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r},t.decodeDelimited=function(t){return t instanceof a||(t=new a(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")&&!l.isString(t.name))return"name: string expected";if(null!=t.refAttrName&&t.hasOwnProperty("refAttrName")&&!l.isString(t.refAttrName))return"refAttrName: string expected";if(null!=t.docString&&t.hasOwnProperty("docString")&&!l.isString(t.docString))return"docString: string expected";if(null!=t.type&&t.hasOwnProperty("type"))switch(t.type){default:return"type: enum value expected";case 0:case 1:case 2:case 3:case 4:case 5:case 6:case 7:case 8:case 9:case 10:}if(null!=t.f&&t.hasOwnProperty("f")&&"number"!=typeof t.f)return"f: number expected";if(null!=t.i&&t.hasOwnProperty("i")&&!(l.isInteger(t.i)||t.i&&l.isInteger(t.i.low)&&l.isInteger(t.i.high)))return"i: integer|Long expected";if(null!=t.s&&t.hasOwnProperty("s")&&!(t.s&&"number"==typeof t.s.length||l.isString(t.s)))return"s: buffer expected";if(null!=t.t&&t.hasOwnProperty("t")&&(n=c.onnx.TensorProto.verify(t.t)))return"t."+n;if(null!=t.g&&t.hasOwnProperty("g")&&(n=c.onnx.GraphProto.verify(t.g)))return"g."+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(!(l.isInteger(t.ints[e])||t.ints[e]&&l.isInteger(t.ints[e].low)&&l.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||l.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=c.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){var n;if(n=c.onnx.GraphProto.verify(t.graphs[e]))return"graphs."+n}}return null},t.fromObject=function(t){if(t instanceof c.onnx.AttributeProto)return t;var e=new c.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){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"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}if(null!=t.f&&(e.f=Number(t.f)),null!=t.i&&(l.Long?(e.i=l.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 l.LongBits(t.i.low>>>0,t.i.high>>>0).toNumber())),null!=t.s&&("string"==typeof t.s?l.base64.decode(t.s,e.s=l.newBuffer(l.base64.length(t.s)),0):t.s.length&&(e.s=t.s)),null!=t.t){if("object"!=typeof t.t)throw TypeError(".onnx.AttributeProto.t: object expected");e.t=c.onnx.TensorProto.fromObject(t.t)}if(null!=t.g){if("object"!=typeof t.g)throw TypeError(".onnx.AttributeProto.g: object expected");e.g=c.onnx.GraphProto.fromObject(t.g)}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)l.Long?(e.ints[n]=l.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 l.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]?l.base64.decode(t.strings[n],e.strings[n]=l.newBuffer(l.base64.length(t.strings[n])),0):t.strings[n].length&&(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]=c.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]=c.onnx.GraphProto.fromObject(t.graphs[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=[]),e.defaults){if(n.name="",n.f=0,l.Long){var r=new l.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=l.newBuffer(n.s))),n.t=null,n.g=null,n.docString="",n.type=e.enums===String?"UNDEFINED":0,n.refAttrName=""}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?l.Long.prototype.toString.call(t.i):e.longs===Number?new l.LongBits(t.i.low>>>0,t.i.high>>>0).toNumber():t.i),null!=t.s&&t.hasOwnProperty("s")&&(n.s=e.bytes===String?l.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=c.onnx.TensorProto.toObject(t.t,e)),null!=t.g&&t.hasOwnProperty("g")&&(n.g=c.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?l.Long.prototype.toString.call(t.ints[i]):e.longs===Number?new l.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?l.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]=c.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]=c.onnx.GraphProto.toObject(t.graphs[i],e);return null!=t.docString&&t.hasOwnProperty("docString")&&(n.docString=t.docString),null!=t.type&&t.hasOwnProperty("type")&&(n.type=e.enums===String?c.onnx.AttributeProto.AttributeType[t.type]:t.type),null!=t.refAttrName&&t.hasOwnProperty("refAttrName")&&(n.refAttrName=t.refAttrName),n},t.prototype.toJSON=function(){return this.constructor.toObject(this,o.util.toJSONOptions)},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[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}(),s.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=u.create()),null!=t.name&&t.hasOwnProperty("name")&&e.uint32(10).string(t.name),null!=t.type&&t.hasOwnProperty("type")&&c.onnx.TypeProto.encode(t.type,e.uint32(18).fork()).ldelim(),null!=t.docString&&t.hasOwnProperty("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 a||(t=a.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new c.onnx.ValueInfoProto;t.pos<n;){var i=t.uint32();switch(i>>>3){case 1:r.name=t.string();break;case 2:r.type=c.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 a||(t=new a(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")&&!l.isString(t.name))return"name: string expected";if(null!=t.type&&t.hasOwnProperty("type")){var e=c.onnx.TypeProto.verify(t.type);if(e)return"type."+e}return null!=t.docString&&t.hasOwnProperty("docString")&&!l.isString(t.docString)?"docString: string expected":null},t.fromObject=function(t){if(t instanceof c.onnx.ValueInfoProto)return t;var e=new c.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=c.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=c.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}(),s.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=l.emptyArray,t.prototype.output=l.emptyArray,t.prototype.name="",t.prototype.opType="",t.prototype.domain="",t.prototype.attribute=l.emptyArray,t.prototype.docString="",t.create=function(e){return new t(e)},t.encode=function(t,e){if(e||(e=u.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&&t.hasOwnProperty("name")&&e.uint32(26).string(t.name),null!=t.opType&&t.hasOwnProperty("opType")&&e.uint32(34).string(t.opType),null!=t.attribute&&t.attribute.length)for(n=0;n<t.attribute.length;++n)c.onnx.AttributeProto.encode(t.attribute[n],e.uint32(42).fork()).ldelim();return null!=t.docString&&t.hasOwnProperty("docString")&&e.uint32(50).string(t.docString),null!=t.domain&&t.hasOwnProperty("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 a||(t=a.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new c.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(c.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 a||(t=new a(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(!l.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(!l.isString(t.output[e]))return"output: string[] expected"}if(null!=t.name&&t.hasOwnProperty("name")&&!l.isString(t.name))return"name: string expected";if(null!=t.opType&&t.hasOwnProperty("opType")&&!l.isString(t.opType))return"opType: string expected";if(null!=t.domain&&t.hasOwnProperty("domain")&&!l.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=c.onnx.AttributeProto.verify(t.attribute[e]);if(n)return"attribute."+n}}return null!=t.docString&&t.hasOwnProperty("docString")&&!l.isString(t.docString)?"docString: string expected":null},t.fromObject=function(t){if(t instanceof c.onnx.NodeProto)return t;var e=new c.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]=c.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]=c.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}(),s.ModelProto=function(){function t(t){if(this.opsetImport=[],this.metadataProps=[],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.irVersion=l.Long?l.Long.fromBits(0,0,!1):0,t.prototype.opsetImport=l.emptyArray,t.prototype.producerName="",t.prototype.producerVersion="",t.prototype.domain="",t.prototype.modelVersion=l.Long?l.Long.fromBits(0,0,!1):0,t.prototype.docString="",t.prototype.graph=null,t.prototype.metadataProps=l.emptyArray,t.create=function(e){return new t(e)},t.encode=function(t,e){if(e||(e=u.create()),null!=t.irVersion&&t.hasOwnProperty("irVersion")&&e.uint32(8).int64(t.irVersion),null!=t.producerName&&t.hasOwnProperty("producerName")&&e.uint32(18).string(t.producerName),null!=t.producerVersion&&t.hasOwnProperty("producerVersion")&&e.uint32(26).string(t.producerVersion),null!=t.domain&&t.hasOwnProperty("domain")&&e.uint32(34).string(t.domain),null!=t.modelVersion&&t.hasOwnProperty("modelVersion")&&e.uint32(40).int64(t.modelVersion),null!=t.docString&&t.hasOwnProperty("docString")&&e.uint32(50).string(t.docString),null!=t.graph&&t.hasOwnProperty("graph")&&c.onnx.GraphProto.encode(t.graph,e.uint32(58).fork()).ldelim(),null!=t.opsetImport&&t.opsetImport.length)for(var n=0;n<t.opsetImport.length;++n)c.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)c.onnx.StringStringEntryProto.encode(t.metadataProps[n],e.uint32(114).fork()).ldelim();return e},t.encodeDelimited=function(t,e){return this.encode(t,e).ldelim()},t.decode=function(t,e){t instanceof a||(t=a.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new c.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(c.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=c.onnx.GraphProto.decode(t,t.uint32());break;case 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i=0;i<t.opsetImport.length;++i)n.opsetImport[i]=c.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]=c.onnx.StringStringEntryProto.toObject(t.metadataProps[i],e);return n},t.prototype.toJSON=function(){return this.constructor.toObject(this,o.util.toJSONOptions)},t}(),s.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=u.create()),null!=t.key&&t.hasOwnProperty("key")&&e.uint32(10).string(t.key),null!=t.value&&t.hasOwnProperty("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 a||(t=a.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new c.onnx.StringStringEntryProto;t.pos<n;){var 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r=0;r<t.quantParameterTensorNames.length;++r)n.quantParameterTensorNames[r]=c.onnx.StringStringEntryProto.toObject(t.quantParameterTensorNames[r],e)}return n},t.prototype.toJSON=function(){return this.constructor.toObject(this,o.util.toJSONOptions)},t}(),s.GraphProto=function(){function t(t){if(this.node=[],this.initializer=[],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=l.emptyArray,t.prototype.name="",t.prototype.initializer=l.emptyArray,t.prototype.docString="",t.prototype.input=l.emptyArray,t.prototype.output=l.emptyArray,t.prototype.valueInfo=l.emptyArray,t.prototype.quantizationAnnotation=l.emptyArray,t.create=function(e){return new t(e)},t.encode=function(t,e){if(e||(e=u.create()),null!=t.node&&t.node.length)for(var 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e},t.encodeDelimited=function(t,e){return this.encode(t,e).ldelim()},t.decode=function(t,e){t instanceof a||(t=a.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new c.onnx.GraphProto;t.pos<n;){var i=t.uint32();switch(i>>>3){case 1:r.node&&r.node.length||(r.node=[]),r.node.push(c.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(c.onnx.TensorProto.decode(t,t.uint32()));break;case 10:r.docString=t.string();break;case 11:r.input&&r.input.length||(r.input=[]),r.input.push(c.onnx.ValueInfoProto.decode(t,t.uint32()));break;case 12:r.output&&r.output.length||(r.output=[]),r.output.push(c.onnx.ValueInfoProto.decode(t,t.uint32()));break;case 13:r.valueInfo&&r.valueInfo.length||(r.valueInfo=[]),r.valueInfo.push(c.onnx.ValueInfoProto.decode(t,t.uint32()));break;case 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instanceof c.onnx.GraphProto)return t;var e=new c.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 expected");e.node[n]=c.onnx.NodeProto.fromObject(t.node[n])}}if(null!=t.name&&(e.name=String(t.name)),t.initializer){if(!Array.isArray(t.initializer))throw TypeError(".onnx.GraphProto.initializer: array expected");for(e.initializer=[],n=0;n<t.initializer.length;++n){if("object"!=typeof t.initializer[n])throw TypeError(".onnx.GraphProto.initializer: object expected");e.initializer[n]=c.onnx.TensorProto.fromObject(t.initializer[n])}}if(null!=t.docString&&(e.docString=String(t.docString)),t.input){if(!Array.isArray(t.input))throw TypeError(".onnx.GraphProto.input: array expected");for(e.input=[],n=0;n<t.input.length;++n){if("object"!=typeof t.input[n])throw TypeError(".onnx.GraphProto.input: object 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TypeError(".onnx.GraphProto.quantizationAnnotation: object expected");e.quantizationAnnotation[n]=c.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=[]),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]=c.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]=c.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]=c.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]=c.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]=c.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]=c.onnx.TensorAnnotation.toObject(t.quantizationAnnotation[r],e);return n},t.prototype.toJSON=function(){return this.constructor.toObject(this,o.util.toJSONOptions)},t}(),s.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=l.emptyArray,t.prototype.dataType=0,t.prototype.segment=null,t.prototype.floatData=l.emptyArray,t.prototype.int32Data=l.emptyArray,t.prototype.stringData=l.emptyArray,t.prototype.int64Data=l.emptyArray,t.prototype.name="",t.prototype.docString="",t.prototype.rawData=l.newBuffer([]),t.prototype.externalData=l.emptyArray,t.prototype.dataLocation=0,t.prototype.doubleData=l.emptyArray,t.prototype.uint64Data=l.emptyArray,t.create=function(e){return new t(e)},t.encode=function(t,e){if(e||(e=u.create()),null!=t.dims&&t.dims.length){e.uint32(10).fork();for(var 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null!=t.dataLocation&&t.hasOwnProperty("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 a||(t=a.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new c.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 s=t.uint32()+t.pos;t.pos<s;)r.dims.push(t.int64());else r.dims.push(t.int64());break;case 2:r.dataType=t.int32();break;case 3:r.segment=c.onnx.TensorProto.Segment.decode(t,t.uint32());break;case 4:if(r.floatData&&r.floatData.length||(r.floatData=[]),2==(7&i))for(s=t.uint32()+t.pos;t.pos<s;)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(s=t.uint32()+t.pos;t.pos<s;)r.int32Data.push(t.int32());else r.int32Data.push(t.int32());break;case 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expected";for(e=0;e<t.int32Data.length;++e)if(!l.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||l.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(!(l.isInteger(t.int64Data[e])||t.int64Data[e]&&l.isInteger(t.int64Data[e].low)&&l.isInteger(t.int64Data[e].high)))return"int64Data: integer|Long[] expected"}if(null!=t.name&&t.hasOwnProperty("name")&&!l.isString(t.name))return"name: string expected";if(null!=t.docString&&t.hasOwnProperty("docString")&&!l.isString(t.docString))return"docString: string expected";if(null!=t.rawData&&t.hasOwnProperty("rawData")&&!(t.rawData&&"number"==typeof t.rawData.length||l.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=c.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 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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]?l.base64.decode(t.stringData[n],e.stringData[n]=l.newBuffer(l.base64.length(t.stringData[n])),0):t.stringData[n].length&&(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)l.Long?(e.int64Data[n]=l.Long.fromValue(t.int64Data[n])).unsigned=!1:"string"==typeof t.int64Data[n]?e.int64Data[n]=parseInt(t.int64Data[n],10):"number"==typeof t.int64Data[n]?e.int64Data[n]=t.int64Data[n]:"object"==typeof t.int64Data[n]&&(e.int64Data[n]=new l.LongBits(t.int64Data[n].low>>>0,t.int64Data[n].high>>>0).toNumber())}if(null!=t.name&&(e.name=String(t.name)),null!=t.docString&&(e.docString=String(t.docString)),null!=t.rawData&&("string"==typeof t.rawData?l.base64.decode(t.rawData,e.rawData=l.newBuffer(l.base64.length(t.rawData)),0):t.rawData.length&&(e.rawData=t.rawData)),t.externalData){if(!Array.isArray(t.externalData))throw TypeError(".onnx.TensorProto.externalData: array expected");for(e.externalData=[],n=0;n<t.externalData.length;++n){if("object"!=typeof t.externalData[n])throw TypeError(".onnx.TensorProto.externalData: object expected");e.externalData[n]=c.onnx.StringStringEntryProto.fromObject(t.externalData[n])}}switch(t.dataLocation){case"DEFAULT":case 0:e.dataLocation=0;break;case"EXTERNAL":case 1:e.dataLocation=1}if(t.doubleData){if(!Array.isArray(t.doubleData))throw TypeError(".onnx.TensorProto.doubleData: array expected");for(e.doubleData=[],n=0;n<t.doubleData.length;++n)e.doubleData[n]=Number(t.doubleData[n])}if(t.uint64Data){if(!Array.isArray(t.uint64Data))throw TypeError(".onnx.TensorProto.uint64Data: array expected");for(e.uint64Data=[],n=0;n<t.uint64Data.length;++n)l.Long?(e.uint64Data[n]=l.Long.fromValue(t.uint64Data[n])).unsigned=!0:"string"==typeof t.uint64Data[n]?e.uint64Data[n]=parseInt(t.uint64Data[n],10):"number"==typeof t.uint64Data[n]?e.uint64Data[n]=t.uint64Data[n]:"object"==typeof t.uint64Data[n]&&(e.uint64Data[n]=new l.LongBits(t.uint64Data[n].low>>>0,t.uint64Data[n].high>>>0).toNumber(!0))}return e},t.toObject=function(t,e){e||(e={});var n={};if((e.arrays||e.defaults)&&(n.dims=[],n.floatData=[],n.int32Data=[],n.stringData=[],n.int64Data=[],n.doubleData=[],n.uint64Data=[],n.externalData=[]),e.defaults&&(n.dataType=0,n.segment=null,n.name="",e.bytes===String?n.rawData="":(n.rawData=[],e.bytes!==Array&&(n.rawData=l.newBuffer(n.rawData))),n.docString="",n.dataLocation=e.enums===String?"DEFAULT":0),t.dims&&t.dims.length){n.dims=[];for(var r=0;r<t.dims.length;++r)"number"==typeof t.dims[r]?n.dims[r]=e.longs===String?String(t.dims[r]):t.dims[r]:n.dims[r]=e.longs===String?l.Long.prototype.toString.call(t.dims[r]):e.longs===Number?new l.LongBits(t.dims[r].low>>>0,t.dims[r].high>>>0).toNumber():t.dims[r]}if(null!=t.dataType&&t.hasOwnProperty("dataType")&&(n.dataType=t.dataType),null!=t.segment&&t.hasOwnProperty("segment")&&(n.segment=c.onnx.TensorProto.Segment.toObject(t.segment,e)),t.floatData&&t.floatData.length)for(n.floatData=[],r=0;r<t.floatData.length;++r)n.floatData[r]=e.json&&!isFinite(t.floatData[r])?String(t.floatData[r]):t.floatData[r];if(t.int32Data&&t.int32Data.length)for(n.int32Data=[],r=0;r<t.int32Data.length;++r)n.int32Data[r]=t.int32Data[r];if(t.stringData&&t.stringData.length)for(n.stringData=[],r=0;r<t.stringData.length;++r)n.stringData[r]=e.bytes===String?l.base64.encode(t.stringData[r],0,t.stringData[r].length):e.bytes===Array?Array.prototype.slice.call(t.stringData[r]):t.stringData[r];if(t.int64Data&&t.int64Data.length)for(n.int64Data=[],r=0;r<t.int64Data.length;++r)"number"==typeof t.int64Data[r]?n.int64Data[r]=e.longs===String?String(t.int64Data[r]):t.int64Data[r]:n.int64Data[r]=e.longs===String?l.Long.prototype.toString.call(t.int64Data[r]):e.longs===Number?new l.LongBits(t.int64Data[r].low>>>0,t.int64Data[r].high>>>0).toNumber():t.int64Data[r];if(null!=t.name&&t.hasOwnProperty("name")&&(n.name=t.name),null!=t.rawData&&t.hasOwnProperty("rawData")&&(n.rawData=e.bytes===String?l.base64.encode(t.rawData,0,t.rawData.length):e.bytes===Array?Array.prototype.slice.call(t.rawData):t.rawData),t.doubleData&&t.doubleData.length)for(n.doubleData=[],r=0;r<t.doubleData.length;++r)n.doubleData[r]=e.json&&!isFinite(t.doubleData[r])?String(t.doubleData[r]):t.doubleData[r];if(t.uint64Data&&t.uint64Data.length)for(n.uint64Data=[],r=0;r<t.uint64Data.length;++r)"number"==typeof t.uint64Data[r]?n.uint64Data[r]=e.longs===String?String(t.uint64Data[r]):t.uint64Data[r]:n.uint64Data[r]=e.longs===String?l.Long.prototype.toString.call(t.uint64Data[r]):e.longs===Number?new l.LongBits(t.uint64Data[r].low>>>0,t.uint64Data[r].high>>>0).toNumber(!0):t.uint64Data[r];if(null!=t.docString&&t.hasOwnProperty("docString")&&(n.docString=t.docString),t.externalData&&t.externalData.length)for(n.externalData=[],r=0;r<t.externalData.length;++r)n.externalData[r]=c.onnx.StringStringEntryProto.toObject(t.externalData[r],e);return null!=t.dataLocation&&t.hasOwnProperty("dataLocation")&&(n.dataLocation=e.enums===String?c.onnx.TensorProto.DataLocation[t.dataLocation]:t.dataLocation),n},t.prototype.toJSON=function(){return this.constructor.toObject(this,o.util.toJSONOptions)},t.DataType=function(){var t={},e=Object.create(t);return e[t[0]="UNDEFINED"]=0,e[t[1]="FLOAT"]=1,e[t[2]="UINT8"]=2,e[t[3]="INT8"]=3,e[t[4]="UINT16"]=4,e[t[5]="INT16"]=5,e[t[6]="INT32"]=6,e[t[7]="INT64"]=7,e[t[8]="STRING"]=8,e[t[9]="BOOL"]=9,e[t[10]="FLOAT16"]=10,e[t[11]="DOUBLE"]=11,e[t[12]="UINT32"]=12,e[t[13]="UINT64"]=13,e[t[14]="COMPLEX64"]=14,e[t[15]="COMPLEX128"]=15,e[t[16]="BFLOAT16"]=16,e}(),t.Segment=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.begin=l.Long?l.Long.fromBits(0,0,!1):0,t.prototype.end=l.Long?l.Long.fromBits(0,0,!1):0,t.create=function(e){return new t(e)},t.encode=function(t,e){return e||(e=u.create()),null!=t.begin&&t.hasOwnProperty("begin")&&e.uint32(8).int64(t.begin),null!=t.end&&t.hasOwnProperty("end")&&e.uint32(16).int64(t.end),e},t.encodeDelimited=function(t,e){return this.encode(t,e).ldelim()},t.decode=function(t,e){t instanceof a||(t=a.create(t));for(var n=void 0===e?t.len:t.pos+e,r=new c.onnx.TensorProto.Segment;t.pos<n;){var i=t.uint32();switch(i>>>3){case 1:r.begin=t.int64();break;case 2:r.end=t.int64();break;default:t.skipType(7&i)}}return r},t.decodeDelimited=function(t){return t instanceof a||(t=new a(t)),this.decode(t,t.uint32())},t.verify=function(t){return"object"!=typeof t||null===t?"object expected":null!=t.begin&&t.hasOwnProperty("begin")&&!(l.isInteger(t.begin)||t.begin&&l.isInteger(t.begin.low)&&l.isInteger(t.begin.high))?"begin: integer|Long expected":null!=t.end&&t.hasOwnProperty("end")&&!(l.isInteger(t.end)||t.end&&l.isInteger(t.end.low)&&l.isInteger(t.end.high))?"end: integer|Long expected":null},t.fromObject=function(t){if(t instanceof c.onnx.TensorProto.Segment)return t;var e=new c.onnx.TensorProto.Segment;return null!=t.begin&&(l.Long?(e.begin=l.Long.fromValue(t.begin)).unsigned=!1:"string"==typeof t.begin?e.begin=parseInt(t.begin,10):"number"==typeof t.begin?e.begin=t.begin:"object"==typeof t.begin&&(e.begin=new 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Object.assign(Object.assign(Object.assign(Object.assign(Object.assign(Object.assign(Object.assign({},this.offsetToCoords()),this.coordsToOffset()),this.toVec()),this.valueFrom()),this.getCommonUtilFuncs()),this.getInputsSamplingSnippets()),this.getOutputSamplingSnippet())}getCustomTypes(){return{}}offsetToCoords(){return{offsetToCoords:new i.GlslLibRoutine("\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.GlslLibRoutine("\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(){const t=this.context.outputTextureLayout;return t.isPacked?this.getPackedOutputSamplingSnippet(t):this.getUnpackedOutputSamplingSnippet(t)}getPackedOutputSamplingSnippet(t){const e=t.unpackedShape,n=[t.width,t.height],r={},o="getOutputCoords";switch(e.length){case 0:r[o]=this.getOutputScalarCoords();break;case 1:r[o]=this.getOutputPacked1DCoords(e,n);break;case 2:r[o]=this.getOutputPacked2DCoords(e,n);break;case 3:r[o]=this.getOutputPacked3DCoords(e,n);break;default:r[o]=this.getOutputPackedNDCoords(e,n)}const a=`\n void setOutput(vec4 val) {\n ${(0,s.getGlsl)(this.context.glContext.version).output} = val;\n }\n `;return r.floatTextureSetRGBA=new i.GlslLibRoutine(a),r}getUnpackedOutputSamplingSnippet(t){const e=t.unpackedShape,n=[t.width,t.height],r={},o="getOutputCoords";switch(e.length){case 0:r[o]=this.getOutputScalarCoords();break;case 1:r[o]=this.getOutputUnpacked1DCoords(e,n);break;case 2:r[o]=this.getOutputUnpacked2DCoords(e,n);break;case 3:r[o]=this.getOutputUnpacked3DCoords(e,n);break;case 4:r[o]=this.getOutputUnpacked4DCoords(e,n);break;case 5:r[o]=this.getOutputUnpacked5DCoords(e,n);break;case 6:r[o]=this.getOutputUnpacked6DCoords(e,n);break;default:throw new Error(`Unsupported output dimensionality: ${e.length}`)}const a=`\n void setOutput(float val) {\n ${(0,s.getGlsl)(this.context.glContext.version).output} = vec4(val, 0, 0, 0);\n }\n `;return r.floatTextureSetR=new i.GlslLibRoutine(a),r}getOutputScalarCoords(){return new i.GlslLibRoutine("\n int getOutputCoords() {\n return 0;\n }\n ")}getOutputPacked1DCoords(t,e){const n=e;let r="";return 1===n[0]?(r=`\n int getOutputCoords() {\n return 2 * int(TexCoords.y * ${n[1]}.0);\n }\n `,new i.GlslLibRoutine(r)):1===n[1]?(r=`\n int getOutputCoords() {\n return 2 * int(TexCoords.x * ${n[0]}.0);\n }\n `,new i.GlslLibRoutine(r)):(r=`\n int getOutputCoords() {\n ivec2 resTexRC = ivec2(TexCoords.xy *\n vec2(${n[0]}, ${n[1]}));\n return 2 * (resTexRC.y * ${n[0]} + resTexRC.x);\n }\n `,new i.GlslLibRoutine(r))}getOutputPacked2DCoords(t,e){let n="";if(r.ArrayUtil.arraysEqual(t,e))return n=`\n ivec2 getOutputCoords() {\n return 2 * ivec2(TexCoords.xy * vec2(${e[0]}, ${e[1]}));\n }\n `,new i.GlslLibRoutine(n);const s=e,o=Math.ceil(t[1]/2);return n=`\n ivec2 getOutputCoords() {\n ivec2 resTexRC = ivec2(TexCoords.xy *\n vec2(${s[0]}, ${s[1]}));\n\n int index = resTexRC.y * ${s[0]} + resTexRC.x;\n\n // reverse r and c order for packed texture\n int r = imod(index, ${o}) * 2;\n int c = 2 * (index / ${o});\n\n return ivec2(r, c);\n }\n `,new i.GlslLibRoutine(n)}getOutputPacked3DCoords(t,e){const n=[e[0],e[1]],r=Math.ceil(t[2]/2),s=r*Math.ceil(t[1]/2),o=`\n ivec3 getOutputCoords() {\n ivec2 resTexRC = ivec2(TexCoords.xy *\n vec2(${n[0]}, ${n[1]}));\n int index = resTexRC.y * ${n[0]} + resTexRC.x;\n\n int b = index / ${s};\n index -= b * ${s};\n\n // reverse r and c order for packed texture\n int r = imod(index, ${r}) * 2;\n int c = 2 * (index / ${r});\n\n return ivec3(b, r, c);\n }\n `;return new i.GlslLibRoutine(o)}getOutputPackedNDCoords(t,e){const n=[e[0],e[1]],r=Math.ceil(t[t.length-1]/2),s=r*Math.ceil(t[t.length-2]/2);let o=s,a="",u="b, r, c";for(let e=2;e<t.length-1;e++)o*=t[t.length-e-1],a=`\n int b${e} = index / ${o};\n index -= b${e} * ${o};\n `+a,u=`b${e}, `+u;const l=`\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 ${a}\n\n int b = index / ${s};\n index -= b * ${s};\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}(${u});\n }\n `;return new i.GlslLibRoutine(l)}getOutputUnpacked1DCoords(t,e){const n=`\n int getOutputCoords() {\n ivec2 resTexRC = ivec2(TexCoords.xy *\n vec2(${e[0]}, ${e[1]}));\n return resTexRC.y * ${e[0]} + resTexRC.x;\n }\n `;return new i.GlslLibRoutine(n)}getOutputUnpacked2DCoords(t,e){const n=`\n ivec2 getOutputCoords() {\n ivec2 resTexRC = ivec2(TexCoords.xy *\n vec2(${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.GlslLibRoutine(n)}getOutputUnpacked3DCoords(t,e){let n="";const r=t.length;let s=null;r<2&&(s=[]),s=new Array(r-1),s[r-2]=t[r-1];for(let e=r-3;e>=0;--e)s[e]=s[e+1]*t[e+1];const o=["r","c","d"],a=s.map(((t,e)=>`int ${o[e]} = index / ${t}; ${e===s.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 ${a}\n return ivec3(r, c, d);\n }\n `,new i.GlslLibRoutine(n)}getOutputUnpacked4DCoords(t,e){let n="";const r=t.length;let s=null;r<2&&(s=[]),s=new Array(r-1),s[r-2]=t[r-1];for(let e=r-3;e>=0;--e)s[e]=s[e+1]*t[e+1];const o=["r","c","d","d2"],a=s.map(((t,e)=>`int ${o[e]} = index / ${t}; ${e===s.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 ${a}\n return ivec4(r, c, d, d2);\n }\n `,new i.GlslLibRoutine(n)}getOutputUnpacked5DCoords(t,e){let n="";const r=t.length;let s=null;r<2&&(s=[]),s=new Array(r-1),s[r-2]=t[r-1];for(let e=r-3;e>=0;--e)s[e]=s[e+1]*t[e+1];const o=["r","c","d","d2","d3"],a=s.map(((t,e)=>`int ${o[e]} = index / ${t}; ${e===s.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 ${a}\n return ivec5(r, c, d, d2, d3);\n }\n `,new i.GlslLibRoutine(n)}getOutputUnpacked6DCoords(t,e){let n="";const r=t.length;let s=null;r<2&&(s=[]),s=new Array(r-1),s[r-2]=t[r-1];for(let e=r-3;e>=0;--e)s[e]=s[e+1]*t[e+1];const o=["r","c","d","d2","d3","d4"],a=s.map(((t,e)=>`int ${o[e]} = index / ${t}; ${e===s.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 ${a}\n return ivec6(r, c, d, d2, d3, d4);\n }\n `,new i.GlslLibRoutine(n)}getCommonUtilFuncs(){const t={};let e="uvFromFlat";t[e]=new i.GlslLibRoutine("\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.GlslLibRoutine("\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.GlslLibRoutine("\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.GlslLibRoutine("\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";const n=(0,s.getGlsl)(this.context.glContext.version);return t[e]=new i.GlslLibRoutine(`\n float sampleTexture(sampler2D textureSampler, vec2 uv) {\n return ${n.texture2D}(textureSampler, uv).r;\n }`),t}getInputsSamplingSnippets(){const t={},e=this.context.outputTextureLayout;return this.context.programInfo.inputNames.forEach(((n,r)=>{const i=this.context.inputTextureLayouts[r],s=(0,a.generateShaderFuncNameFromInputSamplerName)(n);i.isPacked?t[s]=this.getPackedSamplerFromInput(s,n,i):t[s]=this.getUnpackedSamplerFromInput(s,n,i);const o=(0,a.generateShaderFuncNameFromInputSamplerNameAtOutCoords)(n);i.unpackedShape.length<=e.unpackedShape.length&&(i.isPacked?t[o]=this.getPackedSamplerAtOutputCoords(o,i,e,n):t[o]=this.getUnpackedSamplerAtOutputCoords(o,i,e,n))})),t}getPackedSamplerAtOutputCoords(t,e,n,s){const o=e.unpackedShape,u=n.unpackedShape,l=s,c=(0,a.generateShaderFuncNameFromInputSamplerName)(l),d=o.length,h=u.length,p=r.BroadcastUtil.getBroadcastDims(o,u),f=(0,a.getCoordsDataType)(h),g=h-d;let m;const _=(0,a.getGlChannels)();m=0===d?"":h<2&&p.length>=1?"coords = 0;":p.map((t=>`coords.${_[t+g]} = 0;`)).join("\n");let b="";b=h<2&&d>0?"coords":o.map(((t,e)=>`coords.${_[e+g]}`)).join(", ");let y="return outputValue;";const w=1===r.ShapeUtil.size(o),v=1===r.ShapeUtil.size(u);if(1!==d||w||v){if(w&&!v)y=1===h?"\n return vec4(outputValue.x, outputValue.x, 0., 0.);\n ":"\n return vec4(outputValue.x);\n ";else if(p.length){const t=d-2,e=d-1;p.indexOf(t)>-1&&p.indexOf(e)>-1?y="return vec4(outputValue.x);":p.indexOf(t)>-1?y="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":p.indexOf(e)>-1&&(y="return vec4(outputValue.xx, outputValue.zz);")}}else y="\n return vec4(outputValue.xy, outputValue.xy);\n ";const x=`\n vec4 ${t}() {\n ${f} coords = getOutputCoords();\n \n int lastDim = coords.${_[h-1]};\n coords.${_[h-1]} = coords.${_[h-2]};\n coords.${_[h-2]} = lastDim;\n \n ${m}\n vec4 outputValue = ${c}(${b});\n ${y}\n }\n `;return new i.GlslLibRoutine(x,["coordinates.getOutputCoords"])}getUnpackedSamplerAtOutputCoords(t,e,n,s){const o=[n.width,n.height],u=[e.width,e.height],l=e.unpackedShape.length,c=n.unpackedShape.length,d=e.unpackedShape,h=n.unpackedShape,p=(0,a.generateShaderFuncNameFromInputSamplerName)(s);if(l===c&&r.ArrayUtil.arraysEqual(u,o)){const e=`\n float ${t}() {\n return sampleTexture(${s}, TexCoords);\n }\n `;return new i.GlslLibRoutine(e,["coordinates.sampleTexture"])}const f=(0,a.getCoordsDataType)(c),g=r.BroadcastUtil.getBroadcastDims(d,h),m=c-l;let _;const b=(0,a.getGlChannels)();_=0===l?"":c<2&&g.length>=1?"coords = 0;":g.map((t=>`coords.${b[t+m]} = 0;`)).join("\n");let y="";y=c<2&&l>0?"coords":e.unpackedShape.map(((t,e)=>`coords.${b[e+m]}`)).join(", ");const w=`\n float ${t}() {\n ${f} coords = getOutputCoords();\n ${_}\n return ${p}(${y});\n }\n `;return new i.GlslLibRoutine(w,["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){const 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){const n=`\n vec4 ${t}() {\n return ${(0,s.getGlsl)(this.context.glContext.version).texture2D}(${e}, halfCR);\n }\n `;return new i.GlslLibRoutine(n)}getPackedSampler1D(t,e,n){const r=[n.width,n.height],o=[r[1],r[0]],a=(0,s.getGlsl)(this.context.glContext.version),u=`vec4 ${t}(int index) {\n vec2 uv = packedUVfrom1D(\n ${o[0]}, ${o[1]}, index);\n return ${a.texture2D}(${e}, uv);\n }`;return new i.GlslLibRoutine(u,["coordinates.packedUVfrom1D"])}getPackedSampler2D(t,e,n){const o=n.unpackedShape,a=[n.width,n.height],u=(0,s.getGlsl)(this.context.glContext.version),l=a[0],c=a[1];if(null!=a&&r.ArrayUtil.arraysEqual(o,a)){const n=`vec4 ${t}(int row, int col) {\n vec2 uv = (vec2(col, row) + halfCR) / vec2(${c}.0, ${l}.0);\n return ${u.texture2D}(${e}, uv);\n }`;return new i.GlslLibRoutine(n)}const d=a,h=Math.ceil(o[1]/2),p=`vec4 ${t}(int row, int col) {\n vec2 uv = packedUVfrom2D(${d[1]}, ${d[0]}, ${h}, row, col);\n return ${u.texture2D}(${e}, uv);\n }`;return new i.GlslLibRoutine(p,["coordinates.packedUVfrom2D"])}getPackedSampler3D(t,e,n){const r=n.unpackedShape,o=[n.width,n.height],u=[o[0],o[1]],l=(0,s.getGlsl)(this.context.glContext.version);if(1===r[0]){const s=r.slice(1),o=[1,2],u=(0,a.squeezeInputShape)(r,s),l=["b","row","col"],c=JSON.parse(JSON.stringify(n));c.unpackedShape=u;const d=this.getPackedSamplerFromInput(t,e,c),h=`${d.routineBody}\n vec4 ${t}(int b, int row, int col) {\n return ${t}(${(0,a.getSqueezedParams)(l,o)});\n } `;return new i.GlslLibRoutine(h,d.dependencies)}const c=u[0],d=u[1],h=Math.ceil(r[2]/2),p=`vec4 ${t}(int b, int row, int col) {\n vec2 uv = packedUVfrom3D(\n ${d}, ${c}, ${h*Math.ceil(r[1]/2)}, ${h}, b, row, col);\n return ${l.texture2D}(${e}, uv);}`;return new i.GlslLibRoutine(p,["coordinates.packedUVfrom3D"])}getPackedSamplerND(t,e,n){const r=n.unpackedShape,o=r.length,a=[n.width,n.height],u=(0,s.getGlsl)(this.context.glContext.version),l=[a[0],a[1]],c=l[1],d=l[0],h=Math.ceil(r[o-1]/2);let p=h*Math.ceil(r[o-2]/2),f="int b, int row, int col",g=`b * ${p} + (row / 2) * ${h} + (col / 2)`;for(let t=2;t<o-1;t++)f=`int b${t}, `+f,p*=r[o-t-1],g=`b${t} * ${p} + `+g;const m=`vec4 ${t}(${f}) {\n int index = ${g};\n int texR = index / ${d};\n int texC = index - texR * ${d};\n vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${d}, ${c});\n return ${u.texture2D}(${e}, uv);\n }`;return new i.GlslLibRoutine(m)}getUnpackedSamplerScalar(t,e,n){const[r,s]=[n.width,n.height];if(1===r&&1===s){const n=`\n float ${t}() {\n return sampleTexture(${e}, halfCR);\n }\n `;return new i.GlslLibRoutine(n,["coordinates.sampleTexture"])}const o=`\n float ${t}() {\n int offset_${e} = coordsToOffset(TexCoords, ${r}, ${s});\n vec2 uv = uvFromFlat(${r}, ${s}, offset_${e});\n return sampleTexture(${e}, uv);\n }\n `;return new i.GlslLibRoutine(o,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}getUnpackedSampler1D(t,e,n){const r=n.width,s=n.height;if(1===s&&1===r){const n=`\n float ${t}(int index) {\n return sampleTexture(${e}, halfCR);\n }\n `;return new i.GlslLibRoutine(n,["coordinates.sampleTexture"])}if(1===s){const n=`\n float ${t}(int index) {\n vec2 uv = vec2((float(index) + 0.5) / ${r}.0, 0.5);\n return sampleTexture(${e}, uv);\n }\n `;return new i.GlslLibRoutine(n,["coordinates.sampleTexture"])}if(1===r){const n=`\n float ${t}(int index) {\n vec2 uv = vec2(0.5, (float(index) + 0.5) / ${s}.0);\n return sampleTexture(${e}, uv);\n }\n `;return new i.GlslLibRoutine(n,["coordinates.sampleTexture"])}const o=`\n float ${t}(int index) {\n vec2 uv = uvFromFlat(${r}, ${s}, index);\n return sampleTexture(${e}, uv);\n }\n `;return new i.GlslLibRoutine(o,["coordinates.uvFromFlat","coordinates.sampleTexture"])}getUnpackedSampler2D(t,e,n){const s=n.unpackedShape,u=[n.height,n.width];if(null!=u&&r.ArrayUtil.arraysEqual(s,u)){const n=`\n float ${t}(int row, int col) {\n vec2 uv = (vec2(row, col) + halfCR) / vec2(${u[1]}.0, ${u[0]}.0);\n return sampleTexture(${e}, uv);\n }\n `;return new i.GlslLibRoutine(n,["coordinates.sampleTexture"])}const{newShape:l,keptDims:c}=(0,o.squeezeShape)(s),d=l;if(d.length<s.length){const r=(0,a.squeezeInputShape)(s,d),o=JSON.parse(JSON.stringify(n));o.unpackedShape=r;const u=["col","row"],l=`\n ${this.getUnpackedSamplerFromInput(t,e,o).routineBody}\n float ${t}(int row, int col) {\n return ${t}(${(0,a.getSqueezedParams)(u,c)});\n }\n `;return new i.GlslLibRoutine(l,["coordinates.sampleTexture"])}const h=u[1],p=u[0];if(1===p){const n=`\n float ${t}(int row, int col) {\n int offset_${e} = coordsToOffset(TexCoords, ${h}, ${p});\n float index = dot(vec3(row, col, offset_${e}), vec3(${s[1]}, 1, 1));\n vec2 uv = vec2(0.5, (index + 0.5) / ${h}.0);\n return sampleTexture(${e}, uv);\n }\n `;return new i.GlslLibRoutine(n,["coordinates.sampleTexture","coordinates.coordsToOffset"])}if(1===h){const n=`\n float ${t}(int row, int col) {\n int offset_${e} = coordsToOffset(TexCoords, ${h}, ${p});\n float index = dot(vec3(row, col, offset_${e}), vec3(${s[1]}, 1, 1));\n vec2 uv = vec2((index + 0.5) / ${p}.0, 0.5);\n return sampleTexture(${e}, uv);\n }\n `;return new i.GlslLibRoutine(n,["coordinates.sampleTexture","coordinates.coordsToOffset"])}const f=`\n float ${t}(int row, int col) {\n int index = col * ${s[1]} + row;\n vec2 uv = uvFromFlat(${h}, ${p}, index);\n return 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Can't topologically sort routines needed for shader.");e.add(t.name);const i=t.dependencies;if(i&&i.length>0)for(let t=0;t<i.length;++t)this.dfsTraverse(i[t],e,n,r);r.push(t),n.add(t.name),e.delete(t.name)}}},7341:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.EncodingGlslLib=void 0;const r=n(8520);class i extends r.GlslLib{constructor(t){super(t)}getFunctions(){return Object.assign(Object.assign({},this.encodeFloat32()),this.decodeFloat32())}getCustomTypes(){return{}}encodeFloat32(){return{encode:new r.GlslLibRoutine("highp vec4 encode(highp float f) {\n return vec4(f, 0.0, 0.0, 0.0);\n }\n ")}}decodeFloat32(){return{decode:new r.GlslLibRoutine("highp float decode(highp vec4 rgba) {\n return rgba.r;\n }\n ")}}encodeUint8(){const t=i.isLittleEndian()?"rgba.rgba=rgba.abgr;":"";return{encode:new r.GlslLibRoutine(`\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 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));\n return Result;\n }\n `)}}static isLittleEndian(){const 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")}}e.EncodingGlslLib=i},9894:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.FragColorGlslLib=void 0;const r=n(8520),i=n(5060);class s extends r.GlslLib{constructor(t){super(t)}getFunctions(){return Object.assign(Object.assign({},this.setFragColor()),this.getColorAsFloat())}getCustomTypes(){return{}}setFragColor(){const t=(0,i.getGlsl)(this.context.glContext.version);return{setFragColor:new r.GlslLibRoutine(`\n void setFragColor(float value) {\n ${t.output} = encode(value);\n }\n `,["encoding.encode"])}}getColorAsFloat(){return{getColorAsFloat:new r.GlslLibRoutine("\n float getColorAsFloat(vec4 color) {\n return decode(color);\n }\n ",["encoding.decode"])}}}e.FragColorGlslLib=s},2848:(t,e)=>{"use 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r=n(8520),i=n(2848),s=n(5483),o=n(5060);e.GlslPreprocessor=class{constructor(t,e,n,i){this.libs={},this.glslLibRoutineDependencyGraph={},this.context=new r.GlslContext(t,e,n,i),Object.keys(s.glslRegistry).forEach((t=>{const e=new s.glslRegistry[t](this.context);this.libs[t]=e}));const o=this.glslLibRoutineDependencyGraph;for(const t in this.libs){const e=this.libs[t].getFunctions();for(const n in e){const i=t+"."+n;let s;o[i]?(s=o[i],s.routineBody=e[n].routineBody):(s=new r.GlslLibRoutineNode(i,e[n].routineBody),o[i]=s);const a=e[n].dependencies;if(a)for(let t=0;t<a.length;++t)if(o[a[t]])s.addDependency(o[a[t]]);else{const e=new r.GlslLibRoutineNode(a[t]);o[a[t]]=e,s.addDependency(e)}}}}preprocess(){const t=this.context.programInfo;let e=t.shaderSource;return this.context.programInfo.hasMain||(e=`${e}\n ${(0,o.getDefaultFragShaderMain)(this.context.glContext.version,this.context.outputTextureLayout.shape.length)}`),e=(0,i.replaceInlines)(e),`${(0,o.getFragShaderPreamble)(this.context.glContext.version)}\n ${this.getUniforms(t.inputNames,t.variables)}\n ${this.getImports(e)}\n ${e}`}getImports(t){const e=this.selectGlslLibRoutinesToBeIncluded(t);if(0===e.length)return"";let n="";for(let t=0;t<e.length;++t){if(!e[t].routineBody)throw new Error(`Missing body for the Glsl Library routine: ${e[t].name}`);n+=e[t].routineBody+"\n"}return n}selectGlslLibRoutinesToBeIncluded(t){const e=[];return Object.keys(this.glslLibRoutineDependencyGraph).forEach((n=>{const r=n.split(".")[1];-1!==t.indexOf(r)&&e.push(this.glslLibRoutineDependencyGraph[n])})),r.TopologicalSortGlslRoutines.returnOrderedNodes(e)}getUniforms(t,e){const n=[];if(t)for(const e of t)n.push(`uniform sampler2D ${e};`);if(e)for(const t of e)n.push(`uniform ${t.type} ${t.name}${t.arrayLength?`[${t.arrayLength}]`:""};`);return n.join("\n")}}},5483:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.glslRegistry=void 0;const r=n(5107),i=n(7341),s=n(9894),o=n(2655),a=n(3891);e.glslRegistry={encoding:i.EncodingGlslLib,fragcolor:s.FragColorGlslLib,vec:a.VecGlslLib,shapeUtils:o.ShapeUtilsGlslLib,coordinates:r.CoordsGlslLib}},2655:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.ShapeUtilsGlslLib=void 0;const r=n(8520);class i extends r.GlslLib{constructor(t){super(t)}getFunctions(){return Object.assign(Object.assign(Object.assign(Object.assign(Object.assign({},this.bcastIndex()),this.bcastMatmulIndex()),this.offsetToIndices()),this.indicesToOffset()),this.incrementIndices())}getCustomTypes(){return{}}bcastIndex(){const t=this.context.outputTextureLayout.shape.length,e={};return this.context.programInfo.inputNames.forEach(((n,i)=>{const s=this.context.inputTextureLayouts[i].unpackedShape;if(s.length<=t){const i=s.length,o=t-i,a=`bcastIndices_${n}`;let u="";for(let t=0;t<i;++t)u+=`\n realIndices[${t}] = int( mod(float(bcastedIndices[${o+t}]), ${s[t]}.0) );\n `;const l=`\n void ${a} (int bcastedIndices[${t}], out int realIndices[${i}]) {\n ${u}\n }\n `;e[a]=new r.GlslLibRoutine(l)}})),e}bcastMatmulIndex(){const t=this.context.outputTextureLayout.shape.length,e={};return this.context.programInfo.inputNames.forEach(((n,i)=>{const s=this.context.inputTextureLayouts[i].shape;if(!(s.length<2||s.length>t)){const i=s.length,o=t-i,a=`bcastMatmulIndices_${n}`;let u="";for(let t=0;t<i-2;++t)u+=`\n realIndices[${t}] = int( mod(float(bcastedIndices[${o+t}]), ${s[t]}.0) );\n `;const l=`\n void ${a}(int bcastedIndices[${t}], out int realIndices[${i}]) {\n ${u}\n realIndices[${i-1}] = bcastedIndices[${t-1}];\n realIndices[${i-2}] = bcastedIndices[${t-2}];\n }\n `;e[a]=new r.GlslLibRoutine(l)}})),e}indicesToOffset(){const t={};return this.context.programInfo.inputNames.forEach(((e,n)=>{const s=this.context.inputTextureLayouts[n].shape,o=this.context.inputTextureLayouts[n].strides,a=s.length;let u=`indicesToOffset_${e}`;t[u]=new r.GlslLibRoutine(i.indexToOffsetSingle(u,a,o)),u=`indicesToOffset_${e}_T`,t[u]=new r.GlslLibRoutine(i.indexToOffsetSingle(u,a,o.slice().reverse()))})),t}static indexToOffsetSingle(t,e,n){let r="";for(let t=e-1;t>=0;--t)r+=`\n offset += indices[${t}] * ${n[t]};\n `;return`\n int ${t}(int indices[${e}]) {\n int offset = 0;\n ${r}\n return offset;\n }\n `}offsetToIndices(){const t={};return this.context.programInfo.inputNames.forEach(((e,n)=>{const s=this.context.inputTextureLayouts[n].shape,o=this.context.inputTextureLayouts[n].strides,a=s.length;let u=`offsetToIndices_${e}`;t[u]=new r.GlslLibRoutine(i.offsetToIndicesSingle(u,a,o)),u=`offsetToIndices_${e}_T`,t[u]=new r.GlslLibRoutine(i.offsetToIndicesSingle(u,a,o.slice().reverse()))})),t}static offsetToIndicesSingle(t,e,n){const r=[];for(let t=0;t<e-1;++t)r.push(`\n indices[${t}] = offset / ${n[t]};`),r.push(`\n offset -= indices[${t}] * ${n[t]};`);return r.push(`\n indices[${e-1}] = offset;`),`\n void ${t}(int offset, out int indices[${e}]) {\n ${r.join("")}\n }\n `}incrementIndices(){const t={};return this.context.programInfo.inputNames.forEach(((e,n)=>{const i=this.context.inputTextureLayouts[n].shape,s=i.length,o=`incrementIndices_${e}`;let a="";for(let t=0;t<s;++t)a+=`\n shape[${t}] = ${i[t]};`;const u=`\n void ${o}(int axis, out int indices[${s}]) {\n int shape[${s}];\n ${a};\n for(int i = ${s} -1 ; i >= 0; --i) {\n if(i > axis) continue;\n indices[i] += 1;\n if(indices[i] < shape[i]) {\n break;\n }\n indices[i] = 0;\n }\n }\n `;t[o]=new r.GlslLibRoutine(u)})),t}}e.ShapeUtilsGlslLib=i},5060:(t,e)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.getDefaultFragShaderMain=e.getFragShaderPreamble=e.getVertexShaderSource=e.getGlsl=void 0;const 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r=(a=e.length>2,u=n.cacheKey,{name:"ConvTranspose",inputNames:a?["X","W","B"]:["X","W"],inputTypes:a?[s.TextureType.unpacked,s.TextureType.unpacked,s.TextureType.unpacked]:[s.TextureType.unpacked,s.TextureType.unpacked],cacheHint:u});var a,u;return Object.assign(Object.assign({},r),{get:()=>((t,e,n,r)=>{const a=e.length>2?"getB(output_channel)":"0.0",u=e[0].dims,l=e[1].dims,c=l[1],d=l[0]/r.group,h=[e[0].dims[0],e[1].dims[1]*r.group,...r.outputShape],p=(0,i.getGlsl)(t.session.backend.glContext.version),{activationFunction:f,applyActivation:g}=(0,o.getActivationSnippet)(r),m=`\n const ivec2 strides = ivec2(${r.strides[0]}, ${r.strides[1]});\n const ivec2 pads = ivec2(${r.pads[0]}, ${r.pads[1]});\n ${f}\n void main() {\n ivec4 coords = getOutputCoords();\n int batch = coords.x;\n int output_channel = coords.y;\n\n ivec2 loc = coords.zw + pads;\n\n int group_id = output_channel / ${c};\n int wOutChannel = output_channel - group_id * ${c};\n\n float value = ${a};\n for (int inChannelOffset = 0; inChannelOffset < ${d}; inChannelOffset++) {\n int input_channel = group_id * ${d} + inChannelOffset;\n for (int wWOff = 0; wWOff < ${l[2]}; wWOff++) {\n for (int wHOff = 0; wHOff < ${l[3]}; wHOff++) {\n ivec2 wOff = ivec2(wWOff * ${r.dilations[0]}, wHOff * ${r.dilations[1]});\n ivec2 wLoc = loc - wOff;\n ivec2 wLocIn = wLoc / strides;\n if (\n wLocIn * strides == wLoc &&\n wLocIn.x >= 0 && wLocIn.x < ${u[2]} &&\n wLocIn.y >= 0 && wLocIn.y < ${u[3]}\n ) {\n float xVal = getX(batch, input_channel, wLocIn.y, wLocIn.x);\n float wVal = getW(input_channel, wOutChannel, wHOff, wWOff);\n value += xVal * wVal;\n }\n }\n }\n }\n ${g}\n ${p.output} = vec4(value, .0, .0, .0);\n }\n`;return Object.assign(Object.assign({},n),{output:{dims:h,type:e[0].type,textureType:s.TextureType.unpacked},shaderSource:m,hasMain:!0})})(t,e,r,n)})})(t,e,n),e),d=(t,e)=>{const n=t.kernelShape.slice();if(0===t.kernelShape.length)for(let t=2;t<e[1].dims.length;++t)n.push(e[1].dims[t]);const r=t.pads.slice(),i=t.outputShape.slice();((t,e,n,r,i,s,o,l)=>{const c=t.length-2,d=0===l.length;for(let h=0;h<c;++h){const p=d?t[h+2]*s[h]:l[h],f=a(t[h+2],s[h],i[h],e[h],n[h],p);u(f,r,i,h,h+c),d&&l.push(s[h]*(t[h+2]-1)+o[h]+(e[h]-1)*n[h]+1-i[h]-i[h+c])}})(e[0].dims,n,t.dilations,t.autoPad,r,t.strides,t.outputPadding,i);const s=Object.assign({},t);return Object.assign(s,{kernelShape:n,pads:r,outputShape:i,cacheKey:t.cacheKey}),s};e.parseConvTransposeAttributes=t=>{const e=t.attributes,n=(0,o.parseInternalActivationAttributes)(e),i=e.getString("auto_pad","NOTSET"),s=e.getInts("dilations",[1,1]),a=e.getInt("group",1),u=e.getInts("kernel_shape",[]),l=e.getInts("output_padding",[0,0]),c=e.getInts("output_shape",[]),d=e.getInts("pads",[0,0,0,0]),h=e.getInts("strides",[1,1]);return(0,r.createAttributeWithCacheKey)(Object.assign({autoPad:i,dilations:s,group:a,kernelShape:u,outputPadding:l,outputShape:c,pads:d,strides:h},n))};const h=(t,e)=>{if(!t||2!==t.length&&3!==t.length)throw new Error("Conv requires 2 or 3 inputs");if(4!==t[0].dims.length||4!==t[1].dims.length)throw new Error("currently only support 2-dimensional conv");if(t[0].dims[1]!==t[1].dims[0])throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");const n=t[1].dims[1]*e.group;if(3===t.length&&(1!==t[2].dims.length||t[2].dims[0]!==n))throw new Error("invalid bias");const r=t[0].dims.length-2;if(e.dilations.length!==r)throw new Error(`dilations should be ${r}D`);if(e.strides.length!==r)throw new Error(`strides should be ${r}D`);if(e.pads.length!==2*r)throw new Error(`pads should be ${2*r}D`);if(e.outputPadding.length!==r)throw new Error(`output_padding should be ${r}D`);if(0!==e.kernelShape.length&&e.kernelShape.length!==t[1].dims.length-2)throw new Error("invalid kernel shape");if(0!==e.outputShape.length&&e.outputShape.length!==t[0].dims.length-2)throw new Error("invalid output shape");if("float32"!==t[0].type||"float32"!==t[1].type)throw new Error("ConvTranspose input(X,W) should be float tensor");if(3===t.length&&"float32"!==t[2].type)throw new Error("ConvTranspose input(bias) should be float tensor")}},8138:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.parseConvAttributes=e.conv=e.calculateOutputShape=void 0;const r=n(246),i=n(2517),s=n(4770),o=n(1386),a=n(9828),u=n(2823),l=n(3248),c=n(5623);e.calculateOutputShape=(t,e,n,r,i)=>{const s=t[0],o=t.slice(2),a=o.length,u=e[0],l=e.slice(2).map(((t,e)=>t+(t-1)*(n[e]-1))),c=o.map(((t,e)=>t+r[e]+r[e+a])).map(((t,e)=>Math.floor((t-l[e]+i[e])/i[e])));return[s,u].concat(...c)},e.conv=(t,e,n)=>(g(e,n),d(t,e,n));const d=(t,e,n)=>{const r=f(n,e),i=t.session.pack,a=1===r.kernelShape[0]&&1===r.kernelShape[1];return r.group>1?[t.run((0,s.createUnpackedGroupedConvProgramInfoLoader)(t,e,r),e)]:a&&i?[h(t,e,r)]:i&&4===e[0].dims.length&&1===e[0].dims[0]&&!a?[(0,o.conv2DPacked)(t,e,r)]:[p(t,e,r)]},h=(t,n,r)=>{const i=n[0].dims,s=n[1].dims,o=(0,e.calculateOutputShape)(i,s,r.dilations,r.pads,r.strides),a=t.reshapeUnpacked(n[0],[i[1],i[2]*i[3]]),u=t.reshapeUnpacked(n[1],[s[0],s[1]]),l=n.length>2?[u,a,n[2]]:[u,a],d=t.run((0,c.createMatmulProgramInfoLoader)(l,r),l);return t.reshapeUnpacked(d,o)},p=(t,n,r)=>{const i=n[0].dims,s=n[1].dims,o=(0,e.calculateOutputShape)(i,s,r.dilations,r.pads,r.strides),u=t.run((0,l.createIm2ColProgramInfoLoader)(t,n[0],n[1],o,r),[n[0]]),c=3===n.length?[u,n[1],n[2]]:[u,n[1]];return t.run((0,a.createDotProductProgramInfoLoader)(t,n,o,r),c)},f=(t,e)=>{const n=t.kernelShape.slice();if(0===t.kernelShape.length)for(let t=2;t<e[1].dims.length;++t)n.push(e[1].dims[t]);const r=t.pads.slice();i.PoolConvUtil.adjustPadsBasedOnAutoPad(e[0].dims,t.strides,t.dilations,n,r,t.autoPad);const s=Object.assign({},t);return Object.assign(s,{kernelShape:n,pads:r,cacheKey:t.cacheKey}),s};e.parseConvAttributes=t=>{const e=t.attributes,n=(0,u.parseInternalActivationAttributes)(e),i=e.getString("auto_pad","NOTSET"),s=e.getInts("dilations",[1,1]),o=e.getInt("group",1),a=e.getInts("kernel_shape",[]),l=e.getInts("pads",[0,0,0,0]),c=e.getInts("strides",[1,1]);return(0,r.createAttributeWithCacheKey)(Object.assign({autoPad:i,dilations:s,group:o,kernelShape:a,pads:l,strides:c},n))};const g=(t,e)=>{if(!t||2!==t.length&&3!==t.length)throw new Error("Conv requires 2 or 3 inputs");if(4!==t[0].dims.length||4!==t[1].dims.length)throw new Error("currently only support 2-dimensional conv");if(t[0].dims[1]!==t[1].dims[1]*e.group)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");if(3===t.length&&(1!==t[2].dims.length||t[1].dims[0]!==t[2].dims[0]))throw new Error("invalid bias");const n=t[0].dims.length-2;if(e.dilations.length!==n)throw new Error(`dilations should be ${n}D`);if(e.strides.length!==n)throw new Error(`strides should be ${n}D`);if(e.pads.length!==2*n)throw new Error(`pads should be ${2*n}D`);if(0!==e.kernelShape.length&&e.kernelShape.length!==t[1].dims.length-2)throw new Error("invalid kernel shape");if("float32"!==t[0].type||"float32"!==t[1].type)throw new Error("Conv input(X,W) should be float tensor");if(3===t.length&&"float32"!==t[2].type)throw new Error("Conv input(bias) should be float tensor")}},5193:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.parseDepthToSpaceAttributes=e.depthToSpace=void 0;const r=n(3738);e.depthToSpace=(t,e,n)=>{i(e);const s=n.blocksize,o=s*s,a="DCR"===n.mode?[0,3,4,1,5,2]:[0,1,4,2,5,3],u="DCR"===n.mode?[e[0].dims[0],s,s,e[0].dims[1]/o,e[0].dims[2],e[0].dims[3]]:[e[0].dims[0],e[0].dims[1]/o,s,s,e[0].dims[2],e[0].dims[3]],l=t.reshapeUnpacked(e[0],u),c={perm:a,cacheKey:`${a}`},[d]=(0,r.transpose)(t,[l],c),h=[e[0].dims[0],e[0].dims[1]/o,e[0].dims[2]*s,e[0].dims[3]*s];return[t.reshapeUnpacked(d,h)]},e.parseDepthToSpaceAttributes=t=>{const e=t.attributes.getInt("blocksize");if(e<1)throw new Error(`blocksize must be >= 1, but got : ${e} for DepthToSpace`);const n=t.attributes.getString("mode","DCR");if("DCR"!==n&&"CRD"!==n)throw new Error(`unrecognized mode: ${n} for DepthToSpace`);return{mode:n,blocksize:e}};const i=t=>{if(1!==t.length)throw new Error(`DepthToSpace expect 1 inputs, but got ${t.length}`);if("string"===t[0].type||4!==t[0].dims.length)throw new TypeError("DepthToSpace input should be a 4-D numeric tensor")}},9828:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.createDotProductProgramInfoLoader=void 0;const r=n(2517),i=n(5060),s=n(2039),o=n(2823),a=n(3248);e.createDotProductProgramInfoLoader=(t,e,n,u)=>{const l=((t,e)=>({name:"ConvDotProduct",inputNames:t?["Im2Col","K","B"]:["Im2Col","K"],inputTypes:t?[s.TextureType.unpacked,s.TextureType.packedLastDimension,s.TextureType.unpacked]:[s.TextureType.unpacked,s.TextureType.packedLastDimension],cacheKey:e.activationCacheKey}))(e.length>2,u);return Object.assign(Object.assign({},l),{get:()=>((t,e,n,u,l)=>{const c=n[0].dims,d=n[1].dims,h=[d[0],Math.ceil(c[1]*d[2]*d[3]/4)],p=(0,a.calculateIm2ColDims)(c,d,u),[f,g]=t.calculateTextureWidthAndHeight(h,s.TextureType.packedLastDimension),m=r.ShapeUtil.computeStrides(p),[_,b]=t.calculateTextureWidthAndHeight(p,s.TextureType.packedLastDimension),y=u.length,w=n.length<3?"0.0":"_B(b)",v=Math.ceil(c[1]*d[2]*d[3]/4),{activationFunction:x,applyActivation:T}=(0,o.getActivationSnippet)(l),S=(0,i.getGlsl)(t.session.backend.glContext.version),A=`\n${x}\nfloat process(int indices[${y}]) {\n int b[1];\n b[0] = indices[1];\n int im2col[4];\n im2col[0] = indices[0];\n im2col[1] = indices[2];\n im2col[2] = indices[3];\n int im2colOffset = im2col[0] * ${m[0]} + im2col[1] * ${m[1]} + im2col[2] * ${m[2]};\n int kernelOffset = indices[1] * ${h[1]};\n float value = ${w};\n for (int i = 0; i < ${v}; ++i) {\n vec2 im2colCoords = offsetToCoords(im2colOffset, ${_}, ${b});\n vec2 kernelCoords = offsetToCoords(kernelOffset, ${f}, ${g});\n value += dot(${S.texture2D}(Im2Col, im2colCoords), ${S.texture2D}(K, kernelCoords));\n ++im2colOffset;\n ++kernelOffset;\n }\n ${T}\n return value;\n}`;return Object.assign(Object.assign({},e),{output:{dims:u,type:n[0].type,textureType:s.TextureType.unpacked},shaderSource:A})})(t,l,e,n,u)})}},7992:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.parseFlattenAttributes=e.flatten=void 0;const r=n(2517);e.flatten=(t,e,n)=>{i(e,n);const s=r.ShapeUtil.flattenShape(e[0].dims,n);return[t.reshapeUnpacked(e[0],s)]},e.parseFlattenAttributes=t=>t.attributes.getInt("axis",1);const i=(t,e)=>{if(!t||1!==t.length)throw new Error("Flatten requires 1 input.");const n=t[0].dims.length;if(0===n)throw new Error("scalar tensor is not supported.");if(e<-n||e>n)throw new Error("Invalid axis");if("string"===t[0].type)throw new Error("string tensor is not supported.")}},2823:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.parseInternalActivationAttributes=e.getActivationSnippet=void 0;const r=n(2517),i=n(4909);e.getActivationSnippet=function(t){let e;switch(t.activation){case"Relu":e=(0,i.glslRelu)();break;case"Sigmoid":e=(0,i.glslSigmoid)();break;case"Clip":e=(0,i.glslClip)(t.clipMin,t.clipMax);break;default:return{activationFunction:"",applyActivation:""}}const n=e.name;return{activationFunction:e.body,applyActivation:`value = ${n}_(value);`}},e.parseInternalActivationAttributes=t=>{const e=t.getString("activation","");if("Clip"===e){const[n,i]=t.getFloats("activation_params",[r.MIN_CLIP,r.MAX_CLIP]);return{activation:e,clipMax:i,clipMin:n,activationCacheKey:`${e}:${n},${i}`}}return{activation:e,activationCacheKey:e}}},1253:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.parseGatherAttributes=e.gather=void 0;const r=n(246),i=n(782),s=n(2517),o=n(2039);e.gather=(t,e,n)=>(l(e,n.axis),[t.run(u(t,e,n),e)]),e.parseGatherAttributes=t=>(0,r.createAttributeWithCacheKey)({axis:t.attributes.getInt("axis",0)});const a={name:"Gather",inputNames:["A","B"],inputTypes:[o.TextureType.unpacked,o.TextureType.unpacked]},u=(t,e,n)=>{const r=Object.assign(Object.assign({},a),{cacheHint:n.cacheKey});return Object.assign(Object.assign({},r),{get:()=>((t,e,n,r)=>{const i=n[0].dims.slice(),a=n[1].dims.slice(),u=new Array(i.length+a.length-1);r=s.ShapeUtil.normalizeAxis(r,i.length);const l=[];for(let t=0;t<u.length;t++)t<r?(u[t]=i[t],l.push(`inputIdx[${t}] = outputIdx[${t}];`)):t<r+a.length?(u[t]=a[t-r],l.push(`indexDataIdx[${t-r}] = outputIdx[${t}];`)):(u[t]=i[t-a.length+1],l.push(`inputIdx[${t-a.length+1}] = outputIdx[${t}];`));const c=`\n float process(int outputIdx[${u.length||1}]) {\n int inputIdx[${i.length}];\n int indexDataIdx[${a.length||1}];\n indexDataIdx[0] = 0;\n ${l.join("\n ")}\n int idx = int(_B(indexDataIdx));\n inputIdx[${r}] = idx < 0 ? idx + ${i[r]} : idx;\n return _A(inputIdx);\n }`;return Object.assign(Object.assign({},e),{output:{dims:u,type:n[0].type,textureType:o.TextureType.unpacked},shaderSource:c})})(0,r,e,n.axis)})},l=(t,e)=>{if(!t||2!==t.length)throw new Error("Gather requires 2 inputs.");const n=t[0].dims.length;if(n<1)throw new Error("Invalid input shape.");if(e<-n||e>n-1)throw new Error("Invalid axis.");if(-1===i.NUMBER_TYPES.indexOf(t[0].type))throw new Error("Invaid input type.");if("int32"!==t[1].type&&"int16"!==t[1].type)throw new Error("Invaid input type.")}},4776:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.parseGemmAttributesV11=e.parseGemmAttributesV7=e.gemm=void 0;const r=n(246),i=n(2517),s=n(2039);e.gemm=(t,e,n)=>(l(e,n),[t.run(a(e,n),e)]);const o=(t,e)=>{const n=0!==t.attributes.getInt("transA",0),i=0!==t.attributes.getInt("transB",0),s=t.attributes.getFloat("alpha",1),o=t.attributes.getFloat("beta",1);return(0,r.createAttributeWithCacheKey)({transA:n,transB:i,alpha:s,beta:o,isOptionalC:e})};e.parseGemmAttributesV7=t=>o(t,!1),e.parseGemmAttributesV11=t=>o(t,!0);const a=(t,e)=>{const n={name:"Gemm",inputNames:3===t.length?["A","B","C"]:["A","B"],inputTypes:3===t.length?[s.TextureType.unpacked,s.TextureType.unpacked,s.TextureType.unpacked]:[s.TextureType.unpacked,s.TextureType.unpacked],key:e.cacheKey};return Object.assign(Object.assign({},n),{get:()=>u(n,t,e)})},u=(t,e,n)=>{const r=e[0].dims.slice(),o=e[1].dims.slice(),[a,u]=i.GemmUtil.getShapeOfGemmResult(r,n.transA,o,n.transB,3===e.length?e[2].dims:void 0),l=[a,u];if(!l)throw new Error("Can't use gemm on the given tensors");let c=r[r.length-1],d="";n.transA&&(c=r[0]),n.transA&&n.transB?d="value += _A_T(a) * _B_T(b);":n.transA&&!n.transB?d="value += _A_T(a) * _B(b);":!n.transA&&n.transB?d="value += _A(a) * _B_T(b);":n.transA||n.transB||(d="value += _A(a) * _B(b);");const h=l.length,p=`\n float process(int indices[${h}]) {\n int a[${h}];\n int b[${h}];\n ${3===e.length?`int c[${e[2].dims.length}];`:""}\n\n copyVec(indices, a);\n copyVec(indices, b);\n ${3===e.length?"bcastIndices_C(indices, c);":""}\n\n float value = 0.0;\n for (int k=0; k<${c}; ++k) {\n a[${h-1}] = k;\n b[${h-2}] = k;\n ${d}\n }\n\n value = value * alpha;\n ${3===e.length?"value += beta * _C(c);":""}\n return value;\n }`;return Object.assign(Object.assign({},t),{output:{dims:l,type:e[0].type,textureType:s.TextureType.unpacked},variables:[{name:"alpha",type:"float",data:n.alpha},{name:"beta",type:"float",data:n.beta}],shaderSource:p})},l=(t,e)=>{if(!t)throw new Error("Input is missing");if(e.isOptionalC&&(t.length<2||t.length>3))throw new Error("Invaid input shape.");if(!e.isOptionalC&&3!==t.length)throw new Error("Gemm requires 3 inputs");if(3===t.length&&1!==t[2].dims.length&&2!==t[2].dims.length)throw new Error("Invalid input shape of C");if("float32"!==t[0].type&&"float64"!==t[0].type||"float32"!==t[1].type&&"float64"!==t[1].type||3===t.length&&"float32"!==t[2].type&&"float64"!==t[2].type)throw new Error("Invalid input type.");if(t[0].type!==t[1].type||3===t.length&&t[0].type!==t[2].type)throw new Error("Input types are mismatched")}},8555:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.createPackedIm2ColProgramInfoLoader=void 0;const r=n(5060),i=n(2039),s=n(2827);e.createPackedIm2ColProgramInfoLoader=(t,e,n,o,a)=>{const u=(l=a.cacheKey,{name:"Im2Col (packed)",inputNames:["A"],inputTypes:[i.TextureType.packed],cacheHint:l});var l;return Object.assign(Object.assign({},u),{get:()=>((t,e,n,o,a,u)=>{const l=n.dims,c=o.dims,d=a.length,h=[c[1]*c[2]*c[3],a[2]*a[3]],p=c[2]*c[3],f=(0,s.unpackFromChannel)(),g=(0,r.getGlsl)(t.session.backend.glContext.version);let m="";for(let t=0;t<=1;t++)for(let e=0;e<=1;e++)m+=`\n blockIndex = rc.x + ${e};\n pos = rc.y + ${t};\n\n if(blockIndex < ${h[1]} && pos < ${h[0]}) {\n offsetY = int(blockIndex / (${a[d-1]})) * ${u.strides[0]} -\n ${u.pads[0]};\n d0 = offsetY + ${u.dilations[0]} * (imod(pos, ${p}) / ${c[2]});\n\n if(d0 < ${l[2]} && d0 >= 0) {\n offsetX = imod(blockIndex, ${a[d-1]}) * ${u.strides[1]} -\n ${u.pads[1]};\n d1 = offsetX + ${u.dilations[1]} * imod(imod(pos, ${p}), ${c[2]});\n\n if(d1 < ${l[3]} && d1 >= 0) {\n\n ch = int(float(pos)/ ${p}.);\n innerDims = vec2(d0, d1);\n result[${2*t+e}] = getChannel(\n getA(0, ch, int(innerDims.x),\n int(innerDims.y)), innerDims);\n }\n }\n }\n\n `;const _=`\n ${f}\n\n void main() {\n ivec2 rc = getOutputCoords();\n vec4 result = vec4(0.0);\n int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\n vec2 innerDims;\n ${m}\n ${g.output} = result;\n }\n `;return Object.assign(Object.assign({},e),{output:{dims:h,type:n.type,textureType:i.TextureType.packed},shaderSource:_,hasMain:!0})})(t,u,e,n,o,a)})}},3248:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.calculateIm2ColDims=e.createIm2ColProgramInfoLoader=void 0;const r=n(2039);e.createIm2ColProgramInfoLoader=(t,n,i,s,o)=>{const a=(u=o.cacheKey,{name:"Im2Col",inputNames:["X"],inputTypes:[r.TextureType.unpacked],cacheHint:u});var u;return Object.assign(Object.assign({},a),{get:()=>((t,n,i,s,o,a)=>{const u=i.dims,l=s.dims,c=o.length,d=(0,e.calculateIm2ColDims)(u,l,o,4),h=`\n const int XC = ${u[1]};\n const int XH = ${u[2]};\n const int XW = ${u[3]};\n const int KH = ${a.kernelShape[0]};\n const int KW = ${a.kernelShape[1]};\n const int dilationH = ${a.dilations[0]};\n const int dilationW = ${a.dilations[1]};\n const int strideH = ${a.strides[0]};\n const int strideW = ${a.strides[1]};\n const int padH = ${a.pads[0]};\n const int padW = ${a.pads[1]};\n const int KHKW = KH*KW;\n const int XCKHKW = XC * KHKW;\n const int outputChannels = 4;\n vec4 process(int indices[${c}]) {\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 - patchC*KHKW) / KW;\n int patchW = (p - patchC*KHKW) - patchH * KW;\n int xh2 = oh + patchH * dilationH;\n int xw2 = ow + patchW * dilationW;\n int x[${u.length}];\n x[0] = b;\n x[1] = patchC;\n x[2] = xh2;\n x[3] = xw2;\n if(xh2 >= 0 &&\n xh2 < XH &&\n xw2 >= 0 &&\n xw2 < XW) {\n value[i] = _X(x);\n }\n }\n ++p;\n }\n return value;\n }\n `;return Object.assign(Object.assign({},n),{output:{dims:d,type:i.type,textureType:r.TextureType.packedLastDimension},shaderSource:h})})(0,a,n,i,s,o)})},e.calculateIm2ColDims=(t,e,n,r=4)=>[n[0],n[2],n[3],Math.ceil(t[1]*e[2]*e[3]/r)]},6572:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.parseImageScalerAttributes=e.imageScaler=void 0;const r=n(246),i=n(2039);e.imageScaler=(t,e,n)=>(u(e),[t.run(o(t,e,n),e)]),e.parseImageScalerAttributes=t=>{const e=t.attributes.getFloat("scale"),n=t.attributes.getFloats("bias");return(0,r.createAttributeWithCacheKey)({scale:e,bias:n})};const s={name:"ImageScaler",inputNames:["X"],inputTypes:[i.TextureType.unpacked]},o=(t,e,n)=>{const r=Object.assign(Object.assign({},s),{cacheHint:n.cacheKey});return Object.assign(Object.assign({},r),{get:()=>((t,e,n,r)=>{const s=n[0].dims.slice(),o=s.length,u=`\n ${a(r.bias.length)}\n float process(int indices[${o}]) {\n return _X(indices) * scale + getBias(bias, indices[1]);\n }`;return 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Object.assign(Object.assign({},t),{output:{dims:o,type:e.type,textureType:i.TextureType.packedLastDimension},shaderSource:a})})(s,t)}),a={name:"InstanceNormalization_ComputeOutput",inputNames:["X","MeanAndVariance","Scale","B"],inputTypes:[i.TextureType.unpacked,i.TextureType.packedLastDimension,i.TextureType.unpacked,i.TextureType.unpacked]},u=(t,e,n,s)=>{const o=Object.assign(Object.assign({},a),{cacheHint:`${n}`});return Object.assign(Object.assign({},o),{get:()=>((t,e,n,s,o)=>{const a=(0,r.getGlsl)(t.session.backend.glContext.version),[u,l]=t.calculateTextureWidthAndHeight(o,i.TextureType.packedLastDimension),[c,d]=[u/4,l],h=`\n vec4 get_MeanAndVariance(int[2] mv) {\n int offset = indicesToOffset_MeanAndVariance(mv);\n vec2 coords = offsetToCoords(offset, ${c}, ${d});\n return ${a.texture2D}(MeanAndVariance, coords);\n }\n\n float process(int[4] indices) {\n int mv[2];\n mv[0] = indices[0];\n mv[1] = indices[1];\n vec4 mean_and_variance = get_MeanAndVariance(mv);\n float mean = mean_and_variance.r;\n float variance = mean_and_variance.g;\n\n int sb[1];\n sb[0] = indices[1];\n float scale = _Scale(sb);\n float b = _B(sb);\n\n return scale * (_X(indices) - mean) / sqrt(variance + epsilon) + b;\n }`;return Object.assign(Object.assign({},e),{output:{dims:n.dims,type:n.type,textureType:i.TextureType.unpacked},variables:[{name:"epsilon",type:"float",data:s}],shaderSource:h})})(t,o,e,n,s)})},l=t=>{if(!t||3!==t.length)throw new Error("InstanceNormalization requires 3 inputs.");const e=t[0],n=t[1],r=t[2];if(e.dims.length<3||1!==n.dims.length||1!==r.dims.length)throw new Error("Invalid input shape.");if(n.dims[0]!==e.dims[1]||r.dims[0]!==e.dims[1])throw new Error("Input shapes are mismatched.");if("float32"!==e.type&&"float64"!==e.type||"float32"!==n.type&&"float64"!==n.type||"float32"!==r.type&&"float64"!==r.type)throw new Error("Invalid input type.");if(4!==t[0].dims.length)throw new Error("Only support 4-D input shape.")}},708:(t,e,n)=>{"use 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m=h[h.length-1],_=Math.ceil(m/2),b=h.length,y=p.length,w=(0,i.getGlsl)(t.session.backend.glContext.version),v=(0,o.getCoordsDataType)(f.length),x=f.length,T=(0,o.getGlChannels)(),{activationFunction:S,applyActivation:A}=(0,a.getActivationSnippet)(l),k=c?`${(0,u.getBiasForMatmul)(v,T,n[2].dims,f,!0)}`:"",O=g?`${function(t,e,n,i){let s=[],o=[];const a=n[0].dims,u=n[1].dims,l=a.length,c=u.length,d=i.length,h=d-l,p=d-c;s=a.map(((t,n)=>`coords.${e[n+h]}`)),s[l-1]="i*2",s.join(", "),o=u.map(((t,n)=>`coords.${e[n+p]}`)),o[c-2]="i*2",o.join(", ");const f=r.BroadcastUtil.getBroadcastDims(a,i),g=r.BroadcastUtil.getBroadcastDims(u,i),m=f.map((t=>`coords.${e[t+h]} = 0;`)).join("\n"),_=g.map((t=>`coords.${e[t+p]} = 0;`)).join("\n"),b=`int lastDim = coords.${e[d-1]};\n coords.${e[d-1]} = coords.${e[d-2]};\n coords.${e[d-2]} = lastDim;`;return`\nvec4 getAAtOutCoordsMatmul(int i) {\n ${t} coords = getOutputCoords();\n ${b}\n ${m}\n vec4 outputValue = getA(${s});\n return outputValue;\n}\n\nvec4 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i=Array.from(e[1].integerData),s=e.length>=3?e[2].floatData[0]:0;return(0,r.createAttributeWithCacheKey)({mode:n,pads:i,value:s})},l=(t,e,n)=>{const r=i.ShapeUtil.padShape(e.dims.slice(),n.pads),s=r.length,a=`\n ${h(t,e,n)}\n float process(int[${s}] indices) {\n return padA(indices);\n }`;return{name:"Pad",inputNames:["A"],inputTypes:[o.TextureType.unpacked],output:{dims:r,type:e.type,textureType:o.TextureType.unpacked},shaderSource:a}},c=t=>{if(!t||1!==t.length)throw new Error("Pad requires 1 input");if("float32"!==t[0].type&&"float64"!==t[0].type)throw new Error("Invalid input type.")},d=t=>{if(!t||2!==t.length&&3!==t.length)throw new Error("Pad requires 2 or 3 inputs");if("int32"!==t[1].type)throw new Error("Invalid input type.");if(t.length>=3&&"string"===t[2].type)throw new Error("Invalid input type.")},h=(t,e,n)=>{const r=(0,s.getGlsl)(t.session.backend.glContext.version),[a,u]=t.calculateTextureWidthAndHeight(e.dims,o.TextureType.unpacked),l=i.ShapeUtil.computeStrides(e.dims);switch(n.mode){case"constant":return p(r,e.dims,l,a,u,n.pads,n.value);case"reflect":return f(r,e.dims,l,a,u,n.pads);case"edge":return g(r,e.dims,l,a,u,n.pads);default:throw new Error("Invalid mode")}},p=(t,e,n,r,i,s,o)=>{const a=e.length;let u="";for(let t=a-1;t>=0;--t)u+=`\n k = m[${t}] - ${s[t]};\n if (k < 0) return constant;\n if (k >= ${e[t]}) return constant;\n offset += k * ${n[t]};\n `;return`\n float padA(int m[${a}]) {\n const float constant = float(${o});\n int offset = 0;\n int k = 0;\n ${u}\n vec2 coords = offsetToCoords(offset, ${r}, ${i});\n float value = getColorAsFloat(${t.texture2D}(A, coords));\n return value;\n }\n `},f=(t,e,n,r,i,s)=>{const o=e.length;let a="";for(let t=o-1;t>=0;--t)a+=`\n k = m[${t}] - ${s[t]};\n if (k < 0) { k = -k; }\n {\n const int _2n_1 = ${2*(e[t]-1)};\n k = int( mod( float(k), float(_2n_1) ) ) ;\n if(k >= ${e[t]}) { k = _2n_1 - k; }\n }\n offset += k * ${n[t]};\n `;return`\n float padA(int m[${o}]) {\n int offset = 0;\n int k = 0;\n ${a}\n vec2 coords = offsetToCoords(offset, ${r}, ${i});\n float value = getColorAsFloat(${t.texture2D}(A, coords));\n return value;\n }\n `},g=(t,e,n,r,i,s)=>{const o=e.length;let a="";for(let t=o-1;t>=0;--t)a+=`\n k = m[${t}] - ${s[t]};\n if (k < 0) k = 0;\n if (k >= ${e[t]}) k = ${e[t]-1};\n offset += k * ${n[t]};\n `;return`\n float padA(int m[${o}]) {\n int offset = 0;\n int k = 0;\n ${a}\n vec2 coords = offsetToCoords(offset, ${r}, ${i});\n float value = getColorAsFloat(${t.texture2D}(A, coords));\n return value;\n }\n `}},2143:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.globalMaxPool=e.parseMaxPoolAttributes=e.maxPool=e.parseGlobalAveragePoolAttributes=e.globalAveragePool=e.parseAveragePoolAttributes=e.averagePool=void 0;const r=n(246),i=n(2517),s=n(2039);e.averagePool=(t,e,n)=>{d(e);const r={name:"AveragePool",inputNames:["X"],inputTypes:[s.TextureType.unpacked],cacheHint:n.cacheKey};return[t.run(Object.assign(Object.assign({},r),{get:()=>o(e,r,!1,n)}),e)]},e.parseAveragePoolAttributes=t=>{const e=t.attributes.getString("auto_pad","NOTSET"),n=t.attributes.getInt("ceil_mode",0),i=0!==t.attributes.getInt("count_include_pad",0),s=t.attributes.getInts("kernel_shape"),o=t.attributes.getInts("strides",[]),a=t.attributes.getInts("pads",[]);if(0!==n)throw new Error("using ceil() in shape computation is not yet supported for AveragePool");return(0,r.createAttributeWithCacheKey)({autoPad:e,ceilMode:n,countIncludePad:i,kernelShape:s,strides:o,pads:a})};const o=(t,e,n,r)=>{const[o,a]=u(t,r,n),l=i.ShapeUtil.size(o.kernelShape);let c="";o.countIncludePad?c+=`value /= float(${l});`:c+=`value /= float(${l} - pad);`;const d=`\n ${h(t[0].dims,o,"value += _X(x);",c,"0.0")}\n `;return Object.assign(Object.assign({},e),{output:{dims:a,type:t[0].type,textureType:s.TextureType.unpacked},shaderSource:d})};e.globalAveragePool=(t,e,n)=>{d(e);const r={name:"GlobalAveragePool",inputNames:["X"],inputTypes:[s.TextureType.unpacked],cacheHint:`${n.countIncludePad}`};return[t.run(Object.assign(Object.assign({},r),{get:()=>o(e,r,!0,n)}),e)]},e.parseGlobalAveragePoolAttributes=t=>{const e=0!==t.attributes.getInt("count_include_pad",0);return(0,r.createAttributeWithCacheKey)({autoPad:"",ceilMode:0,countIncludePad:e,kernelShape:[],strides:[],pads:[]})},e.maxPool=(t,e,n)=>{d(e);const r={name:"MaxPool",inputNames:["X"],inputTypes:[s.TextureType.unpacked],cacheHint:n.cacheKey};return[t.run(Object.assign(Object.assign({},r),{get:()=>a(e,r,!1,n)}),e)]},e.parseMaxPoolAttributes=t=>{const e=t.attributes.getString("auto_pad","NOTSET"),n=t.attributes.getInt("ceil_mode",0),i=t.attributes.getInts("kernel_shape"),s=t.attributes.getInts("strides",[]),o=t.attributes.getInts("pads",[]),a=t.attributes.getInt("storage_order",0),u=t.attributes.getInts("dilations",[]);if(0!==a)throw new Error("column major storage order is not yet supported for MaxPool");if(0!==n)throw new Error("using ceil() in shape computation is not yet supported for MaxPool");return(0,r.createAttributeWithCacheKey)({autoPad:e,ceilMode:n,countIncludePad:!1,kernelShape:i,strides:s,pads:o,storageOrder:a,dilations:u})};const a=(t,e,n,r)=>{const[i,o]=u(t,r,n),a=`\n ${h(t[0].dims,i,"\n value = max(_X(x), value);\n ","","-1e5")}\n `;return Object.assign(Object.assign({},e),{output:{dims:o,type:t[0].type,textureType:s.TextureType.unpacked},shaderSource:a})},u=(t,e,n)=>{const r=t[0].dims.slice(),s=Object.hasOwnProperty.call(e,"dilations"),o=e.kernelShape.slice(),a=e.strides.slice(),u=s?e.dilations.slice():[],l=e.pads.slice();i.PoolConvUtil.adjustPoolAttributes(n,r,o,a,u,l);const c=i.PoolConvUtil.computePoolOutputShape(n,r,a,u,o,l,e.autoPad),d=Object.assign({},e);return s?Object.assign(d,{kernelShape:o,strides:a,pads:l,dilations:u,cacheKey:e.cacheKey}):Object.assign(d,{kernelShape:o,strides:a,pads:l,cacheKey:e.cacheKey}),[d,c]},l={autoPad:"",ceilMode:0,countIncludePad:!1,kernelShape:[],strides:[],pads:[],storageOrder:0,dilations:[],cacheKey:""},c={name:"GlobalMaxPool",inputNames:["X"],inputTypes:[s.TextureType.unpacked]};e.globalMaxPool=(t,e)=>(d(e),[t.run(Object.assign(Object.assign({},c),{get:()=>a(e,c,!0,l)}),e)]);const d=t=>{if(!t||1!==t.length)throw new Error("Pool ops requires 1 input.");if("float32"!==t[0].type&&"float64"!==t[0].type)throw new Error("Invalid input type.")},h=(t,e,n,r,s)=>{const o=t.length;if(e.kernelShape.length<=2){const i=e.kernelShape[e.kernelShape.length-1],a=e.strides[e.strides.length-1],u=e.pads[e.pads.length/2-1],l=e.pads[e.pads.length-1],c=t[o-1];let d="",h="",p="";if(d=u+l!==0?`\n for (int i = 0; i < ${i}; i++) {\n x[${o} - 1] = indices[${o} - 1] * ${a} - ${u} + i;\n if (x[${o} - 1] < 0 || x[${o} - 1] >= ${c}) {\n pad++;\n continue;\n }\n ${n}\n }`:`\n for (int i = 0; i < ${i}; i++) {\n x[${o} - 1] = indices[${o} - 1] * ${a} - ${u} + i;\n ${n}\n }`,2===e.kernelShape.length){const n=e.kernelShape[e.kernelShape.length-2],r=e.strides[e.strides.length-2],s=e.pads[e.pads.length/2-2],a=e.pads[e.pads.length-2],u=t[o-2];h=s+a!==0?`\n for (int j = 0; j < ${n}; j++) {\n x[${o} - 2] = indices[${o} - 2] * ${r} - ${s} + j;\n if (x[${o} - 2] < 0 || x[${o} - 2] >= ${u}) {\n pad+= ${i};\n continue;\n }\n `:`\n for (int j = 0; j < ${n}; j++) {\n x[${o} - 2] = indices[${o} - 2] * ${r} - ${s} + j;\n `,p="\n }\n "}return`\n float process(int indices[${o}]) {\n int x[${o}];\n copyVec(indices, x);\n\n float value = ${s};\n int pad = 0;\n ${h}\n ${d}\n ${p}\n ${r}\n return value;\n }\n `}{const a=i.ShapeUtil.size(e.kernelShape),u=i.ShapeUtil.computeStrides(e.kernelShape),l=u.length,c=e.pads.length,d=f(l),h=p(t,"inputDims"),g=p(e.pads,"pads"),m=p(u,"kernelStrides"),_=p(e.strides,"strides");let b="";return b=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 ${d}\n float process(int indices[${o}]) {\n int x[${o}];\n copyVec(indices, x);\n int offset[${l}];\n int pads[${c}];\n int inputDims[${o}];\n int kernelStrides[${l}];\n int strides[${l}];\n ${g}\n ${h}\n ${_}\n ${m}\n\n float value = ${s};\n int pad = 0;\n bool isPad = false;\n for (int i = 0; i < ${a}; i++) {\n offsetToIndices(i, kernelStrides, offset);\n isPad = false;\n for (int j = ${o} - ${l}; j < ${o}; j++) {\n x[j] = indices[j] * strides[j - ${o} + ${l}]\n + offset[j - ${o} + ${l}] - pads[j - 2];\n ${b}\n }\n ${r}\n\n return value;\n }\n `}},p=(t,e)=>{let n="";for(let r=0;r<t.length;r++)n+=`\n ${e}[${r}] = ${t[r]};\n `;return n},f=t=>`\n void offsetToIndices(int offset, int[${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 }`},4939:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.reduceLogSumSquare=e.reduceLogSum=e.reduceProd=e.reduceMin=e.reduceMax=e.reduceMean=e.reduceSum=e.parseReduceAttributes=void 0;const r=n(246),i=n(782),s=n(2517),o=n(2039),a=(t,e,n,r,i)=>{l(e);const s={name:r,inputNames:["A"],inputTypes:[o.TextureType.unpacked]};return[t.run(Object.assign(Object.assign({},s),{cacheHint:n.cacheKey,get:()=>u(t,e,n,r,i,s)}),e)]};e.parseReduceAttributes=t=>{const e=t.attributes.getInts("axes",[]),n=1===t.attributes.getInt("keepdims",1);return(0,r.createAttributeWithCacheKey)({axes:e,keepDims:n})};const u=(t,e,n,r,i,a)=>{const u=[],l=e[0].dims.length||1,c=[],d=s.ShapeUtil.normalizeAxes(n.axes,e[0].dims.length),h=i(e,d);let p=h[1];for(let t=0;t<e[0].dims.length;t++)d.indexOf(t)>=0||0===d.length?(n.keepDims&&u.push(1),p=`\n for(int j${t} = 0; j${t} < ${e[0].dims[t]}; j${t}++) {\n inputIdx[${t}] = j${t};\n ${p}\n }`):(c.push(`inputIdx[${t}] = outputIdx[${u.length}];`),u.push(e[0].dims[t]));const f=`\n float process(int outputIdx[${u.length||1}]) {\n float value; // final result\n int inputIdx[${l}]; // addressing input data\n ${c.join("\n")}\n ${h[0]} // init ops for reduce max/min\n ${p}\n ${h[2]} // final computation for reduce mean\n return value;\n }`;return Object.assign(Object.assign({},a),{output:{dims:u,type:e[0].type,textureType:o.TextureType.unpacked},shaderSource:f})},l=t=>{if(!t||1!==t.length)throw new Error("Reduce op requires 1 input.");if(-1===i.NUMBER_TYPES.indexOf(t[0].type))throw new Error("Invalid input type.")};e.reduceSum=(t,e,n)=>a(t,e,n,"ReduceSum",(()=>["value = 0.0;","value += _A(inputIdx);",""])),e.reduceMean=(t,e,n)=>a(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 /= ${n}.;`]})),e.reduceMax=(t,e,n)=>a(t,e,n,"ReduceMax",((t,e)=>{const n=[];for(let r=0;r<t[0].dims.length;r++)(e.indexOf(r)>=0||0===e.length)&&n.push(`inputIdx[${r}] = 0;`);return[`${n.join("\n")}\nvalue = _A(inputIdx);`,"value = max(value, _A(inputIdx));",""]})),e.reduceMin=(t,e,n)=>a(t,e,n,"ReduceMin",((t,e)=>{const n=[];for(let r=0;r<t[0].dims.length;r++)(e.indexOf(r)>=0||0===e.length)&&n.push(`inputIdx[${r}] = 0;`);return[`${n.join("\n")}\nvalue = _A(inputIdx);`,"value = min(value, _A(inputIdx));",""]})),e.reduceProd=(t,e,n)=>a(t,e,n,"ReduceProd",(()=>["value = 1.0;","value *= _A(inputIdx);",""])),e.reduceLogSum=(t,e,n)=>a(t,e,n,"ReduceLogSum",(()=>["value = 0.0;","value += _A(inputIdx);","value = log(value);"])),e.reduceLogSumSquare=(t,e,n)=>a(t,e,n,"ReduceLogSumSquare",(()=>["float t; value = 0.0;","t = _A(inputIdx); value += t * t;",""]))},7019:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.isReshapeCheap=e.processDims3D=e.createPackedReshape3DProgramInfoLoader=void 0;const r=n(2517),i=n(5060),s=n(2039),o=n(2827);e.createPackedReshape3DProgramInfoLoader=(t,e,n)=>{const a=(t=>({name:"Reshape (packed)",inputTypes:[s.TextureType.packed],inputNames:["A"],cacheHint:`${t}`}))(n);return Object.assign(Object.assign({},a),{get:()=>((t,e,n,a)=>{const u=e.dims,l=a;let c="";for(let t=0;t<4;t++){let e="";switch(t){case 0:e="outputCoords = rc;";break;case 1:e="outputCoords = ivec3(rc.x, rc.y+1, rc.z);";break;case 2:e="outputCoords = ivec3(rc.x, rc.y, rc.z+1);";break;case 3:e="outputCoords = ivec3(rc.x, rc.y+1, rc.z+1);";break;default:throw new Error}c+=`\n ${e}\n ${t>0?"if(outputCoords.y < rows && outputCoords.z < cols){":""}\n int flattenedIndex = getFlattenedIndex(outputCoords);\n\n ivec3 inputRC = inputCoordsFromReshapedOutCoords(flattenedIndex);\n vec2 innerDims = vec2(float(inputRC.y),float(inputRC.z));\n\n result[${t}] = getChannel(getA(inputRC.x, inputRC.y, inputRC.z), innerDims);\n\n ${t>0?"}":""}\n `}const d=(0,i.getGlsl)(t.session.backend.glContext.version),h=`\n ${function(t){const e=r.ShapeUtil.computeStrides(t),n=["b","r","c"],i="index";return`\n ivec3 inputCoordsFromReshapedOutCoords(int index) {\n ${e.map(((t,r)=>`int ${n[r]} = ${i} / ${t}; ${r===e.length-1?`int ${n[r+1]} = ${i} - ${n[r]} * ${t}`:`index -= ${n[r]} * ${t}`};`)).join("")}\n return ivec3(b, r, c);\n }\n `}(u)}\n ${function(t){const e=r.ShapeUtil.computeStrides(t);return`\n int getFlattenedIndex(ivec3 coords) {\n // reverse y, z order\n return coords.x * ${e[0]} + coords.z * ${e[1]} + coords.y;\n }\n`}(l)}\n ${(0,o.unpackFromChannel)()}\n\n void main() {\n ivec3 rc = getOutputCoords();\n\n vec4 result = vec4(0.0);\n\n ivec3 outputCoords;\n int rows = ${l[2]};\n int cols = ${l[1]};\n\n ${c}\n ${d.output} = result;\n }\n `;return Object.assign(Object.assign({},n),{output:{dims:l,type:e.type,textureType:s.TextureType.packed},shaderSource:h,hasMain:!0})})(t,e,a,n)})},e.processDims3D=function(t){if(0===t.length)return[1,1,1];let e=1;for(let n=0;n<t.length-2;++n)e*=t[n];return[e,t.length>1?t[t.length-2]:1,t[t.length-1]]},e.isReshapeCheap=function(t,e){let n=!1;return n=0===t.length||0===e.length||(t.length<2||e.length<2?t[t.length-1]===e[e.length-1]:t[t.length-1]===e[e.length-1]&&t[t.length-2]===e[e.length-2]),n}},718:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.reshape=void 0;const r=n(2517);e.reshape=(t,e)=>{const n=r.ShapeUtil.calculateReshapedDims(e[0].dims,e[1].integerData);return t.session.pack?[t.reshapePacked(e[0],n)]:[t.reshapeUnpacked(e[0],n)]}},2268:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.parseResizeAttributesV11=e.parseResizeAttributesV10=e.resize=void 0;const r=n(5060),i=n(2039),s=n(9390),o=n(2827),a=n(9793),u={name:"Resize",inputNames:["A"],inputTypes:[i.TextureType.packed]};e.resize=(t,e,n)=>((0,a.validateInputs)(e,n),[t.run(Object.assign(Object.assign({},u),{cacheHint:n.cacheKey,get:()=>l(t,e,n)}),e)]),e.parseResizeAttributesV10=t=>(0,a.parseUpsampleAttributes)(t,10),e.parseResizeAttributesV11=t=>(0,a.parseUpsampleAttributes)(t,11);const l=(t,e,n)=>{const a=(0,r.getGlsl)(t.session.backend.glContext.version),[l,d]=c(e,n);if(l.every((t=>1===t))&&"tf_crop_and_resize"!==n.coordinateTransformMode)return Object.assign(Object.assign({},u),{output:{dims:d,type:e[0].type,textureType:i.TextureType.packed},hasMain:!0,shaderSource:`void main() {\n vec4 v = ${a.texture2D}(X, TexCoords);\n ${a.output} = v;\n }`});const h=d.length;if(h<2)throw new Error(`output dimension should be at least 2, but got ${h}`);const p=d[h-2],f=d[h-1],g=e[0].dims;if(h!==g.length)throw new Error(`output dimension should match input ${g.length}, but got ${h}`);const m=g[h-2],_=g[h-1],b=l[h-2],y=l[h-1];let w="";if("linear"!==n.mode)throw new Error(`resize (packed) does not support mode: '${n.mode}'`);switch(n.coordinateTransformMode){case"asymmetric":w="\n vec4 getSourceFracIndex(ivec4 coords) {\n return vec4(coords) / scaleWHWH;\n }\n ";break;case"half_pixel":w="\n vec4 getSourceFracIndex(ivec4 coords) {\n return (vec4(coords) + 0.5) / scaleWHWH - 0.5;\n }\n ";break;case"pytorch_half_pixel":w=`\n vec4 getSourceFracIndex(ivec4 coords) {\n vec4 fcoords = vec4(coords);\n return vec4(\n ${f}.0 > 1.0 ? (fcoords.x + 0.5) / scaleWHWH.x - 0.5 : 0.0,\n ${p}.0 > 1.0 ? (fcoords.y + 0.5) / scaleWHWH.y - 0.5 : 0.0,\n ${f}.0 > 1.0 ? (fcoords.z + 0.5) / scaleWHWH.z - 0.5 : 0.0,\n ${p}.0 > 1.0 ? (fcoords.w + 0.5) / scaleWHWH.w - 0.5 : 0.0\n );\n }\n `;break;case"align_corners":w=`\n vec4 getSourceFracIndex(ivec4 coords) {\n vec4 resized = vec4(${f}.0 - 1.0, ${p}.0 - 1.0, ${f}.0 - 1.0,\n ${p}.0 - 1.0);\n vec4 original = vec4(${_}.0 - 1.0, ${m}.0 - 1.0, ${_}.0 - 1.0,\n ${m}.0 - 1.0);\n vec4 new_scale = original / resized;\n return vec4(coords) * new_scale;\n }\n `;break;default:throw new Error(`resize (packed) does not support coordinateTransformMode: '${n.coordinateTransformMode}'`)}const v=(0,s.getCoordsDataType)(h),x=`\n const vec2 inputWH = vec2(${m}.0, ${_}.0);\n const vec4 scaleWHWH = vec4(float(${b}), float(${y}), float(${b}), float(${y}));\n ${(0,o.unpackFromChannel)()}\n ${w}\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 ${v} 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 < ${p-1};\n bool hasNextCol = rc.z < ${f-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 ${a.output} = vec4(newValue);\n }\n `;return Object.assign(Object.assign({},u),{output:{dims:d,type:e[0].type,textureType:i.TextureType.packed},hasMain:!0,shaderSource:x})},c=(t,e)=>{const n=t[0].dims;let r,i=e.scales;if(0===i.length){const s=t[e.scalesInputIdx];if(s&&0!==s.size){if(t[e.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");i=d(s,e.mode,e.isResize)}else{const s=t[e.sizesInputIdx];if(!s||0===s.size)throw new Error("Either scales or sizes MUST be provided as input.");r=Array.from(s.integerData),i=h(r,n,e.mode,e.isResize)}}else if(t[e.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");const s=r||n.map(((t,e)=>Math.floor(t*i[e])));return[i,s]},d=(t,e,n)=>{const r=Array.from(t.floatData);return(0,a.scalesValidation)(r,e,n),r},h=(t,e,n,r)=>{const i=e.length,s=new Array(i);for(let n=0,r=i;n<r;n++)if(0===e[n]){if(0!==t[n])throw new Error("Input dim is zero but required output dim is non-zero.");s[n]=1}else s[n]=t[n]/e[n];return(0,a.scalesValidation)(s,n,r),s}},8117:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.shape=void 0;const r=n(9162);e.shape=(t,e)=>(i(e),[new r.Tensor([e[0].dims.length],"int32",void 0,void 0,new Int32Array(e[0].dims))]);const i=t=>{if(!t||1!==t.length)throw new Error("Shape requires 1 input.")}},2278:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.sliceV10=e.parseSliceAttributes=e.slice=void 0;const r=n(246),i=n(782),s=n(2517),o=n(2039),a={name:"Slice",inputNames:["A"],inputTypes:[o.TextureType.unpacked]};e.slice=(t,e,n)=>(l(e),[t.run(Object.assign(Object.assign({},a),{cacheHint:n.cacheKey,get:()=>u(t,e[0],n)}),e)]),e.parseSliceAttributes=t=>{const e=t.attributes.getInts("starts"),n=t.attributes.getInts("ends"),i=t.attributes.getInts("axes",[]);return(0,r.createAttributeWithCacheKey)({starts:e,ends:n,axes:i})};const u=(t,e,n)=>{const r=0===n.axes.length?e.dims.slice(0).map(((t,e)=>e)):n.axes,i=s.ShapeUtil.normalizeAxes(r,e.dims.length),u=n.starts.map(((t,n)=>t>e.dims[i[n]]-1?e.dims[i[n]]:s.ShapeUtil.normalizeAxis(t,e.dims[i[n]]))),l=n.ends.map(((t,n)=>t>e.dims[i[n]]-1?e.dims[i[n]]:s.ShapeUtil.normalizeAxis(t,e.dims[i[n]]))),c=e.dims.slice(),d=[];for(let t=0;t<i.length;t++)c[i[t]]=l[t]-u[t],u[t]>0&&d.push(`outputIdx[${i[t]}] += ${u[t]};`);const h=`\n float process(int outputIdx[${c.length}]) {\n ${d.join("\n ")}\n return _A(outputIdx);\n }`;return Object.assign(Object.assign({},a),{output:{dims:c,type:e.type,textureType:o.TextureType.unpacked},shaderSource:h})},l=t=>{if(!t||1!==t.length)throw new Error("Slice requires 1 input.");if(-1===i.NUMBER_TYPES.indexOf(t[0].type))throw new Error("Invalid input type.")};e.sliceV10=(t,e)=>{d(e);const n=c(t,e);return[t.run(Object.assign(Object.assign({},a),{cacheHint:n.cacheKey,get:()=>u(t,e[0],n)}),[e[0]])]};const c=(t,e)=>{if(!t.session.isInitializer(e[1].dataId)||!t.session.isInitializer(e[2].dataId)||e.length>=4&&!t.session.isInitializer(e[3].dataId)||e.length>=5&&!t.session.isInitializer(e[4].dataId))throw new Error("dynamic slice attributes are not allowed");if(e.length>=5&&e[4].integerData.some((t=>1!==t)))throw new Error("currently non-1 steps is not supported for Slice");const n=Array.from(e[1].integerData),r=Array.from(e[2].integerData),i=e.length>=4?Array.from(e[3].integerData):[];return{starts:n,ends:r,axes:i,cacheKey:`${i};${n};${r}`}},d=t=>{if(!t||t.length<3||t.length>5)throw new Error("Invalid input number.");if("int32"!==t[1].type||1!==t[1].dims.length)throw new Error("Invalid input type.");if("int32"!==t[2].type||1!==t[2].dims.length)throw new Error("Invalid input type.");if(t.length>=4&&("int32"!==t[3].type||1!==t[3].dims.length))throw new Error("Invalid input type.");if(t.length>=5&&("int32"!==t[4].type||1!==t[4].dims.length))throw new Error("Invalid input type.")}},5524:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.softmaxV13=e.parseSoftmaxAttributesV13=e.parseSoftmaxAttributes=e.softmax=void 0;const r=n(246),i=n(2517),s=n(5060),o=n(2039),a=n(3738),u={name:"SoftmaxComputeMax",inputNames:["A"],inputTypes:[o.TextureType.unpacked]},l={name:"SoftmaxComputeScale",inputNames:["A","Max"],inputTypes:[o.TextureType.unpacked,o.TextureType.unpacked]},c={name:"SoftMax",inputNames:["A","Max","Norm"],inputTypes:[o.TextureType.unpacked,o.TextureType.unpacked,o.TextureType.unpacked]};e.softmax=(t,e,n)=>{g(e);const r=e[0].dims.slice(),s=i.ShapeUtil.normalizeAxis(n.axis,r.length),o=i.ShapeUtil.sizeToDimension(r,s),a=i.ShapeUtil.sizeFromDimension(r,s);return d(t,e,n,o,a)},e.parseSoftmaxAttributes=t=>(0,r.createAttributeWithCacheKey)({axis:t.attributes.getInt("axis",1)}),e.parseSoftmaxAttributesV13=t=>(0,r.createAttributeWithCacheKey)({axis:t.attributes.getInt("axis",-1)}),e.softmaxV13=(t,e,n)=>{g(e);const s=e[0].dims.slice(),o=i.ShapeUtil.normalizeAxis(n.axis,s.length),u=s.length,l=o!==u-1,c=[];let h,p=[],f=[];l&&(p=Array.from({length:u}).map(((t,e)=>e)),p[o]=u-1,p[u-1]=o,p.map((t=>c.push(s[t]))),h=(0,r.createAttributeWithCacheKey)({perm:p}),f=(0,a.transpose)(t,e,h));const m=l?i.ShapeUtil.sizeToDimension(c,u-1):i.ShapeUtil.sizeToDimension(s,u-1),_=l?i.ShapeUtil.sizeFromDimension(c,u-1):i.ShapeUtil.sizeFromDimension(s,u-1),b=d(t,l?f:e,n,m,_);return l?(0,a.transpose)(t,b,h):b};const d=(t,e,n,r,i)=>{const s=h(t,e[0],r,i,[r]),o=t.run(Object.assign(Object.assign({},u),{cacheHint:n.cacheKey,get:()=>s}),e),a=p(t,e[0],r,i,s.output.dims,[r]),d=t.run(Object.assign(Object.assign({},l),{cacheHint:n.cacheKey,get:()=>a}),[e[0],o]),g=f(t,e[0],r,i,s.output.dims,a.output.dims);return[t.run(Object.assign(Object.assign({},c),{cacheHint:n.cacheKey,get:()=>g}),[e[0],o,d])]},h=(t,e,n,r,i)=>{const[a,l]=t.calculateTextureWidthAndHeight(e.dims,o.TextureType.unpacked),c=i.length;if(n<1||r<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(1!==i.length)throw new Error("Dimensionality of the output should be 1");if(i[0]!==n)throw new Error("Shape of the output should be equal to logical row count");const d=(0,s.getGlsl)(t.session.backend.glContext.version),h=`\n float process(int[${c}] indices) {\n int logical_row_start_offset = indices[0] * ${r};\n\n float max = getColorAsFloat(${d.texture2D}(A, offsetToCoords(logical_row_start_offset, ${a},\n ${l} )));\n for(int i=1; i<${r}; ++i)\n {\n float current = getColorAsFloat(${d.texture2D}(A, offsetToCoords(logical_row_start_offset + i,\n ${a}, ${l})));\n if(current > max)\n max = current;\n }\n\n return max;\n }`;return Object.assign(Object.assign({},u),{output:{dims:i,type:e.type,textureType:o.TextureType.unpacked},shaderSource:h})},p=(t,e,n,r,i,a)=>{const[u,c]=t.calculateTextureWidthAndHeight(e.dims,o.TextureType.unpacked),d=a.length;if(n<1||r<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(1!==a.length)throw new Error("Dimensionality of the output should be 1");if(a[0]!==n)throw new Error("Shape of the output should be equal to logical row count");if(1!==i.length)throw new Error("Dimensionality of the intermediate results should be 1");if(i[0]!==n)throw new Error("Shape of the intermediate results should be equal to logical row count");const h=`\n float process(int[${d}] indices) {\n int logical_row_start_offset = indices[0] * ${r};\n\n float norm_factor = 0.0;\n float max = _Max(indices);\n for(int i=0; i<${r}; ++i)\n {\n norm_factor += exp(getColorAsFloat(${(0,s.getGlsl)(t.session.backend.glContext.version).texture2D}(A, offsetToCoords(logical_row_start_offset + i,\n ${u}, ${c}))) - max);\n }\n\n return norm_factor;\n }`;return Object.assign(Object.assign({},l),{output:{dims:a,type:e.type,textureType:o.TextureType.unpacked},shaderSource:h})},f=(t,e,n,r,i,s)=>{const[a,u]=t.calculateTextureWidthAndHeight(e.dims,o.TextureType.unpacked),l=e.dims.length;if(n<1||r<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(1!==i.length||1!==s.length)throw new Error("Dimensionality of the intermediate results should be 1");if(i[0]!==n||s[0]!==n)throw new Error("Shape of the intermediate results should be equal to logical row count");const d=`\n float process(int[${l}] indices) {\n\n // get offset of current logical tensor index from the 2-D texture coordinates (TexCoords)\n int offset = coordsToOffset(TexCoords, ${a}, ${u});\n\n //determine the logical row for this index\n int logical_row_index[1];\n logical_row_index[0] = offset / ${r};\n\n float norm_factor = _Norm(logical_row_index);\n\n // avoid possible division by 0\n // if norm_facor is 0, all elements are zero\n // if so, return 0\n if(norm_factor == 0.0)\n return 0.0;\n\n return exp(_A(indices) - _Max(logical_row_index)) / norm_factor;\n }`;return Object.assign(Object.assign({},c),{output:{dims:e.dims,type:e.type,textureType:o.TextureType.unpacked},shaderSource:d})},g=t=>{if(!t||1!==t.length)throw new Error("Softmax requires 1 input.");if("float32"!==t[0].type&&"float64"!==t[0].type)throw new Error("Invalid input type")}},5975:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.parseSplitAttributes=e.split=void 0;const r=n(246),i=n(2517),s=n(2039),o={name:"Split",inputNames:["A"],inputTypes:[s.TextureType.unpacked]};e.split=(t,e,n)=>{l(e);const r=i.ShapeUtil.normalizeAxis(n.axis,e[0].dims.length),s=a(t,e,r,n),c=[];for(let i=0;i<s;++i)c.push(t.run(Object.assign(Object.assign({},o),{cacheHint:`${n.cacheKey};${i}`,get:()=>u(t,e[0],n,r,i)}),e));return c},e.parseSplitAttributes=t=>{const e=t.attributes.getInt("axis",0),n=t.attributes.getInts("split",[]),i=t.outputs.length;return(0,r.createAttributeWithCacheKey)({axis:e,split:n,numOutputs:i})};const a=(t,e,n,r)=>{const[,s]=i.SplitUtil.splitShape(e[0].dims,n,r.split,r.numOutputs);return s.length},u=(t,e,n,r,a)=>{const[u,l]=i.SplitUtil.splitShape(e.dims,r,n.split,n.numOutputs),c=l[a],d=u[a],h=`\n float process(int indices[${d.length}]) {\n indices[${r}] += ${c};\n return _A(indices);\n }\n `;return Object.assign(Object.assign({},o),{cacheHint:`${n.cacheKey}:${a}`,output:{dims:d,type:e.type,textureType:s.TextureType.unpacked},shaderSource:h})},l=t=>{if(!t||1!==t.length)throw new Error("Split requires one input.");if("int8"!==t[0].type&&"uint8"!==t[0].type&&"int16"!==t[0].type&&"uint16"!==t[0].type&&"int32"!==t[0].type&&"uint32"!==t[0].type&&"float32"!==t[0].type&&"float64"!==t[0].type&&"bool"!==t[0].type)throw new Error("Invalid input type.")}},3933:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.parseSqueezeAttributes=e.squeezeV13=e.squeeze=void 0;const r=n(2517);e.squeeze=(t,e,n)=>{i(e);const s=r.ShapeUtil.squeezeShape(e[0].dims,n);return[t.reshapeUnpacked(e[0],s)]},e.squeezeV13=(t,n)=>(s(n),(0,e.squeeze)(t,[n[0]],Array.from(n[1].integerData))),e.parseSqueezeAttributes=t=>t.attributes.getInts("axes");const i=t=>{if(!t||1!==t.length)throw new Error("Squeeze requires 1 input.");if("string"===t[0].type)throw new Error("invalid input tensor types.")},s=t=>{if(!t||2!==t.length)throw new Error("Squeeze requires 2 inputs.");if("int32"!==t[1].type)throw new Error("Invalid input type.")}},6558:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.sum=void 0;const r=n(5060),i=n(2039);e.sum=(t,e)=>{o(e);const n={name:"Sum",inputNames:e.map(((t,e)=>`X${e}`)),inputTypes:new Array(e.length).fill(i.TextureType.unpacked)};return[t.run(Object.assign(Object.assign({},n),{get:()=>s(t,e,n)}),e)]};const s=(t,e,n)=>{const s=(0,r.getGlsl)(t.session.backend.glContext.version),o=e[0].dims.slice(),a=`\n void main() {\n vec4 result = ${e.map(((t,e)=>`${s.texture2D}(X${e},TexCoords)`)).join(" + ")};\n ${s.output} = result;\n }\n `;return Object.assign(Object.assign({},n),{output:{dims:o,type:e[0].type,textureType:i.TextureType.unpacked},hasMain:!0,shaderSource:a})},o=t=>{if(!t||0===t.length)throw new Error("Sum requires inputs.");const e=t[0].dims.length;for(let n=1;n<t.length;n++){if(e!==t[n].dims.length)throw new Error("Input shapes are mismatched.");for(let r=0;r<e;r++)if(t[0].dims[r]!==t[n].dims[r])throw new Error("Input shapes are not matched.")}if("float32"!==t[0].type&&"float64"!==t[0].type)throw new Error("Invalid input type.");for(let e=1;e<t.length;e++)if(t[0].type!==t[e].type)throw new Error("Input types are not matched.")}},5723:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.tile=void 0;const r=n(782),i=n(2039);e.tile=(t,e)=>{o(e);const n={name:"Tile",inputNames:["A"],inputTypes:[i.TextureType.unpacked]};return[t.run(Object.assign(Object.assign({},n),{get:()=>s(t,e,n)}),e)]};const s=(t,e,n)=>{const r=e[0].dims.slice(),s=new Array(r.length),o=[];for(let t=0;t<r.length;t++)s[t]=r[t]*e[1].numberData[t],o.push(`inputIdx[${t}] = int(mod(float(outputIdx[${t}]), ${r[t]}.));`);const a=s.length,u=`\n float process(int outputIdx[${a}]) {\n int inputIdx[${a}];\n ${o.join("\n")}\n return _A(inputIdx);\n }\n `;return Object.assign(Object.assign({},n),{output:{dims:s,type:e[0].type,textureType:i.TextureType.unpacked},shaderSource:u})},o=t=>{if(!t||2!==t.length)throw new Error("Tile requires 2 input.");if(1!==t[1].dims.length)throw new Error("The second input shape must 1 dimension.");if(t[1].dims[0]!==t[0].dims.length)throw new Error("Invalid input shape.");if(-1===r.NUMBER_TYPES.indexOf(t[0].type))throw new Error("Invalid input type.");if("int32"!==t[1].type&&"int16"!==t[1].type)throw new Error("Invalid repeat type.")}},3738:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.parseTransposeAttributes=e.transpose=void 0;const r=n(246),i=n(2517),s=n(2039),o={name:"Transpose",inputNames:["A"],inputTypes:[s.TextureType.unpacked]};e.transpose=(t,e,n)=>(d(e),[t.run(Object.assign(Object.assign({},o),{cacheHint:n.cacheKey,get:()=>a(t,e[0],n.perm)}),e)]),e.parseTransposeAttributes=t=>(0,r.createAttributeWithCacheKey)({perm:t.attributes.getInts("perm",[])});const a=(t,e,n)=>{const r=e.dims;n=u(r,n);const i=l(r,n),a=r.length,d=`\n ${c("perm",n,a)}\n float process(int indices[${a}]) {\n int a[${a}];\n perm(a, indices);\n return _A(a);\n }`;return Object.assign(Object.assign({},o),{output:{dims:i,type:e.type,textureType:s.TextureType.unpacked},shaderSource:d})},u=(t,e)=>(e&&e.length!==t.length&&(e=[...t.keys()].reverse()),e),l=(t,e)=>(e=u(t,e),i.ShapeUtil.sortBasedOnPerm(t,e)),c=(t,e,n)=>{const r=[];r.push(`void ${t}(out int a[${n}], int src[${n}]) {`);for(let t=0;t<n;++t)r.push(`\ta[${e[t]}]=src[${t}];`);return r.push("\t}"),r.join("\n")},d=t=>{if(!t||1!==t.length)throw new Error("Transpose requires 1 input.");if("float32"!==t[0].type&&"float64"!==t[0].type)throw new Error("input should be float tensor")}},8710:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.encodeAsUint8=void 0;const r=n(5060),i=n(2039);e.encodeAsUint8=(t,e)=>{const n=e.shape,s=(0,r.getGlsl)(t.session.backend.glContext.version),o=`\n const float FLOAT_MAX = 1.70141184e38;\n const float FLOAT_MIN = 1.17549435e-38;\n\n bool isNaN(float val) {\n return (val < 1.0 || 0.0 < val || val == 0.0) ? false : true;\n }\n\n highp vec4 encodeAsUint8(highp float v) {\n if (isNaN(v)) {\n return vec4(255, 255, 255, 255);\n }\n\n highp float av = abs(v);\n\n if(av < FLOAT_MIN) {\n return vec4(0.0, 0.0, 0.0, 0.0);\n } else if(v > FLOAT_MAX) {\n return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;\n } else if(v < -FLOAT_MAX) {\n return vec4(0.0, 0.0, 128.0, 255.0) / 255.0;\n }\n\n highp vec4 c = vec4(0,0,0,0);\n\n highp float e = floor(log2(av));\n highp float m = exp2(fract(log2(av))) - 1.0;\n\n c[2] = floor(128.0 * m);\n m -= c[2] / 128.0;\n c[1] = floor(32768.0 * m);\n m -= c[1] / 32768.0;\n c[0] = floor(8388608.0 * m);\n\n highp float ebias = e + 127.0;\n c[3] = floor(ebias / 2.0);\n ebias -= c[3] * 2.0;\n c[2] += floor(ebias) * 128.0;\n\n c[3] += 128.0 * step(0.0, -v);\n\n return c / 255.0;\n }\n\n void main() {\n float value = ${s.texture2D}(X,TexCoords).r;\n ${s.output} = encodeAsUint8(value);\n 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I("cos")}function f(t){const e="elu";return{body:`\n const float alpha = float(${t});\n\n float ${e}_(float a) {\n return a >= 0.0 ? a: (exp(a) - 1.0) * alpha;\n }\n vec4 ${e}_(vec4 v) {\n return vec4(${e}_(v.x), ${e}_(v.y), ${e}_(v.z), ${e}_(v.w));\n }\n `,name:e,type:s.FunctionType.ValueBased}}function g(){return I("exp")}function m(){return I("floor")}function _(t,e){const n="clip";return{body:`\n const float min = float(${t});\n const float max = float(${e});\n\n float ${n}_(float a) {\n return clamp(a, min, max);\n }\n vec4 ${n}_(vec4 v) {\n return clamp(v, min, max);\n }\n `,name:n,type:s.FunctionType.ValueBased}}function b(){const t="indentity";return{body:`\n float ${t}_(float a) {\n return a;\n }\n vec4 ${t}_(vec4 v) {\n return v;\n }\n `,name:t,type:s.FunctionType.ValueBased}}function y(t){const e="leakyRelu";return{body:`\n const float alpha = float(${t});\n\n float ${e}_(float a) {\n return a < 0.0 ? a * alpha : a;\n }\n vec4 ${e}_(vec4 v) {\n return vec4(${e}_(v.x), 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i=this.gl,s=i.createTexture();i.bindTexture(i.TEXTURE_2D,s),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_MIN_FILTER,i.NEAREST),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_MAG_FILTER,i.NEAREST),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_WRAP_S,i.CLAMP_TO_EDGE),i.texParameteri(i.TEXTURE_2D,i.TEXTURE_WRAP_T,i.CLAMP_TO_EDGE);const o=r?n.encode(r,t*e):null;return i.texImage2D(i.TEXTURE_2D,0,n.internalFormat,t,e,0,n.format,n.textureType,o),this.checkError(),s}updateTexture(t,e,n,r,i){const s=this.gl;s.bindTexture(s.TEXTURE_2D,t);const o=r.encode(i,e*n);s.texSubImage2D(s.TEXTURE_2D,0,0,0,e,n,r.format,r.textureType,o),this.checkError()}attachFramebuffer(t,e,n){const r=this.gl;r.bindTexture(r.TEXTURE_2D,t),r.bindFramebuffer(r.FRAMEBUFFER,this.framebuffer),r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,t,0),this.checkError(),r.viewport(0,0,e,n),r.scissor(0,0,e,n)}readTexture(t,e,n,r,i,s){const o=this.gl;s||(s=1),this.frameBufferBound||this.attachFramebuffer(t,e,n);const a=this.getEncoder(i,s),u=a.allocate(e*n);return o.bindTexture(o.TEXTURE_2D,t),o.framebufferTexture2D(o.FRAMEBUFFER,o.COLOR_ATTACHMENT0,o.TEXTURE_2D,t,0),o.readPixels(0,0,e,n,o.RGBA,a.textureType,u),this.checkError(),a.decode(u,r)}isFramebufferReady(){return!0}getActiveTexture(){const t=this.gl;return"TEXTURE"+(t.getParameter(this.gl.ACTIVE_TEXTURE)-t.TEXTURE0)}getTextureBinding(){return this.gl.getParameter(this.gl.TEXTURE_BINDING_2D)}getFramebufferBinding(){return this.gl.getParameter(this.gl.FRAMEBUFFER_BINDING)}setVertexAttributes(t,e){const n=this.gl;n.vertexAttribPointer(t,3,n.FLOAT,!1,20,0),n.enableVertexAttribArray(t),-1!==e&&(n.vertexAttribPointer(e,2,n.FLOAT,!1,20,12),n.enableVertexAttribArray(e)),this.checkError()}createProgram(t,e){const n=this.gl,r=n.createProgram();return n.attachShader(r,t),n.attachShader(r,e),n.linkProgram(r),r}compileShader(t,e){const n=this.gl,r=n.createShader(e);if(!r)throw new Error(`createShader() returned null with type ${e}`);if(n.shaderSource(r,t),n.compileShader(r),!1===n.getShaderParameter(r,n.COMPILE_STATUS))throw new Error(`Failed to compile shader: ${n.getShaderInfoLog(r)}\nShader source:\n${t}`);return r}deleteShader(t){this.gl.deleteShader(t)}bindTextureToUniform(t,e,n){const r=this.gl;r.activeTexture(r.TEXTURE0+e),this.checkError(),r.bindTexture(r.TEXTURE_2D,t),this.checkError(),r.uniform1i(n,e),this.checkError()}draw(){this.gl.drawArrays(this.gl.TRIANGLE_STRIP,0,4),this.checkError()}checkError(){if(o.env.debug){const t=this.gl,e=t.getError();let n="";switch(e){case t.NO_ERROR:return;case t.INVALID_ENUM:n="INVALID_ENUM";break;case t.INVALID_VALUE:n="INVALID_VALUE";break;case t.INVALID_OPERATION:n="INVALID_OPERATION";break;case t.INVALID_FRAMEBUFFER_OPERATION:n="INVALID_FRAMEBUFFER_OPERATION";break;case t.OUT_OF_MEMORY:n="OUT_OF_MEMORY";break;case t.CONTEXT_LOST_WEBGL:n="CONTEXT_LOST_WEBGL";break;default:n=`Unknown WebGL Error: ${e.toString(16)}`}throw new Error(n)}}deleteTexture(t){this.gl.deleteTexture(t)}deleteProgram(t){this.gl.deleteProgram(t)}getEncoder(t,e,n=0){if(2===this.version)return new a.RedFloat32DataEncoder(this.gl,e);switch(t){case"float":return 1===n||this.isRenderFloat32Supported?new a.RGBAFloatDataEncoder(this.gl,e):new a.RGBAFloatDataEncoder(this.gl,e,this.textureHalfFloatExtension.HALF_FLOAT_OES);case"int":throw new Error("not implemented");case"byte":return new a.Uint8DataEncoder(this.gl,e);default:throw new Error(`Invalid dataType: ${t}`)}}clearActiveTextures(){const t=this.gl;for(let e=0;e<this.maxTextureImageUnits;++e)t.activeTexture(t.TEXTURE0+e),t.bindTexture(t.TEXTURE_2D,null)}dispose(){if(this.disposed)return;const t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,null),t.deleteFramebuffer(this.framebuffer),t.bindBuffer(t.ARRAY_BUFFER,null),t.deleteBuffer(this.vertexbuffer),t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,null),t.finish(),this.disposed=!0}createDefaultGeometry(){return new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0])}createVertexbuffer(){const t=this.gl,e=t.createBuffer();if(!e)throw new Error("createBuffer() returned null");const n=this.createDefaultGeometry();return t.bindBuffer(t.ARRAY_BUFFER,e),t.bufferData(t.ARRAY_BUFFER,n,t.STATIC_DRAW),this.checkError(),e}createFramebuffer(){const t=this.gl.createFramebuffer();if(!t)throw new Error("createFramebuffer returned null");return t}queryVitalParameters(){const t=this.gl;if(this.isFloatTextureAttachableToFrameBuffer=this.checkFloatTextureAttachableToFrameBuffer(),this.isRenderFloat32Supported=this.checkRenderFloat32(),this.isFloat32DownloadSupported=this.checkFloat32Download(),1===this.version&&!this.textureHalfFloatExtension&&!this.isRenderFloat32Supported)throw new Error("both float32 and float16 TextureType are not supported");this.isBlendSupported=!this.isRenderFloat32Supported||this.checkFloat32Blend(),this.maxTextureSize=t.getParameter(t.MAX_TEXTURE_SIZE),this.maxTextureImageUnits=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS),this.version}getExtensions(){2===this.version?(this.colorBufferFloatExtension=this.gl.getExtension("EXT_color_buffer_float"),this.disjointTimerQueryWebgl2Extension=this.gl.getExtension("EXT_disjoint_timer_query_webgl2")):(this.textureFloatExtension=this.gl.getExtension("OES_texture_float"),this.textureHalfFloatExtension=this.gl.getExtension("OES_texture_half_float"))}checkFloatTextureAttachableToFrameBuffer(){const t=this.gl,e=t.createTexture();t.bindTexture(t.TEXTURE_2D,e);const n=2===this.version?t.RGBA32F:t.RGBA;t.texImage2D(t.TEXTURE_2D,0,n,1,1,0,t.RGBA,t.FLOAT,null);const r=t.createFramebuffer();t.bindFramebuffer(t.FRAMEBUFFER,r),t.framebufferTexture2D(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.TEXTURE_2D,e,0);const i=t.checkFramebufferStatus(t.FRAMEBUFFER)===t.FRAMEBUFFER_COMPLETE;return t.bindTexture(t.TEXTURE_2D,null),t.bindFramebuffer(t.FRAMEBUFFER,null),t.deleteTexture(e),t.deleteFramebuffer(r),i}checkRenderFloat32(){if(2===this.version){if(!this.colorBufferFloatExtension)return!1}else if(!this.textureFloatExtension)return!1;return this.isFloatTextureAttachableToFrameBuffer}checkFloat32Download(){if(2===this.version){if(!this.colorBufferFloatExtension)return!1}else{if(!this.textureFloatExtension)return!1;if(!this.gl.getExtension("WEBGL_color_buffer_float"))return!1}return this.isFloatTextureAttachableToFrameBuffer}checkFloat32Blend(){const t=this.gl;let e,n,r,i,s;try{e=t.createTexture(),n=t.createFramebuffer(),t.bindTexture(t.TEXTURE_2D,e);const o=2===this.version?t.RGBA32F:t.RGBA;return t.texImage2D(t.TEXTURE_2D,0,o,1,1,0,t.RGBA,t.FLOAT,null),t.bindFramebuffer(t.FRAMEBUFFER,n),t.framebufferTexture2D(t.FRAMEBUFFER,t.COLOR_ATTACHMENT0,t.TEXTURE_2D,e,0),t.enable(t.BLEND),r=t.createShader(t.VERTEX_SHADER),!!r&&(t.shaderSource(r,"void main(){}"),t.compileShader(r),i=t.createShader(t.FRAGMENT_SHADER),!!i&&(t.shaderSource(i,"precision highp float;void main(){gl_FragColor=vec4(0.5);}"),t.compileShader(i),s=t.createProgram(),!!s&&(t.attachShader(s,r),t.attachShader(s,i),t.linkProgram(s),t.useProgram(s),t.drawArrays(t.POINTS,0,1),t.getError()===t.NO_ERROR)))}finally{t.disable(t.BLEND),s&&t.deleteProgram(s),r&&t.deleteShader(r),i&&t.deleteShader(i),n&&(t.bindFramebuffer(t.FRAMEBUFFER,null),t.deleteFramebuffer(n)),e&&(t.bindTexture(t.TEXTURE_2D,null),t.deleteTexture(e))}}beginTimer(){if(2===this.version&&this.disjointTimerQueryWebgl2Extension){const t=this.gl,e=this.disjointTimerQueryWebgl2Extension,n=t.createQuery();return t.beginQuery(e.TIME_ELAPSED_EXT,n),n}throw new Error("WebGL1 profiling currently not supported.")}endTimer(){if(2!==this.version||!this.disjointTimerQueryWebgl2Extension)throw new Error("WebGL1 profiling currently not supported");{const t=this.gl,e=this.disjointTimerQueryWebgl2Extension;t.endQuery(e.TIME_ELAPSED_EXT)}}isTimerResultAvailable(t){let e=!1,n=!1;if(2!==this.version||!this.disjointTimerQueryWebgl2Extension)throw new Error("WebGL1 profiling currently not supported");{const r=this.gl,i=this.disjointTimerQueryWebgl2Extension;e=r.getQueryParameter(t,r.QUERY_RESULT_AVAILABLE),n=r.getParameter(i.GPU_DISJOINT_EXT)}return e&&!n}getTimerResult(t){let e=0;if(2!==this.version)throw new Error("WebGL1 profiling currently not supported");{const n=this.gl;e=n.getQueryParameter(t,n.QUERY_RESULT),n.deleteQuery(t)}return e/1e6}async waitForQueryAndGetTime(t){return await(0,u.repeatedTry)((()=>this.isTimerResultAvailable(t))),this.getTimerResult(t)}async createAndWaitForFence(){const t=this.createFence(this.gl);return this.pollFence(t)}createFence(t){let e;const n=t,r=n.fenceSync(n.SYNC_GPU_COMMANDS_COMPLETE,0);return t.flush(),e=null===r?()=>!0:()=>{const t=n.clientWaitSync(r,0,0);return t===n.ALREADY_SIGNALED||t===n.CONDITION_SATISFIED},{query:r,isFencePassed:e}}async pollFence(t){return new Promise((e=>{this.addItemToPoll((()=>t.isFencePassed()),(()=>e()))}))}pollItems(){const t=l(this.itemsToPoll.map((t=>t.isDoneFn)));for(let e=0;e<=t;++e){const{resolveFn:t}=this.itemsToPoll[e];t()}this.itemsToPoll=this.itemsToPoll.slice(t+1)}async addItemToPoll(t,e){this.itemsToPoll.push({isDoneFn:t,resolveFn:e}),this.itemsToPoll.length>1||await(0,u.repeatedTry)((()=>(this.pollItems(),0===this.itemsToPoll.length)))}}},1036:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.ExecutionPlan=void 0;const r=n(6231);class i{constructor(t,e){this.op=t,this.node=e}}e.ExecutionPlan=class{constructor(t,e,n){this.graph=t,this.profiler=n,this.initialize(e)}initialize(t){this.profiler.event("session","ExecutionPlan.initialize",(()=>{const e=this.graph.getNodes();if(e.length!==t.length)throw new Error("The size of nodes and OPs do not match.");this._ops=t.map(((t,n)=>new i(t,e[n]))),this.reset(),this._starter=[],this._ops.forEach(((t,e)=>{let n=!0;for(const e of t.node.inputs)if(!this._values[e]&&-1===this.graph.getInputIndices().indexOf(e)){n=!1;break}n&&this._starter.push(e)}))}))}reset(){this._values=this.graph.getValues().map((t=>t.tensor))}async execute(t,e){return this.profiler.event("session","ExecutionPlan.execute",(async()=>{this.reset();const n=t.createInferenceHandler(),i=this.graph.getInputIndices();if(e.length!==i.length)throw new Error(`number of input tensors don't match the number of inputs to the model: actual: ${e.length} expected: ${i.length}`);e.forEach(((t,e)=>{const n=i[e];this._values[n]=t}));const s=this._starter.slice(0),o=this.graph.getValues(),a=this.graph.getNodes();let u=0;for(;u<s.length;){const t=s[u++],e=this._ops[t],i=e.node.inputs.map((t=>this._values[t]));if(-1!==i.indexOf(void 0))throw new Error(`unresolved input detected: op: ${e.node}`);const l=i;r.Logger.verbose("ExecPlan",`Runing op:${e.node.name} (${l.map(((t,n)=>`'${e.node.inputs[n]}': ${t.type}[${t.dims.join(",")}]`)).join(", ")})`);const c=await this.profiler.event("node",e.node.name,(async()=>e.op.impl(n,l,e.op.context)));if(c.length!==e.node.outputs.length)throw new Error("the size of output does not match model definition.");c.forEach(((t,n)=>{const r=e.node.outputs[n];if(this._values[r])throw new Error(`output [${r}] already has value: op:${e.node.name}`);this._values[r]=t}));const d=new Set;c.forEach(((t,n)=>{const r=e.node.outputs[n];for(const t of o[r].to){const e=a[t];let n=!0;for(const t of e.inputs)if(!this._values[t]){n=!1;break}n&&d.add(t)}})),s.push(...d)}const l=[];for(let t=0;t<this.graph.getOutputIndices().length;t++){const e=this.graph.getOutputIndices()[t],n=this._values[e];if(void 0===n)throw new Error(`required output [${e}] does not have value`);0===e?await n.getData():n.data,l.push(n)}return r.Logger.verbose("ExecPlan","disposing of inferenceHandler"),n.dispose(),l}))}}},7070:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.Graph=void 0;const r=n(1446),i=n(7778),s=n(9395),o=n(9162),a=n(2517);var u=s.onnxruntime.experimental.fbs;e.Graph={from:(t,e)=>new d(t,e)};class l{constructor(t){this._from=void 0,this._to=[],this.tensor=void 0,this.type=void 0,t&&(this.type=a.ProtoUtil.tensorValueTypeFromProto(t.type.tensorType))}get from(){return this._from}get to(){return this._to}}class c{constructor(t,e){t instanceof r.onnx.NodeProto?(this.name=t.name,this.opType=t.opType,this.attributes=new i.Attribute(t.attribute)):t instanceof u.Node&&(this.name=null!=e?e:t.name(),this.opType=t.opType(),this.attributes=new i.Attribute(a.ProtoUtil.tensorAttributesFromORTFormat(t))),this.inputs=[],this.outputs=[],this.executeNode=!0}}class d{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 this._allOutputIndices}getOutputNames(){return this._allOutputNames}getValues(){return this._allData}getNodes(){return this._nodes}buildGraph(t){if(t instanceof r.onnx.GraphProto)this.buildGraphFromOnnxFormat(t);else{if(!(t instanceof u.Graph))throw new TypeError("Graph type is not supported.");this.buildGraphFromOrtFormat(t)}}buildGraphFromOnnxFormat(t){const e=new Map;this._allData=[],this._allInputIndices=[],this._allInputNames=[],this._allOutputIndices=[],this._allOutputNames=[],this._nodes=[];const n=new Map;if(!t.input)throw new Error("missing information in graph: input");const r=[];for(const n of t.input){if(e.has(n.name))throw new Error(`duplicated input name: ${n.name}`);const t=this._allData.push(new l(n))-1;e.set(n.name,t),r.push(n.name)}if(!t.initializer)throw new Error("missing information in graph: initializer");for(const n of t.initializer){let t=e.get(n.name);if(void 0===t){const r=new l;r.type={shape:{dims:a.ProtoUtil.tensorDimsFromProto(n.dims)},tensorType:a.ProtoUtil.tensorDataTypeFromProto(n.dataType)},t=this._allData.push(r)-1,e.set(n.name,t)}this._allData[t]._from=-1,this._allData[t].tensor=o.Tensor.fromProto(n)}for(let t=0;t<this._allData.length;t++)this._allData[t].tensor||(this._allInputIndices.push(t),this._allInputNames.push(r[t]));if(!t.output)throw new Error("missing information in graph: output");for(const n of t.output){if(e.has(n.name))throw new Error(`duplicated output name: ${n.name}`);const t=this._allData.push(new l(n))-1;e.set(n.name,t),this._allOutputIndices.push(t),this._allOutputNames.push(n.name)}if(!t.node)throw new Error("missing information in graph: node");for(const e of t.node){if(!e.name)for(let t=0;;t++){const r=`unnamed_${e.opType}_${t}`;if(!n.has(r)){e.name=r;break}}if(n.has(e.name))throw new Error(`duplicated node name: ${e.name}`);const t=this._nodes.push(new c(e))-1;n.set(e.name,t)}for(let n=0;n<this._nodes.length;n++){const r=this._nodes[n],i=t.node[n];if(!i.output)throw new Error(`missing output for node: ${i.name}`);for(const t of i.output){let s=e.get(t);if(void 0===s&&(s=this._allData.push(new l)-1,e.set(t,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(!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[s]._from=-1,this._allData[s].tensor=o.Tensor.fromProto(i.attribute[0].t)}}}for(let n=0;n<this._nodes.length;n++){const r=this._nodes[n],i=t.node[n];if(!i.input)throw new Error(`missing input for node: ${i.name}`);for(const t of i.input){const s=e.get(t);if(void 0===s){if(""===t&&3===i.input.length&&"Resize"===i.opType)continue;throw new Error(`unrecognized input '${t}' for node: ${i.name}`)}r.inputs.push(s),this._allData[s]._to.push(n)}}return!0}buildGraphFromOrtFormat(t){var e,n,r;const i=new Map;this._allData=[],this._allInputIndices=[],this._allInputNames=[],this._allOutputIndices=[],this._allOutputNames=[],this._nodes=[];const s=new Map,d=[];for(let s=0;s<t.inputsLength();s++){const o=t.inputs(s);if(i.has(o))throw new Error(`duplicated input name: ${o}`);for(let s=0;s<t.nodeArgsLength();s++)if((null===(e=t.nodeArgs(s))||void 0===e?void 0:e.name())===o){const e=new l;if((null===(r=null===(n=t.nodeArgs(s))||void 0===n?void 0:n.type())||void 0===r?void 0:r.valueType())!==u.TypeInfoValue.tensor_type)throw new Error("Unexpected value type for the nodeArg.");const c=t.nodeArgs(s).type().value(new u.TensorTypeAndShape),h=a.ProtoUtil.tensorDataTypeFromProto(c.elemType()),p=c.shape(),f=[];for(let t=0;t<p.dimLength();t++)f.push(a.LongUtil.longToNumber(p.dim(t).value().dimValue()));e.type={shape:{dims:f},tensorType:h};const g=this._allData.push(e)-1;i.set(o,g),d.push(o)}}for(let e=0;e<t.initializersLength();e++){const n=t.initializers(e);let r=i.get(n.name());if(void 0===r){const t=new l,e=a.ProtoUtil.tensorDimsFromORTFormat(n),s=a.ProtoUtil.tensorDataTypeFromProto(n.dataType());t.type={shape:{dims:e},tensorType:s},r=this._allData.push(t)-1,i.set(n.name(),r)}this._allData[r]._from=-1,this._allData[r].tensor=o.Tensor.fromOrtTensor(n)}for(let t=0;t<this._allData.length;t++)this._allData[t].tensor||(this._allInputIndices.push(t),this._allInputNames.push(d[t]));for(let e=0;e<t.outputsLength();e++){const n=t.outputs(e);if(i.has(n))throw new Error(`duplicated output name: ${n}`);const r=this._allData.push(new l)-1;i.set(n,r),this._allOutputIndices.push(r),this._allOutputNames.push(n)}if(!t.nodes)throw new Error("missing information in graph: node");for(let e=0;e<t.nodesLength();e++){const n=t.nodes(e);let r=n.name();if(!r)for(let t=0;r=`unnamed_${n.opType()}_${t}`,s.has(r);t++);if(s.has(r))throw new Error(`duplicated node name: ${r}`);const i=this._nodes.push(new c(n,r))-1;s.set(r,i)}for(let e=0;e<this._nodes.length;e++){const n=this._nodes[e],r=t.nodes(e);if(null==r)throw new Error(`No node exists at index ${e}`);if(0===(null==r?void 0:r.outputsLength()))throw new Error(`missing output for node: ${r.name}`);for(let t=0;t<(null==r?void 0:r.outputsLength());t++){const s=null==r?void 0:r.outputs(t);let a=i.get(s);if(void 0===a&&(a=this._allData.push(new l)-1,i.set(s,a)),n.outputs.push(a),void 0!==this._allData[a]._from)throw new Error(`multiple nodes output to one data value: ${a}`);if(this._allData[a]._from=e,"Constant"===r.opType()){if(1!==r.attributesLength()||!r.attributes(0).t())throw new Error("missing attributes or missing tensor value in attributes for this Constant operator");if(1!==r.outputsLength())throw new Error("missing output or incorrect number of outputs for this Constant operator");n.outputs.pop(),n.executeNode=!1,this._allData[a]._from=-1,this._allData[a].tensor=o.Tensor.fromOrtTensor(r.attributes(0).t())}}}for(let e=0;e<this._nodes.length;e++){const n=this._nodes[e],r=t.nodes(e);if(0===r.inputsLength())throw new Error(`missing input for node: ${r.name}`);for(let t=0;t<r.inputsLength();t++){const s=r.inputs(t),o=i.get(s);if(void 0===o)throw new Error(`unrecognized input '${s}' for node: ${r.name()}`);n.inputs.push(o),this._allData[o]._to.push(e)}}}checkIsAcyclic(){const t=new Set;this._allInputIndices.forEach((e=>{this._allData[e]._to.forEach((e=>{t.add(e)}))}));const e=Array.from(t),n=new Array(this._nodes.length).fill("white");for(;e.length>0;){const t=e.pop();"gray"===n[t]?n[t]="black":(e.push(t),n[t]="gray",this._nodes[t].outputs.forEach((r=>{const i=this._allData[r];if(void 0!==i.tensor)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 cyclic");"white"===n[t]&&e.push(t)}))})))}}transformGraph(t){this.removeAllIdentityNodes(),this.removeAllDropoutNodes(),this.fuseConvActivationNodes(),t&&t.transformGraph(this),this.finalizeGraph()}finalizeGraph(){let t=0;for(let e=0;e<this._nodes.length;e++)this._nodes[e].executeNode?t>0&&(this._nodes[e].inputs.forEach((n=>{const r=this._allData[n]._to.indexOf(e+t);-1!==r&&(this._allData[n]._to[r]=e)})),this._nodes[e].outputs.forEach((n=>{this._allData[n]._from&&this._allData[n]._from===e+t&&(this._allData[n]._from=e)}))):(t++,this._nodes[e].outputs.forEach((t=>{this._allData[t]._from=-2})),this._nodes.splice(e,1),e--);t=0;for(let e=0;e<this._allData.length;e++)if(-2!==this._allData[e].from||-1!==this._allOutputIndices.indexOf(e+t)){if(t>0){let n=-1;void 0!==this._allData[e].from&&-1!==this._allData[e].from?(n=this._nodes[this._allData[e].from].outputs.indexOf(e+t),-1!==n&&(this._nodes[this._allData[e].from].outputs[n]=e)):(n=this._allInputIndices.indexOf(e+t),-1!==n&&(this._allInputIndices[n]=e)),this._allData[e].to.forEach((r=>{n=this._nodes[r].inputs.indexOf(e+t),-1!==n&&(this._nodes[r].inputs[n]=e)})),0===this._allData[e].to.length&&(n=this._allOutputIndices.indexOf(e+t),-1!==n&&(this._allOutputIndices[n]=e))}}else t++,this._allData.splice(e,1),e--}deleteNode(t){const e=this._nodes[t];if(e.outputs.length>1)for(let t=1;t<e.outputs.length;t++)if(this._allData[e.outputs[t]].to.length>0)throw new Error("Node deletion with more than one output connected to other nodes is not supported. 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r=n(1670),i=n(9162);e.OnnxjsSessionHandler=class{constructor(t){this.session=t,this.inputNames=this.session.inputNames,this.outputNames=this.session.outputNames}async dispose(){}async run(t,e,n){const s=new Map;for(const e in t)if(Object.hasOwnProperty.call(t,e)){const n=t[e];s.set(e,new i.Tensor(n.dims,n.type,void 0,void 0,n.data))}const o=await this.session.run(s),a={};return o.forEach(((t,e)=>{a[e]=new r.Tensor(t.type,t.data,t.dims)})),a}startProfiling(){this.session.startProfiling()}endProfiling(){this.session.endProfiling()}}},6919:(t,e,n)=>{"use strict";Object.defineProperty(e,"__esModule",{value:!0}),e.Session=void 0;const r=n(7067),i=n(1296),s=n(7091),o=n(1036),a=n(6231),u=n(2644);e.Session=class{constructor(t={}){this._initialized=!1,this.backendHint=t.backendHint,this.profiler=a.Profiler.create(t.profiler),this.context={profiler:this.profiler,graphInputTypes:[],graphInputDims:[]}}get inputNames(){return this._model.graph.getInputNames()}get outputNames(){return this._model.graph.getOutputNames()}startProfiling(){this.profiler.start()}endProfiling(){this.profiler.stop()}async loadModel(t,e,n){await this.profiler.event("session","Session.loadModel",(async()=>{const o=await(0,s.resolveBackend)(this.backendHint);if(this.sessionHandler=o.createSessionHandler(this.context),this._model=new u.Model,"string"==typeof t){const e=t.endsWith(".ort");if("undefined"==typeof fetch){const n=await(0,i.promisify)(r.readFile)(t);this.initialize(n,e)}else{const n=await fetch(t),r=await n.arrayBuffer();this.initialize(new Uint8Array(r),e)}}else if(ArrayBuffer.isView(t))this.initialize(t);else{const r=new Uint8Array(t,e||0,n||t.byteLength);this.initialize(r)}}))}initialize(t,e){if(this._initialized)throw new Error("already initialized");this.profiler.event("session","Session.initialize",(()=>{const n=this.sessionHandler.transformGraph?this.sessionHandler:void 0;this._model.load(t,n,e),this.sessionHandler.onGraphInitialized&&this.sessionHandler.onGraphInitialized(this._model.graph),this.initializeOps(this._model.graph),this._executionPlan=new o.ExecutionPlan(this._model.graph,this._ops,this.profiler)})),this._initialized=!0}async run(t){if(!this._initialized)throw new Error("session not initialized yet");return this.profiler.event("session","Session.run",(async()=>{const e=this.normalizeAndValidateInputs(t),n=await this._executionPlan.execute(this.sessionHandler,e);return this.createOutput(n)}))}normalizeAndValidateInputs(t){const e=this._model.graph.getInputNames();if(Array.isArray(t)){if(t.length!==e.length)throw new Error(`incorrect input array length: expected ${e.length} but got ${t.length}`)}else{if(t.size!==e.length)throw new Error(`incorrect input map size: expected ${e.length} but got ${t.size}`);const n=new Array(t.size);let r=0;for(let i=0;i<e.length;++i){const s=t.get(e[i]);if(!s)throw new Error(`missing input tensor for: '${name}'`);n[r++]=s}t=n}if(this.context.graphInputTypes&&0!==this.context.graphInputTypes.length&&this.context.graphInputDims&&0!==this.context.graphInputDims.length)this.validateInputTensorDims(this.context.graphInputDims,t,!1);else{const e=this._model.graph.getInputIndices(),n=this._model.graph.getValues(),r=new Array(e.length);for(let i=0;i<e.length;++i){const s=n[e[i]];r[i]=s.type.shape.dims,this.context.graphInputTypes.push(s.type.tensorType),this.context.graphInputDims.push(t[i].dims)}this.validateInputTensorDims(r,t,!0)}return this.validateInputTensorTypes(this.context.graphInputTypes,t),t}validateInputTensorTypes(t,e){for(let n=0;n<e.length;n++){const r=t[n],i=e[n].type;if(r!==i)throw new Error(`input tensor[${n}] check failed: expected type '${r}' but got ${i}`)}}validateInputTensorDims(t,e,n){for(let r=0;r<e.length;r++){const i=t[r],s=e[r].dims;if(!this.compareTensorDims(i,s,n))throw new Error(`input tensor[${r}] check failed: expected shape '[${i.join(",")}]' but got [${s.join(",")}]`)}}compareTensorDims(t,e,n){if(t.length!==e.length)return!1;for(let r=0;r<t.length;++r)if(t[r]!==e[r]&&(!n||0!==t[r]))return!1;return!0}createOutput(t){const e=this._model.graph.getOutputNames();if(t.length!==e.length)throw new Error("expected number of outputs do not match number of generated outputs");const n=new Map;for(let r=0;r<e.length;++r)n.set(e[r],t[r]);return n}initializeOps(t){const e=t.getNodes();this._ops=new Array(e.length);for(let n=0;n<e.length;n++)this._ops[n]=this.sessionHandler.resolve(e[n],this._model.opsets,t)}}},9162:function(t,e,n){"use strict";var r=this&&this.__importDefault||function(t){return t&&t.__esModule?t:{default:t}};Object.defineProperty(e,"__esModule",{value:!0}),e.Tensor=void 0;const i=n(3442),s=r(n(3720)),o=n(1446),a=n(9395),u=n(2517);var l=a.onnxruntime.experimental.fbs;class c{get data(){if(void 0===this.cache){const t=this.dataProvider(this.dataId);if(t.length!==this.size)throw new Error("Length of data provided by the Data Provider is inconsistent with the dims of this Tensor.");this.cache=t}return this.cache}get stringData(){if("string"!==this.type)throw new TypeError("data type is not string");return this.data}get integerData(){switch(this.type){case"uint8":case"int8":case"uint16":case"int16":case"int32":case"uint32":case"bool":return this.data;default:throw new TypeError("data type is not integer (uint8, int8, uint16, int16, int32, uint32, bool)")}}get floatData(){switch(this.type){case"float32":case"float64":return this.data;default:throw new TypeError("data type is not float (float32, float64)")}}get numberData(){if("string"!==this.type)return this.data;throw new TypeError("type cannot be non-number (string)")}get(t){return this.data[u.ShapeUtil.indicesToOffset(t,this.strides)]}set(t,e){this.data[u.ShapeUtil.indicesToOffset(t,this.strides)]=e}async getData(){return void 0===this.cache&&(this.cache=await this.asyncDataProvider(this.dataId)),this.cache}get strides(){return this._strides||(this._strides=u.ShapeUtil.computeStrides(this.dims)),this._strides}constructor(t,e,n,r,s,o=i.Guid.create()){this.dims=t,this.type=e,this.dataProvider=n,this.asyncDataProvider=r,this.cache=s,this.dataId=o,this.size=u.ShapeUtil.validateDimsAndCalcSize(t);const a=this.size,l=void 0===n&&void 0===r&&void 0===s;if(void 0!==s&&s.length!==a)throw new RangeError("Input dims doesn't match data length.");if("string"===e){if(!(void 0===s||Array.isArray(s)&&s.every((t=>"string"==typeof t))))throw new TypeError("cache should be a string array");l&&(this.cache=new Array(a))}else{if(void 0!==s){const t=h(e);if(!(s instanceof t))throw new TypeError(`cache should be type ${t.name}`)}if(l){const t=new ArrayBuffer(a*function(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}`)}}(e));this.cache=function(t,e){return new(h(e))(t)}(t,e)}}}static fromProto(t){if(!t)throw new Error("cannot construct Value from an empty tensor");const e=u.ProtoUtil.tensorDataTypeFromProto(t.dataType),n=u.ProtoUtil.tensorDimsFromProto(t.dims),r=new c(n,e);if("string"===e)t.stringData.forEach(((t,e)=>{r.data[e]=(0,u.decodeUtf8String)(t)}));else if(t.rawData&&"number"==typeof t.rawData.byteLength&&t.rawData.byteLength>0){const e=r.data,n=new DataView(t.rawData.buffer,t.rawData.byteOffset,t.rawData.byteLength),i=d(t.dataType),s=t.rawData.byteLength/i;if(t.rawData.byteLength%i!=0)throw new Error("invalid buffer length");if(e.length!==s)throw new Error("buffer length mismatch");for(let r=0;r<s;r++){const s=f(n,t.dataType,r*i);e[r]=s}}else{let e;switch(t.dataType){case o.onnx.TensorProto.DataType.FLOAT:e=t.floatData;break;case o.onnx.TensorProto.DataType.INT32:case o.onnx.TensorProto.DataType.INT16:case o.onnx.TensorProto.DataType.UINT16:case o.onnx.TensorProto.DataType.INT8:case o.onnx.TensorProto.DataType.UINT8:case o.onnx.TensorProto.DataType.BOOL:e=t.int32Data;break;case o.onnx.TensorProto.DataType.INT64:e=t.int64Data;break;case o.onnx.TensorProto.DataType.DOUBLE:e=t.doubleData;break;case o.onnx.TensorProto.DataType.UINT32:case o.onnx.TensorProto.DataType.UINT64:e=t.uint64Data;break;default:throw new Error("unspecific error")}if(null==e)throw new Error("failed to populate data from a tensorproto value");const n=r.data;if(n.length!==e.length)throw new Error("array length mismatch");for(let r=0;r<e.length;r++){const i=e[r];s.default.isLong(i)?n[r]=p(i,t.dataType):n[r]=i}}return r}static fromData(t,e,n){return new c(e,n,void 0,void 0,t)}static fromOrtTensor(t){if(!t)throw new Error("cannot construct Value from an empty tensor");const e=u.ProtoUtil.tensorDimsFromORTFormat(t),n=u.ProtoUtil.tensorDataTypeFromProto(t.dataType()),r=new c(e,n);if("string"===n)for(let e=0;e<t.stringDataLength();e++)r.data[e]=t.stringData(e);else if(t.rawDataArray()&&"number"==typeof t.rawDataLength()&&t.rawDataLength()>0){const e=r.data,n=new DataView(t.rawDataArray().buffer,t.rawDataArray().byteOffset,t.rawDataLength()),i=d(t.dataType()),s=t.rawDataLength()/i;if(t.rawDataLength()%i!=0)throw new Error("invalid buffer length");if(e.length!==s)throw new Error("buffer length mismatch");for(let r=0;r<s;r++){const s=f(n,t.dataType(),r*i);e[r]=s}}return r}}function d(t){switch(t){case o.onnx.TensorProto.DataType.UINT8:case o.onnx.TensorProto.DataType.INT8:case o.onnx.TensorProto.DataType.BOOL:return 1;case o.onnx.TensorProto.DataType.UINT16:case o.onnx.TensorProto.DataType.INT16:return 2;case o.onnx.TensorProto.DataType.FLOAT:case o.onnx.TensorProto.DataType.INT32:case o.onnx.TensorProto.DataType.UINT32:return 4;case o.onnx.TensorProto.DataType.INT64:case o.onnx.TensorProto.DataType.DOUBLE:case o.onnx.TensorProto.DataType.UINT64:return 8;default:throw new Error(`cannot calculate sizeof() on type ${o.onnx.TensorProto.DataType[t]}`)}}function h(t){switch(t){case"bool":case"uint8":return Uint8Array;case"int8":return Int8Array;case"int16":return Int16Array;case"uint16":return Uint16Array;case"int32":return Int32Array;case"uint32":return Uint32Array;case"float32":return Float32Array;case"float64":return Float64Array;default:throw new Error("unspecified error")}}function p(t,e){if(e===o.onnx.TensorProto.DataType.INT64||e===l.TensorDataType.INT64){if(t.greaterThanOrEqual(2147483648)||t.lessThan(-2147483648))throw new TypeError("int64 is not supported")}else{if(e!==o.onnx.TensorProto.DataType.UINT32&&e!==l.TensorDataType.UINT32&&e!==o.onnx.TensorProto.DataType.UINT64&&e!==l.TensorDataType.UINT64)throw new TypeError(`not a LONG type: ${o.onnx.TensorProto.DataType[e]}`);if(t.greaterThanOrEqual(4294967296)||t.lessThan(0))throw new TypeError("uint64 is not supported")}return t.toNumber()}function f(t,e,n){switch(e){case o.onnx.TensorProto.DataType.BOOL:case o.onnx.TensorProto.DataType.UINT8:return t.getUint8(n);case o.onnx.TensorProto.DataType.INT8:return t.getInt8(n);case o.onnx.TensorProto.DataType.UINT16:return t.getUint16(n,!0);case o.onnx.TensorProto.DataType.INT16:return t.getInt16(n,!0);case o.onnx.TensorProto.DataType.FLOAT:return t.getFloat32(n,!0);case o.onnx.TensorProto.DataType.INT32:return t.getInt32(n,!0);case o.onnx.TensorProto.DataType.UINT32:return t.getUint32(n,!0);case o.onnx.TensorProto.DataType.INT64:return p(s.default.fromBits(t.getUint32(n,!0),t.getUint32(n+4,!0),!1),e);case o.onnx.TensorProto.DataType.DOUBLE:return t.getFloat64(n,!0);case o.onnx.TensorProto.DataType.UINT64:return p(s.default.fromBits(t.getUint32(n,!0),t.getUint32(n+4,!0),!0),e);default:throw new Error(`cannot read from DataView for type ${o.onnx.TensorProto.DataType[e]}`)}}e.Tensor=c},2517:function(t,e,n){"use strict";var r=this&&this.__importDefault||function(t){return t&&t.__esModule?t:{default:t}};Object.defineProperty(e,"__esModule",{value:!0}),e.decodeUtf8String=e.MAX_CLIP=e.MIN_CLIP=e.PoolConvUtil=e.ReduceUtil=e.SplitUtil=e.MathUtil=e.ShapeUtil=e.LongUtil=e.ProtoUtil=e.GemmUtil=e.arrayCopyHelper=e.BroadcastUtil=e.MatMulUtil=e.ArrayUtil=e.assert=e.checkInputsShape=void 0;const i=n(5686),s=r(n(3720)),o=n(1446),a=n(9162);e.checkInputsShape=function(t,...e){if(!t||t.length!==e.length)return!1;for(let n=0;n<t.length;n++)if(!t[n].dims||t[n].dims.length!==e[n])return!1;return!0},e.assert=function(t,e){if(!t)throw new Error("string"==typeof e?e:e())},e.ArrayUtil=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}};class u{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]]}}e.MatMulUtil=u;class l{static calcShape(t,e,n=!1){const r=t.length,i=e.length;if(0===r)return e;if(0===i)return t;const s=Math.max(t.length,e.length),o=new Array(s);if(n){if(r<2||i<2)return;const n=u.calcMatMulShape([t[r-2],t[r-1]],[e[i-2],e[i-1]]);if(void 0===n)return;[o[s-2],o[s-1]]=n}for(let a=n?3:1;a<=s;a++){const n=r-a<0?1:t[r-a],u=i-a<0?1:e[i-a];if(n!==u&&n>1&&u>1)return;o[s-a]=Math.max(n,u)}return o}static index(t,e){const n=new Array(e.length);return l.fillIndex(t,e,n),n}static fillIndex(t,e,n){const r=t.length-e.length;for(let i=0;i<e.length;i++)n[i]=t[r+i]%e[i]}static calc(t,e,n,r,i){const s=l.calcShape(t.dims,e.dims);if(s){if(r&&!h.areEqual(s,t.dims))return;const o=h.size(s),u=r?t:new a.Tensor(s,i||t.type);if(0===s.length)u.set([],n(t.get([]),e.get([])));else{const r=new Array(s.length),i=new Array(t.dims.length),a=new Array(e.dims.length);let c,d=0,h=0,p=!1,f=!1;0===t.dims.length&&(d=t.get([]),p=!0),0===e.dims.length&&(h=e.get([]),f=!0);for(let g=0;g<o;g++){c=g;for(let t=s.length-1;t>=0;t--)r[t]=c%s[t],c=Math.floor(c/s[t]);p||(l.fillIndex(r,t.dims,i),d=t.get(i)),f||(l.fillIndex(r,e.dims,a),h=e.get(a)),u.set(r,n(d,h))}}return u}}static isValidBroadcast(t,e){const 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){const n=t.length,r=[];for(let i=0;i<n;i++){const s=n-1-i,o=t[s]||1;(e[e.length-1-i]||1)>1&&1===o&&r.unshift(s)}return r}}e.BroadcastUtil=l,e.arrayCopyHelper=function(t,e,n,r,i){if(r<0||r>=e.length)throw new Error("sourceIndex out of bounds");if(n<0||n>=t.length)throw new Error("targetIndex out of bounds");if(r+i>e.length)throw new Error("source indices to be copied are outside bounds");if(n+i>t.length)throw new Error("target array is too small to hold result");for(let s=0;s<i;s++)t[n+s]=e[r+s]},e.GemmUtil=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 s,o,a;e?(s=t[1],o=t[0]):(s=t[0],o=t[1]);let u=-1;if(r?(a=n[0],u=1):(a=n[1],u=0),n[u]!==o)throw new Error("dimension mismatch");if(s<=0||a<=0||o<=0)throw new Error("invalid shape specified");if(i&&!l.isValidBroadcast(i,[s,a]))throw new Error("gemm: invalid bias shape for broadcast");return[s,a,o]}};class c{static tensorDataTypeFromProto(t){switch(t){case o.onnx.TensorProto.DataType.INT8:return"int8";case o.onnx.TensorProto.DataType.UINT8:return"uint8";case o.onnx.TensorProto.DataType.BOOL:return"bool";case o.onnx.TensorProto.DataType.INT16:return"int16";case o.onnx.TensorProto.DataType.UINT16:return"uint16";case o.onnx.TensorProto.DataType.INT32:return"int32";case o.onnx.TensorProto.DataType.UINT32:return"uint32";case o.onnx.TensorProto.DataType.FLOAT:return"float32";case o.onnx.TensorProto.DataType.DOUBLE:return"float64";case o.onnx.TensorProto.DataType.STRING:return"string";case o.onnx.TensorProto.DataType.INT64:return"int32";case o.onnx.TensorProto.DataType.UINT64:return"uint32";default:throw new Error(`unsupported data type: ${o.onnx.TensorProto.DataType[t]}`)}}static tensorDataTypeStringToEnum(t){switch(t){case"int8":return o.onnx.TensorProto.DataType.INT8;case"uint8":return o.onnx.TensorProto.DataType.UINT8;case"bool":return o.onnx.TensorProto.DataType.BOOL;case"int16":return o.onnx.TensorProto.DataType.INT16;case"uint16":return o.onnx.TensorProto.DataType.UINT16;case"int32":return o.onnx.TensorProto.DataType.INT32;case"uint32":return o.onnx.TensorProto.DataType.UINT32;case"float32":return o.onnx.TensorProto.DataType.FLOAT;case"float64":return o.onnx.TensorProto.DataType.DOUBLE;case"string":return o.onnx.TensorProto.DataType.STRING;case"int64":return o.onnx.TensorProto.DataType.INT64;case"uint64":return o.onnx.TensorProto.DataType.UINT64;default:throw new Error(`unsupported data type: ${t}`)}}static tensorDimsFromProto(t){return t.map((t=>s.default.isLong(t)?t.toNumber():t))}static tensorValueTypeFromProto(t){return{tensorType:c.tensorDataTypeFromProto(t.elemType),shape:{dims:c.tensorDimsFromProto(t.shape.dim.map((t=>t.dimValue)))}}}static tensorDimsFromORTFormat(t){const e=[];for(let n=0;n<t.dimsLength();n++)e.push(d.longToNumber(t.dims(n)));return e}static tensorAttributesFromORTFormat(t){const e=[];for(let n=0;n<t.attributesLength();n++)e.push(t.attributes(n));return e}}e.ProtoUtil=c;class d{static longToNumber(t,e){return s.default.isLong(t)?t.toNumber():t instanceof i.flatbuffers.Long?s.default.fromValue({low:t.low,high:t.high,unsigned:null!=e&&e}).toNumber():t}static isLong(t){return s.default.isLong(t)||t instanceof i.flatbuffers.Long}}e.LongUtil=d;class h{static size(t){return h.getSizeFromDimensionRange(t,0,t.length)}static sizeFromDimension(t,e){if(e<0||e>t.length)throw new Error(`invalid dimension of ${e} for sizeFromDimension as Tensor has ${t.length} dimensions.`);return h.getSizeFromDimensionRange(t,e,t.length)}static sizeToDimension(t,e){if(e<0||e>t.length)throw new Error(`invalid dimension of ${e} for sizeToDimension as Tensor has ${t.length} dimensions.`);return h.getSizeFromDimensionRange(t,0,e)}static getSizeFromDimensionRange(t,e,n){let r=1;for(let i=e;i<n;i++){if(t[i]<=0)throw new Error("cannot get valid size from specified dimension range. Most likely the range contains 0 or negative values in them.");r*=t[i]}return r}static computeStrides(t){const e=t.length;if(0===e)return[];if(1===e)return[1];const n=new Array(e);n[e-1]=1,n[e-2]=t[e-1];for(let r=e-3;r>=0;--r)n[r]=n[r+1]*t[r+1];return n}static transpose(t){return t.slice().reverse()}static indicesToOffset(t,e,n){void 0===n&&(n=t.length);let r=0;for(let i=0;i<n;++i)r+=e[i]*t[i];return r}static offsetToIndices(t,e){const n=e.length;if(0===n)return[];if(1===n)return[t*e[0]];const r=new Array(e.length);for(let n=0;n<r.length-1;++n)r[n]=Math.floor(t/e[n]),t-=r[n]*e[n];return r[r.length-1]=t,r}static normalizeAxis(t,e){if(t<-e&&t>=e)throw new Error("unsupported axis for this operation.");return t<0?t+e:t}static normalizeAxes(t,e){return t.map((t=>this.normalizeAxis(t,e)))}static incrementIndex(t,e,n){if(0===e.length||0===t.length)throw new Error("Index incrementing unsupported for scalar Tensor");if(void 0===n)n=e.length;else if(n<=0||n>e.length)throw new Error("Incorrect axis to increment on");for(let r=n-1;r>=0&&(t[r]++,!(t[r]<e[r]));--r)t[r]=0}static calculateReshapedDims(t,e){if(0===e.length){if(0===t.length||1===h.size(t))return[];throw new Error("cannot reshape to a scalar Tensor")}const n=e.length,r=new Array(n);let i=-1,s=1;for(let o=0;o<n;o++){if(e[o]<-1)throw new Error("a dimension in shape hints cannot be less than -1");if(-1===e[o]){if(-1!==i)throw new Error("at most one dimension in shape hints can be -1");i=o}else{if(0===e[o]){if(o>=t.length)throw new Error("the dimension with value zero exceeds the dimension size of the input tensor");r[o]=t[o]}else r[o]=e[o];s*=r[o]}}const o=h.size(t);if(-1!==i){if(o%s!=0)throw new Error(`the input tensor cannot be reshaped to the requested shape. Input shape: [${t}] Output shape: [${e}]`);r[i]=o/s}else if(s!==o)throw new Error("reshapedDims and originalDims don't have matching sizes");return r}static sortBasedOnPerm(t,e){return e?e.map((e=>t[e])):t.slice().reverse()}static padShape(t,e){const 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(const 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);const n=t.reduce(((t,e)=>t*e),1),r=t.slice(e).reduce(((t,e)=>t*e),1);return[n/r,r]}static squeezeShape(t,e){const n=new Array;e=h.normalizeAxes(e,t.length);for(let r=0;r<t.length;r++){const i=e.indexOf(r)>=0;if(i&&1!==t[r])throw new Error("squeeze an 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o=2*i,a=3*i,u=t[r],l=t[r+i],c=t[r+o],d=t[r+a],h=u+c,p=u-c,f=l+d,g=s*(l-d);e[n]=h+f,e[n+1]=0,e[n+2]=p,e[n+3]=-g,e[n+4]=h-f,e[n+5]=0,e[n+6]=p,e[n+7]=g}}class K{constructor(t){const e=2*(t-1),n=2*(2*t-1),r=2**Math.ceil(Math.log2(n));this.bufferSize=r,this._a=e;const i=new Float64Array(n),s=new Float64Array(r);this._chirpBuffer=new Float64Array(r),this._buffer1=new Float64Array(r),this._buffer2=new Float64Array(r),this._outBuffer1=new Float64Array(r),this._outBuffer2=new Float64Array(r);const o=-2*Math.PI/t,a=Math.cos(o),u=Math.sin(o);for(let e=0;e<n>>1;++e){const n=(e+1-t)**2/2,r=Math.sqrt(a**2+u**2)**n,o=n*Math.atan2(u,a),l=2*e;i[l]=r*Math.cos(o),i[l+1]=r*Math.sin(o),s[l]=i[l],s[l+1]=-i[l+1]}this._slicedChirpBuffer=i.subarray(e,n),this._f=new Y(r>>1),this._f.transform(this._chirpBuffer,s)}_transform(t,e,n){const r=this._buffer1,i=this._buffer2,s=this._outBuffer1,o=this._outBuffer2,a=this._chirpBuffer,u=this._slicedChirpBuffer,l=this._a;if(n)for(let t=0;t<u.length;t+=2){const n=t+1,i=e[t>>1];r[t]=i*u[t],r[n]=i*u[n]}else for(let t=0;t<u.length;t+=2){const n=t+1;r[t]=e[t]*u[t]-e[n]*u[n],r[n]=e[t]*u[n]+e[n]*u[t]}this._f.transform(s,r);for(let t=0;t<a.length;t+=2){const e=t+1;i[t]=s[t]*a[t]-s[e]*a[e],i[e]=s[t]*a[e]+s[e]*a[t]}this._f.inverseTransform(o,i);for(let e=0;e<o.length;e+=2){const n=o[e+l],r=o[e+l+1],i=u[e],s=u[e+1];t[e]=n*i-r*s,t[e+1]=n*s+r*i}}transform(t,e){this._transform(t,e,!1)}realTransform(t,e){this._transform(t,e,!0)}}class Z{constructor(t){this.fft_length=t,this.isPowerOfTwo=X(t),this.isPowerOfTwo?(this.fft=new Y(t),this.outputBufferSize=2*t):(this.fft=new K(t),this.outputBufferSize=this.fft.bufferSize)}realTransform(t,e){this.fft.realTransform(t,e)}transform(t,e){this.fft.transform(t,e)}}function J(t,e){if(e%2==0||e<=0)throw new Error("Window size must be a positive odd number");const n=new t.constructor(t.length),r=new t.constructor(e),i=Math.floor(e/2);for(let e=0;e<t.length;++e){let s=0;for(let n=-i;n<=i;++n){let i=e+n;i<0?i=Math.abs(i):i>=t.length&&(i=2*(t.length-1)-i),r[s++]=t[i]}r.sort(),n[e]=r[i]}return n}function Q(t,e){const n=Math.pow(10,e);return Math.round(t*n)/n}const tt=Object.freeze({float32:Float32Array,float64:Float64Array,string:Array,int8:Int8Array,uint8:Uint8Array,int16:Int16Array,uint16:Uint16Array,int32:Int32Array,uint32:Uint32Array,int64:BigInt64Array,uint64:BigUint64Array,bool:Uint8Array}),et=x.Tensor;class nt{dims;type;data;size;constructor(...t){return t[0]instanceof et?Object.assign(this,t[0]):Object.assign(this,new et(t[0],t[1],t[2])),new Proxy(this,{get:(t,e)=>{if("string"==typeof e){let n=Number(e);if(Number.isInteger(n))return t._getitem(n)}return t[e]},set:(t,e,n)=>t[e]=n})}*[Symbol.iterator](){const[t,...e]=this.dims;if(e.length>0){const n=e.reduce(((t,e)=>t*e));for(let r=0;r<t;++r)yield this._subarray(r,n,e)}else yield*this.data}_getitem(t){const[e,...n]=this.dims;if(t=ot(t,e),n.length>0){const e=n.reduce(((t,e)=>t*e));return this._subarray(t,e,n)}return new nt(this.type,[this.data[t]],n)}indexOf(t){for(let e=0;e<this.data.length;++e)if(this.data[e]==t)return e;return-1}_subarray(t,e,n){const r=t*e,i=(t+1)*e,s="subarray"in this.data?this.data.subarray(r,i):this.data.slice(r,i);return new nt(this.type,s,n)}item(){if(1!==this.data.length)throw new Error(`a Tensor with ${this.data.length} elements cannot be converted to Scalar`);return this.data[0]}tolist(){return function(t,e){const n=t.length;if(n!==e.reduce(((t,e)=>t*e)))throw Error(`cannot reshape array of size ${n} into shape (${e})`);let r=t;for(let t=e.length-1;t>=0;t--)r=r.reduce(((n,r)=>{let i=n[n.length-1];return i.length<e[t]?i.push(r):n.push([r]),n}),[[]]);return r[0]}(this.data,this.dims)}sigmoid(){return this.clone().sigmoid_()}sigmoid_(){for(let t=0;t<this.data.length;++t)this.data[t]=1/(1+Math.exp(-this.data[t]));return this}mul(t){return this.clone().mul_(t)}mul_(t){for(let e=0;e<this.data.length;++e)this.data[e]*=t;return this}add(t){return this.clone().add_(t)}add_(t){for(let e=0;e<this.data.length;++e)this.data[e]+=t;return this}clone(){return new nt(this.type,this.data.slice(),this.dims.slice())}slice(...t){let e=[],n=[];for(let r=0;r<this.dims.length;++r){let i=t[r];if(null==i)n.push([0,this.dims[r]]),e.push(this.dims[r]);else if("number"==typeof i)i=ot(i,this.dims[r],r),n.push([i,i+1]);else{if(!Array.isArray(i)||2!==i.length)throw new Error(`Invalid slice: ${i}`);{if(i[0]>i[1])throw new Error(`Invalid slice: ${i}`);let t=[Math.max(i[0],0),Math.min(i[1],this.dims[r])];n.push(t),e.push(t[1]-t[0])}}}let r=n.map((([t,e])=>e-t)),i=r.reduce(((t,e)=>t*e)),s=new this.data.constructor(i);const o=this.stride();for(let t=0;t<i;++t){let e=0;for(let i=r.length-1,s=t;i>=0;--i){const t=r[i];e+=(s%t+n[i][0])*o[i],s=Math.floor(s/t)}s[t]=this.data[e]}return new nt(this.type,s,e)}permute(...t){return function(t,e){const[n,r]=function(t,e,n){const r=new Array(n.length),i=new Array(n.length);for(let t=n.length-1,s=1;t>=0;--t)i[t]=s,r[t]=e[n[t]],s*=r[t];const s=n.map(((t,e)=>i[n.indexOf(e)])),o=new t.constructor(t.length);for(let n=0;n<t.length;++n){let r=0;for(let t=e.length-1,i=n;t>=0;--t)r+=i%e[t]*s[t],i=Math.floor(i/e[t]);o[r]=t[n]}return[o,r]}(t.data,t.dims,e);return new nt(t.type,n,r)}(this,t)}transpose(...t){return this.permute(...t)}sum(t=null,e=!1){return this.norm(1,t,e)}norm(t="fro",e=null,n=!1){if("fro"===t)t=2;else if("string"==typeof t)throw Error(`Unsupported norm: ${t}`);if(null===e){let e=this.data.reduce(((e,n)=>e+n**t),0)**(1/t);return new nt(this.type,[e],[])}e=ot(e,this.dims.length);const r=this.dims.slice();r[e]=1;const i=new this.data.constructor(this.data.length/this.dims[e]);for(let n=0;n<this.data.length;++n){let s=0;for(let t=this.dims.length-1,i=n,o=1;t>=0;--t){const n=this.dims[t];t!==e&&(s+=i%n*o,o*=r[t]),i=Math.floor(i/n)}i[s]+=this.data[n]**t}if(1!==t)for(let e=0;e<i.length;++e)i[e]=i[e]**(1/t);return n||r.splice(e,1),new nt(this.type,i,r)}normalize_(t=2,e=1){e=ot(e,this.dims.length);const n=this.norm(t,e,!0);for(let t=0;t<this.data.length;++t){let r=0;for(let n=this.dims.length-1,i=t,s=1;n>=0;--n){const t=this.dims[n];n!==e&&(r+=i%t*s,s*=this.dims[n]),i=Math.floor(i/t)}this.data[t]/=n.data[r]}return this}normalize(t=2,e=1){return this.clone().normalize_(t,e)}stride(){return function(t){const e=new Array(t.length);for(let n=t.length-1,r=1;n>=0;--n)e[n]=r,r*=t[n];return e}(this.dims)}squeeze(t=null){return new nt(this.type,this.data,it(this.dims,t))}squeeze_(t=null){return this.dims=it(this.dims,t),this}unsqueeze(t=null){return new nt(this.type,this.data,st(this.dims,t))}unsqueeze_(t=null){return this.dims=st(this.dims,t),this}flatten_(t=0,e=-1){e=(e+this.dims.length)%this.dims.length;let n=this.dims.slice(0,t),r=this.dims.slice(t,e+1),i=this.dims.slice(e+1);return this.dims=[...n,r.reduce(((t,e)=>t*e),1),...i],this}flatten(t=0,e=-1){return this.clone().flatten_(t,e)}view(...t){let e=-1;for(let n=0;n<t.length;++n)if(-1===t[n]){if(-1!==e)throw new Error("Only one dimension can be inferred");e=n}if(-1!==e){const n=t.reduce(((t,n,r)=>r!==e?t*n:t),1);t[e]=this.data.length/n}return new nt(this.type,this.data,t)}neg_(){for(let t=0;t<this.data.length;++t)this.data[t]=-this.data[t];return this}neg(){return this.clone().neg_()}clamp_(t,e){for(let n=0;n<this.data.length;++n)this.data[n]=Math.min(Math.max(this.data[n],t),e);return this}clamp(t,e){return this.clone().clamp_(t,e)}round_(){for(let t=0;t<this.data.length;++t)this.data[t]=Math.round(this.data[t]);return this}round(){return this.clone().round_()}to(t){if(this.type===t)return this;if(!tt.hasOwnProperty(t))throw new Error(`Unsupported type: ${t}`);return new nt(t,tt[t].from(this.data),this.dims)}}function rt(t,[e,n],r="bilinear",i=!1){const s=t.dims.at(-3)??1,o=t.dims.at(-2),a=t.dims.at(-1);let u=function(t,[e,n,r],[i,s],o="bilinear",a=!1){const u=s/r,l=i/n,c=new t.constructor(i*s*e),d=n*r,h=i*s;for(let o=0;o<i;++o)for(let i=0;i<s;++i){const a=o*s+i,p=(i+.5)/u-.5,f=(o+.5)/l-.5;let g=Math.floor(p),m=Math.floor(f);const _=Math.min(g+1,r-1),b=Math.min(m+1,n-1);g=Math.max(g,0),m=Math.max(m,0);const y=p-g,w=f-m,v=(1-y)*(1-w),x=y*(1-w),T=(1-y)*w,S=y*w,A=m*r,k=b*r,O=A+g,E=A+_,I=k+g,P=k+_;for(let n=0;n<e;++n){const e=n*d;c[n*h+a]=v*t[e+O]+x*t[e+E]+T*t[e+I]+S*t[e+P]}}return c}(t.data,[s,o,a],[e,n],r,i);return new nt(t.type,u,[s,e,n])}function it(t,e){return t=t.slice(),null===e?t=t.filter((t=>1!==t)):"number"==typeof e?1===t[e]&&t.splice(e,1):Array.isArray(e)&&(t=t.filter(((t,n)=>1!==t||!e.includes(n)))),t}function st(t,e){return e=ot(e,t.length+1),(t=t.slice()).splice(e,0,1),t}function ot(t,e,n=null){if(t<-e||t>=e)throw new Error(`IndexError: index ${t} is out of bounds for dimension${null===n?"":" "+n} with size ${e}`);return t<0&&(t=(t%e+e)%e),t}function at(t,e=0){e=ot(e,t[0].dims.length);const n=t[0].dims.slice();n[e]=t.reduce(((t,n)=>t+n.dims[e]),0);const r=n.reduce(((t,e)=>t*e),1),i=new t[0].data.constructor(r),s=t[0].type;if(0===e){let e=0;for(let n of t)i.set(n.data,e),e+=n.data.length}else{let r=0;for(let s=0;s<t.length;++s){let o=t[s];for(let t=0;t<o.data.length;++t){let s=0;for(let i=o.dims.length-1,a=t,u=1;i>=0;--i){const t=o.dims[i];let l=a%t;i===e&&(l+=r),s+=l*u,u*=n[i],a=Math.floor(a/t)}i[s]=o.data[t]}r+=o.dims[e]}}return new nt(s,i,n)}function ut(t,e=0){return at(t.map((t=>t.unsqueeze(e))),e)}function lt(t,e=null,n=!1){if(null===e){let e=t.data.reduce(((t,e)=>t+e),0);return new nt(t.type,[e/t.data.length],[])}e=ot(e,t.dims.length);const r=t.dims.slice();r[e]=1;const i=new t.data.constructor(t.data.length/t.dims[e]);for(let n=0;n<t.data.length;++n){let s=0;for(let i=t.dims.length-1,o=n,a=1;i>=0;--i){const n=t.dims[i];i!==e&&(s+=o%n*a,a*=r[i]),o=Math.floor(o/n)}i[s]+=t.data[n]}if(1!==t.dims[e])for(let n=0;n<i.length;++n)i[n]=i[n]/t.dims[e];return n||r.splice(e,1),new nt(t.type,i,r)}function ct(t){const[e,n]=t.dims,r=[e+1,n+1],i=new nt("float32",new Float32Array(r[0]*r[1]).fill(1/0),r),s=new nt("float32",new Float32Array(r[0]*r[1]).fill(-1),r);i[0].data[0]=0;for(let r=1;r<n+1;++r)for(let n=1;n<e+1;++n){const e=i[n-1][r-1].item(),o=i[n-1][r].item(),a=i[n][r-1].item();let u,l;e<o&&e<a?(u=e,l=0):o<e&&o<a?(u=o,l=1):(u=a,l=2),i[n].data[r]=t[n-1][r-1].item()+u,s[n].data[r]=l}let o=e,a=n;s.data.fill(2,0,r[1]);for(let t=0;t<r[0];++t)s[t].data[0]=1;let u=[],l=[];for(;o>0||a>0;)switch(u.push(o-1),l.push(a-1),s[o][a].item()){case 0:--o,--a;break;case 1:--o;break;case 2:--a;break;default:throw new Error(`Internal error in dynamic time warping. Unexpected trace[${o}, ${a}]. Please file a bug report.`)}return u.reverse(),l.reverse(),[u,l]}class dt{constructor(t=((t,e)=>t>e)){this._heap=[],this._comparator=t}get size(){return this._heap.length}isEmpty(){return 0===this.size}peek(){return this._heap[0]}push(...t){return this.extend(t)}extend(t){for(const e of t)this._heap.push(e),this._siftUp();return this.size}pop(){const t=this.peek(),e=this.size-1;return e>0&&this._swap(0,e),this._heap.pop(),this._siftDown(),t}replace(t){const e=this.peek();return this._heap[0]=t,this._siftDown(),e}_parent(t){return(t+1>>>1)-1}_left(t){return 1+(t<<1)}_right(t){return t+1<<1}_greater(t,e){return this._comparator(this._heap[t],this._heap[e])}_swap(t,e){const n=this._heap[t];this._heap[t]=this._heap[e],this._heap[e]=n}_siftUp(){let t=this.size-1;for(;t>0&&this._greater(t,this._parent(t));)this._swap(t,this._parent(t)),t=this._parent(t)}_siftDown(){let t=0;for(;this._left(t)<this.size&&this._greater(this._left(t),t)||this._right(t)<this.size&&this._greater(this._right(t),t);){const e=this._right(t)<this.size&&this._greater(this._right(t),this._left(t))?this._right(t):this._left(t);this._swap(t,e),t=e}}}class ht{constructor(){this.root=pt.default()}extend(t){for(let e of t)this.push(e)}push(t){let e=this.root;for(let n of t){let t=e.children.get(n);void 0===t&&(t=pt.default(),e.children.set(n,t)),e=t}e.isLeaf=!0}*commonPrefixSearch(t){let e=this.root,n="";for(let r=0;r<t.length&&void 0!==e;++r){const i=t[r];n+=i,e=e.children.get(i),void 0!==e&&e.isLeaf&&(yield n)}}}class pt{constructor(t,e){this.isLeaf=t,this.children=e}static default(){return new pt(!1,new Map)}}class ft{constructor(t,e,n){this.sentence=t,this.len=t.length,this.bosTokenId=e,this.eosTokenId=n,this.nodes=[],this.beginNodes=Array.from({length:this.len+1},(()=>[])),this.endNodes=Array.from({length:this.len+1},(()=>[]));const r=new gt(this.bosTokenId,0,0,0,0),i=new gt(this.eosTokenId,1,this.len,0,0);this.nodes.push(r.clone()),this.nodes.push(i.clone()),this.beginNodes[this.len].push(i),this.endNodes[0].push(r)}insert(t,e,n,r){const i=this.nodes.length,s=new gt(r,i,t,e,n);this.beginNodes[t].push(s),this.endNodes[t+e].push(s),this.nodes.push(s)}viterbi(){const t=this.len;let e=0;for(;e<=t;){if(0==this.beginNodes[e].length)return[];for(let t of this.beginNodes[e]){t.prev=null;let n=0,r=null;for(let i of this.endNodes[e]){const e=i.backtraceScore+t.score;(null===r||e>n)&&(r=i.clone(),n=e)}if(null===r)return[];t.prev=r,t.backtraceScore=n}++e}const n=[],r=this.beginNodes[t][0].prev;if(null===r)return[];let i=r.clone();for(;null!==i.prev;){n.push(i.clone());const t=i.clone();i=t.prev.clone()}return n.reverse(),n}piece(t){return this.sentence.slice(t.pos,t.pos+t.length)}tokens(){return this.viterbi().map((t=>this.piece(t)))}tokenIds(){return this.viterbi().map((t=>t.tokenId))}}class gt{constructor(t,e,n,r,i){this.tokenId=t,this.nodeId=e,this.pos=n,this.length=r,this.score=i,this.prev=null,this.backtraceScore=0}clone(){const t=new gt(this.tokenId,this.nodeId,this.pos,this.length,this.score);return t.prev=this.prev,t.backtraceScore=this.backtraceScore,t}}var mt=Object.freeze({Text:"Text",NumericLiteral:"NumericLiteral",BooleanLiteral:"BooleanLiteral",StringLiteral:"StringLiteral",Identifier:"Identifier",Equals:"Equals",OpenParen:"OpenParen",CloseParen:"CloseParen",OpenStatement:"OpenStatement",CloseStatement:"CloseStatement",OpenExpression:"OpenExpression",CloseExpression:"CloseExpression",OpenSquareBracket:"OpenSquareBracket",CloseSquareBracket:"CloseSquareBracket",OpenCurlyBracket:"OpenCurlyBracket",CloseCurlyBracket:"CloseCurlyBracket",Comma:"Comma",Dot:"Dot",Colon:"Colon",Pipe:"Pipe",CallOperator:"CallOperator",AdditiveBinaryOperator:"AdditiveBinaryOperator",MultiplicativeBinaryOperator:"MultiplicativeBinaryOperator",ComparisonBinaryOperator:"ComparisonBinaryOperator",UnaryOperator:"UnaryOperator",Set:"Set",If:"If",For:"For",In:"In",Is:"Is",NotIn:"NotIn",Else:"Else",EndIf:"EndIf",ElseIf:"ElseIf",EndFor:"EndFor",And:"And",Or:"Or",Not:"UnaryOperator"}),_t=Object.freeze({set:mt.Set,for:mt.For,in:mt.In,is:mt.Is,if:mt.If,else:mt.Else,endif:mt.EndIf,elif:mt.ElseIf,endfor:mt.EndFor,and:mt.And,or:mt.Or,not:mt.Not,"not 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Map([["n","\n"],["t","\t"],["r","\r"],["b","\b"],["f","\f"],["v","\v"],["'","'"],['"','"'],["\\","\\"]]),Tt=class{type="Statement"},St=class extends Tt{constructor(t){super(),this.body=t}type="Program"},At=class extends Tt{constructor(t,e,n){super(),this.test=t,this.body=e,this.alternate=n}type="If"},kt=class extends Tt{constructor(t,e,n){super(),this.loopvar=t,this.iterable=e,this.body=n}type="For"},Ot=class extends Tt{constructor(t,e){super(),this.assignee=t,this.value=e}type="Set"},Et=class extends Tt{type="Expression"},It=class extends Et{constructor(t,e,n){super(),this.object=t,this.property=e,this.computed=n}type="MemberExpression"},Pt=class extends Et{constructor(t,e){super(),this.callee=t,this.args=e}type="CallExpression"},Dt=class extends Et{constructor(t){super(),this.value=t}type="Identifier"},Ct=class extends Et{constructor(t){super(),this.value=t}type="Literal"},$t=class extends Ct{type="NumericLiteral"},Mt=class extends Ct{type="StringLiteral"},Ft=class extends 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r,i;if(t.computed){if("SliceExpression"===t.property.type)return this.evaluateSliceExpression(n,t.property,e);r=this.evaluate(t.property,e)}else r=new Zt(t.property.value);if(n instanceof Qt){if(!(r instanceof Zt))throw new Error(`Cannot access property with non-string: got ${r.type}`);i=n.value.get(r.value)??n.builtins.get(r.value)}else if(n instanceof te||n instanceof Zt)if(r instanceof Kt)i=n.value.at(r.value),n instanceof Zt&&(i=new Zt(n.value.at(r.value)));else{if(!(r instanceof Zt))throw new Error(`Cannot access property with non-string/non-number: got ${r.type}`);i=n.builtins.get(r.value)}else{if(!(r instanceof Zt))throw new Error(`Cannot access property with non-string: got ${r.type}`);i=n.builtins.get(r.value)}return i instanceof Yt?i:new ie}evaluateSet(t,e){const n=this.evaluate(t.value,e);if("Identifier"===t.assignee.type){const r=t.assignee.value;e.setVariable(r,n)}else{if("MemberExpression"!==t.assignee.type)throw new Error(`Invalid LHS inside assignment expression: 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o=r.value[e];if("Identifier"===t.loopvar.type)n.setVariable(t.loopvar.value,o);else if("TupleLiteral"===t.loopvar.type){const e=t.loopvar;if("ArrayValue"!==o.type)throw new Error(`Cannot unpack non-iterable type: ${o.type}`);const r=o;if(e.value.length!==r.value.length)throw new Error(`Too ${e.value.length>r.value.length?"few":"many"} items to unpack`);for(let t=0;t<e.value.length;++t){if("Identifier"!==e.value[t].type)throw new Error(`Cannot unpack non-identifier type: ${e.value[t].type}`);n.setVariable(e.value[t].value,r.value[t])}}i+=this.evaluateBlock(t.body,n).value}return new Zt(i)}evaluate(t,e){if(void 0===t)return new ie;switch(t.type){case"Program":return this.evalProgram(t,e);case"Set":return this.evaluateSet(t,e);case"If":return this.evaluateIf(t,e);case"For":return this.evaluateFor(t,e);case"NumericLiteral":return new Kt(Number(t.value));case"StringLiteral":return new Zt(t.value);case"BooleanLiteral":return new Jt(t.value);case"ArrayLiteral":return new te(t.value.map((t=>this.evaluate(t,e))));case"TupleLiteral":return new ee(t.value.map((t=>this.evaluate(t,e))));case"ObjectLiteral":{const n=new Map;for(const[r,i]of t.value){const t=this.evaluate(r,e);if(!(t instanceof Zt))throw new Error(`Object keys must be strings: got ${t.type}`);n.set(t.value,this.evaluate(i,e))}return new Qt(n)}case"Identifier":return this.evaluateIdentifier(t,e);case"CallExpression":return this.evaluateCallExpression(t,e);case"MemberExpression":return this.evaluateMemberExpression(t,e);case"UnaryExpression":return this.evaluateUnaryExpression(t,e);case"BinaryExpression":return this.evaluateBinaryExpression(t,e);case"FilterExpression":return this.evaluateFilterExpression(t,e);case"TestExpression":return this.evaluateTestExpression(t,e);default:throw new SyntaxError(`Unknown node type: ${t.type}`)}}};function ae(t){switch(typeof t){case"number":return new Kt(t);case"string":return new Zt(t);case"boolean":return new Jt(t);case"object":return null===t?new re:Array.isArray(t)?new te(t.map(ae)):new Qt(new Map(Object.entries(t).map((([t,e])=>[t,ae(e)]))));case"function":return new ne(((e,n)=>ae(t(...e.map((t=>t.value)))??null)));default:throw new Error(`Cannot convert to runtime value: ${t}`)}}var ue=class{parsed;constructor(t){const e=function(t,e={}){const n=[],r=function(t,e={}){return t.endsWith("\n")&&(t=t.slice(0,-1)),t=t.replace(/{#.*?#}/gs,"{##}"),e.lstrip_blocks&&(t=t.replace(/^[ \t]*({[#%])/gm,"$1")),e.trim_blocks&&(t=t.replace(/([#%]})\n/g,"$1")),t.replace(/{##}/g,"").replace(/-%}\s*/g,"%}").replace(/\s*{%-/g,"{%").replace(/-}}\s*/g,"}}").replace(/\s*{{-/g,"{{")}(t,e);let i=0;const s=t=>{let e="";for(;t(r[i]);)if("\\"!==r[i]){if(e+=r[i++],i>=r.length)throw new SyntaxError("Unexpected end of input")}else{if(++i,i>=r.length)throw new SyntaxError("Unexpected end of input");const t=r[i++],n=xt.get(t);if(void 0===n)throw new SyntaxError(`Unexpected escaped character: ${t}`);e+=n}return e};t:for(;i<r.length;){const t=n.at(-1)?.type;if(void 0===t||t===mt.CloseStatement||t===mt.CloseExpression){let t="";for(;i<r.length&&("{"!==r[i]||"%"!==r[i+1]&&"{"!==r[i+1]);)t+=r[i++];if(t.length>0){n.push(new bt(t,mt.Text));continue}}s((t=>/\s/.test(t)));const e=r[i];if("-"===e||"+"===e){const t=n.at(-1)?.type;if(t===mt.Text||void 0===t)throw new SyntaxError(`Unexpected character: ${e}`);switch(t){case mt.Identifier:case mt.NumericLiteral:case mt.BooleanLiteral:case mt.StringLiteral:case mt.CloseParen:case mt.CloseSquareBracket:break;default:{++i;const t=s(wt);n.push(new bt(`${e}${t}`,t.length>0?mt.NumericLiteral:mt.UnaryOperator));continue}}}for(const[t,e]of vt)if(r.slice(i,i+t.length)===t){n.push(new bt(t,e)),i+=t.length;continue t}if("'"!==e&&'"'!==e)if(wt(e)){const t=s(wt);n.push(new bt(t,mt.NumericLiteral))}else{if(!yt(e))throw new SyntaxError(`Unexpected character: ${e}`);{const t=s(yt),e=Object.hasOwn(_t,t)?_t[t]:mt.Identifier;e===mt.In&&n.at(-1)?.type===mt.Not?(n.pop(),n.push(new bt("not in",mt.NotIn))):n.push(new bt(t,e))}}else{++i;const t=s((t=>t!==e));n.push(new bt(t,mt.StringLiteral)),++i}}return n}(t,{lstrip_blocks:!0,trim_blocks:!0});this.parsed=qt(e)}render(t){const e=new se;e.set("false",!1),e.set("true",!0),e.set("raise_exception",(t=>{throw new Error(t)})),e.set("range",Wt);for(const[n,r]of Object.entries(t))e.set(n,r);return new oe(e).run(this.parsed).value}};async function le(t,e){const n=await Promise.all([U(t,"tokenizer.json",!0,e),U(t,"tokenizer_config.json",!0,e)]);return null!==e.legacy&&(n[1].legacy=e.legacy),n}function ce(t,e=!0){if(void 0!==t.Regex){let e=t.Regex.replace(/\\([#&~])/g,"$1");for(const[t,n]of me)e=e.replaceAll(t,n);return new RegExp(e,"gu")}if(void 0!==t.String){const n=i(t.String);return new RegExp(e?n:`(${n})`,"gu")}return console.warn("Unknown pattern type:",t),null}function de(t){return new Map(Object.entries(t))}function he(t){const e=t.dims;switch(e.length){case 1:return t.tolist();case 2:if(1!==e[0])throw new Error("Unable to decode tensor with `batch size !== 1`. Use `tokenizer.batch_decode(...)` for batched inputs.");return t.tolist()[0];default:throw new Error(`Expected tensor to have 1-2 dimensions, got ${e.length}.`)}}function pe(t){return t.replace(/ \./g,".").replace(/ \?/g,"?").replace(/ \!/g,"!").replace(/ ,/g,",").replace(/ \' /g,"'").replace(/ n\'t/g,"n't").replace(/ \'m/g,"'m").replace(/ \'s/g,"'s").replace(/ \'ve/g,"'ve").replace(/ \'re/g,"'re")}function fe(t){return t.replace(/[\u0300-\u036f]/g,"")}const ge="\\p{P}\\u0021-\\u002F\\u003A-\\u0040\\u005B-\\u0060\\u007B-\\u007E",me=new Map([["(?i:'s|'t|'re|'ve|'m|'ll|'d)","(?:'([sS]|[tT]|[rR][eE]|[vV][eE]|[mM]|[lL][lL]|[dD]))"]]);class _e{constructor(t){this.content=t.content,this.id=t.id,this.single_word=t.single_word??!1,this.lstrip=t.lstrip??!1,this.rstrip=t.rstrip??!1,this.special=t.special??!1,this.normalized=t.normalized??null}}class be extends s{constructor(t){super(),this.config=t,this.vocab=[],this.tokens_to_ids=new Map,this.unk_token_id=void 0,this.unk_token=void 0,this.end_of_word_suffix=void 0,this.fuse_unk=this.config.fuse_unk??!1}static fromConfig(t,...e){switch(t.type){case"WordPiece":return new ye(t);case"Unigram":return new we(t,...e);case"BPE":return new Se(t);default:if(t.vocab)return new Ae(t,...e);throw new Error(`Unknown TokenizerModel type: ${t.type}`)}}_call(t){let e=this.encode(t);return this.fuse_unk&&(e=function(t,e,n){const r=[];let i=0;for(;i<t.length;)if(r.push(t[i]),(n.get(t[i])??e)===e)for(;i<t.length&&(n.get(t[i])??e)===e;)++i;else++i;return r}(e,this.unk_token_id,this.tokens_to_ids)),e}encode(t){throw Error("encode should be implemented in subclass.")}convert_tokens_to_ids(t){return t.map((t=>this.tokens_to_ids.get(t)??this.unk_token_id))}convert_ids_to_tokens(t){return t.map((t=>this.vocab[t]??this.unk_token))}}class ye extends be{constructor(t){super(t),this.tokens_to_ids=de(t.vocab),this.unk_token_id=this.tokens_to_ids.get(t.unk_token),this.unk_token=t.unk_token,this.max_input_chars_per_word=t.max_input_chars_per_word??100,this.vocab=new Array(this.tokens_to_ids.size);for(const[t,e]of this.tokens_to_ids)this.vocab[e]=t}encode(t){const e=[];for(const n of t){const t=[...n];if(t.length>this.max_input_chars_per_word){e.push(this.unk_token);continue}let r=!1,i=0;const s=[];for(;i<t.length;){let e=t.length,n=null;for(;i<e;){let r=t.slice(i,e).join("");if(i>0&&(r=this.config.continuing_subword_prefix+r),this.tokens_to_ids.has(r)){n=r;break}--e}if(null===n){r=!0;break}s.push(n),i=e}r?e.push(this.unk_token):e.push(...s)}return e}}class we extends be{constructor(t,e){super(t);const n=t.vocab.length;this.vocab=new Array(n),this.scores=new Array(n);for(let e=0;e<n;++e){const n=t.vocab[e];this.vocab[e]=n[0],this.scores[e]=n[1]}this.unk_token_id=t.unk_id,this.unk_token=this.vocab[t.unk_id],this.tokens_to_ids=new Map(this.vocab.map(((t,e)=>[t,e]))),this.bosToken=" ",this.bosTokenId=this.tokens_to_ids.get(this.bosToken),this.eosToken=e.eos_token,this.eosTokenId=this.tokens_to_ids.get(this.eosToken),this.unkToken=this.vocab[this.unk_token_id],this.minScore=W(this.scores)[0],this.unkScore=this.minScore-10,this.scores[this.unk_token_id]=this.unkScore,this.trie=new ht,this.trie.extend(this.vocab),this.fuse_unk=!0}populateNodes(t){const e=t.sentence,n=e.length;let r=0;for(;r<n;){const n=1;let i=!1;const s=[];for(let o of this.trie.commonPrefixSearch(e.slice(r))){s.push(o);const e=this.tokens_to_ids.get(o),a=this.scores[e],u=o.length;t.insert(r,u,a,e),i||u!==n||(i=!0)}i||t.insert(r,n,this.unkScore,this.unk_token_id),r+=n}}tokenize(t){const e=new ft(t,this.bosTokenId,this.eosTokenId);return this.populateNodes(e),e.tokens()}encode(t){const e=[];for(const n of t){const t=this.tokenize(n);e.push(...t)}return e}}const ve=(()=>{const t=[...Array.from({length:"~".charCodeAt(0)-"!".charCodeAt(0)+1},((t,e)=>e+"!".charCodeAt(0))),...Array.from({length:"¬".charCodeAt(0)-"¡".charCodeAt(0)+1},((t,e)=>e+"¡".charCodeAt(0))),...Array.from({length:"ÿ".charCodeAt(0)-"®".charCodeAt(0)+1},((t,e)=>e+"®".charCodeAt(0)))],e=t.slice();let n=0;for(let r=0;r<256;++r)t.includes(r)||(t.push(r),e.push(256+n),n+=1);const r=e.map((t=>String.fromCharCode(t)));return Object.fromEntries(t.map(((t,e)=>[t,r[e]])))})(),xe=(Te=ve,Object.fromEntries(Object.entries(Te).map((([t,e])=>[e,t]))));var Te;class Se extends be{constructor(t){super(t),this.BPE_SPLIT_TOKEN=" ",this.tokens_to_ids=de(t.vocab),this.unk_token_id=this.tokens_to_ids.get(t.unk_token),this.unk_token=t.unk_token,this.vocab=new Array(this.tokens_to_ids.size);for(const[t,e]of this.tokens_to_ids)this.vocab[e]=t;this.bpe_ranks=new Map(t.merges.map(((t,e)=>[t,e]))),this.merges=t.merges.map((t=>t.split(this.BPE_SPLIT_TOKEN))),this.end_of_word_suffix=t.end_of_word_suffix,this.continuing_subword_suffix=t.continuing_subword_suffix??null,this.byte_fallback=this.config.byte_fallback??!1,this.byte_fallback&&(this.text_encoder=new TextEncoder),this.cache=new Map}bpe(t){if(0===t.length)return[];const e=this.cache.get(t);if(void 0!==e)return e;const n=Array.from(t);this.end_of_word_suffix&&(n[n.length-1]+=this.end_of_word_suffix);let r=[];if(n.length>1){const t=new dt(((t,e)=>t.score<e.score));let e={token:n[0],bias:0,prev:null,next:null},i=e;for(let e=1;e<n.length;++e){const r={bias:e/n.length,token:n[e],prev:i,next:null};i.next=r,this._add_node(t,i),i=r}for(;!t.isEmpty();){const n=t.pop();if(n.deleted||!n.next||n.next.deleted)continue;if(n.deleted=!0,n.next.deleted=!0,n.prev){const t={...n.prev};n.prev.deleted=!0,n.prev=t,t.prev?t.prev.next=t:e=t}const r={token:n.token+n.next.token,bias:n.bias,prev:n.prev,next:n.next.next};r.prev?(r.prev.next=r,this._add_node(t,r.prev)):e=r,r.next&&(r.next.prev=r,this._add_node(t,r))}for(let t=e;null!==t;t=t.next)r.push(t.token)}else r=n;if(this.continuing_subword_suffix)for(let t=0;t<r.length-1;++t)r[t]+=this.continuing_subword_suffix;return this.cache.set(t,r),r}_add_node(t,e){const n=this.bpe_ranks.get(e.token+this.BPE_SPLIT_TOKEN+e.next.token);void 0!==n&&(e.score=n+e.bias,t.push(e))}encode(t){const e=[];for(const n of t){const t=this.bpe(n);for(const n of t)this.tokens_to_ids.has(n)?e.push(n):this.byte_fallback?e.push(...Array.from(this.text_encoder.encode(n)).map((t=>`<0x${t.toString(16).toUpperCase().padStart(2,"0")}>`))):e.push(this.unk_token)}return e}}class Ae extends be{constructor(t,e){super(t),this.tokens_to_ids=de(e.target_lang?t.vocab[e.target_lang]:t.vocab),this.bos_token=e.bos_token,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=e.eos_token,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.pad_token=e.pad_token,this.pad_token_id=this.tokens_to_ids.get(this.pad_token),this.unk_token=e.unk_token,this.unk_token_id=this.tokens_to_ids.get(this.unk_token),this.vocab=new Array(this.tokens_to_ids.size);for(const[t,e]of this.tokens_to_ids)this.vocab[e]=t}encode(t){return t}}class ke extends s{constructor(t){super(),this.config=t}static fromConfig(t){if(null===t)return null;switch(t.type){case"BertNormalizer":return new Le(t);case"Precompiled":return new un(t);case"Sequence":return new Fe(t);case"Replace":return new Oe(t);case"NFC":return new Ee(t);case"NFKC":return new Ie(t);case"NFKD":return new Pe(t);case"Strip":return new De(t);case"StripAccents":return new Ce(t);case"Lowercase":return new $e(t);case"Prepend":return new Me(t);default:throw new Error(`Unknown Normalizer type: ${t.type}`)}}normalize(t){throw Error("normalize should be implemented in subclass.")}_call(t){return this.normalize(t)}}class Oe extends ke{normalize(t){const e=ce(this.config.pattern);return null===e?t:t.replaceAll(e,this.config.content)}}class Ee extends ke{normalize(t){return t.normalize("NFC")}}class Ie extends ke{normalize(t){return t.normalize("NFKC")}}class Pe extends ke{normalize(t){return t.normalize("NFKD")}}class De extends ke{normalize(t){return this.config.strip_left&&this.config.strip_right?t=t.trim():(this.config.strip_left&&(t=t.trimStart()),this.config.strip_right&&(t=t.trimEnd())),t}}class Ce extends ke{normalize(t){return fe(t)}}class $e extends ke{normalize(t){return t.toLowerCase()}}class Me extends ke{normalize(t){return this.config.prepend+t}}class Fe extends ke{constructor(t){super(t),this.normalizers=t.normalizers.map((t=>ke.fromConfig(t)))}normalize(t){return this.normalizers.reduce(((t,e)=>e.normalize(t)),t)}}class Le extends ke{_tokenize_chinese_chars(t){const e=[];for(let n=0;n<t.length;++n){const r=t[n],i=r.charCodeAt(0);this._is_chinese_char(i)?(e.push(" "),e.push(r),e.push(" ")):e.push(r)}return e.join("")}_is_chinese_char(t){return t>=19968&&t<=40959||t>=13312&&t<=19903||t>=131072&&t<=173791||t>=173824&&t<=177983||t>=177984&&t<=178207||t>=178208&&t<=183983||t>=63744&&t<=64255||t>=194560&&t<=195103}stripAccents(t){return t.normalize("NFD").replace(/[\u0300-\u036f]/g,"")}_is_control(t){switch(t){case"\t":case"\n":case"\r":return!1;default:return/^\p{Cc}|\p{Cf}|\p{Co}|\p{Cs}$/u.test(t)}}_clean_text(t){const e=[];for(const n of t){const t=n.charCodeAt(0);0===t||65533===t||this._is_control(n)||(/^\s$/.test(n)?e.push(" "):e.push(n))}return e.join("")}normalize(t){return this.config.clean_text&&(t=this._clean_text(t)),this.config.handle_chinese_chars&&(t=this._tokenize_chinese_chars(t)),this.config.lowercase?(t=t.toLowerCase(),!1!==this.config.strip_accents&&(t=this.stripAccents(t))):this.config.strip_accents&&(t=this.stripAccents(t)),t}}class Ne extends s{static fromConfig(t){if(null===t)return null;switch(t.type){case"BertPreTokenizer":return new Re(t);case"Sequence":return new ln(t);case"Whitespace":return new cn(t);case"WhitespaceSplit":return new dn(t);case"Metaspace":return new on(t);case"ByteLevel":return new je(t);case"Split":return new ze(t);case"Punctuation":return new Be(t);case"Digits":return new Ue(t);case"Replace":return new hn(t);default:throw new Error(`Unknown PreTokenizer type: ${t.type}`)}}pre_tokenize_text(t,e){throw Error("pre_tokenize_text should be implemented in subclass.")}pre_tokenize(t,e){return(Array.isArray(t)?t.map((t=>this.pre_tokenize_text(t,e))):this.pre_tokenize_text(t,e)).flat()}_call(t,e){return this.pre_tokenize(t,e)}}class Re extends Ne{constructor(t){super(),this.pattern=new RegExp(`[^\\s${ge}]+|[${ge}]`,"gu")}pre_tokenize_text(t,e){return t.trim().match(this.pattern)||[]}}class je extends Ne{constructor(t){super(),this.config=t,this.add_prefix_space=this.config.add_prefix_space,this.trim_offsets=this.config.trim_offsets,this.use_regex=this.config.use_regex??!0,this.pattern=/'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+/gu,this.byte_encoder=ve,this.text_encoder=new TextEncoder}pre_tokenize_text(t,e){return this.add_prefix_space&&!t.startsWith(" ")&&(t=" "+t),(this.use_regex?t.match(this.pattern)||[]:[t]).map((t=>Array.from(this.text_encoder.encode(t),(t=>this.byte_encoder[t])).join("")))}}class ze extends Ne{constructor(t){super(),this.config=t,this.pattern=ce(this.config.pattern,this.config.invert)}pre_tokenize_text(t,e){return null===this.pattern?[]:this.config.invert?t.match(this.pattern)||[]:function(t,e){const n=[];let r=0;for(const i of t.matchAll(e)){const e=i[0];r<i.index&&n.push(t.slice(r,i.index)),e.length>0&&n.push(e),r=i.index+e.length}return r<t.length&&n.push(t.slice(r)),n}(t,this.pattern)}}class Be extends Ne{constructor(t){super(),this.config=t,this.pattern=new RegExp(`[^${ge}]+|[${ge}]+`,"gu")}pre_tokenize_text(t,e){return t.match(this.pattern)||[]}}class Ue extends Ne{constructor(t){super(),this.config=t;const e="[^\\d]+|\\d"+(this.config.individual_digits?"":"+");this.pattern=new RegExp(e,"gu")}pre_tokenize_text(t,e){return t.match(this.pattern)||[]}}class Ve extends s{constructor(t){super(),this.config=t}static fromConfig(t){if(null===t)return null;switch(t.type){case"TemplateProcessing":return new We(t);case"ByteLevel":return new He(t);case"RobertaProcessing":return new qe(t);case"BertProcessing":return new Ge(t);default:throw new Error(`Unknown PostProcessor type: ${t.type}`)}}post_process(t,...e){throw Error("post_process should be implemented in subclass.")}_call(t,...e){return this.post_process(t,...e)}}class Ge extends Ve{constructor(t){super(t),this.cls=t.cls[0],this.sep=t.sep[0]}post_process(t,e=null,{add_special_tokens:n=!0}={}){n&&(t=l([this.cls],t,[this.sep]));let r=new Array(t.length).fill(0);if(null!==e){const i=n&&this instanceof qe?[this.sep]:[],s=n?[this.sep]:[];t=l(t,i,e,s),r=l(r,new Array(e.length+i.length+s.length).fill(1))}return{tokens:t,token_type_ids:r}}}class qe extends Ge{}class We extends Ve{constructor(t){super(t),this.single=t.single,this.pair=t.pair}post_process(t,e=null,{add_special_tokens:n=!0}={}){const r=null===e?this.single:this.pair;let i=[],s=[];for(const o of r)"SpecialToken"in o?n&&(i.push(o.SpecialToken.id),s.push(o.SpecialToken.type_id)):"Sequence"in o&&("A"===o.Sequence.id?(i=l(i,t),s=l(s,new Array(t.length).fill(o.Sequence.type_id))):"B"===o.Sequence.id&&(i=l(i,e),s=l(s,new Array(e.length).fill(o.Sequence.type_id))));return{tokens:i,token_type_ids:s}}}class He extends Ve{post_process(t,e=null){return e&&(t=l(t,e)),{tokens:t}}}class Xe extends s{constructor(t){super(),this.config=t,this.added_tokens=[],this.end_of_word_suffix=null,this.trim_offsets=t.trim_offsets}static fromConfig(t){if(null===t)return null;switch(t.type){case"WordPiece":return new Qe(t);case"Metaspace":return new an(t);case"ByteLevel":return new tn(t);case"Replace":return new Ye(t);case"ByteFallback":return new Ke(t);case"Fuse":return new Ze(t);case"Strip":return new Je(t);case"Sequence":return new nn(t);case"CTC":return new en(t);case"BPEDecoder":return new rn(t);default:throw new Error(`Unknown Decoder type: ${t.type}`)}}_call(t){return this.decode(t)}decode(t){return this.decode_chain(t).join("")}decode_chain(t){throw Error("`decode_chain` should be implemented in subclass.")}}class Ye extends Xe{decode_chain(t){const e=ce(this.config.pattern);return null===e?t:t.map((t=>t.replaceAll(e,this.config.content)))}}class Ke extends Xe{constructor(t){super(t),this.text_decoder=new TextDecoder}decode_chain(t){const e=[];let n=[];for(const r of t){let t=null;if(6===r.length&&r.startsWith("<0x")&&r.endsWith(">")){const e=parseInt(r.slice(3,5),16);isNaN(e)||(t=e)}if(null!==t)n.push(t);else{if(n.length>0){const t=this.text_decoder.decode(Uint8Array.from(n));e.push(t),n=[]}e.push(r)}}if(n.length>0){const t=this.text_decoder.decode(Uint8Array.from(n));e.push(t),n=[]}return e}}class Ze extends Xe{decode_chain(t){return[t.join("")]}}class Je extends Xe{constructor(t){super(t),this.content=this.config.content,this.start=this.config.start,this.stop=this.config.stop}decode_chain(t){return t.map((t=>{let e=0;for(let n=0;n<this.start&&t[n]===this.content;++n)e=n+1;let n=t.length;for(let e=0;e<this.stop;++e){const r=t.length-e-1;if(t[r]!==this.content)break;n=r}return t.slice(e,n)}))}}class Qe extends Xe{constructor(t){super(t),this.cleanup=t.cleanup}decode_chain(t){return t.map(((t,e)=>(0!==e&&(t=t.startsWith(this.config.prefix)?t.replace(this.config.prefix,""):" "+t),this.cleanup&&(t=pe(t)),t)))}}class tn extends Xe{constructor(t){super(t),this.byte_decoder=xe,this.text_decoder=new TextDecoder("utf-8",{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(t){const e=t.join(""),n=new Uint8Array([...e].map((t=>this.byte_decoder[t])));return this.text_decoder.decode(n)}decode_chain(t){const e=[];let n=[];for(const r of t)void 0!==this.added_tokens.find((t=>t.content===r))?(n.length>0&&(e.push(this.convert_tokens_to_string(n)),n=[]),e.push(r)):n.push(r);return n.length>0&&e.push(this.convert_tokens_to_string(n)),e}}class en extends Xe{constructor(t){super(t),this.pad_token=this.config.pad_token,this.word_delimiter_token=this.config.word_delimiter_token,this.cleanup=this.config.cleanup}convert_tokens_to_string(t){if(0===t.length)return"";const e=[t[0]];for(let n=1;n<t.length;++n)t[n]!==e.at(-1)&&e.push(t[n]);let n=e.filter((t=>t!==this.pad_token)).join("");return this.cleanup&&(n=pe(n).replaceAll(this.word_delimiter_token," ").trim()),n}decode_chain(t){return[this.convert_tokens_to_string(t)]}}class nn extends Xe{constructor(t){super(t),this.decoders=t.decoders.map((t=>Xe.fromConfig(t)))}decode_chain(t){return this.decoders.reduce(((t,e)=>e.decode_chain(t)),t)}}class rn extends Xe{constructor(t){super(t),this.suffix=this.config.suffix}decode_chain(t){return t.map(((e,n)=>e.replaceAll(this.suffix,n===t.length-1?"":" ")))}}class sn extends Xe{decode_chain(t){let e="";for(let n=1;n<t.length;n+=2)e+=t[n];return[e]}}class on extends Ne{constructor(t){super(),this.addPrefixSpace=t.add_prefix_space,this.replacement=t.replacement,this.strRep=t.str_rep||this.replacement,this.prepend_scheme=t.prepend_scheme??"always"}pre_tokenize_text(t,{section_index:e}={}){let n=t.replaceAll(" ",this.strRep);return this.addPrefixSpace&&!n.startsWith(this.replacement)&&("always"===this.prepend_scheme||"first"===this.prepend_scheme&&0===e)&&(n=this.strRep+n),[n]}}class an extends Xe{constructor(t){super(t),this.addPrefixSpace=t.add_prefix_space,this.replacement=t.replacement}decode_chain(t){const e=[];for(let n=0;n<t.length;++n){let r=t[n].replaceAll(this.replacement," ");this.addPrefixSpace&&0==n&&r.startsWith(" ")&&(r=r.substring(1)),e.push(r)}return e}}class un extends ke{constructor(t){super(t),this.charsmap=t.precompiled_charsmap}normalize(t){if((t=(t=t.replace(/[\u0001-\u0008\u000B\u000E-\u001F\u007F\u008F\u009F]/gm,"")).replace(/[\u0009\u000A\u000C\u000D\u1680\u200B\u200C\u200E\u200F\u2028\u2029\u2581\uFEFF\uFFFD]/gm," ")).includes("～")){const e=t.split("～");t=e.map((t=>t.normalize("NFKC"))).join("～")}else t=t.normalize("NFKC");return t}}class ln extends Ne{constructor(t){super(),this.tokenizers=t.pretokenizers.map((t=>Ne.fromConfig(t)))}pre_tokenize_text(t,e){return this.tokenizers.reduce(((t,n)=>n.pre_tokenize(t,e)),[t])}}class cn extends Ne{constructor(t){super()}pre_tokenize_text(t,e){return t.match(/\w+|[^\w\s]+/g)||[]}}class dn extends Ne{constructor(t){super()}pre_tokenize_text(t,e){return function(t){return t.match(/\S+/g)||[]}(t)}}class hn extends Ne{constructor(t){super(),this.config=t,this.pattern=ce(this.config.pattern),this.content=this.config.content}pre_tokenize_text(t,e){return null===this.pattern?[t]:[t.replaceAll(this.pattern,this.config.content)]}}const pn=["bos_token","eos_token","unk_token","sep_token","pad_token","cls_token","mask_token"];function fn(t,e,n,r){for(const i of Object.keys(t)){const s=e-t[i].length,o=n(i),a=new Array(s).fill(o);t[i]="right"===r?l(t[i],a):l(a,t[i])}}function gn(t,e){for(const n of Object.keys(t))t[n].length=e}class mn extends s{return_token_type_ids=!1;_default_chat_template="{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}";constructor(t,e){super(),this._tokenizer_config=e,this.normalizer=ke.fromConfig(t.normalizer),this.pre_tokenizer=Ne.fromConfig(t.pre_tokenizer),this.model=be.fromConfig(t.model,e),this.post_processor=Ve.fromConfig(t.post_processor),this.decoder=Xe.fromConfig(t.decoder),this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];for(const e of t.added_tokens){const t=new _e(e);this.added_tokens.push(t),this.model.tokens_to_ids.set(t.content,t.id),this.model.vocab[t.id]=t.content,t.special&&(this.special_tokens.push(t.content),this.all_special_ids.push(t.id))}if(this.additional_special_tokens=e.additional_special_tokens??[],this.special_tokens.push(...this.additional_special_tokens),this.special_tokens=[...new Set(this.special_tokens)],this.decoder&&(this.decoder.added_tokens=this.added_tokens,this.decoder.end_of_word_suffix=this.model.end_of_word_suffix),this.added_tokens_regex=this.added_tokens.length>0?new RegExp(this.added_tokens.map((t=>`${t.lstrip?"\\s*":""}(${i(t.content)})${t.rstrip?"\\s*":""}`)).join("|")):null,this.mask_token=this.getToken("mask_token"),this.mask_token_id=this.model.tokens_to_ids.get(this.mask_token),this.pad_token=this.getToken("pad_token","eos_token"),this.pad_token_id=this.model.tokens_to_ids.get(this.pad_token),this.sep_token=this.getToken("sep_token"),this.sep_token_id=this.model.tokens_to_ids.get(this.sep_token),this.unk_token=this.getToken("unk_token"),this.unk_token_id=this.model.tokens_to_ids.get(this.unk_token),this.model_max_length=e.model_max_length,this.remove_space=e.remove_space,this.clean_up_tokenization_spaces=e.clean_up_tokenization_spaces??!0,this.do_lowercase_and_remove_accent=e.do_lowercase_and_remove_accent??!1,this.padding_side="right",this.legacy=!1,this.chat_template=e.chat_template??null,Array.isArray(this.chat_template)){const t=Object.create(null);for(const{name:e,template:n}of this.chat_template){if("string"!=typeof e||"string"!=typeof n)throw new Error('Chat template must be a list of objects with "name" and "template" properties');t[e]=n}this.chat_template=t}this._compiled_template_cache=new Map}getToken(...t){for(const e of t){const t=this._tokenizer_config[e];if(t){if("object"==typeof t){if("AddedToken"===t.__type)return t.content;throw Error(`Unknown token: ${t}`)}return t}}return null}static async from_pretrained(t,{progress_callback:e=null,config:n=null,cache_dir:r=null,local_files_only:i=!1,revision:s="main",legacy:o=null}={}){return new this(...await le(t,{progress_callback:e,config:n,cache_dir:r,local_files_only:i,revision:s,legacy:o}))}_call(t,{text_pair:e=null,add_special_tokens:n=!0,padding:r=!1,truncation:i=null,max_length:s=null,return_tensor:o=!0}={}){const a=Array.isArray(t);let u;if(a){if(0===t.length)throw Error("text array must be non-empty");if(null!==e){if(!Array.isArray(e))throw Error("text_pair must also be an array");if(t.length!==e.length)throw Error("text and text_pair must have the same length");u=t.map(((t,r)=>this._encode_plus(t,e[r],{add_special_tokens:n})))}else u=t.map((t=>this._encode_plus(t,null,{add_special_tokens:n})))}else{if(null===t)throw Error("text may not be null");if(Array.isArray(e))throw Error("When specifying `text_pair`, since `text` is a string, `text_pair` must also be a string (i.e., not an array).");u=[this._encode_plus(t,e,{add_special_tokens:n})]}if(null===s?s="max_length"===r?this.model_max_length:H(u.map((t=>t.input_ids.length)))[0]:i||console.warn("Truncation was not explicitly activated but `max_length` is provided a specific value, please use `truncation=true` to explicitly truncate examples to max length."),s=Math.min(s,this.model_max_length),r||i)for(let t=0;t<u.length;++t)u[t].input_ids.length!==s&&(u[t].input_ids.length>s?i&&gn(u[t],s):r&&fn(u[t],s,(t=>"input_ids"===t?this.pad_token_id:0),this.padding_side));const l={};if(o){if((!r||!i)&&u.some((t=>{for(const e of Object.keys(t))if(t[e].length!==u[0][e]?.length)return!0;return!1})))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=true' and 'truncation=true' to have batched tensors with the same length.");const t=[u.length,u[0].input_ids.length];for(const e of Object.keys(u[0]))l[e]=new nt("int64",BigInt64Array.from(u.flatMap((t=>t[e])).map(BigInt)),t)}else{for(const t of Object.keys(u[0]))l[t]=u.map((e=>e[t]));if(!a)for(const t of Object.keys(l))l[t]=l[t][0]}return l}_encode_text(t){if(null===t)return null;const e=(this.added_tokens_regex?t.split(this.added_tokens_regex).filter((t=>t)):[t]).map(((t,e)=>{if(void 0!==this.added_tokens.find((e=>e.content===t)))return t;{if(!0===this.remove_space&&(t=t.trim().split(/\s+/).join(" ")),this.do_lowercase_and_remove_accent&&(t=function(t){return fe(t.toLowerCase())}(t)),null!==this.normalizer&&(t=this.normalizer(t)),0===t.length)return[];const n=null!==this.pre_tokenizer?this.pre_tokenizer(t,{section_index:e}):[t];return this.model(n)}})).flat();return e}_encode_plus(t,e=null,{add_special_tokens:n=!0}={}){const r=this._encode_text(t),i=this._encode_text(e),s=this.post_processor?this.post_processor(r,i,{add_special_tokens:n}):{tokens:l(r??[],i??[])},o=this.model.convert_tokens_to_ids(s.tokens),a={input_ids:o,attention_mask:new Array(o.length).fill(1)};return this.return_token_type_ids&&s.token_type_ids&&(a.token_type_ids=s.token_type_ids),a}encode(t,e=null,{add_special_tokens:n=!0}={}){const{input_ids:r}=this._encode_plus(t,e,{add_special_tokens:n});return r}batch_decode(t,e={}){return t instanceof nt&&(t=t.tolist()),t.map((t=>this.decode(t,e)))}decode(t,e={}){if(t instanceof nt&&(t=he(t)),!Array.isArray(t)||0===t.length||!o(t[0]))throw Error("token_ids must be a non-empty array of integers.");return this.decode_single(t,e)}decode_single(t,{skip_special_tokens:e=!1,clean_up_tokenization_spaces:n=null}){let r=this.model.convert_ids_to_tokens(t);e&&(r=r.filter((t=>!this.special_tokens.includes(t))));let i=this.decoder?this.decoder(r):r.join(" ");return this.decoder&&this.decoder.end_of_word_suffix&&(i=i.replaceAll(this.decoder.end_of_word_suffix," "),e&&(i=i.trim())),(n??this.clean_up_tokenization_spaces)&&(i=pe(i)),i}get default_chat_template(){return this._warned_about_chat_template||(console.warn("No chat template is defined for this tokenizer - using a default chat template that implements the ChatML format. If the default is not appropriate for your model, please set `tokenizer.chat_template` to an appropriate template. See https://huggingface.co/docs/transformers/main/chat_templating for more information."),this._warned_about_chat_template=!0),this._default_chat_template}apply_chat_template(t,{chat_template:e=null,add_generation_prompt:n=!1,tokenize:r=!0,padding:i=!1,truncation:s=!1,max_length:o=null,return_tensor:a=!0,tokenizer_kwargs:u={},...l}={}){if(this.chat_template&&"object"==typeof this.chat_template||null===this.chat_template&&this.default_chat_template&&"object"==typeof this.default_chat_template){const t=this.chat_template??this.default_chat_template;if(null!==e&&Object.hasOwn(t,e))e=t[e];else if(null===e&&"default"in t)e=t.default;else if(null===e)throw Error(`This model has multiple chat templates with no default specified! Please either pass a chat template or the name of the template you wish to use to the 'chat_template' argument. Available template names are ${Object.keys(t).sort()}.`)}else e??=this.chat_template??this.default_chat_template;if("string"!=typeof e)throw Error("chat_template must be a string, but got "+typeof e);let c=this._compiled_template_cache.get(e);void 0===c&&(c=new ue(e),this._compiled_template_cache.set(e,c));const d=Object.create(null);for(const t of pn){const e=this.getToken(t);e&&(d[t]=e)}const h=c.render({messages:t,add_generation_prompt:n,...d,...l});return r?this._call(h,{add_special_tokens:!1,padding:i,truncation:s,max_length:o,return_tensor:a,...u}).input_ids:h}}class _n extends mn{return_token_type_ids=!0}class bn extends mn{return_token_type_ids=!0}class yn extends mn{return_token_type_ids=!0}class wn extends mn{return_token_type_ids=!0}class vn extends mn{return_token_type_ids=!0}class xn extends mn{return_token_type_ids=!0}class Tn extends mn{return_token_type_ids=!0}class Sn extends mn{return_token_type_ids=!0}class An extends mn{return_token_type_ids=!0}class kn extends mn{}class On extends mn{}class En extends mn{return_token_type_ids=!0;constructor(t,e){super(t,e),console.warn('WARNING: `XLMTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}}class In extends mn{return_token_type_ids=!0}class Pn extends mn{}class Dn extends mn{_default_chat_template='{% for message in messages %}" "{{ message.content }}{{ eos_token }}" "{% endfor %}'}class Cn extends mn{}class $n extends mn{constructor(t,e){super(t,e),this.languageRegex=/^[a-z]{2}_[A-Z]{2}$/,this.language_codes=this.special_tokens.filter((t=>this.languageRegex.test(t))),this.lang_to_token=t=>t}_build_translation_inputs(t,e,n){return Xn(this,t,e,n)}}class Mn extends $n{}class Fn extends mn{}class Ln extends Dn{constructor(t,e){const n=".,!?…。，、।۔،",r=t.pre_tokenizer?.pretokenizers[0]?.pattern;r&&r.Regex===` ?[^(\\s|[${n}])]+`&&(r.Regex=` ?[^\\s${n}]+`),super(t,e)}}const Nn="▁";class Rn extends mn{_default_chat_template="{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif USE_DEFAULT_PROMPT == true and not '<<SYS>>' in messages[0]['content'] %}{% set loop_messages = messages %}{% set system_message = 'DEFAULT_SYSTEM_MESSAGE' %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\n' + system_message + '\n<</SYS>>\n\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'system' %}{{ '<<SYS>>\n' + content.strip() + '\n<</SYS>>\n\n' }}{% elif message['role'] == 'assistant' %}{{ ' ' + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}";DEFAULT_SYSTEM_PROMPT="You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.\n\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.";constructor(t,e){super(t,e),this.use_default_system_prompt=e.use_default_system_prompt??!1,this.legacy=e.legacy??!0,this.legacy||(this.normalizer=null,this.pre_tokenizer=new on({replacement:Nn,add_prefix_space:!0,prepend_scheme:"first"}))}_encode_text(t){if(null===t)return null;if(this.legacy||0===t.length)return super._encode_text(t);let e=super._encode_text(Nn+t.replaceAll(Nn," "));return e.length>1&&e[0]===Nn&&this.special_tokens.includes(e[1])&&(e=e.slice(1)),e}get default_chat_template(){return super.default_chat_template.replaceAll("USE_DEFAULT_PROMPT",this.use_default_system_prompt?"true":"false").replaceAll("DEFAULT_SYSTEM_MESSAGE",this.DEFAULT_SYSTEM_PROMPT.replaceAll("\n","\\n").replaceAll("'","\\'"))}}class jn extends Rn{}class zn extends mn{}class Bn extends mn{}class Un extends mn{}class Vn extends mn{}class Gn extends mn{}class qn extends mn{}class Wn extends mn{_default_chat_template="{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}"}class Hn extends mn{}function Xn(t,e,n,r){if(!("language_codes"in t)||!Array.isArray(t.language_codes))throw new Error("Tokenizer must have `language_codes` attribute set and it should be an array of language ids.");if(!("languageRegex"in t&&t.languageRegex instanceof RegExp))throw new Error("Tokenizer must have `languageRegex` attribute set and it should be a regular expression.");if(!("lang_to_token"in t)||"function"!=typeof t.lang_to_token)throw new Error("Tokenizer must have `lang_to_token` attribute set and it should be a function.");const i=r.src_lang,s=r.tgt_lang;if(!t.language_codes.includes(s))throw new Error(`Target language code "${s}" is not valid. Must be one of: {${t.language_codes.join(", ")}}`);if(void 0!==i){if(!t.language_codes.includes(i))throw new Error(`Source language code "${i}" is not valid. Must be one of: {${t.language_codes.join(", ")}}`);for(const e of t.post_processor.config.single)if("SpecialToken"in e&&t.languageRegex.test(e.SpecialToken.id)){e.SpecialToken.id=t.lang_to_token(i);break}}return r.forced_bos_token_id=t.model.convert_tokens_to_ids([t.lang_to_token(s)])[0],t._call(e,n)}class Yn extends mn{constructor(t,e){super(t,e),this.languageRegex=/^[a-z]{3}_[A-Z][a-z]{3}$/,this.language_codes=this.special_tokens.filter((t=>this.languageRegex.test(t))),this.lang_to_token=t=>t}_build_translation_inputs(t,e,n){return Xn(this,t,e,n)}}class Kn extends mn{constructor(t,e){super(t,e),this.languageRegex=/^__[a-z]{2,3}__$/,this.language_codes=this.special_tokens.filter((t=>this.languageRegex.test(t))).map((t=>t.slice(2,-2))),this.lang_to_token=t=>`__${t}__`}_build_translation_inputs(t,e,n){return Xn(this,t,e,n)}}const Zn=[["en","english"],["zh","chinese"],["de","german"],["es","spanish"],["ru","russian"],["ko","korean"],["fr","french"],["ja","japanese"],["pt","portuguese"],["tr","turkish"],["pl","polish"],["ca","catalan"],["nl","dutch"],["ar","arabic"],["sv","swedish"],["it","italian"],["id","indonesian"],["hi","hindi"],["fi","finnish"],["vi","vietnamese"],["he","hebrew"],["uk","ukrainian"],["el","greek"],["ms","malay"],["cs","czech"],["ro","romanian"],["da","danish"],["hu","hungarian"],["ta","tamil"],["no","norwegian"],["th","thai"],["ur","urdu"],["hr","croatian"],["bg","bulgarian"],["lt","lithuanian"],["la","latin"],["mi","maori"],["ml","malayalam"],["cy","welsh"],["sk","slovak"],["te","telugu"],["fa","persian"],["lv","latvian"],["bn","bengali"],["sr","serbian"],["az","azerbaijani"],["sl","slovenian"],["kn","kannada"],["et","estonian"],["mk","macedonian"],["br","breton"],["eu","basque"],["is","icelandic"],["hy","armenian"],["ne","nepali"],["mn","mongolian"],["bs","bosnian"],["kk","kazakh"],["sq","albanian"],["sw","swahili"],["gl","galician"],["mr","marathi"],["pa","punjabi"],["si","sinhala"],["km","khmer"],["sn","shona"],["yo","yoruba"],["so","somali"],["af","afrikaans"],["oc","occitan"],["ka","georgian"],["be","belarusian"],["tg","tajik"],["sd","sindhi"],["gu","gujarati"],["am","amharic"],["yi","yiddish"],["lo","lao"],["uz","uzbek"],["fo","faroese"],["ht","haitian creole"],["ps","pashto"],["tk","turkmen"],["nn","nynorsk"],["mt","maltese"],["sa","sanskrit"],["lb","luxembourgish"],["my","myanmar"],["bo","tibetan"],["tl","tagalog"],["mg","malagasy"],["as","assamese"],["tt","tatar"],["haw","hawaiian"],["ln","lingala"],["ha","hausa"],["ba","bashkir"],["jw","javanese"],["su","sundanese"]],Jn=new Map(Zn),Qn=new Map([...Zn.map((([t,e])=>[e,t])),["burmese","my"],["valencian","ca"],["flemish","nl"],["haitian","ht"],["letzeburgesch","lb"],["pushto","ps"],["panjabi","pa"],["moldavian","ro"],["moldovan","ro"],["sinhalese","si"],["castilian","es"]]);class tr extends mn{_default_chat_template='{% for message in messages %}" "{{ message.content }}{{ eos_token }}" "{% endfor %}';_decode_asr(t,{return_timestamps:e=!1,return_language:n=!1,time_precision:r=null,force_full_sequences:i=!0}={}){if(null===r)throw Error("Must specify time_precision");let s=null;const o="word"===e;function a(){return{language:s,timestamp:[null,null],text:""}}const u=[];let l=a(),c=0;const d=this.model.convert_tokens_to_ids(["<|notimestamps|>"])[0]+1;let h=[],p=[],f=!1,g=null;const m=new Set(this.all_special_ids);for(const n of t){const t=n.tokens,i=o?n.token_timestamps:null;let _=null,b=d;if("stride"in n){const[e,i,s]=n.stride;if(c-=i,g=e-s,i&&(b=i/r+d),s)for(let e=t.length-1;e>=0;--e){const n=t[e];if(n>=d){if(null!==_&&(n-d)*r<g)break;_=n}}}let y=[],w=[];for(let n=0;n<t.length;++n){const g=t[n];if(m.has(g)){const t=this.decode([g]),n=Jn.get(t.slice(2,-2));if(void 0!==n){if(null!==s&&n!==s&&!e){h.push(y);const t=this.findLongestCommonSequence(h)[0],e=this.decode(t);l.text=e,u.push(l),h=[],y=[],l=a()}s=l.language=n}}else if(g>=d){const t=Q((g-d)*r+c,2);if(null!==_&&g>=_)f=!0;else if(f||h.length>0&&g<b)f=!1;else if(null===l.timestamp[0])l.timestamp[0]=t;else if(t===l.timestamp[0]);else{l.timestamp[1]=t,h.push(y),o&&p.push(w);const[e,n]=this.findLongestCommonSequence(h,p),r=this.decode(e);l.text=r,o&&(l.words=this.collateWordTimestamps(e,n,s)),u.push(l),h=[],y=[],p=[],w=[],l=a()}}else if(y.push(g),o){let t,e=Q(i[n]+c,2);t=n+1<i.length?Q(i[n+1]+c,2):null,w.push([e,t])}}if("stride"in n){const[t,e,r]=n.stride;c+=t-r}y.length>0?(h.push(y),o&&p.push(w)):h.every((t=>0===t.length))&&(l=a(),h=[],y=[],p=[],w=[])}if(h.length>0){if(i&&e)throw new Error("Whisper did not predict an ending timestamp, which can happen if audio is cut off in the middle of a word. Also make sure WhisperTimeStampLogitsProcessor was used during generation.");const[t,n]=this.findLongestCommonSequence(h,p),r=this.decode(t);l.text=r,o&&(l.words=this.collateWordTimestamps(t,n,s)),u.push(l)}let _=Object.create(null);const b=u.map((t=>t.text)).join("");if(e||n){for(let t=0;t<u.length;++t){const r=u[t];e||delete r.timestamp,n||delete r.language}if(o){const t=[];for(const e of u)for(const n of e.words)t.push(n);_={chunks:t}}else _={chunks:u}}return[b,_]}findLongestCommonSequence(t,e=null){let n=t[0],r=n.length,i=[];const s=Array.isArray(e)&&e.length>0;let o=s?[]:null,a=s?e[0]:null;for(let u=1;u<t.length;++u){const l=t[u];let c=0,d=[r,r,0,0];const h=l.length;for(let t=1;t<r+h;++t){const e=t/1e4,i=Math.max(0,r-t),s=Math.min(r,r+h-t),o=n.slice(i,s),a=Math.max(0,t-r),u=Math.min(h,t),p=l.slice(a,u);if(o.length!==p.length)throw new Error("There is a bug within whisper `decode_asr` function, please report it. Dropping to prevent bad inference.");const f=o.filter(((t,e)=>t===p[e])).length,g=f/t+e;f>1&&g>c&&(c=g,d=[i,s,a,u])}const[p,f,g,m]=d,_=Math.floor((f+p)/2),b=Math.floor((m+g)/2);i.push(...n.slice(0,_)),n=l.slice(b),r=n.length,s&&(o.push(...a.slice(0,_)),a=e[u].slice(b))}return i.push(...n),s?(o.push(...a),[i,o]):[i,[]]}collateWordTimestamps(t,e,n){const[r,i,s]=this.combineTokensIntoWords(t,n),o=[];for(let t=0;t<r.length;++t){const n=s[t];o.push({text:r[t],timestamp:[e[n.at(0)][0],e[n.at(-1)][1]]})}return o}combineTokensIntoWords(t,e,n="\"'“¡¿([{-",r="\"'.。,，!！?？:：”)]}、"){let i,s,o;return["chinese","japanese","thai","lao","myanmar"].includes(e=e??"english")?[i,s,o]=this.splitTokensOnUnicode(t):[i,s,o]=this.splitTokensOnSpaces(t),this.mergePunctuations(i,s,o,n,r)}decode(t,e){let n;return e&&e.decode_with_timestamps?(t instanceof nt&&(t=he(t)),n=this.decodeWithTimestamps(t,e)):n=super.decode(t,e),n}decodeWithTimestamps(t,e){const n=e?.time_precision??.02,r=Array.from(this.all_special_ids).at(-1)+1;let i=[[]];for(const e of t)if(e>=r){const t=Q((e-r)*n,2);i.push(`<|${t}|>`),i.push([])}else i[i.length-1].push(e);return i=i.map((t=>"string"==typeof t?t:super.decode(t,e))),i.join("")}splitTokensOnUnicode(t){const e=this.decode(t,{decode_with_timestamps:!0}),n=[],r=[],i=[];let s=[],o=[],a=0;for(let u=0;u<t.length;++u){const l=t[u];s.push(l),o.push(u);const c=this.decode(s,{decode_with_timestamps:!0});c.includes("�")&&"�"!==e[a+c.indexOf("�")]||(n.push(c),r.push(s),i.push(o),s=[],o=[],a+=c.length)}return[n,r,i]}splitTokensOnSpaces(t){const[e,n,r]=this.splitTokensOnUnicode(t),i=[],s=[],o=[],a=new RegExp(`^[${ge}]$`,"gu");for(let t=0;t<e.length;++t){const u=e[t],l=n[t],c=r[t],d=l[0]>=this.model.tokens_to_ids.get("<|endoftext|>"),h=u.startsWith(" "),p=u.trim(),f=a.test(p);if(d||h||f||0===i.length)i.push(u),s.push(l),o.push(c);else{const t=i.length-1;i[t]+=u,s[t].push(...l),o[t].push(...c)}}return[i,s,o]}mergePunctuations(t,e,n,r,i){const s=structuredClone(t),o=structuredClone(e),a=structuredClone(n);let u=s.length-2,c=s.length-1;for(;u>=0;)s[u].startsWith(" ")&&r.includes(s[u].trim())?(s[c]=s[u]+s[c],o[c]=l(o[u],o[c]),a[c]=l(a[u],a[c]),s[u]="",o[u]=[],a[u]=[]):c=u,--u;for(u=0,c=1;c<s.length;)!s[u].endsWith(" ")&&i.includes(s[c])?(s[u]+=s[c],o[u]=l(o[u],o[c]),a[u]=l(a[u],a[c]),s[c]="",o[c]=[],a[c]=[]):u=c,++c;return[s.filter((t=>t)),o.filter((t=>t.length>0)),a.filter((t=>t.length>0))]}get_decoder_prompt_ids({language:t=null,task:e=null,no_timestamps:n=!0}={}){const r=[];if(t){t=t.toLowerCase();let e=Qn.get(t);if(void 0===e){if(!Jn.has(t)){const e=2===t.length?Jn.keys():Jn.values();throw new Error(`Language "${t}" is not supported. Must be one of: ${JSON.stringify(e)}`)}e=t}const n=this.model.tokens_to_ids.get(`<|${e}|>`);if(void 0===n)throw new Error(`Unable to find language "${e}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);r.push(n)}else r.push(null);if(e){if("transcribe"!==(e=e.toLowerCase())&&"translate"!==e)throw new Error(`Task "${e}" is not supported. Must be one of: ["transcribe", "translate"]`);const t=this.model.tokens_to_ids.get(`<|${e}|>`);if(void 0===t)throw new Error(`Unable to find task "${e}" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.`);r.push(t)}else r.push(null);if(n){const t=this.model.tokens_to_ids.get("<|notimestamps|>");if(void 0===t)throw new Error('Unable to find "<|notimestamps|>" in model vocabulary. Please report this issue at https://github.com/xenova/transformers.js/issues/new/choose.');r.push(t)}return r.map(((t,e)=>[e+1,t])).filter((t=>null!==t[1]))}}class er extends mn{}class nr extends mn{}class rr extends mn{}class ir extends mn{constructor(t,e){super(t,e),this.languageRegex=/^(>>\w+<<)\s*/g,this.supported_language_codes=this.model.vocab.filter((t=>this.languageRegex.test(t))),console.warn('WARNING: `MarianTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}_encode_text(t){if(null===t)return null;const[e,...n]=t.trim().split(this.languageRegex);if(0===n.length)return super._encode_text(e);if(2===n.length){const[t,e]=n;return this.supported_language_codes.includes(t)||console.warn(`Unsupported language code "${t}" detected, which may lead to unexpected behavior. Should be one of: ${JSON.stringify(this.supported_language_codes)}`),l([t],super._encode_text(e))}}}class sr extends mn{}class or extends mn{_default_chat_template="{% for message in messages %}{% if message['role'] == 'user' %}{{ ' ' }}{% endif %}{{ message['content'] }}{% if not loop.last %}{{ ' ' }}{% endif %}{% endfor %}{{ eos_token }}"}class ar extends or{}class ur extends mn{}class lr extends mn{}class cr extends mn{constructor(t,e){super(t,e),this.decoder=new sn({})}}class dr extends mn{}class hr{static TOKENIZER_CLASS_MAPPING={T5Tokenizer:Pn,DistilBertTokenizer:kn,CamembertTokenizer:On,DebertaTokenizer:vn,DebertaV2Tokenizer:xn,BertTokenizer:_n,HerbertTokenizer:Tn,ConvBertTokenizer:Sn,RoFormerTokenizer:An,XLMTokenizer:En,ElectraTokenizer:In,MobileBertTokenizer:yn,SqueezeBertTokenizer:wn,AlbertTokenizer:bn,GPT2Tokenizer:Dn,BartTokenizer:Cn,MBartTokenizer:$n,MBart50Tokenizer:Mn,RobertaTokenizer:Fn,WhisperTokenizer:tr,CodeGenTokenizer:er,CLIPTokenizer:nr,SiglipTokenizer:rr,MarianTokenizer:ir,BloomTokenizer:Ln,NllbTokenizer:Yn,M2M100Tokenizer:Kn,LlamaTokenizer:Rn,CodeLlamaTokenizer:jn,XLMRobertaTokenizer:zn,MPNetTokenizer:Bn,FalconTokenizer:Un,GPTNeoXTokenizer:Vn,EsmTokenizer:Gn,Wav2Vec2CTCTokenizer:sr,BlenderbotTokenizer:or,BlenderbotSmallTokenizer:ar,SpeechT5Tokenizer:ur,NougatTokenizer:lr,VitsTokenizer:cr,Qwen2Tokenizer:qn,GemmaTokenizer:Wn,Grok1Tokenizer:Hn,CohereTokenizer:dr,PreTrainedTokenizer:mn};static async from_pretrained(t,{quantized:e=!0,progress_callback:n=null,config:r=null,cache_dir:i=null,local_files_only:s=!1,revision:o="main",legacy:a=null}={}){const[u,l]=await le(t,{quantized:e,progress_callback:n,config:r,cache_dir:i,local_files_only:s,revision:o,legacy:a}),c=l.tokenizer_class?.replace(/Fast$/,"")??"PreTrainedTokenizer";let d=this.TOKENIZER_CLASS_MAPPING[c];return d||(console.warn(`Unknown tokenizer class "${c}", attempting to construct from base class.`),d=mn),new d(u,l)}}class pr{constructor(t){this.model_type=null,this.is_encoder_decoder=!1,Object.assign(this,t)}static async from_pretrained(t,{progress_callback:e=null,config:n=null,cache_dir:r=null,local_files_only:i=!1,revision:s="main"}={}){let o=n??await async function(t,e){return await U(t,"config.json",!0,e)}(t,{progress_callback:e,config:n,cache_dir:r,local_files_only:i,revision:s});return new this(o)}}class fr{static async from_pretrained(...t){return pr.from_pretrained(...t)}}class gr extends s{constructor(){super(),this.processors=[]}push(t){this.processors.push(t)}extend(t){this.processors.push(...t)}_call(t,e){for(let n of e)this.processors.forEach((e=>e(t,n)))}[Symbol.iterator](){return this.processors.values()}}class mr extends s{_call(t,e){throw Error("`_call` should be implemented in a subclass")}}class _r extends mr{constructor(t){super(),this.force_token_map=Object.fromEntries(t??[])}_call(t,e){let n=this.force_token_map[t.length];return null!=n&&(e.data.fill(-1/0),e.data[n]=0),e}}class br extends mr{constructor(t){super(),this.bos_token_id=t}_call(t,e){return 1===t.length&&(e.data.fill(-1/0),e.data[this.bos_token_id]=0),e}}class yr extends mr{constructor(t,e){super(),this.max_length=t,this.forced_eos_token_id=e}_call(t,e){}}class wr extends mr{constructor(t,e){super(),this.begin_suppress_tokens=t,this.begin_index=e}_call(t,e){if(t.length===this.begin_index)for(let t of this.begin_suppress_tokens)e.data[t]=-1/0;return e}}class vr extends mr{constructor(t){super(),this.eos_token_id=t.eos_token_id,this.no_timestamps_token_id=t.no_timestamps_token_id,this.timestamp_begin=this.no_timestamps_token_id+1,this.begin_index=(t.forced_decoder_ids||[]).length+2,t.forced_decoder_ids.slice(-1)[0][1]===this.no_timestamps_token_id&&(this.begin_index-=1),this.max_initial_timestamp_index=t.max_initial_timestamp_index}_call(t,e){const n=e.data;if(n[this.no_timestamps_token_id]=-1/0,t.length===this.begin_index-1)return n.fill(-1/0),n[this.timestamp_begin]=0,e;const r=t.slice(this.begin_index),i=r.length>=1&&r[r.length-1]>=this.timestamp_begin,s=r.length<2||r[r.length-2]>=this.timestamp_begin;if(i&&(s?n.subarray(this.timestamp_begin).fill(-1/0):n.subarray(0,this.eos_token_id).fill(-1/0)),t.length===this.begin_index&&null!==this.max_initial_timestamp_index){const t=this.timestamp_begin+this.max_initial_timestamp_index;n.subarray(t+1).fill(-1/0)}const o=G(n).map((t=>Math.log(t)));return Math.log(o.subarray(this.timestamp_begin).map(Math.exp).reduce(((t,e)=>t+e)))>H(o.subarray(0,this.timestamp_begin))[0]&&n.subarray(0,this.timestamp_begin).fill(-1/0),e}}class xr extends mr{constructor(t){super(),this.no_repeat_ngram_size=t}getNgrams(t){const e=t.length,n=[];for(let r=0;r<e+1-this.no_repeat_ngram_size;++r){const e=[];for(let n=0;n<this.no_repeat_ngram_size;++n)e.push(t[r+n]);n.push(e)}const r=new Map;for(const t of n){const e=t.slice(0,t.length-1),n=JSON.stringify(e),i=r.get(n)??[];i.push(t[t.length-1]),r.set(n,i)}return r}getGeneratedNgrams(t,e){const n=e.slice(e.length+1-this.no_repeat_ngram_size,e.length);return t.get(JSON.stringify(n))??[]}calcBannedNgramTokens(t){if(t.length+1<this.no_repeat_ngram_size)return[];{const e=this.getNgrams(t);return this.getGeneratedNgrams(e,t)}}_call(t,e){const n=this.calcBannedNgramTokens(t);for(const t of n)e.data[t]=-1/0;return e}}class Tr extends mr{constructor(t){super(),this.penalty=t}_call(t,e){for(const n of t)e.data[n]<0?e.data[n]*=this.penalty:e.data[n]/=this.penalty;return e}}class Sr extends mr{constructor(t,e){super(),this.min_length=t,this.eos_token_id=Array.isArray(e)?e:[e]}_call(t,e){if(t.length<this.min_length)for(const t of this.eos_token_id)e.data[t]=-1/0;return e}}class Ar extends mr{constructor(t,e,n){super(),this.prompt_length_to_skip=t,this.min_new_tokens=e,this.eos_token_id=Array.isArray(n)?n:[n]}_call(t,e){if(t.length-this.prompt_length_to_skip<this.min_new_tokens)for(const t of this.eos_token_id)e.data[t]=-1/0;return e}}class kr extends mr{constructor(t,e){super(),this.bad_words_ids=t,this.eos_token_id=Array.isArray(e)?e:[e]}_call(t,e){for(const n of this.bad_words_ids){let r=!0;for(let e=1;e<=n.length-1&&n.length<t.length;++e)if(n.at(-e-1)!==t.at(-e)){r=!1;break}r&&(e.data[n.at(-1)]=-1/0)}return e}}const Or=class{constructor(t={}){this.max_length=t.max_length??20,this.max_new_tokens=t.max_new_tokens??null,this.min_length=t.min_length??0,this.min_new_tokens=t.min_new_tokens??null,this.early_stopping=t.early_stopping??!1,this.max_time=t.max_time??null,this.do_sample=t.do_sample??!1,this.num_beams=t.num_beams??1,this.num_beam_groups=t.num_beam_groups??1,this.penalty_alpha=t.penalty_alpha??null,this.use_cache=t.use_cache??!0,this.temperature=t.temperature??1,this.top_k=t.top_k??50,this.top_p=t.top_p??1,this.typical_p=t.typical_p??1,this.epsilon_cutoff=t.epsilon_cutoff??0,this.eta_cutoff=t.eta_cutoff??0,this.diversity_penalty=t.diversity_penalty??0,this.repetition_penalty=t.repetition_penalty??1,this.encoder_repetition_penalty=t.encoder_repetition_penalty??1,this.length_penalty=t.length_penalty??1,this.no_repeat_ngram_size=t.no_repeat_ngram_size??0,this.bad_words_ids=t.bad_words_ids??null,this.force_words_ids=t.force_words_ids??null,this.renormalize_logits=t.renormalize_logits??!1,this.constraints=t.constraints??null,this.forced_bos_token_id=t.forced_bos_token_id??null,this.forced_eos_token_id=t.forced_eos_token_id??null,this.remove_invalid_values=t.remove_invalid_values??!1,this.exponential_decay_length_penalty=t.exponential_decay_length_penalty??null,this.suppress_tokens=t.suppress_tokens??null,this.begin_suppress_tokens=t.begin_suppress_tokens??null,this.forced_decoder_ids=t.forced_decoder_ids??null,this.num_return_sequences=t.num_return_sequences??1,this.output_attentions=t.output_attentions??!1,this.output_hidden_states=t.output_hidden_states??!1,this.output_scores=t.output_scores??!1,this.return_dict_in_generate=t.return_dict_in_generate??!1,this.pad_token_id=t.pad_token_id??null,this.bos_token_id=t.bos_token_id??null,this.eos_token_id=t.eos_token_id??null,this.encoder_no_repeat_ngram_size=t.encoder_no_repeat_ngram_size??0,this.decoder_start_token_id=t.decoder_start_token_id??null,this.generation_kwargs=t.generation_kwargs??{}}};class Er extends s{constructor(t){super(),this.generation_config=t}_call(t,e=-1){return this.sample(t,e)}sample(t,e){throw Error("sample should be implemented in subclasses.")}getLogits(t,e){let n=t.dims.at(-1),r=t.data;if(-1===e)r=r.slice(-n);else{let t=e*n;r=r.slice(t,t+n)}return this.generation_config.temperature>0&&(r=r.map((t=>t/this.generation_config.temperature))),r}randomSelect(t){let e=t.reduce(((t,e)=>t+e),0),n=Math.random()*e;for(let e=0;e<t.length;++e)if(n-=t[e],n<=0)return e;return 0}static getSampler(t){if(t.do_sample)return new Pr(t);if(t.num_beams>1)return new Dr(t);if(t.num_return_sequences>1)throw Error(`num_return_sequences has to be 1 when doing greedy search, but is ${t.num_return_sequences}.`);return new Ir(t)}}class Ir extends Er{sample(t,e=-1){return[[H(this.getLogits(t,e))[1],0]]}}class Pr extends Er{sample(t,e=-1){let n=t.dims.at(-1);this.generation_config.top_k>0&&(n=Math.min(this.generation_config.top_k,n));const r=q(this.getLogits(t,e),n),i=G(r.map((t=>t[1])));return Array.from({length:this.generation_config.num_beams},(()=>{const t=this.randomSelect(i);return[r[t][0],Math.log(i[t])]}))}}class Dr extends Er{sample(t,e=-1){let n=t.dims.at(-1);this.generation_config.top_k>0&&(n=Math.min(this.generation_config.top_k,n));const r=q(this.getLogits(t,e),n),i=G(r.map((t=>t[1])));return Array.from({length:this.generation_config.num_beams},((t,e)=>[r[e][0],Math.log(i[e])]))}}const{InferenceSession:Cr,Tensor:$r,env:Mr}=x,Fr=new Map,Lr=new Map,Nr=new Map;async function Rr(t,e,n){let r=`onnx/${e}${n.quantized?"_quantized":""}.onnx`,i=await B(t,r,!0,n);try{return await Cr.create(i,{executionProviders:T})}catch(t){if(1===T.length&&"wasm"===T[0])throw t;return console.warn(t),console.warn("Something went wrong during model construction (most likely a missing operation). Using `wasm` as a fallback. "),await Cr.create(i,{executionProviders:["wasm"]})}}async function jr(t,e){const n=function(t,e){const n=Object.create(null),r=[];for(const i of t.inputNames){const t=e[i];t instanceof nt?n[i]=Mr.wasm.proxy?t.clone():t:r.push(i)}if(r.length>0)throw new Error(`An error occurred during model execution: "Missing the following inputs: ${r.join(", ")}.`);const i=Object.keys(e).length,s=t.inputNames.length;if(i>s){let n=Object.keys(e).filter((e=>!t.inputNames.includes(e)));console.warn(`WARNING: Too many inputs were provided (${i} > ${s}). The following inputs will be ignored: "${n.join(", ")}".`)}return n}(t,e);try{let e=await t.run(n);return e=zr(e),e}catch(t){throw console.error(`An error occurred during model execution: "${t}".`),console.error("Inputs given to model:",n),t}}function zr(t){for(let e in t)t[e]instanceof $r?t[e]=new nt(t[e]):"object"==typeof t[e]&&zr(t[e]);return t}function Br(t){if(t instanceof nt)return t;if(0===t.length)throw Error("items must be non-empty");if(Array.isArray(t[0])){if(t.some((e=>e.length!==t[0].length)))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' and/or 'truncation=True' to have batched tensors with the same length.");return new nt("int64",BigInt64Array.from(t.flat().map((t=>BigInt(t)))),[t.length,t[0].length])}return new nt("int64",BigInt64Array.from(t.map((t=>BigInt(t)))),[1,t.length])}function Ur(t,e){let n=t.config.pad_token_id??null,r=t.config.eos_token_id??null;o(r)&&(r=[r]);let i=-1!==e.indexOf(n),s=null===r||!r.includes(n);if(i&&s){let t=BigInt64Array.from(e.data.map((t=>t!=n)));return new nt("int64",t,e.dims)}return function(t){const e=t.reduce(((t,e)=>t*e),1);return new nt("int64",new BigInt64Array(e).fill(1n),t)}(e.dims)}function Vr(t,e,n){if(!t.inputNames.includes("position_ids"))return;const r=new BigInt64Array(e.attention_mask.data.length);for(let t=0;t<e.attention_mask.dims[0];++t){let n=t*e.attention_mask.dims[1],i=BigInt(0);for(let t=0;t<e.attention_mask.dims[1];++t){const s=n+t;0n===e.attention_mask.data[s]?r[s]=BigInt(1):(r[s]=i,i+=e.attention_mask.data[s])}}e.position_ids=new nt("int64",r,e.attention_mask.dims),n&&(e.position_ids=e.position_ids.slice(null,-1).unsqueeze_(-1))}function Gr(t){return new nt("bool",[t],[1])}async function qr(t,e){let{encoder_outputs:n,past_key_values:r}=e;n||(n=(await Yr(t,e)).last_hidden_state);let i={input_ids:e.decoder_input_ids,encoder_hidden_states:n};const s=!!r;t.decoder_merged_session.inputNames.includes("use_cache_branch")&&(i.use_cache_branch=Gr(s)),t.decoder_merged_session.inputNames.includes("encoder_attention_mask")&&(i.encoder_attention_mask=e.attention_mask),Vr(t.decoder_merged_session,i,s),t.addPastKeyValues(i,r);const o=await jr(t.decoder_merged_session,i);let a=o.logits;r=t.getPastKeyValues(o,r);const u=t.getAttentions(o);return new bo({logits:a,past_key_values:r,encoder_outputs:n,...u})}function Wr(t,e,n,r){let i=[],s=0;const o=t.requires_attention_mask??!0;let a=n.decoder_input_ids??n.decoder_start_token_id??n.bos_token_id??n.eos_token_id;a instanceof nt?a=a.tolist().flat():Array.isArray(a)||(a=[a]);for(let n of e){n.dims=[1,...n.dims];let e={inputs:n,encoder_outputs:null,prev_model_outputs:null,output_token_ids:a,done:!1,score:0,id:s++};o&&(e.attention_mask=Ur(t,n)),i.push(e)}return i}async function Hr(t,e){const n=t.main_input_name;let r=e.output_token_ids;e.prev_model_outputs&&(r=r.slice(-1));let i={[n]:e.inputs,decoder_input_ids:Br(r),encoder_outputs:e.encoder_outputs,past_key_values:e.prev_model_outputs?.past_key_values};e.attention_mask&&(i.attention_mask=e.attention_mask);let s=await t.forward(i);return e.prev_model_outputs=s,e.encoder_outputs=s.encoder_outputs,s}function Xr(t,e){t.output_token_ids=[...t.output_token_ids,e]}async function Yr(t,e){const n=Object.create(null);for(const r of t.session.inputNames)n[r]=e[r];return t.session.inputNames.includes("token_type_ids")&&!n.token_type_ids&&(n.token_type_ids=new nt("int64",new BigInt64Array(n.input_ids.data.length),n.input_ids.dims)),await jr(t.session,n)}async function Kr(t,e){let{input_ids:n,past_key_values:r,attention_mask:i}=e,s={input_ids:n,attention_mask:i??Ur(t,n)};const o=!!r;t.session.inputNames.includes("use_cache_branch")&&(s.use_cache_branch=Gr(o)),Vr(t.session,s,o),t.addPastKeyValues(s,r);let a=await jr(t.session,s),u=a.logits;return r=t.getPastKeyValues(a,r),{logits:u,past_key_values:r}}function Zr(t,e,n,r,i){let s=[],o=0;for(let n of e){let e,a=n.tolist().map(Number);n.dims=[1,...n.dims],i?(e=i[o],e.dims=[1,...e.dims]):e=Ur(t,n);let u={input:n,model_input_ids:n,attention_mask:e,prev_model_outputs:null,output_token_ids:a,num_output_tokens:r,done:!1,score:0,id:o++};s.push(u)}return s}async function Jr(t,e){let n=new BigInt64Array(e.output_token_ids.length).fill(1n),r={input_ids:e.model_input_ids,attention_mask:new nt("int64",n,[1,n.length]),past_key_values:e.prev_model_outputs?.past_key_values},i=await t.forward(r);return e.prev_model_outputs=i,i}function Qr(t,e){t.output_token_ids=[...t.output_token_ids,e],t.model_input_ids=new nt("int64",[BigInt(e)],[1,1])}class ti extends s{main_input_name="input_ids";constructor(t,e){super(),this.config=t,this.session=e;const n=Nr.get(this.constructor),r=Fr.get(n);this.can_generate=!1,this._runBeam=null,this._getStartBeams=null,this._updateBeam=null,this._forward=null,4===r?(this.can_generate=!0,this._runBeam=Jr,this._getStartBeams=Zr,this._updateBeam=Qr,this._forward=Kr):2===r||3===r?(this.can_generate=!0,this._runBeam=Hr,this._getStartBeams=Wr,this._updateBeam=Xr,this._forward=qr):this._forward=Yr}async dispose(){const t=[];for(let e of Object.keys(this)){const n=this[e];n instanceof Cr&&t.push(n.handler.dispose())}return await Promise.all(t)}static async from_pretrained(t,{quantized:e=!0,progress_callback:n=null,config:r=null,cache_dir:i=null,local_files_only:s=!1,revision:o="main",model_file_name:a=null}={}){let u={quantized:e,progress_callback:n,config:r,cache_dir:i,local_files_only:s,revision:o,model_file_name:a};const l=Nr.get(this),c=Fr.get(l);let d;return 4===c?d=await Promise.all([fr.from_pretrained(t,u),Rr(t,u.model_file_name??"decoder_model_merged",u),U(t,"generation_config.json",!1,u)]):2===c||3===c?d=await Promise.all([fr.from_pretrained(t,u),Rr(t,"encoder_model",u),Rr(t,"decoder_model_merged",u),U(t,"generation_config.json",!1,u)]):5===c?d=await Promise.all([fr.from_pretrained(t,u),Rr(t,"vision_encoder",u),Rr(t,"prompt_encoder_mask_decoder",u)]):1===c?d=await Promise.all([fr.from_pretrained(t,u),Rr(t,"encoder_model",u),Rr(t,"decoder_model_merged",u)]):(0!==c&&console.warn(`Model type for '${l??r?.model_type}' not found, assuming encoder-only architecture. Please report this at https://github.com/xenova/transformers.js/issues/new/choose.`),d=await Promise.all([fr.from_pretrained(t,u),Rr(t,u.model_file_name??"model",u)])),new this(...d)}async _call(t){return await this.forward(t)}async forward(t){return await this._forward(this,t)}_get_logits_processor(t,e,n=null){const r=new gr;if(null!==t.repetition_penalty&&1!==t.repetition_penalty&&r.push(new Tr(t.repetition_penalty)),null!==t.no_repeat_ngram_size&&t.no_repeat_ngram_size>0&&r.push(new xr(t.no_repeat_ngram_size)),null!==t.bad_words_ids&&r.push(new kr(t.bad_words_ids,t.eos_token_id)),null!==t.min_length&&null!==t.eos_token_id&&t.min_length>0&&r.push(new Sr(t.min_length,t.eos_token_id)),null!==t.min_new_tokens&&null!==t.eos_token_id&&t.min_new_tokens>0&&r.push(new Ar(e,t.min_new_tokens,t.eos_token_id)),null!==t.forced_bos_token_id&&r.push(new br(t.forced_bos_token_id)),null!==t.forced_eos_token_id&&r.push(new yr(t.max_length,t.forced_eos_token_id)),null!==t.begin_suppress_tokens){let n=e>1||null===t.forced_bos_token_id?e:e+1;null!==t.forced_decoder_ids&&(n+=t.forced_decoder_ids[t.forced_decoder_ids.length-1][0]),r.push(new wr(t.begin_suppress_tokens,n))}return null!==t.forced_decoder_ids&&r.push(new _r(t.forced_decoder_ids)),null!==n&&r.extend(n),r}_get_generation_config(t){let e=new Or(this.config);return"generation_config"in this&&Object.assign(e,this.generation_config),null!==t&&Object.assign(e,t),e}async generate(t,e=null,n=null,{inputs_attention_mask:r=null}={}){if(!this.can_generate){let t=`The current model class (${Nr.get(this.constructor)}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;const e=this.config.model_type,n=Hs.get(e)??Ws.get(e)??Bs.get(e)??Ks.get(e);throw n&&(t+=` Please use the following class instead: '${n[0]}'`),Error(t)}if(!(t instanceof nt||(i=t,"TypedArray"===i?.prototype?.__proto__?.constructor?.name)||Array.isArray(t)))throw Error(`\`inputs\` must be a Tensor, TypedArray, or Array, but is "${t.constructor.name}".`);var i;let s;if(this.config.is_encoder_decoder)s=0;else if(s=t instanceof nt?t.dims.at(-1):t.length,0===s)throw Error("Must supply a non-empty array of input token ids.");e=this._get_generation_config(e),n=n??new gr,n=this._get_logits_processor(e,s,n);let o=e.eos_token_id;null===o||Array.isArray(o)||(o=[o]);let a=1;const u=a+(e.max_new_tokens??1/0),l=Number.isInteger(e.max_length)&&null===(e.max_new_tokens??null);let c=Er.getSampler(e),d=this.getStartBeams(t,e,a,r);for(;d.some((t=>!t.done))&&a<u;){let t=[];for(let r of d){if(r.done){t.push(r);continue}if(l&&r.output_token_ids.length>=e.max_length){r.done=!0,t.push(r);continue}let i=await this.runBeam(r);e.output_attentions&&this.addAttentionsToBeam(r,i),e.output_scores;let s=i.logits.slice(null,-1,null);n(r.output_token_ids,s);let a=c(s);for(let[e,n]of a){let i={...r};this.updateBeam(i,e),i.score+=n,o&&o.includes(e)&&(i.done=!0),t.push(i)}}++a,t=this.groupBeams(t).map((t=>t.sort(((t,e)=>e.score-t.score)).slice(0,e.num_beams))),d=t.flat(),e.callback_function&&e.callback_function(d)}const h=this.groupBeams(d),p=t=>h.map((n=>e.num_return_sequences>1?n.slice(0,e.num_return_sequences).map((e=>e[t])):[n[0][t]])).flat(),f=p("output_token_ids");return e.return_dict_in_generate?{sequences:f,decoder_attentions:p("decoder_attentions"),cross_attentions:p("cross_attentions")}:f}addAttentionsToBeam(t,e){if(this.config.is_encoder_decoder){if(!e.cross_attentions||0===e.cross_attentions.length)throw Error("`output_attentions` is true, but the model did not produce cross-attentions. This is most likely because the model was not exported with `output_attentions=True`.");t.cross_attentions||(t.cross_attentions=[]),t.cross_attentions.push(e.cross_attentions)}if(!e.decoder_attentions||0===e.decoder_attentions.length)throw Error("`output_attentions` is true, but the model did not produce decoder-attentions. This is most likely because the model was not exported with `output_attentions=True`.");t.decoder_attentions||(t.decoder_attentions=[]),t.decoder_attentions.push(e.decoder_attentions)}groupBeams(t){const e=Object.create(null);for(const n of t)void 0===e[n.id]?e[n.id]=[n]:e[n.id].push(n);return Object.values(e)}getPastKeyValues(t,e){const n=Object.create(null);for(const r in t)if(r.startsWith("present")){let i=r.replace("present","past_key_values");e&&r.includes("encoder")?n[i]=e[i]:n[i]=t[r]}return n}getAttentions(t){const e=Object.create(null);for(const n of["cross_attentions","decoder_attentions"]){const r=[];for(const e in t)e.startsWith(n)&&(r[e.split(".").pop()]=t[e]);e[n]=r}return e}addPastKeyValues(t,e){if(e)Object.assign(t,e);else{const e=1;if(this.config.is_encoder_decoder&&(this.add_encoder_pkv??1)){let n=[e,this.num_encoder_heads,0,this.encoder_dim_kv],r=[e,this.num_decoder_heads,0,this.decoder_dim_kv];for(let e=0;e<this.num_decoder_layers;++e)t[`past_key_values.${e}.encoder.key`]=new nt("float32",[],n),t[`past_key_values.${e}.encoder.value`]=new nt("float32",[],n),t[`past_key_values.${e}.decoder.key`]=new nt("float32",[],r),t[`past_key_values.${e}.decoder.value`]=new nt("float32",[],r)}else if("falcon"===this.config.model_type){let n=[e*this.num_heads,0,this.dim_kv];for(let e=0;e<this.num_layers;++e)t[`past_key_values.${e}.key`]=new nt("float32",[],n),t[`past_key_values.${e}.value`]=new nt("float32",[],n)}else if(this.config.multi_query){let n=[e*this.num_heads,0,2*this.dim_kv];for(let e=0;e<this.num_layers;++e)t[`past_key_values.${e}.key_value`]=new nt("float32",[],n)}else if("bloom"===this.config.model_type){let n=[e*this.num_heads,this.dim_kv,0],r=[e*this.num_heads,0,this.dim_kv];for(let e=0;e<this.num_layers;++e)t[`past_key_values.${e}.key`]=new nt("float32",[],n),t[`past_key_values.${e}.value`]=new nt("float32",[],r)}else{let n=[e,this.num_heads,0,this.dim_kv];for(let e=0;e<this.num_layers;++e)t[`past_key_values.${e}.key`]=new nt("float32",[],n),t[`past_key_values.${e}.value`]=new nt("float32",[],n)}}}getStartBeams(t,e,n,r){return this._getStartBeams(this,t,e,n,r)}async runBeam(t){return await this._runBeam(this,t)}updateBeam(t,e){return this._updateBeam(t,e)}}class ei{}class ni extends ti{}class ri extends ti{}class ii extends ti{}class si extends ti{}class oi extends ti{}class ai extends ti{}class ui extends ti{}class li extends ti{}class ci extends ti{}class di extends ti{}class hi extends ti{}class pi extends ti{}class fi extends ti{}class gi extends ti{}class mi extends ti{}class _i extends ti{}class bi extends ti{}class yi extends ti{}class wi extends ti{}class vi extends ti{}class xi extends ti{}class Ti extends ti{}class Si extends ti{}class Ai extends ti{}class ki extends ti{}class Oi extends ti{}class Ei extends ti{main_input_name="pixel_values";constructor(t,e,n,r){super(t,e),this.decoder_merged_session=n,this.generation_config=r;const i=this.config.encoder,s=this.config.decoder,o=i.model_type;(Rs.get(o)??js.get(o))||console.warn(`Model type for encoder '${o}' not found, assuming encoder-only architecture. Please report this at https://github.com/xenova/transformers.js/issues/new/choose.`);const a=Hs.get(s.model_type);if(!a)throw new Error(`Unable to construct \`VisionEncoderDecoder\` due to unsupported decoder: "${this.config.decoder.model_type}"`);const u=new(0,a[1])(s,n,r);this.add_encoder_pkv="num_decoder_layers"in u,this.add_encoder_pkv?(this.num_decoder_layers=u.num_decoder_layers,this.num_decoder_heads=u.num_decoder_heads,this.decoder_dim_kv=u.decoder_dim_kv,this.num_encoder_layers=u.num_encoder_layers,this.num_encoder_heads=u.num_encoder_heads,this.encoder_dim_kv=u.encoder_dim_kv):(this.num_layers=u.num_layers,this.num_heads=u.num_heads,this.dim_kv=u.dim_kv)}}class Ii extends ti{}class Pi extends ti{}class Di extends ti{}class Ci extends ti{}class $i extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.n_embd/this.num_heads}}class Mi extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_heads,this.num_layers=this.config.num_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class Fi extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class Li extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.n_embd/this.num_heads}}class Ni extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.n_embd/this.num_heads}}class Ri extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.n_embd/this.num_heads}}class ji extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads??this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class zi extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads??this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class Bi extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class Ui extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_head,this.num_layers=this.config.n_layer,this.dim_kv=this.config.hidden_size/this.num_heads}}class Vi extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.n_heads,this.num_layers=this.config.n_layers,this.dim_kv=this.config.d_model/this.num_heads}}class Gi extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class qi extends ti{}class Wi extends ti{}class Hi extends ti{}class Xi extends ti{}class Yi extends ti{}class Ki extends ti{}class Zi extends ti{}class Ji extends ei{constructor({logits:t,pred_boxes:e}){super(),this.logits=t,this.pred_boxes=e}}class Qi extends ei{constructor({logits:t,pred_boxes:e,pred_masks:n}){super(),this.logits=t,this.pred_boxes=e,this.pred_masks=n}}class ts extends ti{}class es extends Ji{}class ns extends ti{}class rs extends ti{}class is extends ti{}class ss extends ti{}class os extends ti{}class as extends ti{}class us extends ti{}class ls extends ti{}class cs extends ti{}class ds extends ti{}class hs extends ti{}class ps extends ti{}class fs extends ei{constructor({logits:t,pred_boxes:e}){super(),this.logits=t,this.pred_boxes=e}}class gs extends ti{}class ms extends ei{constructor({iou_scores:t,pred_masks:e}){super(),this.iou_scores=t,this.pred_masks=e}}class _s extends ti{}class bs extends ti{}class ys extends ti{}class ws extends ti{}class vs extends ti{}class xs extends ti{}class Ts extends ti{}class Ss extends ti{}class As extends Ss{constructor(t,e,n,r){super(t,e),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.hidden_size/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.hidden_size/this.num_encoder_heads}async generate_speech(t,e,{threshold:n=.5,minlenratio:r=0,maxlenratio:i=20,vocoder:s=null}={}){const o={input_ids:t},{encoder_outputs:a,encoder_attention_mask:u}=await Yr(this,o),l=a.dims[1]/this.config.reduction_factor,c=Math.floor(l*i),d=Math.floor(l*r),h=this.config.num_mel_bins;let p=[],f=null,g=null,m=0;for(;;){++m;const t=Gr(!!g);let r;r=g?g.output_sequence_out:new nt("float32",new Float32Array(h),[1,1,h]);let i={use_cache_branch:t,output_sequence:r,encoder_attention_mask:u,speaker_embeddings:e,encoder_hidden_states:a};this.addPastKeyValues(i,f),g=await jr(this.decoder_merged_session,i),f=this.getPastKeyValues(g,f);const{prob:s,spectrum:o}=g;if(p.push(o),m>=d&&(Array.from(s.data).filter((t=>t>=n)).length>0||m>=c))break}const _=at(p),{waveform:b}=await jr(s.session,{spectrogram:_});return{spectrogram:_,waveform:b}}}class ks extends ti{main_input_name="spectrogram"}class Os extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_encoder_layers=this.num_decoder_layers=this.config.decoder_layers,this.num_encoder_heads=this.num_decoder_heads=this.config.decoder_attention_heads,this.encoder_dim_kv=this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads}}class Es extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class Is extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class Ps extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class Ds extends ti{}class Cs extends ti{}class $s extends Cs{async _call(t){return new ko(await super._call(t))}}class Ms extends ti{}class Fs extends ti{constructor(t,e,n){super(t,e),this.generation_config=n,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class Ls extends ti{}class Ns{static MODEL_CLASS_MAPPINGS=null;static BASE_IF_FAIL=!1;static async from_pretrained(t,{quantized:e=!0,progress_callback:n=null,config:r=null,cache_dir:i=null,local_files_only:s=!1,revision:o="main",model_file_name:a=null}={}){let u={quantized:e,progress_callback:n,config:r,cache_dir:i,local_files_only:s,revision:o,model_file_name:a};if(r=await fr.from_pretrained(t,u),u.config||(u.config=r),!this.MODEL_CLASS_MAPPINGS)throw new Error("`MODEL_CLASS_MAPPINGS` not implemented for this type of `AutoClass`: "+this.name);for(let e of this.MODEL_CLASS_MAPPINGS){const n=e.get(r.model_type);if(n)return await n[1].from_pretrained(t,u)}if(this.BASE_IF_FAIL)return console.warn(`Unknown model class "${r.model_type}", attempting to construct from base class.`),await ti.from_pretrained(t,u);throw Error(`Unsupported model type: ${r.model_type}`)}}const Rs=new Map([["bert",["BertModel",class extends ni{}]],["nomic_bert",["NomicBertModel",class extends ri{}]],["roformer",["RoFormerModel",class extends ii{}]],["electra",["ElectraModel",class extends oi{}]],["esm",["EsmModel",class extends di{}]],["convbert",["ConvBertModel",class extends si{}]],["camembert",["CamembertModel",class extends ai{}]],["deberta",["DebertaModel",class extends ui{}]],["deberta-v2",["DebertaV2Model",class extends li{}]],["mpnet",["MPNetModel",class extends pi{}]],["albert",["AlbertModel",class extends gi{}]],["distilbert",["DistilBertModel",class extends ci{}]],["roberta",["RobertaModel",class extends Ti{}]],["xlm",["XLMModel",class extends Si{}]],["xlm-roberta",["XLMRobertaModel",class extends Ai{}]],["clap",["ClapModel",class extends Ds{}]],["clip",["CLIPModel",class extends Ii{}]],["clipseg",["CLIPSegModel",class extends Ci{}]],["chinese_clip",["ChineseCLIPModel",class extends Di{}]],["siglip",["SiglipModel",class extends Pi{}]],["mobilebert",["MobileBertModel",class extends hi{}]],["squeezebert",["SqueezeBertModel",class extends fi{}]],["wav2vec2",["Wav2Vec2Model",class extends ys{}]],["wav2vec2-bert",["Wav2Vec2BertModel",class extends xs{}]],["unispeech",["UniSpeechModel",class extends ws{}]],["unispeech-sat",["UniSpeechSatModel",class extends vs{}]],["hubert",["HubertModel",class extends ys{}]],["wavlm",["WavLMModel",class extends Ts{}]],["audio-spectrogram-transformer",["ASTModel",class extends ki{}]],["vits",["VitsModel",$s]],["detr",["DetrModel",class extends Zi{}]],["table-transformer",["TableTransformerModel",class extends ts{}]],["vit",["ViTModel",class extends qi{}]],["mobilevit",["MobileViTModel",class extends Hi{}]],["owlvit",["OwlViTModel",class extends Xi{}]],["owlv2",["Owlv2Model",class extends Yi{}]],["beit",["BeitModel",class extends Ki{}]],["deit",["DeiTModel",class extends ns{}]],["convnext",["ConvNextModel",class extends cs{}]],["convnextv2",["ConvNextV2Model",class extends ds{}]],["dinov2",["Dinov2Model",class extends hs{}]],["resnet",["ResNetModel",class extends rs{}]],["swin",["SwinModel",class extends is{}]],["swin2sr",["Swin2SRModel",class extends ss{}]],["donut-swin",["DonutSwinModel",class extends ls{}]],["yolos",["YolosModel",class extends ps{}]],["dpt",["DPTModel",class extends os{}]],["glpn",["GLPNModel",class extends us{}]],["hifigan",["SpeechT5HifiGan",ks]],["efficientnet",["EfficientNetModel",class extends Ls{}]]]),js=new Map([["t5",["T5Model",class extends mi{}]],["longt5",["LongT5Model",class extends _i{}]],["mt5",["MT5Model",class extends bi{}]],["bart",["BartModel",class extends yi{}]],["mbart",["MBartModel",class extends wi{}]],["marian",["MarianModel",class extends _s{}]],["whisper",["WhisperModel",class extends Oi{}]],["m2m_100",["M2M100Model",class extends bs{}]],["blenderbot",["BlenderbotModel",class extends vi{}]],["blenderbot-small",["BlenderbotSmallModel",class extends xi{}]]]),zs=new Map([["bloom",["BloomModel",class extends Ui{}]],["gpt2",["GPT2Model",class extends $i{}]],["gptj",["GPTJModel",class extends Li{}]],["gpt_bigcode",["GPTBigCodeModel",class extends Ni{}]],["gpt_neo",["GPTNeoModel",class extends Mi{}]],["gpt_neox",["GPTNeoXModel",class extends Fi{}]],["codegen",["CodeGenModel",class extends Ri{}]],["llama",["LlamaModel",class extends ji{}]],["qwen2",["Qwen2Model",class extends zi{}]],["phi",["PhiModel",class extends Bi{}]],["mpt",["MptModel",class extends Vi{}]],["opt",["OPTModel",class extends Gi{}]],["mistral",["MistralModel",class extends Es{}]],["starcoder2",["Starcoder2Model",class extends Is{}]],["falcon",["FalconModel",class extends Ps{}]]]),Bs=new Map([["speecht5",["SpeechT5ForSpeechToText",class extends Ss{}]],["whisper",["WhisperForConditionalGeneration",class extends Oi{requires_attention_mask=!1;main_input_name="input_features";constructor(t,e,n,r){super(t,e),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}async generate(t,e=null,n=null){if(e=this._get_generation_config(e),e.return_timestamps??=!1,e.return_timestamps&&(n=[new vr(e)]),e.return_token_timestamps&&(e.output_attentions=!0,e.return_dict_in_generate=!0,"translate"===e.task&&console.warn("Token-level timestamps may not be reliable for task 'translate'."),!e.alignment_heads))throw new Error("Model generation config has no `alignment_heads`, token-level timestamps not available. See https://gist.github.com/hollance/42e32852f24243b748ae6bc1f985b13a on how to add this property to the generation config.");const r=await super.generate(t,e,n);return e.return_token_timestamps&&e.alignment_heads&&(r.token_timestamps=this._extract_token_timestamps(r,e.alignment_heads,e.num_frames)),r}_extract_token_timestamps(t,e,n=null,r=.02){if(!t.cross_attentions)throw new Error("Model outputs must contain cross attentions to extract timestamps. This is most likely because the model was not exported with `output_attentions=True`.");let i=this.config.median_filter_width;void 0===i&&(console.warn("Model config has no `median_filter_width`, using default value of 7."),i=7);const s=t.cross_attentions.map((t=>{let r=Array.from({length:this.config.decoder_layers},((e,n)=>at(t.map((t=>t[n])),2))),s=ut(e.map((([t,e])=>n?r[t].slice(null,e,null,[0,n]):r[t].slice(null,e))));s=s.transpose(1,0,2,3);let[o,a]=function(t,e=null,n=1,r=!1){if(null===e){const e=t.data.reduce(((t,e)=>t+e),0)/t.data.length,r=Math.sqrt(t.data.reduce(((t,n)=>t+(n-e)**2),0)/(t.data.length-n)),i=new nt(t.type,[e],[]);return[new nt(t.type,[r],[]),i]}const i=lt(t,e=ot(e,t.dims.length),r),s=t.dims.slice();s[e]=1;const o=new t.data.constructor(t.data.length/t.dims[e]);for(let n=0;n<t.data.length;++n){let r=0;for(let i=t.dims.length-1,o=n,a=1;i>=0;--i){const n=t.dims[i];i!==e&&(r+=o%n*a,a*=s[i]),o=Math.floor(o/n)}o[r]+=(t.data[n]-i.data[r])**2}for(let r=0;r<o.length;++r)o[r]=Math.sqrt(o[r]/(t.dims[e]-n));return r||s.splice(e,1),[new nt(t.type,o,s),i]}(s,-2,0,!0),u=s.clone();for(let t=0;t<u.dims[0];++t){let e=u[t];for(let n=0;n<e.dims[0];++n){let r=e[n];const s=o[t][n][0],u=a[t][n][0];for(let t=0;t<r.dims[0];++t){let e=r[t];for(let t=0;t<e.data.length;++t)e.data[t]=(e.data[t]-u.data[t])/s.data[t];e.data.set(J(e.data,i))}}}return lt(u,1)})),o=[t.sequences.length,t.sequences[0].length],a=new nt("float32",new Float32Array(o[0]*o[1]),o);for(let t=0;t<o[0];++t){const e=s[t].neg().squeeze_(0);let[n,i]=ct(e),o=l([1],Array.from({length:n.length-1},((t,e)=>n[e+1]-n[e]))).map((t=>!!t)),u=[];for(let t=0;t<o.length;++t)o[t]&&u.push(i[t]*r);a[t].data.set(u,1)}return a}}]]]),Us=new Map([["speecht5",["SpeechT5ForTextToSpeech",As]]]),Vs=new Map([["vits",["VitsModel",$s]]]),Gs=new Map([["bert",["BertForSequenceClassification",class extends ni{async _call(t){return new yo(await super._call(t))}}]],["roformer",["RoFormerForSequenceClassification",class extends ii{async _call(t){return new yo(await super._call(t))}}]],["electra",["ElectraForSequenceClassification",class extends oi{async _call(t){return new yo(await super._call(t))}}]],["esm",["EsmForSequenceClassification",class extends di{async _call(t){return new yo(await super._call(t))}}]],["convbert",["ConvBertForSequenceClassification",class extends si{async _call(t){return new yo(await super._call(t))}}]],["camembert",["CamembertForSequenceClassification",class extends ai{async _call(t){return new yo(await super._call(t))}}]],["deberta",["DebertaForSequenceClassification",class extends ui{async _call(t){return new yo(await super._call(t))}}]],["deberta-v2",["DebertaV2ForSequenceClassification",class extends li{async _call(t){return new yo(await super._call(t))}}]],["mpnet",["MPNetForSequenceClassification",class extends pi{async _call(t){return new yo(await super._call(t))}}]],["albert",["AlbertForSequenceClassification",class extends gi{async _call(t){return new yo(await super._call(t))}}]],["distilbert",["DistilBertForSequenceClassification",class extends ci{async _call(t){return new yo(await super._call(t))}}]],["roberta",["RobertaForSequenceClassification",class extends Ti{async _call(t){return new yo(await super._call(t))}}]],["xlm",["XLMForSequenceClassification",class extends Si{async _call(t){return new yo(await super._call(t))}}]],["xlm-roberta",["XLMRobertaForSequenceClassification",class extends Ai{async _call(t){return new yo(await super._call(t))}}]],["bart",["BartForSequenceClassification",class extends yi{async _call(t){return new yo(await super._call(t))}}]],["mbart",["MBartForSequenceClassification",class extends wi{async _call(t){return new yo(await super._call(t))}}]],["mobilebert",["MobileBertForSequenceClassification",class extends hi{async _call(t){return new yo(await super._call(t))}}]],["squeezebert",["SqueezeBertForSequenceClassification",class extends fi{async _call(t){return new yo(await super._call(t))}}]]]),qs=new Map([["bert",["BertForTokenClassification",class extends ni{async _call(t){return new vo(await super._call(t))}}]],["roformer",["RoFormerForTokenClassification",class extends ii{async _call(t){return new vo(await super._call(t))}}]],["electra",["ElectraForTokenClassification",class extends oi{async _call(t){return new vo(await super._call(t))}}]],["esm",["EsmForTokenClassification",class extends di{async _call(t){return new vo(await super._call(t))}}]],["convbert",["ConvBertForTokenClassification",class extends si{async _call(t){return new vo(await super._call(t))}}]],["camembert",["CamembertForTokenClassification",class extends ai{async _call(t){return new vo(await super._call(t))}}]],["deberta",["DebertaForTokenClassification",class extends ui{async _call(t){return new vo(await super._call(t))}}]],["deberta-v2",["DebertaV2ForTokenClassification",class extends li{async _call(t){return new vo(await super._call(t))}}]],["mpnet",["MPNetForTokenClassification",class extends pi{async _call(t){return new vo(await super._call(t))}}]],["distilbert",["DistilBertForTokenClassification",class extends ci{async _call(t){return new vo(await super._call(t))}}]],["roberta",["RobertaForTokenClassification",class extends Ti{async _call(t){return new vo(await super._call(t))}}]],["xlm",["XLMForTokenClassification",class extends Si{async _call(t){return new vo(await super._call(t))}}]],["xlm-roberta",["XLMRobertaForTokenClassification",class extends Ai{async _call(t){return new vo(await super._call(t))}}]]]),Ws=new Map([["t5",["T5ForConditionalGeneration",class extends mi{constructor(t,e,n,r){super(t,e),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.num_decoder_layers,this.num_decoder_heads=this.config.num_heads,this.decoder_dim_kv=this.config.d_kv,this.num_encoder_layers=this.config.num_layers,this.num_encoder_heads=this.config.num_heads,this.encoder_dim_kv=this.config.d_kv}}]],["longt5",["LongT5ForConditionalGeneration",class extends _i{constructor(t,e,n,r){super(t,e),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.num_decoder_layers,this.num_decoder_heads=this.config.num_heads,this.decoder_dim_kv=this.config.d_kv,this.num_encoder_layers=this.config.num_layers,this.num_encoder_heads=this.config.num_heads,this.encoder_dim_kv=this.config.d_kv}}]],["mt5",["MT5ForConditionalGeneration",class extends bi{constructor(t,e,n,r){super(t,e),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.num_decoder_layers,this.num_decoder_heads=this.config.num_heads,this.decoder_dim_kv=this.config.d_kv,this.num_encoder_layers=this.config.num_layers,this.num_encoder_heads=this.config.num_heads,this.encoder_dim_kv=this.config.d_kv}}]],["bart",["BartForConditionalGeneration",class extends yi{constructor(t,e,n,r){super(t,e),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}]],["mbart",["MBartForConditionalGeneration",class extends wi{constructor(t,e,n,r){super(t,e),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}]],["marian",["MarianMTModel",class extends _s{constructor(t,e,n,r){super(t,e),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}]],["m2m_100",["M2M100ForConditionalGeneration",class extends bs{constructor(t,e,n,r){super(t,e),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}]],["blenderbot",["BlenderbotForConditionalGeneration",class extends vi{constructor(t,e,n,r){super(t,e),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}]],["blenderbot-small",["BlenderbotSmallForConditionalGeneration",class extends xi{constructor(t,e,n,r){super(t,e),this.decoder_merged_session=n,this.generation_config=r,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}]]]),Hs=new Map([["bloom",["BloomForCausalLM",class extends Ui{}]],["gpt2",["GPT2LMHeadModel",class extends $i{}]],["gptj",["GPTJForCausalLM",class extends Li{}]],["gpt_bigcode",["GPTBigCodeForCausalLM",class extends Ni{}]],["gpt_neo",["GPTNeoForCausalLM",class extends Mi{}]],["gpt_neox",["GPTNeoXForCausalLM",class extends Fi{}]],["codegen",["CodeGenForCausalLM",class extends Ri{}]],["llama",["LlamaForCausalLM",class extends ji{}]],["qwen2",["Qwen2ForCausalLM",class extends zi{}]],["phi",["PhiForCausalLM",class extends Bi{}]],["mpt",["MptForCausalLM",class extends Vi{}]],["opt",["OPTForCausalLM",class extends Gi{}]],["mbart",["MBartForCausalLM",class extends wi{constructor(t,e,n){super(t,e),this.generation_config=n,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}]],["mistral",["MistralForCausalLM",class extends Es{}]],["starcoder2",["Starcoder2ForCausalLM",class extends Is{}]],["falcon",["FalconForCausalLM",class extends Ps{}]],["trocr",["TrOCRForCausalLM",class extends Os{}]],["stablelm",["StableLmForCausalLM",class extends Fs{}]]]),Xs=new Map([["bert",["BertForMaskedLM",class extends ni{async _call(t){return new xo(await super._call(t))}}]],["roformer",["RoFormerForMaskedLM",class extends ii{async _call(t){return new xo(await super._call(t))}}]],["electra",["ElectraForMaskedLM",class extends oi{async _call(t){return new xo(await super._call(t))}}]],["esm",["EsmForMaskedLM",class extends di{async _call(t){return new xo(await super._call(t))}}]],["convbert",["ConvBertForMaskedLM",class extends si{async _call(t){return new xo(await super._call(t))}}]],["camembert",["CamembertForMaskedLM",class extends ai{async _call(t){return new xo(await super._call(t))}}]],["deberta",["DebertaForMaskedLM",class extends ui{async _call(t){return new xo(await super._call(t))}}]],["deberta-v2",["DebertaV2ForMaskedLM",class extends li{async _call(t){return new xo(await super._call(t))}}]],["mpnet",["MPNetForMaskedLM",class extends pi{async _call(t){return new xo(await super._call(t))}}]],["albert",["AlbertForMaskedLM",class extends gi{async _call(t){return new xo(await super._call(t))}}]],["distilbert",["DistilBertForMaskedLM",class extends ci{async _call(t){return new xo(await super._call(t))}}]],["roberta",["RobertaForMaskedLM",class extends Ti{async _call(t){return new xo(await super._call(t))}}]],["xlm",["XLMWithLMHeadModel",class extends Si{async _call(t){return new xo(await super._call(t))}}]],["xlm-roberta",["XLMRobertaForMaskedLM",class extends Ai{async _call(t){return new xo(await super._call(t))}}]],["mobilebert",["MobileBertForMaskedLM",class extends hi{async _call(t){return new xo(await super._call(t))}}]],["squeezebert",["SqueezeBertForMaskedLM",class extends fi{async _call(t){return new xo(await super._call(t))}}]]]),Ys=new Map([["bert",["BertForQuestionAnswering",class extends ni{async _call(t){return new To(await super._call(t))}}]],["roformer",["RoFormerForQuestionAnswering",class extends ii{async _call(t){return new To(await super._call(t))}}]],["electra",["ElectraForQuestionAnswering",class extends oi{async _call(t){return new To(await super._call(t))}}]],["convbert",["ConvBertForQuestionAnswering",class extends si{async _call(t){return new To(await super._call(t))}}]],["camembert",["CamembertForQuestionAnswering",class extends ai{async _call(t){return new To(await super._call(t))}}]],["deberta",["DebertaForQuestionAnswering",class extends ui{async _call(t){return new To(await super._call(t))}}]],["deberta-v2",["DebertaV2ForQuestionAnswering",class extends li{async _call(t){return new To(await super._call(t))}}]],["mpnet",["MPNetForQuestionAnswering",class extends pi{async _call(t){return new To(await super._call(t))}}]],["albert",["AlbertForQuestionAnswering",class extends gi{async _call(t){return new To(await super._call(t))}}]],["distilbert",["DistilBertForQuestionAnswering",class extends ci{async _call(t){return new To(await super._call(t))}}]],["roberta",["RobertaForQuestionAnswering",class extends Ti{async _call(t){return new To(await super._call(t))}}]],["xlm",["XLMForQuestionAnswering",class extends Si{async _call(t){return new To(await super._call(t))}}]],["xlm-roberta",["XLMRobertaForQuestionAnswering",class extends Ai{async _call(t){return new To(await super._call(t))}}]],["mobilebert",["MobileBertForQuestionAnswering",class extends hi{async _call(t){return new To(await super._call(t))}}]],["squeezebert",["SqueezeBertForQuestionAnswering",class extends fi{async _call(t){return new To(await super._call(t))}}]]]),Ks=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",Ei]]]),Zs=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",Ei]]]),Js=new Map([["vit",["ViTForImageClassification",class extends qi{async _call(t){return new yo(await super._call(t))}}]],["mobilevit",["MobileViTForImageClassification",class extends Hi{async _call(t){return new yo(await super._call(t))}}]],["beit",["BeitForImageClassification",class extends Ki{async _call(t){return new yo(await super._call(t))}}]],["deit",["DeiTForImageClassification",class extends ns{async _call(t){return new yo(await super._call(t))}}]],["convnext",["ConvNextForImageClassification",class extends cs{async _call(t){return new yo(await super._call(t))}}]],["convnextv2",["ConvNextV2ForImageClassification",class extends ds{async _call(t){return new yo(await super._call(t))}}]],["dinov2",["Dinov2ForImageClassification",class extends hs{async _call(t){return new yo(await super._call(t))}}]],["resnet",["ResNetForImageClassification",class extends rs{async _call(t){return new yo(await super._call(t))}}]],["swin",["SwinForImageClassification",class extends is{async _call(t){return new yo(await super._call(t))}}]],["segformer",["SegformerForImageClassification",class extends Ms{}]],["efficientnet",["EfficientNetForImageClassification",class extends Ls{async _call(t){return new yo(await super._call(t))}}]]]),Qs=new Map([["detr",["DetrForObjectDetection",class extends Zi{async _call(t){return new Ji(await super._call(t))}}]],["table-transformer",["TableTransformerForObjectDetection",class extends ts{async _call(t){return new es(await super._call(t))}}]],["yolos",["YolosForObjectDetection",class extends ps{async _call(t){return new fs(await super._call(t))}}]]]),to=new Map([["owlvit",["OwlViTForObjectDetection",class extends Xi{}]],["owlv2",["Owlv2ForObjectDetection",class extends Yi{}]]]),eo=new Map([["detr",["DetrForSegmentation",class extends Zi{async _call(t){return new Qi(await super._call(t))}}]],["clipseg",["CLIPSegForImageSegmentation",class extends Ci{}]]]),no=new Map([["segformer",["SegformerForSemanticSegmentation",class extends Ms{}]]]),ro=new Map([["sam",["SamModel",class extends gs{constructor(t,e,n){super(t,e),this.prompt_encoder_mask_decoder=n}async get_image_embeddings({pixel_values:t}){return await Yr(this,{pixel_values:t})}async forward(t){if(t.image_embeddings&&t.image_positional_embeddings||(t={...t,...await this.get_image_embeddings(t)}),!t.input_labels){const e=t.input_points.dims.slice(0,-1),n=e.reduce(((t,e)=>t*e),1);t.input_labels=new nt("int64",new BigInt64Array(n).fill(1n),e)}return await jr(this.prompt_encoder_mask_decoder,{input_points:t.input_points,input_labels:t.input_labels,image_embeddings:t.image_embeddings,image_positional_embeddings:t.image_positional_embeddings})}async _call(t){return new ms(await super._call(t))}}]]]),io=new Map([["wav2vec2",["Wav2Vec2ForCTC",class extends ys{async _call(t){return new So(await super._call(t))}}]],["wav2vec2-bert",["Wav2Vec2BertForCTC",class extends xs{async _call(t){return new So(await super._call(t))}}]],["unispeech",["UniSpeechForCTC",class extends ws{async _call(t){return new So(await super._call(t))}}]],["unispeech-sat",["UniSpeechSatForCTC",class extends vs{async _call(t){return new So(await super._call(t))}}]],["wavlm",["WavLMForCTC",class extends Ts{async _call(t){return new So(await super._call(t))}}]],["hubert",["HubertForCTC",class extends ys{async _call(t){return new So(await super._call(t))}}]]]),so=new Map([["wav2vec2",["Wav2Vec2ForSequenceClassification",class extends ys{async _call(t){return new yo(await super._call(t))}}]],["wav2vec2-bert",["Wav2Vec2BertForSequenceClassification",class extends xs{async _call(t){return new yo(await super._call(t))}}]],["unispeech",["UniSpeechForSequenceClassification",class extends ws{async _call(t){return new yo(await super._call(t))}}]],["unispeech-sat",["UniSpeechSatForSequenceClassification",class extends vs{async _call(t){return new yo(await super._call(t))}}]],["wavlm",["WavLMForSequenceClassification",class extends Ts{async _call(t){return new yo(await super._call(t))}}]],["hubert",["HubertForSequenceClassification",class extends ys{async _call(t){return new yo(await super._call(t))}}]],["audio-spectrogram-transformer",["ASTForAudioClassification",class extends ki{}]]]),oo=new Map([["wavlm",["WavLMForXVector",class extends Ts{async _call(t){return new wo(await super._call(t))}}]]]),ao=new Map([["unispeech-sat",["UniSpeechSatForAudioFrameClassification",class extends vs{async _call(t){return new vo(await super._call(t))}}]],["wavlm",["WavLMForAudioFrameClassification",class extends Ts{async _call(t){return new vo(await super._call(t))}}]],["wav2vec2",["Wav2Vec2ForAudioFrameClassification",class extends ys{async _call(t){return new vo(await super._call(t))}}]]]),uo=new Map([["vitmatte",["VitMatteForImageMatting",class extends Wi{async _call(t){return new Ao(await super._call(t))}}]]]),lo=new Map([["swin2sr",["Swin2SRForImageSuperResolution",class extends ss{}]]]),co=new Map([["dpt",["DPTForDepthEstimation",class extends os{}]],["depth_anything",["DepthAnythingForDepthEstimation",class extends as{}]],["glpn",["GLPNForDepthEstimation",class extends us{}]]]),ho=new Map([["clip",["CLIPVisionModelWithProjection",class extends Ii{static async from_pretrained(t,e={}){return e.model_file_name??="vision_model",super.from_pretrained(t,e)}}]],["siglip",["SiglipVisionModel",class extends Ii{static async from_pretrained(t,e={}){return e.model_file_name??="vision_model",super.from_pretrained(t,e)}}]]]),po=[[Rs,0],[js,1],[zs,4],[Gs,0],[qs,0],[Ws,2],[Bs,2],[Hs,4],[Xs,0],[Ys,0],[Ks,3],[Js,0],[eo,0],[no,0],[uo,0],[lo,0],[co,0],[Qs,0],[to,0],[ro,5],[io,0],[so,0],[Us,2],[Vs,0],[oo,0],[ao,0],[ho,0]];for(const[t,e]of po)for(const[n,r]of t.values())Fr.set(n,e),Nr.set(r,n),Lr.set(n,r);const fo=[["CLIPTextModelWithProjection",class extends Ii{static async from_pretrained(t,e={}){return e.model_file_name??="text_model",super.from_pretrained(t,e)}},0],["SiglipTextModel",class extends Pi{static async from_pretrained(t,e={}){return e.model_file_name??="text_model",super.from_pretrained(t,e)}},0],["ClapTextModelWithProjection",class extends Ds{static async from_pretrained(t,e={}){return e.model_file_name??="text_model",super.from_pretrained(t,e)}},0],["ClapAudioModelWithProjection",class extends Ds{static async from_pretrained(t,e={}){return e.model_file_name??="audio_model",super.from_pretrained(t,e)}},0]];for(const[t,e,n]of fo)Fr.set(t,n),Nr.set(e,t),Lr.set(t,e);class go extends Ns{static MODEL_CLASS_MAPPINGS=po.map((t=>t[0]));static BASE_IF_FAIL=!0}class mo extends Ns{static MODEL_CLASS_MAPPINGS=[Gs]}class _o extends Ns{static MODEL_CLASS_MAPPINGS=[Ws]}class bo extends ei{constructor({logits:t,past_key_values:e,encoder_outputs:n,decoder_attentions:r=null,cross_attentions:i=null}){super(),this.logits=t,this.past_key_values=e,this.encoder_outputs=n,this.decoder_attentions=r,this.cross_attentions=i}}class yo extends ei{constructor({logits:t}){super(),this.logits=t}}class wo extends ei{constructor({logits:t,embeddings:e}){super(),this.logits=t,this.embeddings=e}}class vo extends ei{constructor({logits:t}){super(),this.logits=t}}class xo extends ei{constructor({logits:t}){super(),this.logits=t}}class To extends ei{constructor({start_logits:t,end_logits:e}){super(),this.start_logits=t,this.end_logits=e}}class So extends ei{constructor({logits:t}){super(),this.logits=t}}class Ao extends ei{constructor({alphas:t}){super(),this.alphas=t}}class ko extends ei{constructor({waveform:t,spectrogram:e}){super(),this.waveform=t,this.spectrogram=e}}var Oo=n(806);const Eo="undefined"!=typeof self,Io=Eo&&"DedicatedWorkerGlobalScope"===self.constructor.name;let Po,Do,Co;if(Eo)Po=(t,e)=>{if(!self.OffscreenCanvas)throw new Error("OffscreenCanvas not supported by this browser.");return new self.OffscreenCanvas(t,e)},Co=self.createImageBitmap,Do=self.ImageData;else{if(!Oo)throw new Error("Unable to load image processing library.");Co=async t=>{const e=(await t.metadata()).channels;let{data:n,info:r}=await t.raw().toBuffer({resolveWithObject:!0});const i=new Fo(new Uint8ClampedArray(n),r.width,r.height,r.channels);return void 0!==e&&e!==r.channels&&i.convert(e),i}}const $o={0:"nearest",1:"lanczos",2:"bilinear",3:"bicubic",4:"box",5:"hamming"},Mo=new Map([["png","image/png"],["jpg","image/jpeg"],["jpeg","image/jpeg"],["gif","image/gif"]]);class Fo{constructor(t,e,n,r){this.data=t,this.width=e,this.height=n,this.channels=r}get size(){return[this.width,this.height]}static async read(t){if(t instanceof Fo)return t;if("string"==typeof t||t instanceof URL)return await this.fromURL(t);throw new Error("Unsupported input type: "+typeof t)}static async fromURL(t){let e=await R(t);if(200!==e.status)throw new Error(`Unable to read image from "${t}" (${e.status} ${e.statusText})`);let n=await e.blob();return this.fromBlob(n)}static async fromBlob(t){if(Eo){let e=await Co(t);const n=Po(e.width,e.height).getContext("2d");return n.drawImage(e,0,0),new this(n.getImageData(0,0,e.width,e.height).data,e.width,e.height,4)}{let e=Oo(await t.arrayBuffer());return await Co(e)}}static fromTensor(t,e="CHW"){if(3!==t.dims.length)throw new Error(`Tensor should have 3 dimensions, but has ${t.dims.length} dimensions.`);if("CHW"===e)t=t.transpose(1,2,0);else if("HWC"!==e)throw new Error(`Unsupported channel format: ${e}`);if(!(t.data instanceof Uint8ClampedArray||t.data instanceof Uint8Array))throw new Error(`Unsupported tensor type: ${t.type}`);switch(t.dims[2]){case 1:case 2:case 3:case 4:return new Fo(t.data,t.dims[1],t.dims[0],t.dims[2]);default:throw new Error(`Unsupported number of channels: ${t.dims[2]}`)}}grayscale(){if(1===this.channels)return this;let t=new Uint8ClampedArray(this.width*this.height*1);switch(this.channels){case 3:case 4:for(let e=0,n=0;e<this.data.length;e+=this.channels){const r=this.data[e],i=this.data[e+1],s=this.data[e+2];t[n++]=Math.round(.2989*r+.587*i+.114*s)}break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(t,this.width,this.height,1)}rgb(){if(3===this.channels)return this;let t=new Uint8ClampedArray(this.width*this.height*3);switch(this.channels){case 1:for(let e=0,n=0;e<this.data.length;++e)t[n++]=this.data[e],t[n++]=this.data[e],t[n++]=this.data[e];break;case 4:for(let e=0,n=0;e<this.data.length;e+=4)t[n++]=this.data[e],t[n++]=this.data[e+1],t[n++]=this.data[e+2];break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(t,this.width,this.height,3)}rgba(){if(4===this.channels)return this;let t=new Uint8ClampedArray(this.width*this.height*4);switch(this.channels){case 1:for(let e=0,n=0;e<this.data.length;++e)t[n++]=this.data[e],t[n++]=this.data[e],t[n++]=this.data[e],t[n++]=255;break;case 3:for(let e=0,n=0;e<this.data.length;e+=3)t[n++]=this.data[e],t[n++]=this.data[e+1],t[n++]=this.data[e+2],t[n++]=255;break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(t,this.width,this.height,4)}async resize(t,e,{resample:n=2}={}){let r=$o[n]??n;if(Eo){let n=this.channels,r=this.toCanvas();const i=Po(t,e).getContext("2d");return i.drawImage(r,0,0,t,e),new Fo(i.getImageData(0,0,t,e).data,t,e,4).convert(n)}{let n=this.toSharp();switch(r){case"box":case"hamming":"box"!==r&&"hamming"!==r||(console.warn(`Resampling method ${r} is not yet supported. Using bilinear instead.`),r="bilinear");case"nearest":case"bilinear":case"bicubic":n=n.affine([t/this.width,0,0,e/this.height],{interpolator:r});break;case"lanczos":n=n.resize({width:t,height:e,fit:"fill",kernel:"lanczos3"});break;default:throw new Error(`Resampling method ${r} is not supported.`)}return await Co(n)}}async pad([t,e,n,r]){if(t=Math.max(t,0),e=Math.max(e,0),n=Math.max(n,0),r=Math.max(r,0),0===t&&0===e&&0===n&&0===r)return this;if(Eo){let i=this.channels,s=this.toCanvas(),o=this.width+t+e,a=this.height+n+r;const u=Po(o,a).getContext("2d");return u.drawImage(s,0,0,this.width,this.height,t,n,o,a),new Fo(u.getImageData(0,0,o,a).data,o,a,4).convert(i)}{let i=this.toSharp().extend({left:t,right:e,top:n,bottom:r});return await Co(i)}}async crop([t,e,n,r]){if(t=Math.max(t,0),e=Math.max(e,0),n=Math.min(n,this.width-1),r=Math.min(r,this.height-1),0===t&&0===e&&n===this.width-1&&r===this.height-1)return this;const i=n-t+1,s=r-e+1;if(Eo){const n=this.channels,r=this.toCanvas(),o=Po(i,s).getContext("2d");return o.drawImage(r,t,e,i,s,0,0,i,s),new Fo(o.getImageData(0,0,i,s).data,i,s,4).convert(n)}{const n=this.toSharp().extract({left:t,top:e,width:i,height:s});return await Co(n)}}async center_crop(t,e){if(this.width===t&&this.height===e)return this;let n=(this.width-t)/2,r=(this.height-e)/2;if(Eo){let i=this.channels,s=this.toCanvas();const o=Po(t,e).getContext("2d");let a=0,u=0,l=0,c=0;return n>=0?a=n:l=-n,r>=0?u=r:c=-r,o.drawImage(s,a,u,t,e,l,c,t,e),new Fo(o.getImageData(0,0,t,e).data,t,e,4).convert(i)}{let i=this.toSharp();if(n>=0&&r>=0)i=i.extract({left:Math.floor(n),top:Math.floor(r),width:t,height:e});else if(n<=0&&r<=0){let s=Math.floor(-r),o=Math.floor(-n);i=i.extend({top:s,left:o,right:t-this.width-o,bottom:e-this.height-s})}else{let s=[0,0],o=0;r<0?(s[0]=Math.floor(-r),s[1]=e-this.height-s[0]):o=Math.floor(r);let a=[0,0],u=0;n<0?(a[0]=Math.floor(-n),a[1]=t-this.width-a[0]):u=Math.floor(n),i=i.extend({top:s[0],bottom:s[1],left:a[0],right:a[1]}).extract({left:u,top:o,width:t,height:e})}return await Co(i)}}async toBlob(t="image/png",e=1){if(!Eo)throw new Error("toBlob() is only supported in browser environments.");const n=this.toCanvas();return await n.convertToBlob({type:t,quality:e})}toTensor(t="CHW"){let e=new nt("uint8",new Uint8Array(this.data),[this.height,this.width,this.channels]);if("HWC"===t);else{if("CHW"!==t)throw new Error(`Unsupported channel format: ${t}`);e=e.permute(2,0,1)}return e}toCanvas(){if(!Eo)throw new Error("toCanvas() is only supported in browser environments.");let t=this.clone().rgba(),e=Po(t.width,t.height),n=new Do(t.data,t.width,t.height);return e.getContext("2d").putImageData(n,0,0),e}_update(t,e,n,r=null){return this.data=t,this.width=e,this.height=n,null!==r&&(this.channels=r),this}clone(){return new Fo(this.data.slice(),this.width,this.height,this.channels)}convert(t){if(this.channels===t)return this;switch(t){case 1:this.grayscale();break;case 3:this.rgb();break;case 4:this.rgba();break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this}async save(t){if(!Eo){if(M.useFS){const e=this.toSharp();return await e.toFile(t)}throw new Error("Unable to save the image because filesystem is disabled in this environment.")}{if(Io)throw new Error("Unable to save an image from a Web Worker.");const e=t.split(".").pop().toLowerCase(),n=Mo.get(e)??"image/png",r=await this.toBlob(n),i=URL.createObjectURL(r),s=document.createElement("a");s.href=i,s.download=t,s.click(),s.remove()}}toSharp(){if(Eo)throw new Error("toSharp() is only supported in server-side environments.");return Oo(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}})}}function Lo(t){if(t<1)return new Float64Array;if(1===t)return new Float64Array([1]);const e=t-1,n=Math.PI/e,r=new Float64Array(t);for(let i=0;i<t;++i){const t=2*i-e;r[i]=.5+.5*Math.cos(n*t)}return r}const No={htk:t=>2595*Math.log10(1+t/700),kaldi:t=>1127*Math.log(1+t/700),slaney:(t,e=1e3,n=15,r=27/Math.log(6.4))=>t>=e?n+Math.log(t/e)*r:3*t/200};function Ro(t,e="htk"){const n=No[e];if(!n)throw new Error('mel_scale should be one of "htk", "slaney" or "kaldi".');return"number"==typeof t?n(t):t.map((t=>n(t)))}const jo={htk:t=>700*(10**(t/2595)-1),kaldi:t=>700*(Math.exp(t/1127)-1),slaney:(t,e=1e3,n=15,r=Math.log(6.4)/27)=>t>=n?e*Math.exp(r*(t-n)):200*t/3};function zo(t,e,n){const r=(e-t)/(n-1);return Float64Array.from({length:n},((e,n)=>t+r*n))}function Bo(t,e,n,r,i,s=null,o="htk",a=!1){if(null!==s&&"slaney"!==s)throw new Error('norm must be one of null or "slaney"');const u=zo(Ro(n,o),Ro(r,o),e+2);let l,c=function(t,e="htk"){const n=jo[e];if(!n)throw new Error('mel_scale should be one of "htk", "slaney" or "kaldi".');return"number"==typeof t?n(t):t.map((t=>n(t)))}(u,o);if(a){const e=i/(2*t);l=Ro(Float64Array.from({length:t},((t,n)=>n*e)),o),c=u}else l=zo(0,Math.floor(i/2),t);const d=function(t,e){const n=Float64Array.from({length:e.length-1},((t,n)=>e[n+1]-e[n])),r=Array.from({length:t.length},(()=>new Array(e.length)));for(let n=0;n<t.length;++n){const i=r[n];for(let r=0;r<e.length;++r)i[r]=e[r]-t[n]}const i=e.length-2,s=Array.from({length:i},(()=>new Array(t.length)));for(let e=0;e<t.length;++e){const t=r[e];for(let r=0;r<i;++r){const i=-t[r]/n[r],o=t[r+2]/n[r+1];s[r][e]=Math.max(0,Math.min(i,o))}}return s}(l,c);if(null!==s&&"slaney"===s)for(let n=0;n<e;++n){const e=d[n],r=2/(c[n+2]-c[n]);for(let n=0;n<t;++n)e[n]*=r}return d}function Uo(t,e,n,r,i){if(n<=0)throw new Error("reference must be greater than zero");if(r<=0)throw new Error("min_value must be greater than zero");n=Math.max(r,n);const s=Math.log10(n);for(let n=0;n<t.length;++n)t[n]=e*Math.log10(Math.max(r,t[n])-s);if(null!==i){if(i<=0)throw new Error("db_range must be greater than zero");const e=H(t)[0]-i;for(let n=0;n<t.length;++n)t[n]=Math.max(t[n],e)}return t}function Vo(t,e,n,r,{fft_length:i=null,power:s=1,center:o=!0,pad_mode:a="reflect",onesided:u=!0,preemphasis:l=null,mel_filters:c=null,mel_floor:h=1e-10,log_mel:p=null,reference:f=1,min_value:g=1e-10,db_range:m=null,remove_dc_offset:_=null,max_num_frames:b=null,do_pad:y=!0,transpose:w=!1}={}){const v=e.length;if(null===i&&(i=n),n>i)throw Error(`frame_length (${n}) may not be larger than fft_length (${i})`);if(v!==n)throw new Error(`Length of the window (${v}) must equal frame_length (${n})`);if(r<=0)throw new Error("hop_length must be greater than zero");if(o){if("reflect"!==a)throw new Error(`pad_mode="${a}" not implemented yet.`);const e=Math.floor((i-1)/2)+1;t=function(t,e,n){const r=new t.constructor(t.length+e+n),i=t.length-1;for(let n=0;n<t.length;++n)r[e+n]=t[n];for(let n=1;n<=e;++n)r[e-n]=t[d(n,i)];for(let s=1;s<=n;++s)r[i+e+s]=t[d(i-s,i)];return r}(t,e,e)}const x=Math.floor(1+Math.floor((t.length-n)/r)),T=u?Math.floor(i/2)+1:i;let S=x,A=x;null!==b&&(b>x?y&&(A=b):A=S=b);const k=new Z(i),O=new Float64Array(i),E=new Float64Array(k.outputBufferSize),I=new Array(S);for(let i=0;i<S;++i){const s=i*r;for(let e=0;e<n;++e)O[e]=t[s+e];if(_){let t=0;for(let e=0;e<n;++e)t+=O[e];const e=t/n;for(let t=0;t<n;++t)O[t]-=e}if(null!==l){for(let t=n-1;t>=1;--t)O[t]-=l*O[t-1];O[0]*=1-l}for(let t=0;t<e.length;++t)O[t]*=e[t];k.realTransform(E,O);const o=new Array(T);for(let t=0;t<o.length;++t){const e=t<<1;o[t]=E[e]**2+E[e+1]**2}I[i]=o}if(null!==s&&2!==s){const t=2/s;for(let e=0;e<I.length;++e){const n=I[e];for(let e=0;e<n.length;++e)n[e]**=t}}const P=c.length,D=new Float32Array(P*A),C=w?[A,P]:[P,A];for(let t=0;t<P;++t){const e=c[t];for(let n=0;n<S;++n){const r=I[n];let i=0;for(let t=0;t<T;++t)i+=e[t]*r[t];D[w?n*P+t:t*S+n]=Math.max(h,i)}}if(null!==s&&null!==p){const t=Math.min(D.length,S*P);switch(p){case"log":for(let e=0;e<t;++e)D[e]=Math.log(D[e]);break;case"log10":for(let e=0;e<t;++e)D[e]=Math.log10(D[e]);break;case"dB":if(1===s)!function(t,e=1,n=1e-5,r=null){Uo(t,20,e,n,r)}(D,f,g,m);else{if(2!==s)throw new Error(`Cannot use log_mel option '${p}' with power ${s}`);!function(t,e=1,n=1e-10,r=null){Uo(t,10,e,n,r)}(D,f,g,m)}break;default:throw new Error(`log_mel must be one of null, 'log', 'log10' or 'dB'. Got '${p}'`)}}return{data:D,dims:C}}function Go(t,e,{periodic:n=!0,frame_length:r=null,center:i=!0}={}){const s=n?t+1:t;let o;switch(e){case"boxcar":o=new Float64Array(s).fill(1);break;case"hann":case"hann_window":o=Lo(s);break;case"povey":o=Lo(s).map((t=>Math.pow(t,.85)));break;default:throw new Error(`Unknown window type ${e}.`)}if(n&&(o=o.subarray(0,t)),null===r)return o;if(t>r)throw new Error(`Length of the window (${t}) may not be larger than frame_length (${r})`);return o}function qo([t,e,n,r]){return[t-n/2,e-r/2,t+n/2,e+r/2]}function Wo(t,e=.5,n=null,r=!1){const i=t.logits,s=t.pred_boxes,[o,a,u]=i.dims;if(null!==n&&n.length!==o)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let l=[];for(let t=0;t<o;++t){let o=null!==n?n[t]:null,c={boxes:[],classes:[],scores:[]},d=i[t],h=s[t];for(let t=0;t<a;++t){let n,i=d[t],s=[];if(r){n=i.sigmoid().data;for(let t=0;t<n.length;++t)n[t]>e&&s.push(t)}else{let t=H(i.data)[1];if(t===u-1)continue;s.push(t),n=G(i.data)}for(const e of s){let r=h[t].data;r=qo(r),null!==o&&(r=r.map(((t,e)=>t*o[(e+1)%2]))),c.boxes.push(r),c.classes.push(e),c.scores.push(n[e])}}l.push(c)}return l}function Ho(t,e){if(!(t instanceof Float32Array||t instanceof Float64Array))throw new Error(`${e} expects input to be a Float32Array or a Float64Array, but got ${t?.constructor?.name??typeof t} instead. If using the feature extractor directly, remember to use \`read_audio(url, sampling_rate)\` to obtain the raw audio data of the file/url.`)}function Xo(t,e,n=0,r=null){const i=t/e;let s=function(t){const e=Math.round(t);return Math.abs(t)%1==.5?e%2==0?e:e-1:e}(i)*e;return null!==r&&s>r&&(s=Math.floor(i)*e),s<n&&(s=Math.ceil(i)*e),s}function Yo([t,e],n){return[Math.max(Math.floor(t/n),1)*n,Math.max(Math.floor(e/n),1)*n]}class Ko extends s{constructor(t){super(),this.config=t}}class Zo extends Ko{constructor(t){super(t),this.image_mean=this.config.image_mean??this.config.mean,this.image_std=this.config.image_std??this.config.std,this.resample=this.config.resample??2,this.do_rescale=this.config.do_rescale??!0,this.rescale_factor=this.config.rescale_factor??1/255,this.do_normalize=this.config.do_normalize,this.do_resize=this.config.do_resize,this.do_thumbnail=this.config.do_thumbnail,this.size=this.config.size,this.size_divisibility=this.config.size_divisibility??this.config.size_divisor,this.do_center_crop=this.config.do_center_crop,this.crop_size=this.config.crop_size,this.do_convert_rgb=this.config.do_convert_rgb??!0,this.do_crop_margin=this.config.do_crop_margin,this.pad_size=this.config.pad_size,this.do_pad=this.config.do_pad,this.do_pad&&!this.pad_size&&this.size&&void 0!==this.size.width&&void 0!==this.size.height&&(this.pad_size=this.size)}async thumbnail(t,e,n=2){const r=t.height,i=t.width,s=e.height,o=e.width;let a=Math.min(r,s),u=Math.min(i,o);return a===r&&u===i?t:(r>i?u=Math.floor(i*a/r):i>r&&(a=Math.floor(r*u/i)),await t.resize(u,a,{resample:n}))}async crop_margin(t,e=200){const n=t.clone().grayscale(),r=W(n.data)[0],i=H(n.data)[0]-r;if(0===i)return t;const s=e/255;let o=n.width,a=n.height,u=0,l=0;for(let t=0;t<n.height;++t){const e=t*n.width;for(let c=0;c<n.width;++c)(n.data[e+c]-r)/i<s&&(o=Math.min(o,c),a=Math.min(a,t),u=Math.max(u,c),l=Math.max(l,t))}return await t.crop([o,a,u,l])}pad_image(t,e,n,{mode:r="constant",center:i=!1,constant_values:s=0}={}){const[o,a,u]=e;let l,c;if("number"==typeof n?(l=n,c=n):(l=n.width,c=n.height),l!==a||c!==o){const n=new Float32Array(l*c*u);if(Array.isArray(s))for(let t=0;t<n.length;++t)n[t]=s[t%u];else 0!==s&&n.fill(s);const[h,p]=i?[Math.floor((l-a)/2),Math.floor((c-o)/2)]:[0,0];for(let e=0;e<o;++e){const r=(e+p)*l,i=e*a;for(let e=0;e<a;++e){const s=(r+e+h)*u,o=(i+e)*u;for(let e=0;e<u;++e)n[s+e]=t[o+e]}}if("symmetric"===r){if(i)throw new Error("`center` padding is not supported when `mode` is set to `symmetric`.");const e=o-1,r=a-1;for(let i=0;i<c;++i){const s=i*l,c=d(i,e)*a;for(let e=0;e<l;++e){if(i<o&&e<a)continue;const l=(s+e)*u,h=(c+d(e,r))*u;for(let e=0;e<u;++e)n[l+e]=t[h+e]}}}t=n,e=[c,l,u]}return[t,e]}rescale(t){for(let e=0;e<t.length;++e)t[e]=this.rescale_factor*t[e]}get_resize_output_image_size(t,e){const[n,r]=t.size;let i,s;if(this.do_thumbnail){const{height:t,width:n}=e;i=Math.min(t,n)}else Number.isInteger(e)?(i=e,s=this.config.max_size??i):void 0!==e&&(i=e.shortest_edge,s=e.longest_edge);if(void 0!==i||void 0!==s){const t=void 0===i?1:Math.max(i/n,i/r),e=n*t,o=r*t,a=void 0===s?1:Math.min(s/e,s/o);let u=Math.floor(Number((e*a).toFixed(2))),l=Math.floor(Number((o*a).toFixed(2)));return void 0!==this.size_divisibility&&([u,l]=Yo([u,l],this.size_divisibility)),[u,l]}if(void 0!==e&&void 0!==e.width&&void 0!==e.height){let t=e.width,i=e.height;if(this.config.keep_aspect_ratio&&this.config.ensure_multiple_of){let e=i/r,s=t/n;Math.abs(1-s)<Math.abs(1-e)?e=s:s=e,i=Xo(e*r,this.config.ensure_multiple_of),t=Xo(s*n,this.config.ensure_multiple_of)}return[t,i]}if(void 0!==this.size_divisibility)return Yo([n,r],this.size_divisibility);throw new Error(`Could not resize image due to unsupported \`this.size\` option in config: ${JSON.stringify(e)}`)}async resize(t){const[e,n]=this.get_resize_output_image_size(t,this.size);return await t.resize(e,n,{resample:this.resample})}async preprocess(t,{do_normalize:e=null,do_pad:n=null,do_convert_rgb:r=null,do_convert_grayscale:i=null}={}){this.do_crop_margin&&(t=await this.crop_margin(t));const[s,o]=t.size;if(r??this.do_convert_rgb?t=t.rgb():i&&(t=t.grayscale()),this.do_resize&&(t=await this.resize(t)),this.do_thumbnail&&(t=await this.thumbnail(t,this.size,this.resample)),this.do_center_crop){let e,n;Number.isInteger(this.crop_size)?(e=this.crop_size,n=this.crop_size):(e=this.crop_size.width,n=this.crop_size.height),t=await t.center_crop(e,n)}const a=[t.height,t.width];let u=Float32Array.from(t.data),l=[t.height,t.width,t.channels];if(this.do_rescale&&this.rescale(u),e??this.do_normalize){let e=this.image_mean;Array.isArray(this.image_mean)||(e=new Array(t.channels).fill(e));let n=this.image_std;if(Array.isArray(this.image_std)||(n=new Array(t.channels).fill(e)),e.length!==t.channels||n.length!==t.channels)throw new Error(`When set to arrays, the length of \`image_mean\` (${e.length}) and \`image_std\` (${n.length}) must match the number of channels in the image (${t.channels}).`);for(let r=0;r<u.length;r+=t.channels)for(let i=0;i<t.channels;++i)u[r+i]=(u[r+i]-e[i])/n[i]}if(n??this.do_pad)if(this.pad_size){const e=this.pad_image(u,[t.height,t.width,t.channels],this.pad_size);[u,l]=e}else if(this.size_divisibility){const[t,e]=Yo([l[1],l[0]],this.size_divisibility);[u,l]=this.pad_image(u,l,{width:t,height:e})}return{original_size:[o,s],reshaped_input_size:a,pixel_values:new nt("float32",u,l).permute(2,0,1)}}async _call(t,...e){Array.isArray(t)||(t=[t]);const n=await Promise.all(t.map((t=>this.preprocess(t))));return{pixel_values:ut(n.map((t=>t.pixel_values)),0),original_sizes:n.map((t=>t.original_size)),reshaped_input_sizes:n.map((t=>t.reshaped_input_size))}}}class Jo extends Zo{post_process_semantic_segmentation(t,e=null){const n=t.logits,r=n.dims[0];if(null!==e&&e.length!==r)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");const i=[];for(let t=0;t<r;++t){const r=null!==e?e[t]:null;let s=n[t];null!==r&&(s=rt(s,r,"bilinear",!1));const[o,a]=r??s.dims.slice(-2),u=new nt("int32",new Int32Array(o*a),[o,a]),l=s[0].data;for(let t=1;t<s.dims[0];++t){const e=s[t].data;for(let n=0;n<e.length;++n)e[n]>l[n]&&(l[n]=e[n],u.data[n]=t)}const c=new Array(s.dims[0]),d=u.data;for(let t=0;t<d.length;++t){const e=d[t];c[e]=e}const h=c.filter((t=>void 0!==t));i.push({segmentation:u,labels:h})}return i}}class Qo extends Zo{}class ta extends Qo{}class ea extends Zo{}class na extends Zo{}class ra extends Zo{}class ia extends Zo{}class sa extends Zo{}class oa extends Zo{constructor(t){super(t),this.crop_pct=this.config.crop_pct??.875}async resize(t){const e=this.size?.shortest_edge;if(void 0===e)throw new Error("Size dictionary must contain 'shortest_edge' key.");if(e<384){const n=Math.floor(e/this.crop_pct),[r,i]=this.get_resize_output_image_size(t,{shortest_edge:n});t=await t.resize(r,i,{resample:this.resample}),t=await t.center_crop(e,e)}else t=await t.resize(e,e,{resample:this.resample});return t}}class aa extends oa{}class ua extends Zo{}class la extends Zo{}class ca extends Zo{constructor(t){super(t),this.include_top=this.config.include_top??!0,this.include_top&&(this.image_std=this.image_std.map((t=>t*t)))}}class da extends Zo{}class ha extends Zo{post_process_object_detection(...t){return Wo(...t)}}class pa extends ha{}class fa extends Zo{}class ga extends Zo{}class ma extends Zo{pad_image(t,e,n,r={}){const[i,s,o]=e;let a=this.image_mean;Array.isArray(this.image_mean)||(a=new Array(o).fill(a));let u=this.image_std;Array.isArray(u)||(u=new Array(o).fill(a));const l=a.map(((t,e)=>-t/u[e]));return super.pad_image(t,e,n,{center:!0,constant_values:l,...r})}}class _a extends ma{}class ba extends Zo{async _call(t){const e=await super._call(t),n=[e.pixel_values.dims[0],64,64],r=new nt("int64",new BigInt64Array(n.reduce(((t,e)=>t*e))).fill(1n),n);return{...e,pixel_mask:r}}post_process_object_detection(...t){return Wo(...t)}remove_low_and_no_objects(t,e,n,r){let i=[],s=[],o=[];for(let a=0;a<t.dims[0];++a){let u=t[a],l=e[a],c=H(u.data)[1];if(c===r)continue;let d=G(u.data)[c];d>n&&(i.push(l),s.push(d),o.push(c))}return[i,s,o]}check_segment_validity(t,e,n,r=.5,i=.8){let s=[],o=0,a=0;for(let i=0;i<t.length;++i)t[i]===n&&(s.push(i),++o),e[n].data[i]>=r&&++a;let u=o>0&&a>0;return u&&(u=o/a>i),[u,s]}compute_segments(t,e,n,r,i,s=null,o=null){let[a,u]=o??t[0].dims,l=new nt("int32",new Int32Array(a*u),[a,u]),c=[];if(null!==o)for(let e=0;e<t.length;++e)t[e]=rt(t[e],o,"bilinear",!1);let d=new Int32Array(t[0].data.length),h=new Float32Array(t[0].data.length);for(let n=0;n<t.length;++n){let r=e[n];for(let e=0;e<t[n].data.length;++e)t[n].data[e]*=r,t[n].data[e]>h[e]&&(d[e]=n,h[e]=t[n].data[e])}let p=0;for(let s=0;s<n.length;++s){let o=n[s],[a,u]=this.check_segment_validity(d,t,s,r,i);if(a){++p;for(let t of u)l.data[t]=p;c.push({id:p,label_id:o,score:e[s]})}}return[l,c]}post_process_panoptic_segmentation(t,e=.5,n=.5,r=.8,i=null,s=null){null===i&&(console.warn("`label_ids_to_fuse` unset. No instance will be fused."),i=new Set);const o=t.logits,a=t.pred_masks.sigmoid();let[u,l,c]=o.dims;if(c-=1,null!==s&&s.length!==u)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let d=[];for(let t=0;t<u;++t){let u=null!==s?s[t]:null,l=o[t],h=a[t],[p,f,g]=this.remove_low_and_no_objects(l,h,e,c);if(0===g.length){let[t,e]=u??h.dims.slice(-2),n=new nt("int32",new Int32Array(t*e).fill(-1),[t,e]);d.push({segmentation:n,segments_info:[]});continue}let[m,_]=this.compute_segments(p,f,g,n,r,i,u);d.push({segmentation:m,segments_info:_})}return d}post_process_instance_segmentation(){throw Error("Not implemented yet")}}class ya extends Zo{post_process_object_detection(...t){return Wo(...t)}}class wa extends Zo{reshape_input_points(t,e,n){let r=a(t=structuredClone(t));if(3===r.length)r=[1,...r],t=[t];else if(4!==r.length)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");for(let r=0;r<t.length;++r){let i=e[r],s=n[r],o=[s[0]/i[0],s[1]/i[1]];for(let e=0;e<t[r].length;++e)for(let n=0;n<t[r][e].length;++n)for(let i=0;i<t[r][e][n].length;++i)t[r][e][n][i]*=o[i]}return new nt("float32",Float32Array.from(t.flat(1/0)),r)}add_input_labels(t,e){let n=a(t);if(2===n.length)n=[1,...n],t=[t];else if(3!==n.length)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");if(n.some(((t,n)=>t!==e.dims[n])))throw Error(`The first ${n.length} dimensions of 'input_points' and 'input_labels' must be the same.`);return new nt("int64",t.flat(1/0).map(BigInt),n)}async _call(t,e=null,n=null){const r=await super._call(t);if(e&&(r.input_points=this.reshape_input_points(e,r.original_sizes,r.reshaped_input_sizes)),n){if(!r.input_points)throw Error("`input_points` must be provided if `input_labels` are provided.");r.input_labels=this.add_input_labels(n,r.input_points)}return r}post_process_masks(t,e,n,{mask_threshold:r=0,binarize:i=!0,pad_size:s=null}={}){const o=[],a=[(s=s??this.pad_size).height,s.width];for(let s=0;s<e.length;++s){const u=e[s],l=n[s],c=t[s],d=[];for(let t=0;t<c.dims[0];++t){let e=rt(c[t],a,"bilinear",!1);if(e=e.slice(null,[0,l[0]],[0,l[1]]),e=rt(e,u,"bilinear",!1),i){const t=new Uint8Array(e.data.length);for(let n=0;n<e.data.length;++n)e.data[n]>r&&(t[n]=1);e=new nt("bool",t,e.dims)}d.push(e)}o.push(ut(d))}return o}}class va extends Zo{pad_image(t,e,n,r={}){const[i,s,o]=e;return super.pad_image(t,e,{width:s+(n-s%n)%n,height:i+(n-i%n)%n},{mode:"symmetric",center:!1,constant_values:-1,...r})}}class xa extends Zo{async _call(t,e){Array.isArray(t)||(t=[t]),Array.isArray(e)||(e=[e]);const n=await Promise.all(t.map((t=>this.preprocess(t)))),r=await Promise.all(e.map((t=>this.preprocess(t,{do_normalize:!1,do_convert_rgb:!1,do_convert_grayscale:!0}))));return{pixel_values:ut(n.map(((t,e)=>at([t.pixel_values,r[e].pixel_values],0))),0),original_sizes:n.map((t=>t.original_size)),reshaped_input_sizes:n.map((t=>t.reshaped_input_size))}}}class Ta extends Ko{constructor(t){super(t),this.config.mel_filters??=Bo(Math.floor(1+this.config.n_fft/2),this.config.feature_size,0,8e3,this.config.sampling_rate,"slaney","slaney"),this.window=Go(this.config.n_fft,"hann")}_extract_fbank_features(t){const{data:e,dims:n}=Vo(t,this.window,this.config.n_fft,this.config.hop_length,{power:2,mel_filters:this.config.mel_filters,log_mel:"log10",max_num_frames:this.config.nb_max_frames}),r=H(e)[0];for(let t=0;t<e.length;++t)e[t]=(Math.max(e[t],r-8)+4)/4;return{data:e,dims:n}}async _call(t){let e;Ho(t,"WhisperFeatureExtractor"),t.length>this.config.n_samples?(console.warn("Attempting to extract features for audio longer than 30 seconds. If using a pipeline to extract transcript from a long audio clip, remember to specify `chunk_length_s` and/or `stride_length_s`."),e=t.slice(0,this.config.n_samples)):(e=new Float32Array(this.config.n_samples),e.set(t));const{data:n,dims:r}=this._extract_fbank_features(e);return{input_features:new nt("float32",n,[1,...r])}}}class Sa extends Ko{_zero_mean_unit_var_norm(t){const e=t.reduce(((t,e)=>t+e),0)/t.length,n=t.reduce(((t,n)=>t+(n-e)**2),0)/t.length;return t.map((t=>(t-e)/Math.sqrt(n+1e-7)))}async _call(t){Ho(t,"Wav2Vec2FeatureExtractor"),t instanceof Float64Array&&(t=new Float32Array(t));let e=t;this.config.do_normalize&&(e=this._zero_mean_unit_var_norm(e));const n=[1,e.length];return{input_values:new nt("float32",e,n),attention_mask:new nt("int64",new BigInt64Array(e.length).fill(1n),n)}}}class Aa extends Ko{constructor(t){super(t);const e=this.config.sampling_rate,n=Bo(256,this.config.num_mel_bins,20,Math.floor(e/2),e,null,"kaldi",!0);for(let t=0;t<n.length;++t)n[t].push(0);this.mel_filters=n,this.window=Go(400,"povey",{periodic:!1})}_extract_fbank_features(t,e){return Vo(t=t.map((t=>32768*t)),this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1.192092955078125e-7,remove_dc_offset:!0,max_num_frames:e,transpose:!0})}async _call(t,{padding:e=!0,pad_to_multiple_of:n=2,do_normalize_per_mel_bins:r=!0,return_attention_mask:i=!0}={}){Ho(t,"SeamlessM4TFeatureExtractor");let s,o=this._extract_fbank_features(t,this.config.max_length);if(r){const[t,e]=o.dims;for(let n=0;n<e;++n){let r=0;for(let i=0;i<t;++i)r+=o.data[i*e+n];const i=r/t;let s=0;for(let r=0;r<t;++r)s+=(o.data[r*e+n]-i)**2;s/=t-1;const a=Math.sqrt(s+1e-7);for(let r=0;r<t;++r){const t=r*e+n;o.data[t]=(o.data[t]-i)/a}}}if(e){const[t,e]=o.dims,r=t%n;if(r>0){const n=new Float32Array(e*(t+r));n.set(o.data),n.fill(this.config.padding_value,o.data.length);const a=t+r;o={data:n,dims:[a,e]},i&&(s=new nt("int64",new BigInt64Array(a),[1,a]),s.data.fill(1n,0,t))}}const[a,u]=o.dims,l=this.config.stride;if(0!=a%l)throw new Error(`The number of frames (${a}) must be a multiple of the stride (${l}).`);const c=new nt("float32",o.data,o.dims).view(1,Math.floor(a/l),u*l),d={input_features:c};if(i){const t=c.dims[1],e=new nt("int64",new BigInt64Array(t),[1,t]);if(s)for(let t=1,n=0;t<a;t+=l,++n)e.data[n]=s.data[t];else e.data.fill(1n);d.attention_mask=e}return d}}class ka extends Ko{constructor(t){super(t);const e=this.config.sampling_rate,n=Bo(256,this.config.num_mel_bins,20,Math.floor(e/2),e,null,"kaldi",!0);for(let t=0;t<n.length;++t)n[t].push(0);this.mel_filters=n,this.window=Go(400,"hann",{periodic:!1}),this.mean=this.config.mean,this.std=this.config.std}_extract_fbank_features(t,e){return Vo(t,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1.192092955078125e-7,remove_dc_offset:!0,max_num_frames:e,transpose:!0})}async _call(t){Ho(t,"ASTFeatureExtractor");const e=this._extract_fbank_features(t,this.config.max_length);if(this.config.do_normalize){const t=2*this.std;for(let n=0;n<e.data.length;++n)e.data[n]=(e.data[n]-this.mean)/t}return{input_values:new nt("float32",e.data,[1,...e.dims])}}}class Oa extends Ko{constructor(t){super(t),this.mel_filters=Bo(this.config.nb_frequency_bins,this.config.feature_size,this.config.frequency_min,this.config.frequency_max,this.config.sampling_rate,null,"htk"),this.mel_filters_slaney=Bo(this.config.nb_frequency_bins,this.config.feature_size,this.config.frequency_min,this.config.frequency_max,this.config.sampling_rate,"slaney","slaney"),this.window=Go(this.config.fft_window_size,"hann")}_get_input_mel(t,e,n,r){let i,s=!1;const o=t.length-e;if(o>0){if("rand_trunc"!==n)throw new Error(`Truncation strategy "${n}" not implemented`);{s=!0;const n=Math.floor(Math.random()*(o+1));t=t.subarray(n,n+e),i=this._extract_fbank_features(t,this.mel_filters_slaney,this.config.nb_max_samples),i.dims=[1,...i.dims]}}else{if(o<0){let n=new Float64Array(e);if(n.set(t),"repeat"===r)for(let r=t.length;r<e;r+=t.length)n.set(t.subarray(0,Math.min(t.length,e-r)),r);else if("repeatpad"===r)for(let e=t.length;e<-o;e+=t.length)n.set(t,e);t=n}if("fusion"===n)throw new Error(`Truncation strategy "${n}" not implemented`);i=this._extract_fbank_features(t,this.mel_filters_slaney,this.config.nb_max_samples),i.dims=[1,...i.dims]}return{...i,longer:s}}_extract_fbank_features(t,e,n=null){return Vo(t,this.window,this.config.fft_window_size,this.config.hop_length,{power:2,mel_filters:e,log_mel:"dB",max_num_frames:n,do_pad:!1,transpose:!0})}async _call(t,{max_length:e=null}={}){Ho(t,"ClapFeatureExtractor");const n=this._get_input_mel(t,e??this.config.nb_max_samples,this.config.truncation,this.config.padding);return{input_features:new nt("float32",n.data,[1,...n.dims])}}}class Ea extends Ko{}class Ia extends s{constructor(t){super(),this.feature_extractor=t}async _call(t,...e){return await this.feature_extractor(t,...e)}}class Pa extends Ia{async _call(...t){return await this.feature_extractor(...t)}post_process_masks(...t){return this.feature_extractor.post_process_masks(...t)}reshape_input_points(...t){return this.feature_extractor.reshape_input_points(...t)}}class Da extends Ia{async _call(t){return await this.feature_extractor(t)}}class Ca extends Ia{async _call(t){return await this.feature_extractor(t)}}class $a extends Ia{async _call(t){return await this.feature_extractor(t)}}class Ma extends Ia{}class Fa{static FEATURE_EXTRACTOR_CLASS_MAPPING={ImageFeatureExtractor:Zo,WhisperFeatureExtractor:Ta,ViTFeatureExtractor:ua,MobileViTFeatureExtractor:da,OwlViTFeatureExtractor:ha,Owlv2ImageProcessor:pa,CLIPFeatureExtractor:ra,ChineseCLIPFeatureExtractor:ia,SiglipImageProcessor:sa,ConvNextFeatureExtractor:oa,ConvNextImageProcessor:aa,SegformerFeatureExtractor:Jo,BitImageProcessor:ea,DPTImageProcessor:ta,DPTFeatureExtractor:Qo,GLPNFeatureExtractor:na,BeitFeatureExtractor:ga,DeiTFeatureExtractor:fa,DetrFeatureExtractor:ba,YolosFeatureExtractor:ya,DonutFeatureExtractor:ma,NougatImageProcessor:_a,EfficientNetImageProcessor:ca,ViTImageProcessor:la,VitMatteImageProcessor:xa,SamImageProcessor:wa,Swin2SRImageProcessor:va,Wav2Vec2FeatureExtractor:Sa,SeamlessM4TFeatureExtractor:Aa,SpeechT5FeatureExtractor:Ea,ASTFeatureExtractor:ka,ClapFeatureExtractor:Oa};static PROCESSOR_CLASS_MAPPING={WhisperProcessor:Da,Wav2Vec2ProcessorWithLM:Ca,SamProcessor:Pa,SpeechT5Processor:$a,OwlViTProcessor:Ma};static async from_pretrained(t,{progress_callback:e=null,config:n=null,cache_dir:r=null,local_files_only:i=!1,revision:s="main"}={}){let o=n??await U(t,"preprocessor_config.json",!0,{progress_callback:e,config:n,cache_dir:r,local_files_only:i,revision:s}),a=o.feature_extractor_type??o.image_processor_type,u=this.FEATURE_EXTRACTOR_CLASS_MAPPING[a];if(!u){if(void 0===o.size)throw new Error(`Unknown Feature Extractor type: ${a}`);console.warn(`Feature extractor type "${a}" not found, assuming ImageFeatureExtractor due to size parameter in config.`),u=Zo}return new(this.PROCESSOR_CLASS_MAPPING[o.processor_class]??Ia)(new u(o))}}async function La(t){return Array.isArray(t)||(t=[t]),await Promise.all(t.map((t=>Fo.read(t))))}async function Na(t,e){return Array.isArray(t)||(t=[t]),await Promise.all(t.map((t=>"string"==typeof t||t instanceof URL?async function(t,e){if("undefined"==typeof AudioContext)throw Error("Unable to load audio from path/URL since `AudioContext` is not available in your environment. Instead, audio data should be passed directly to the pipeline/processor. For more information and some example code, see https://huggingface.co/docs/transformers.js/guides/node-audio-processing.");const n=await(await R(t)).arrayBuffer(),r=new AudioContext({sampleRate:e});void 0===e&&console.warn(`No sampling rate provided, using default of ${r.sampleRate}Hz.`);const i=await r.decodeAudioData(n);let s;if(2===i.numberOfChannels){const t=Math.sqrt(2),e=i.getChannelData(0),n=i.getChannelData(1);s=new Float32Array(e.length);for(let r=0;r<i.length;++r)s[r]=t*(e[r]+n[r])/2}else s=i.getChannelData(0);return s}(t,e):t instanceof Float64Array?new Float32Array(t):t)))}function Ra(t,e){e&&(t=t.map((t=>0|t)));const[n,r,i,s]=t;return{xmin:n,ymin:r,xmax:i,ymax:s}}class ja extends s{constructor({task:t,model:e,tokenizer:n=null,processor:r=null}){super(),this.task=t,this.model=e,this.tokenizer=n,this.processor=r}async dispose(){await this.model.dispose()}}class za extends ja{_key="generated_text";constructor(t){super(t)}async _call(t,e={}){Array.isArray(t)||(t=[t]),this.model.config.prefix&&(t=t.map((t=>this.model.config.prefix+t)));const n=this.model.config.task_specific_params;n&&n[this.task]&&n[this.task].prefix&&(t=t.map((t=>n[this.task].prefix+t)));const r=this.tokenizer,i={padding:!0,truncation:!0};let s;s=this instanceof Ba&&"_build_translation_inputs"in r?r._build_translation_inputs(t,i,e).input_ids:r(t,i).input_ids;const o=await this.model.generate(s,e);return r.batch_decode(o,{skip_special_tokens:!0}).map((t=>({[this._key]:t})))}}class Ba extends za{_key="translation_text";constructor(t){super(t)}}Object.freeze({"text-classification":{tokenizer:hr,pipeline:class extends ja{constructor(t){super(t)}async _call(t,{topk:e=1}={}){const n=this.tokenizer(t,{padding:!0,truncation:!0}),r=await this.model(n),i="multi_label_classification"===this.model.config.problem_type?t=>t.sigmoid().data:t=>G(t.data),s=this.model.config.id2label,o=[];for(const t of r.logits){const n=q(i(t),e).map((t=>({label:s[t[0]],score:t[1]})));1===e?o.push(...n):o.push(n)}return Array.isArray(t)||1===e?o:o[0]}},model:mo,default:{model:"Xenova/distilbert-base-uncased-finetuned-sst-2-english"},type:"text"},"token-classification":{tokenizer:hr,pipeline:class extends ja{constructor(t){super(t)}async _call(t,{ignore_labels:e=["O"]}={}){const n=Array.isArray(t),r=this.tokenizer(n?t:[t],{padding:!0,truncation:!0}),i=(await this.model(r)).logits,s=this.model.config.id2label,o=[];for(let t=0;t<i.dims[0];++t){const n=r.input_ids[t],a=i[t],u=[];for(let t=0;t<a.dims[0];++t){const r=a[t],i=H(r.data)[1],o=s?s[i]:`LABEL_${i}`;if(e.includes(o))continue;const l=this.tokenizer.decode([n[t].item()],{skip_special_tokens:!0});if(""===l)continue;const c=G(r.data);u.push({entity:o,score:c[i],index:t,word:l,start:null,end:null})}o.push(u)}return n?o:o[0]}},model:class extends Ns{static MODEL_CLASS_MAPPINGS=[qs]},default:{model:"Xenova/bert-base-multilingual-cased-ner-hrl"},type:"text"},"question-answering":{tokenizer:hr,pipeline:class extends ja{constructor(t){super(t)}async _call(t,e,{topk:n=1}={}){const r=this.tokenizer(t,{text_pair:e,padding:!0,truncation:!0}),i=await this.model(r),s=[];for(let t=0;t<i.start_logits.dims[0];++t){const e=r.input_ids[t],o=e.indexOf(this.tokenizer.sep_token_id),a=c(Array.from(G(i.start_logits[t].data)).map(((t,e)=>[t,e])).filter((t=>t[1]>o)),Array.from(G(i.end_logits[t].data)).map(((t,e)=>[t,e])).filter((t=>t[1]>o))).filter((t=>t[0][1]<=t[1][1])).map((t=>[t[0][1],t[1][1],t[0][0]*t[1][0]])).sort(((t,e)=>e[2]-t[2]));for(let t=0;t<Math.min(a.length,n);++t){const[n,r,i]=a[t],o=[...e].slice(n,r+1),u=this.tokenizer.decode(o,{skip_special_tokens:!0});s.push({answer:u,score:i})}}return 1===n?s[0]:s}},model:class extends Ns{static MODEL_CLASS_MAPPINGS=[Ys]},default:{model:"Xenova/distilbert-base-cased-distilled-squad"},type:"text"},"fill-mask":{tokenizer:hr,pipeline:class extends ja{constructor(t){super(t)}async _call(t,{topk:e=5}={}){const n=this.tokenizer(t,{padding:!0,truncation:!0}),r=await this.model(n),i=[];for(let t=0;t<n.input_ids.dims[0];++t){const s=n.input_ids[t],o=s.indexOf(this.tokenizer.mask_token_id);if(-1===o)throw Error(`Mask token (${this.tokenizer.mask_token}) not found in text.`);const a=q(G(r.logits[t][o].data),e);i.push(a.map((t=>{const e=[...s];return e[o]=t[0],{score:t[1],token:t[0],token_str:this.tokenizer.model.vocab[t[0]],sequence:this.tokenizer.decode(e,{skip_special_tokens:!0})}})))}return Array.isArray(t)?i:i[0]}},model:class extends Ns{static MODEL_CLASS_MAPPINGS=[Xs]},default:{model:"Xenova/bert-base-uncased"},type:"text"},summarization:{tokenizer:hr,pipeline:class extends za{_key="summary_text";constructor(t){super(t)}},model:_o,default:{model:"Xenova/distilbart-cnn-6-6"},type:"text"},translation:{tokenizer:hr,pipeline:Ba,model:_o,default:{model:"Xenova/t5-small"},type:"text"},"text2text-generation":{tokenizer:hr,pipeline:za,model:_o,default:{model:"Xenova/flan-t5-small"},type:"text"},"text-generation":{tokenizer:hr,pipeline:class extends ja{constructor(t){super(t)}async _call(t,e={}){const n=Array.isArray(t);n||(t=[t]);const r=e.add_special_tokens??!1;this.tokenizer.padding_side="left";const{input_ids:i,attention_mask:s}=this.tokenizer(t,{add_special_tokens:r,padding:!0,truncation:!0}),o=await this.model.generate(i,e,null,{inputs_attention_mask:s}),a=this.tokenizer.batch_decode(o,{skip_special_tokens:!0}),u=Array.from({length:t.length},(t=>[]));for(let e=0;e<a.length;++e)u[Math.floor(e/o.length*t.length)].push({generated_text:a[e]});return n||1!==u.length?u:u[0]}},model:class extends Ns{static 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Using 2 as entailment_id."),this.entailment_id=2),this.contradiction_id=this.label2id.contradiction??this.label2id.not_entailment,void 0===this.contradiction_id&&(console.warn("Could not find 'contradiction' in label2id mapping. Using 0 as contradiction_id."),this.contradiction_id=0)}async _call(t,e,{hypothesis_template:n="This example is {}.",multi_label:r=!1}={}){const i=Array.isArray(t);i||(t=[t]),Array.isArray(e)||(e=[e]);const s=e.map((t=>n.replace("{}",t))),o=r||1===e.length,a=[];for(const n of t){const t=[];for(const e of s){const r=this.tokenizer(n,{text_pair:e,padding:!0,truncation:!0}),i=await this.model(r);o?t.push([i.logits.data[this.contradiction_id],i.logits.data[this.entailment_id]]):t.push(i.logits.data[this.entailment_id])}const r=(o?t.map((t=>G(t)[1])):G(t)).map(((t,e)=>[t,e])).sort(((t,e)=>e[0]-t[0]));a.push({sequence:n,labels:r.map((t=>e[t[1]])),scores:r.map((t=>t[0]))})}return i?a:a[0]}},model:mo,default:{model:"Xenova/distilbert-base-uncased-mnli"},type:"text"},"audio-classification":{pipeline:class extends ja{constructor(t){super(t)}async _call(t,{topk:e=null}={}){const n=!Array.isArray(t),r=this.processor.feature_extractor.config.sampling_rate,i=await Na(t,r),s=this.model.config.id2label,o=[];for(const t of i){const n=await this.processor(t),r=q(G((await this.model(n)).logits[0].data),e).map((t=>({label:s[t[0]],score:t[1]})));1===e?o.push(...r):o.push(r)}return n&&1!==e?o[0]:o}},model:class extends Ns{static MODEL_CLASS_MAPPINGS=[so]},processor:Fa,default:{model:"Xenova/wav2vec2-base-superb-ks"},type:"audio"},"zero-shot-audio-classification":{tokenizer:hr,pipeline:class extends ja{constructor(t){super(t)}async _call(t,e,{hypothesis_template:n="This is a sound of {}."}={}){const r=!Array.isArray(t);r&&(t=[t]);const i=e.map((t=>n.replace("{}",t))),s=this.tokenizer(i,{padding:!0,truncation:!0}),o=this.processor.feature_extractor.config.sampling_rate,a=await Na(t,o),u=[];for(const t of a){const n=await this.processor(t),r=G((await this.model({...s,...n})).logits_per_audio.data);u.push([...r].map(((t,n)=>({score:t,label:e[n]}))))}return r?u[0]:u}},model:go,processor:Fa,default:{model:"Xenova/clap-htsat-unfused"},type:"multimodal"},"automatic-speech-recognition":{tokenizer:hr,pipeline:class extends ja{constructor(t){super(t)}async _call(t,e={}){switch(this.model.config.model_type){case"whisper":return this._call_whisper(t,e);case"wav2vec2":case"wav2vec2-bert":case"unispeech":case"unispeech-sat":case"hubert":return this._call_wav2vec2(t,e);default:throw new Error(`AutomaticSpeechRecognitionPipeline does not support model type '${this.model.config.model_type}'.`)}}async _call_wav2vec2(t,e={}){e.language&&console.warn('`language` parameter is not yet supported for `wav2vec2` models, defaulting to "English".'),e.task&&console.warn('`task` parameter is not yet supported for `wav2vec2` models, defaulting to "transcribe".');const n=!Array.isArray(t);n&&(t=[t]);const r=this.processor.feature_extractor.config.sampling_rate,i=await Na(t,r),s=[];for(const t of i){const e=await this.processor(t),n=(await this.model(e)).logits[0],r=[];for(const t of n)r.push(H(t.data)[1]);const i=this.tokenizer.decode(r);s.push({text:i})}return n?s[0]:s}async _call_whisper(t,e={}){const n=e.return_timestamps??!1,r=e.chunk_length_s??0,i=e.chunk_callback??null,s=e.force_full_sequences??!1;let o=e.stride_length_s??null;"word"===n&&(e.return_token_timestamps=!0);const a=u(e,"language",null),l=u(e,"task",null);if(a||l||n){if(e.forced_decoder_ids)throw new Error("Cannot specify `language`/`task`/`return_timestamps` and `forced_decoder_ids` at the same time.");const t=this.tokenizer.get_decoder_prompt_ids({language:a,task:l,no_timestamps:!n});t.length>0&&(e.forced_decoder_ids=t)}const c=!Array.isArray(t);c&&(t=[t]);const d=this.processor.feature_extractor.config.chunk_length/this.model.config.max_source_positions,h=this.processor.feature_extractor.config.hop_length,p=this.processor.feature_extractor.config.sampling_rate,f=await Na(t,p),g=[];for(const t of f){let a=[];if(r>0){if(null===o)o=r/6;else if(r<=o)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");const e=p*r,n=p*o,i=e-2*n;let s=0;for(;s<t.length;){const r=t.subarray(s,s+e),o=await this.processor(r),u=0===s,l=s+i>=t.length;a.push({stride:[r.length,u?0:n,l?0:n],input_features:o.input_features,is_last:l}),s+=i}}else a=[{stride:[t.length,0,0],input_features:(await this.processor(t)).input_features,is_last:!0}];for(const t of a){e.num_frames=Math.floor(t.stride[0]/h);const r=await this.model.generate(t.input_features,e);"word"===n?(t.tokens=r.sequences[0],t.token_timestamps=r.token_timestamps.tolist()[0].map((t=>Q(t,2)))):t.tokens=r[0],t.stride=t.stride.map((t=>t/p)),null!==i&&i(t)}const[u,l]=this.tokenizer._decode_asr(a,{time_precision:d,return_timestamps:n,force_full_sequences:s});g.push({text:u,...l})}return c?g[0]:g}},model:[class extends Ns{static MODEL_CLASS_MAPPINGS=[Bs]},class extends Ns{static 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instanceof nt))throw new Error("Speaker embeddings must be a `Tensor`, `Float32Array`, `string`, or `URL`.");const{input_ids:n}=this.tokenizer(t,{padding:!0,truncation:!0}),{waveform:r}=await this.model.generate_speech(n,e,{vocoder:this.vocoder}),i=this.processor.feature_extractor.config.sampling_rate;return{audio:r.data,sampling_rate:i}}},model:[class extends Ns{static MODEL_CLASS_MAPPINGS=[Vs]},class extends Ns{static MODEL_CLASS_MAPPINGS=[Us]}],processor:[Fa,null],default:{model:"Xenova/speecht5_tts"},type:"text"},"image-to-text":{tokenizer:hr,pipeline:class extends ja{constructor(t){super(t)}async _call(t,e={}){const n=Array.isArray(t),r=await La(t),{pixel_values:i}=await this.processor(r),s=[];for(const t of i){t.dims=[1,...t.dims];const n=await this.model.generate(t,e),r=this.tokenizer.batch_decode(n,{skip_special_tokens:!0}).map((t=>({generated_text:t.trim()})));s.push(r)}return n?s:s[0]}},model:class extends Ns{static 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_call(t,{threshold:e=.5,mask_threshold:n=.5,overlap_mask_area_threshold:r=.8,label_ids_to_fuse:i=null,target_sizes:s=null,subtask:o=null}={}){if(Array.isArray(t)&&1!==t.length)throw Error("Image segmentation pipeline currently only supports a batch size of 1.");const a=await La(t),u=a.map((t=>[t.height,t.width])),{pixel_values:l,pixel_mask:c}=await this.processor(a),d=await this.model({pixel_values:l,pixel_mask:c});let h=null;if(null!==o)h=this.subtasks_mapping[o];else for(let[t,e]of Object.entries(this.subtasks_mapping))if(e in this.processor.feature_extractor){h=this.processor.feature_extractor[e].bind(this.processor.feature_extractor),o=t;break}const p=this.model.config.id2label,f=[];if("panoptic"===o||"instance"===o){const t=h(d,e,n,r,i,s??u)[0],o=t.segmentation;for(const e of t.segments_info){const t=new Uint8ClampedArray(o.data.length);for(let n=0;n<o.data.length;++n)o.data[n]===e.id&&(t[n]=255);const n=new Fo(t,o.dims[1],o.dims[0],1);f.push({score:e.score,label:p[e.label_id],mask:n})}}else{if("semantic"!==o)throw Error(`Subtask ${o} not supported.`);{const{segmentation:t,labels:e}=h(d,s??u)[0];for(const n of e){const e=new Uint8ClampedArray(t.data.length);for(let r=0;r<t.data.length;++r)t.data[r]===n&&(e[r]=255);const r=new Fo(e,t.dims[1],t.dims[0],1);f.push({score:null,label:p[n],mask:r})}}}return f}},model:[class extends Ns{static MODEL_CLASS_MAPPINGS=[eo]},class extends Ns{static MODEL_CLASS_MAPPINGS=[no]}],processor:Fa,default:{model:"Xenova/detr-resnet-50-panoptic"},type:"multimodal"},"zero-shot-image-classification":{tokenizer:hr,pipeline:class extends ja{constructor(t){super(t)}async _call(t,e,{hypothesis_template:n="This is a photo of {}"}={}){const r=Array.isArray(t),i=await La(t),s=e.map((t=>n.replace("{}",t))),o=this.tokenizer(s,{padding:"siglip"!==this.model.config.model_type||"max_length",truncation:!0}),{pixel_values:a}=await this.processor(i),u=await 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ja{constructor(t){super(t)}async _call(t,e,n={}){const r=(await La(t))[0],{pixel_values:i}=await this.processor(r),s=`<s_docvqa><s_question>${e}</s_question><s_answer>`,o=this.tokenizer(s,{add_special_tokens:!1,padding:!0,truncation:!0}).input_ids,a=await this.model.generate(i,{...n,decoder_input_ids:o,max_length:this.model.config.decoder.max_position_embeddings}),u=this.tokenizer.batch_decode(a)[0].match(/<s_answer>(.*?)<\/s_answer>/);let l=null;return u&&u.length>=2&&(l=u[1].trim()),[{answer:l}]}},model:class extends Ns{static MODEL_CLASS_MAPPINGS=[Zs]},processor:Fa,default:{model:"Xenova/donut-base-finetuned-docvqa"},type:"multimodal"},"image-to-image":{pipeline:class extends ja{constructor(t){super(t)}async _call(t){const e=await La(t),n=await this.processor(e),r=await this.model(n),i=[];for(const t of r.reconstruction){const e=t.squeeze().clamp_(0,1).mul_(255).round_().to("uint8");i.push(Fo.fromTensor(e))}return i.length>1?i:i[0]}},model:class extends Ns{static MODEL_CLASS_MAPPINGS=[lo]},processor:Fa,default:{model:"Xenova/swin2SR-classical-sr-x2-64"},type:"image"},"depth-estimation":{pipeline:class extends ja{constructor(t){super(t)}async _call(t){const e=await La(t),n=await this.processor(e),{predicted_depth:r}=await this.model(n),i=[];for(let t=0;t<e.length;++t){const n=rt(r[t],e[t].size.reverse(),"bilinear",!1),s=n.mul_(255/H(n.data)[0]).to("uint8");i.push({predicted_depth:r[t],depth:Fo.fromTensor(s)})}return i.length>1?i:i[0]}},model:class extends Ns{static MODEL_CLASS_MAPPINGS=[co]},processor:Fa,default:{model:"Xenova/dpt-large"},type:"image"},"feature-extraction":{tokenizer:hr,pipeline:class extends ja{constructor(t){super(t)}async _call(t,{pooling:e="none",normalize:n=!1}={}){const r=this.tokenizer(t,{padding:!0,truncation:!0}),i=await this.model(r);let s=i.last_hidden_state??i.logits;if("none"===e);else if("mean"===e)s=function(t,e){let n=[t.dims[0],t.dims[2]],r=new t.data.constructor(n[0]*n[1]),[i,s,o]=t.dims,a=0;for(let n=0;n<i;++n){let i=n*o*s;for(let u=0;u<o;++u){let l=0,c=0,d=n*s,h=i+u;for(let n=0;n<s;++n){let r=Number(e.data[d+n]);c+=r,l+=t.data[h+n*o]*r}let p=l/c;r[a++]=p}}return new nt(t.type,r,n)}(s,r.attention_mask);else{if("cls"!==e)throw Error(`Pooling method '${e}' not supported.`);s=s.slice(null,0)}return n&&(s=s.normalize(2,-1)),s}},model:go,default:{model:"Xenova/all-MiniLM-L6-v2"},type:"text"},"image-feature-extraction":{processor:Fa,pipeline:class extends ja{constructor(t){super(t)}async _call(t,{pool:e=null}={}){const n=await La(t),{pixel_values:r}=await this.processor(n),i=await this.model({pixel_values:r});let s;if(e){if(!("pooler_output"in i))throw Error("No pooled output was returned. Make sure the model has a 'pooler' layer when using the 'pool' option.");s=i.pooler_output}else s=i.last_hidden_state??i.logits??i.image_embeds;return s}},model:[class extends Ns{static MODEL_CLASS_MAPPINGS=[ho]},go],default:{model:"Xenova/vit-base-patch16-224-in21k"},type:"image"}}),Object.freeze({"sentiment-analysis":"text-classification",ner:"token-classification",asr:"automatic-speech-recognition","text-to-speech":"text-to-audio",embeddings:"feature-extraction"})}}]);
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