify(n));o.unpackedShape=i;let u=["col","row"],l=`\n          ${this.getUnpackedSamplerFromInput(t,e,o).routineBody}\n          float ${t}(int row, int col) {\n            return ${t}(${le(u,s)});\n          }\n        `;return new I(l,["coordinates.sampleTexture"])}let u=i[1],l=i[0];if(1===l){let n=`\n          float ${t}(int row, int col) {\n            int offset_${e} = coordsToOffset(TexCoords, ${u}, ${l});\n            float index = dot(vec3(row, col, offset_${e}), vec3(${r[1]}, 1, 1));\n            vec2 uv = vec2(0.5, (index + 0.5) / ${u}.0);\n            return sampleTexture(${e}, uv);\n          }\n        `;return new I(n,["coordinates.sampleTexture","coordinates.coordsToOffset"])}if(1===u){let n=`\n          float ${t}(int row, int col) {\n            int offset_${e} = coordsToOffset(TexCoords, ${u}, ${l});\n            float index = dot(vec3(row, col, offset_${e}), vec3(${r[1]}, 1, 1));\n            vec2 uv = vec2((index + 0.5) / ${l}.0, 0.5);\n            return sampleTexture(${e}, uv);\n          }\n        `;return new I(n,["coordinates.sampleTexture","coordinates.coordsToOffset"])}let p=`\n        float ${t}(int row, int col) {\n          int index = col * ${r[1]} + row;\n          vec2 uv = uvFromFlat(${u}, ${l}, index);\n          return sampleTexture(${e}, uv);\n        }\n      `;return new I(p,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}getUnpackedSampler3D(t,e,n){let r=n.unpackedShape,i=r[1]*r[2],o=r[2],{newShape:s,keptDims:a}=de(r),u=s;if(u.length<r.length){let i=ue(r,u),o=["batch","col","row"],s=JSON.parse(JSON.stringify(n));s.unpackedShape=i;let l=this.getUnpackedSamplerFromInput(t,e,s),p=a.reverse(),c=`\n          ${l.routineBody}\n          float ${t}(int batch, int row, int col) {\n            return ${t}(${le(o,p)});\n          }\n        `;return new I(c,l.dependencies)}let l=n.width,p=n.height;return new I(`\n          float ${t}(int depth, int row, int col) {\n            // Explicitly use integer operations as dot() only works on floats.\n            int index = depth * ${i} + col * ${o} + row;\n            vec2 uv = uvFromFlat(${l}, ${p}, index);\n            return sampleTexture(${e}, uv);\n          }\n      `,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}getUnpackedSampler4D(t,e,n){let r=n.unpackedShape,i=r[3],o=r[2]*i,s=r[1]*o,a=n.width,u=n.height;return new I(`\n        float ${t}(int row, int 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depth2 * ${o} + depth3 * ${i} + depth4;\n            vec2 uv = uvFromFlat(${c}, ${d}, index);\n            return sampleTexture(${e}, uv);\n          }\n        `,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}toVec(){let t=this.context.outputTextureLayout,e=t.shape.length,n=t.strides,r=t.width,i=t.height,o=[];for(let t=0;t<e-1;++t)o.push(`\n        c[${t}] = offset / ${n[t]};`),o.push(`\n        offset -= c[${t}] * ${n[t]};`);o.push(`\n        c[${e-1}] = offset;`);let s=`\n      void toVec(vec2 texCoords, out int c[${e}]) {\n        int offset = coordsToOffset(texCoords, ${r}, ${i});\n        ${o.join("")}\n      }\n      void toVec(int offset, out int c[${e}]) {\n        ${o.join("")}\n      }\n    `;return{toVec:new I(s,["coordinates.coordsToOffset"])}}valueFrom(){let t={};return this.context.programInfo.inputNames.forEach(((e,n)=>{let r=this.context.inputTextureLayouts[n],i=(r.unpackedShape.length>0?r.unpackedShape:r.shape).length,o=`_${e}`;t[o]=new I(this.getValueFromSingle(e,i,r.width,r.height,!1),[`shapeUtils.indicesToOffset${o}`,"coordinates.offsetToCoords","fragcolor.getColorAsFloat"]),o+="_T",t[o]=new I(this.getValueFromSingle(e,i,r.width,r.height,!0),[`shapeUtils.indicesToOffset${o}`,"coordinates.offsetToCoords","fragcolor.getColorAsFloat"])})),t}getValueFromSingle(t,e,n,r,i){let o=`_${t}`;return i&&(o+="_T"),`\n        float ${o}(int m[${e}]) {\n          int offset = indicesToOffset${o}(m);\n          vec2 coords = offsetToCoords(offset, ${n}, ${r});\n          float value = getColorAsFloat(${D(this.context.glContext.version).texture2D}(${t}, coords));\n          return value;\n        }\n        `}getPackedValueFrom(t,e,n,r,i){let o=`_${t}_Pack`;return i&&(o+="_T"),`\n        vec4 ${o}(int m[${e}]) {\n          int offset = indicesToOffset_${t}(m);\n          vec2 coords = offsetToCoords(offset, ${n}, ${r});\n          return ${D(this.context.glContext.version).texture2D}(${t}, coords);\n        }\n        `}}})),gr,nl=x((()=>{kt(),gr=class t extends mt{constructor(t){super(t)}getFunctions(){return{...this.encodeFloat32(),...this.decodeFloat32()}}getCustomTypes(){return{}}encodeFloat32(){return{encode:new I("highp vec4 encode(highp float f) {\n        return vec4(f, 0.0, 0.0, 0.0);\n      }\n        ")}}decodeFloat32(){return{decode:new I("highp float decode(highp vec4 rgba) {\n        return rgba.r;\n      }\n        ")}}encodeUint8(){let e=t.isLittleEndian()?"rgba.rgba=rgba.abgr;":"";return{encode:new I(`\n      highp vec4 encode(highp float f) {\n        highp float F = abs(f);\n        highp float Sign = step(0.0,-f);\n        highp float Exponent = floor(log2(F));\n        highp float Mantissa = (exp2(- Exponent) * F);\n        Exponent = floor(log2(F) + 127.0) + floor(log2(Mantissa));\n        highp vec4 rgba;\n        rgba[0] = 128.0 * Sign  + floor(Exponent*exp2(-1.0));\n    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t=new ArrayBuffer(4),e=new Uint32Array(t),n=new Uint8Array(t);if(e[0]=3735928559,239===n[0])return!0;if(222===n[0])return!1;throw new Error("unknown endianness")}}})),xr,ol=x((()=>{kt(),q(),xr=class extends mt{constructor(t){super(t)}getFunctions(){return{...this.setFragColor(),...this.getColorAsFloat()}}getCustomTypes(){return{}}setFragColor(){let t=D(this.context.glContext.version);return{setFragColor:new I(`\n        void setFragColor(float value) {\n            ${t.output} = encode(value);\n        }\n        `,["encoding.encode"])}}getColorAsFloat(){return{getColorAsFloat:new I("\n        float getColorAsFloat(vec4 color) {\n            return decode(color);\n        }\n        ",["encoding.decode"])}}}})),Tr,il=x((()=>{kt(),Tr=class t extends mt{constructor(t){super(t)}getFunctions(){return{...this.bcastIndex(),...this.bcastMatmulIndex(),...this.offsetToIndices(),...this.indicesToOffset(),...this.incrementIndices()}}getCustomTypes(){return{}}bcastIndex(){let t=this.context.outputTextureLayout.shape.length,e={};return this.context.programInfo.inputNames.forEach(((n,r)=>{let i=this.context.inputTextureLayouts[r].unpackedShape;if(i.length<=t){let r=i.length,o=t-r,s=`bcastIndices_${n}`,a="";for(let t=0;t<r;++t)a+=`\n          realIndices[${t}] = int( mod(float(bcastedIndices[${o+t}]), ${i[t]}.0) );\n          `;let u=`\n        void ${s} (int bcastedIndices[${t}], out int realIndices[${r}]) {\n          ${a}\n        }\n        `;e[s]=new I(u)}})),e}bcastMatmulIndex(){let t=this.context.outputTextureLayout.shape.length,e={};return this.context.programInfo.inputNames.forEach(((n,r)=>{let i=this.context.inputTextureLayouts[r].shape;if(!(i.length<2||i.length>t)){let r=i.length,o=t-r,s=`bcastMatmulIndices_${n}`,a="";for(let t=0;t<r-2;++t)a+=`\n          realIndices[${t}] = int( mod(float(bcastedIndices[${o+t}]), ${i[t]}.0) );\n          `;let u=`\n        void ${s}(int bcastedIndices[${t}], out int realIndices[${r}]) {\n          ${a}\n          realIndices[${r-1}] = bcastedIndices[${t-1}];\n          realIndices[${r-2}] = bcastedIndices[${t-2}];\n        }\n        `;e[s]=new I(u)}})),e}indicesToOffset(){let e={};return this.context.programInfo.inputNames.forEach(((n,r)=>{let i=this.context.inputTextureLayouts[r].shape,o=this.context.inputTextureLayouts[r].strides,s=i.length,a=`indicesToOffset_${n}`;e[a]=new I(t.indexToOffsetSingle(a,s,o)),a=`indicesToOffset_${n}_T`,e[a]=new I(t.indexToOffsetSingle(a,s,o.slice().reverse()))})),e}static indexToOffsetSingle(t,e,n){let r="";for(let t=e-1;t>=0;--t)r+=`\n        offset += indices[${t}] * ${n[t]};\n        `;return`\n      int ${t}(int indices[${e}]) {\n        int offset = 0;\n        ${r}\n        return offset;\n      }\n      `}offsetToIndices(){let e={};return this.context.programInfo.inputNames.forEach(((n,r)=>{let i=this.context.inputTextureLayouts[r].shape,o=this.context.inputTextureLayouts[r].strides,s=i.length,a=`offsetToIndices_${n}`;e[a]=new 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indices[i] = 0;\n          }\n        }\n        `;t[o]=new I(a)})),t}}})),vr,al=x((()=>{kt(),vr=class extends mt{constructor(t){super(t)}getCustomTypes(){return{}}getFunctions(){return{...this.binaryVecFunctions(),...this.copyVec(),...this.setVecItem(),...this.getVecItem()}}binaryVecFunctions(){let t=this.context.outputTextureLayout.shape.length,e={add:"+=",sub:"-=",mul:"*=",div:"/="},n={};for(let r in e){let i=`${r}Vec`,o="";for(let n=0;n<t;++n)o+=`\n          dest[${n}] ${e[r]} src[${n}];\n          `;let s=`\n        void ${i}(int src[${t}], out int dest[${t}]) {\n          ${o}\n        }\n        `;n[i]=new I(s)}return n}copyVec(){let t=this.context.outputTextureLayout.shape.length,e="";for(let n=0;n<t;++n)e+=`\n        dest[${n}] = src[${n}];\n        `;return{copyVec:new I(`\n      void copyVec(int src[${t}], out int dest[${t}]) {\n        ${e}\n      }\n      `)}}setVecItem(){let t=this.context.outputTextureLayout.shape.length,e=`\n        if(index < 0)\n            index =${t} + index;\n        if (index == 0)\n            m[0] = value;\n        `;for(let n=1;n<t-1;++n)e+=`\n        else if (index == ${n})\n            m[${n}] = value;\n            `;return e+=`\n        else\n            m[${t-1}] = value;\n        `,{setVecItem:new I(`\n      void setVecItem(out int m[${t}], int index, int value) {\n        ${e}\n      }\n        `)}}getVecItem(){let t=this.context.outputTextureLayout.shape.length,e=`\n        if(index < 0)\n            index = ${t} + index;\n        if (index == 0)\n            return m[0];\n      `;for(let n=1;n<t-1;++n)e+=`\n        else if (index == ${n})\n            return m[${n}];\n      `;return e+=`\n        else\n            return m[${t-1}];\n        `,{getVecItem:new I(`\n      int getVecItem(int m[${t}], int index) {\n        ${e}\n      }\n    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Error("duplicated attribute names")}}set(t,e,n){this._attributes.set(t,[n,e])}delete(t){this._attributes.delete(t)}getFloat(t,e){return this.get(t,"float",e)}getInt(t,e){return this.get(t,"int",e)}getString(t,e){return this.get(t,"string",e)}getTensor(t,e){return this.get(t,"tensor",e)}getFloats(t,e){return this.get(t,"floats",e)}getInts(t,e){return this.get(t,"ints",e)}getStrings(t,e){return this.get(t,"strings",e)}getTensors(t,e){return this.get(t,"tensors",e)}get(t,e,n){let r=this._attributes.get(t);if(void 0===r){if(void 0!==n)return n;throw new Error(`required attribute not found: ${t}`)}if(r[1]!==e)throw new Error(`type mismatch: expected ${e} but got ${r[1]}`);return r[0]}static getType(t){let e=t instanceof B.onnx.AttributeProto?t.type:t.type();switch(e){case B.onnx.AttributeProto.AttributeType.FLOAT:return"float";case B.onnx.AttributeProto.AttributeType.INT:return"int";case B.onnx.AttributeProto.AttributeType.STRING:return"string";case 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B.onnx.AttributeProto?Y.fromProto(n):Y.fromOrtTensor(n);if(e===B.onnx.AttributeProto.AttributeType.TENSORS){if(t instanceof B.onnx.AttributeProto)return n.map((t=>Y.fromProto(t)));if(t instanceof gt.Attribute)return n.map((t=>Y.fromOrtTensor(t)))}return e===B.onnx.AttributeProto.AttributeType.STRING&&t instanceof B.onnx.AttributeProto?Se(n):e===B.onnx.AttributeProto.AttributeType.STRINGS&&t instanceof B.onnx.AttributeProto?n.map(Se):n}static getValueNoCheck(t){return t instanceof B.onnx.AttributeProto?this.getValueNoCheckFromOnnxFormat(t):this.getValueNoCheckFromOrtFormat(t)}static getValueNoCheckFromOnnxFormat(t){switch(t.type){case B.onnx.AttributeProto.AttributeType.FLOAT:return t.f;case B.onnx.AttributeProto.AttributeType.INT:return t.i;case B.onnx.AttributeProto.AttributeType.STRING:return t.s;case B.onnx.AttributeProto.AttributeType.TENSOR:return t.t;case B.onnx.AttributeProto.AttributeType.GRAPH:return t.g;case B.onnx.AttributeProto.AttributeType.FLOATS:return t.floats;case B.onnx.AttributeProto.AttributeType.INTS:return t.ints;case B.onnx.AttributeProto.AttributeType.STRINGS:return t.strings;case B.onnx.AttributeProto.AttributeType.TENSORS:return t.tensors;case B.onnx.AttributeProto.AttributeType.GRAPHS:return t.graphs;default:throw new Error(`unsupported attribute type: ${B.onnx.AttributeProto.AttributeType[t.type]}`)}}static getValueNoCheckFromOrtFormat(t){switch(t.type()){case gt.AttributeType.FLOAT:return t.f();case gt.AttributeType.INT:return t.i();case gt.AttributeType.STRING:return t.s();case gt.AttributeType.TENSOR:return t.t();case gt.AttributeType.GRAPH:return t.g();case gt.AttributeType.FLOATS:return t.floatsArray();case gt.AttributeType.INTS:{let e=[];for(let n=0;n<t.intsLength();n++)e.push(t.ints(n));return e}case gt.AttributeType.STRINGS:{let e=[];for(let n=0;n<t.stringsLength();n++)e.push(t.strings(n));return e}case gt.AttributeType.TENSORS:{let e=[];for(let n=0;n<t.tensorsLength();n++)e.push(t.tensors(n));return e}default:throw new Error(`unsupported attribute type: ${gt.AttributeType[t.type()]}`)}}}})),Un,Pr,Wn,Dt,Er,Mn,Tl=x((()=>{xl(),Te(),Un=re(ae()),Zt(),z(),Pr=P.experimental.fbs,Wn={from:(t,e)=>new Mn(t,e)},Dt=class{constructor(t){this._from=void 0,this._to=[],this.tensor=void 0,this.type=void 0,t&&(this.type=et.tensorValueTypeFromProto(t.type.tensorType))}get from(){return this._from}get to(){return this._to}},Er=class{constructor(t,e){t instanceof Un.onnx.NodeProto?(this.name=t.name,this.opType=t.opType,this.attributes=new ke(t.attribute)):t instanceof Pr.Node&&(this.name=e??t.name(),this.opType=t.opType(),this.attributes=new ke(et.tensorAttributesFromORTFormat(t))),this.inputs=[],this.outputs=[],this.executeNode=!0}},Mn=class{constructor(t,e){if(!t)throw new TypeError("graph is empty");this.buildGraph(t),this.transformGraph(e),this.checkIsAcyclic()}getInputIndices(){return this._allInputIndices}getInputNames(){return this._allInputNames}getOutputIndices(){return 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r=this._nodes[n],i=t.node[n];if(!i.output)throw new Error(`missing output for node: ${i.name}`);for(let t of i.output){let o=e.get(t);if(typeof o>"u"&&(o=this._allData.push(new Dt)-1,e.set(t,o)),r.outputs.push(o),void 0!==this._allData[o]._from)throw new Error(`multiple nodes output to one data value: ${o}`);if(this._allData[o]._from=n,"Constant"===i.opType){if(!i.attribute||1!==i.attribute.length||!i.attribute[0].t)throw new Error("missing attributes or missing tensor value in attributes for this Constant operator");if(!i.output||1!==i.output.length)throw new Error("missing output or incorrect number of outputs for this Constant operator");r.outputs.pop(),r.executeNode=!1,this._allData[o]._from=-1,this._allData[o].tensor=Y.fromProto(i.attribute[0].t)}}}for(let n=0;n<this._nodes.length;n++){let r=this._nodes[n],i=t.node[n];if(!i.input)throw new Error(`missing input for node: ${i.name}`);for(let t of i.input){let o=e.get(t);if(typeof o>"u"){if(""===t&&(3===i.input.length||4===i.input.length)&&"Resize"===i.opType)continue;throw new Error(`unrecognized input '${t}' for node: ${i.name}`)}r.inputs.push(o),this._allData[o]._to.push(n)}}return!0}buildGraphFromOrtFormat(t){let e=new Map;this._allData=[],this._allInputIndices=[],this._allInputNames=[],this._allOutputIndices=[],this._allOutputNames=[],this._nodes=[];let n=new Map,r=[];for(let n=0;n<t.inputsLength();n++){let i=t.inputs(n);if(e.has(i))throw new Error(`duplicated input name: ${i}`);for(let n=0;n<t.nodeArgsLength();n++)if(t.nodeArgs(n)?.name()===i){let o=new Dt;if(t.nodeArgs(n)?.type()?.valueType()!==Pr.TypeInfoValue.tensor_type)throw new Error("Unexpected value type for the nodeArg.");let s=t.nodeArgs(n).type().value(new Pr.TensorTypeAndShape),a=et.tensorDataTypeFromProto(s.elemType()),u=s.shape(),l=[];for(let t=0;t<u.dimLength();t++)l.push(ft.longToNumber(u.dim(t).value().dimValue()));o.type={shape:{dims:l},tensorType:a};let p=this._allData.push(o)-1;e.set(i,p),r.push(i)}}for(let n=0;n<t.initializersLength();n++){let r=t.initializers(n),i=e.get(r.name());if(void 0===i){let t=new Dt,n=et.tensorDimsFromORTFormat(r),o=et.tensorDataTypeFromProto(r.dataType());t.type={shape:{dims:n},tensorType:o},i=this._allData.push(t)-1,e.set(r.name(),i)}this._allData[i]._from=-1,this._allData[i].tensor=Y.fromOrtTensor(r)}for(let t=0;t<this._allData.length;t++)this._allData[t].tensor||(this._allInputIndices.push(t),this._allInputNames.push(r[t]));for(let n=0;n<t.outputsLength();n++){let r=t.outputs(n);if(e.has(r))throw new Error(`duplicated output name: ${r}`);let i=this._allData.push(new Dt)-1;e.set(r,i),this._allOutputIndices.push(i),this._allOutputNames.push(r)}if(!t.nodes)throw new Error("missing information in graph: node");for(let e=0;e<t.nodesLength();e++){let r=t.nodes(e),i=r.name();if(!i)for(let t=0;i=`unnamed_${r.opType()}_${t}`,n.has(i);t++);if(n.has(i))throw new Error(`duplicated node name: ${i}`);let o=this._nodes.push(new Er(r,i))-1;n.set(i,o)}for(let n=0;n<this._nodes.length;n++){let r=this._nodes[n],i=t.nodes(n);if(null==i)throw new Error(`No node exists at index ${n}`);if(0===i?.outputsLength())throw new Error(`missing output for node: ${i.name}`);for(let t=0;t<i?.outputsLength();t++){let o=i?.outputs(t),s=e.get(o);if(typeof s>"u"&&(s=this._allData.push(new Dt)-1,e.set(o,s)),r.outputs.push(s),void 0!==this._allData[s]._from)throw new Error(`multiple nodes output to one data value: ${s}`);if(this._allData[s]._from=n,"Constant"===i.opType()){if(1!==i.attributesLength()||!i.attributes(0).t())throw new Error("missing attributes or missing tensor value in attributes for this Constant operator");if(1!==i.outputsLength())throw new Error("missing output or incorrect number of outputs for this Constant operator");r.outputs.pop(),r.executeNode=!1,this._allData[s]._from=-1,this._allData[s].tensor=Y.fromOrtTensor(i.attributes(0).t())}}}for(let n=0;n<this._nodes.length;n++){let r=this._nodes[n],i=t.nodes(n);if(0===i.inputsLength())throw new Error(`missing input for node: ${i.name}`);for(let t=0;t<i.inputsLength();t++){let o=i.inputs(t),s=e.get(o);if(typeof s>"u")throw new Error(`unrecognized input '${o}' for node: ${i.name()}`);r.inputs.push(s),this._allData[s]._to.push(n)}}}checkIsAcyclic(){let t=new Set;this._allInputIndices.forEach((e=>{this._allData[e]._to.forEach((e=>{t.add(e)}))}));let e=Array.from(t),n=new Array(this._nodes.length).fill("white");for(;e.length>0;){let t=e.pop();"gray"===n[t]?n[t]="black":(e.push(t),n[t]="gray",this._nodes[t].outputs.forEach((r=>{let i=this._allData[r];if(typeof i.tensor<"u")throw new Error("node outputs should not be initialized");if(i._from!==t)throw new Error("from property of the Value object doesn't match index of Node being processed");i._to.forEach((t=>{if("gray"===n[t])throw new Error("model graph is 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