first commit
This commit is contained in:
nasir@endelospay.com
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var ortWasmThreaded = (() => {
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var _scriptName = import.meta.url;
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return (
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async function(moduleArg = {}) {
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var moduleRtn;
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e._JsepGetNodeName=a=>(e._JsepGetNodeName=K.fb)(a);
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var Ka=()=>(Ka=K.gb)(),Y=e._free=a=>(Y=e._free=K.hb)(a),sd=e._malloc=a=>(sd=e._malloc=K.ib)(a),Ma=(a,b,c,d,f,g)=>(Ma=K.lb)(a,b,c,d,f,g),Sa=()=>(Sa=K.mb)(),Pc=(a,b,c,d,f)=>(Pc=K.nb)(a,b,c,d,f),Vc=a=>(Vc=K.ob)(a),Zc=a=>(Zc=K.pb)(a),je=(a,b)=>(je=K.qb)(a,b),Bd=()=>(Bd=K.rb)(),Xc=(a,b)=>(Xc=K.sb)(a,b),Qc=a=>(Qc=K.tb)(a),Oc=a=>(Oc=K.ub)(a),Nc=()=>(Nc=K.vb)(),Yc=e.dynCall_ii=(a,b)=>(Yc=e.dynCall_ii=K.wb)(a,b),Vd=a=>(Vd=K.xb)(a),Kd=()=>(Kd=K.yb)(),Ud=a=>(Ud=K.zb)(a),Xd=()=>(Xd=K.Ab)();
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e.setValue=function(a,b,c="i8"){c.endsWith("*")&&(c="*");switch(c){case "i1":D()[a>>>0]=b;break;case "i8":D()[a>>>0]=b;break;case "i16":G()[a>>>1>>>0]=b;break;case "i32":H()[a>>>2>>>0]=b;break;case "i64":C[a>>>3]=BigInt(b);break;case "float":Ga()[a>>>2>>>0]=b;break;case "double":J()[a>>>3>>>0]=b;break;case "*":I()[a>>>2>>>0]=b;break;default:L(`invalid type for setValue: ${c}`)}};
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e.getValue=function(a,b="i8"){b.endsWith("*")&&(b="*");switch(b){case "i1":return D()[a>>>0];case "i8":return D()[a>>>0];case "i16":return G()[a>>>1>>>0];case "i32":return H()[a>>>2>>>0];case "i64":return C[a>>>3];case "float":return Ga()[a>>>2>>>0];case "double":return J()[a>>>3>>>0];case "*":return I()[a>>>2>>>0];default:L(`invalid type for getValue: ${b}`)}};e.UTF8ToString=M;e.stringToUTF8=gd;e.lengthBytesUTF8=fd;
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function xe(){if(0<Ua)Va=xe;else if(q)aa(e),Ta();else{for(;0<Ic.length;)Ic.shift()(e);0<Ua?Va=xe:(e.calledRun=!0,A||(Ta(),aa(e)))}}xe();e.PTR_SIZE=4;moduleRtn=da;
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|
||||
|
||||
return moduleRtn;
|
||||
}
|
||||
);
|
||||
})();
|
||||
export default ortWasmThreaded;
|
||||
var isPthread = globalThis.self?.name?.startsWith('em-pthread');
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||||
var isNode = typeof globalThis.process?.versions?.node == 'string';
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if (isNode) isPthread = (await import('worker_threads')).workerData === 'em-pthread';
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|
||||
// When running as a pthread, construct a new instance on startup
|
||||
isPthread && ortWasmThreaded();
|
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Binary file not shown.
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var ortWasmThreaded = (() => {
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||||
var _scriptName = import.meta.url;
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return (
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async function(moduleArg = {}) {
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||||
var moduleRtn;
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||||
f.mountExternalData=(a,b)=>{a.startsWith("./")&&(a=a.substring(2));(f.Sa||(f.Sa=new Map)).set(a,b)};f.unmountExternalData=()=>{delete f.Sa};var SharedArrayBuffer=globalThis.SharedArrayBuffer??(new WebAssembly.Memory({initial:0,maximum:0,lb:!0})).buffer.constructor,ea=Object.assign({},f),fa="./this.program",q=(a,b)=>{throw b;},r="",ha,t;
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if(l){var fs=require("fs"),ia=require("path");import.meta.url.startsWith("data:")||(r=ia.dirname(require("url").fileURLToPath(import.meta.url))+"/");t=a=>{a=u(a)?new URL(a):a;return fs.readFileSync(a)};ha=async a=>{a=u(a)?new URL(a):a;return fs.readFileSync(a,void 0)};!f.thisProgram&&1<process.argv.length&&(fa=process.argv[1].replace(/\\/g,"/"));process.argv.slice(2);q=(a,b)=>{process.exitCode=a;throw b;}}else if(da||k)k?r=self.location.href:"undefined"!=typeof document&&document.currentScript&&
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(r=document.currentScript.src),_scriptName&&(r=_scriptName),r.startsWith("blob:")?r="":r=r.slice(0,r.replace(/[?#].*/,"").lastIndexOf("/")+1),l||(k&&(t=a=>{var b=new XMLHttpRequest;b.open("GET",a,!1);b.responseType="arraybuffer";b.send(null);return new Uint8Array(b.response)}),ha=async a=>{if(u(a))return new Promise((c,d)=>{var e=new XMLHttpRequest;e.open("GET",a,!0);e.responseType="arraybuffer";e.onload=()=>{200==e.status||0==e.status&&e.response?c(e.response):d(e.status)};e.onerror=d;e.send(null)});
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|
||||
f._OrtCreateTensor=(a,b,c,d,e,g)=>(f._OrtCreateTensor=L.ma)(a,b,c,d,e,g);f._OrtGetTensorData=(a,b,c,d,e)=>(f._OrtGetTensorData=L.na)(a,b,c,d,e);f._OrtReleaseTensor=a=>(f._OrtReleaseTensor=L.oa)(a);f._OrtCreateRunOptions=(a,b,c,d)=>(f._OrtCreateRunOptions=L.pa)(a,b,c,d);f._OrtAddRunConfigEntry=(a,b,c)=>(f._OrtAddRunConfigEntry=L.qa)(a,b,c);f._OrtReleaseRunOptions=a=>(f._OrtReleaseRunOptions=L.ra)(a);f._OrtCreateBinding=a=>(f._OrtCreateBinding=L.sa)(a);
|
||||
f._OrtBindInput=(a,b,c)=>(f._OrtBindInput=L.ta)(a,b,c);f._OrtBindOutput=(a,b,c,d)=>(f._OrtBindOutput=L.ua)(a,b,c,d);f._OrtClearBoundOutputs=a=>(f._OrtClearBoundOutputs=L.va)(a);f._OrtReleaseBinding=a=>(f._OrtReleaseBinding=L.wa)(a);f._OrtRunWithBinding=(a,b,c,d,e)=>(f._OrtRunWithBinding=L.xa)(a,b,c,d,e);f._OrtRun=(a,b,c,d,e,g,h,p)=>(f._OrtRun=L.ya)(a,b,c,d,e,g,h,p);f._OrtEndProfiling=a=>(f._OrtEndProfiling=L.za)(a);var J=()=>(J=L.Aa)();f._free=a=>(f._free=L.Ba)(a);f._malloc=a=>(f._malloc=L.Ca)(a);
|
||||
var Aa=(a,b,c,d,e,g)=>(Aa=L.Fa)(a,b,c,d,e,g),Ea=()=>(Ea=L.Ga)(),Vb=(a,b,c,d,e)=>(Vb=L.Ha)(a,b,c,d,e),$b=a=>($b=L.Ia)(a),dc=a=>(dc=L.Ja)(a),rc=(a,b)=>(rc=L.Ka)(a,b),lc=()=>(lc=L.La)(),bc=(a,b)=>(bc=L.Ma)(a,b),U=a=>(U=L.Na)(a),Ub=a=>(Ub=L.Oa)(a),Tb=()=>(Tb=L.Pa)();function Ac(){var a=L;a=Object.assign({},a);var b=d=>()=>d()>>>0,c=d=>e=>d(e)>>>0;a.Aa=b(a.Aa);a.Ca=c(a.Ca);a.Oa=c(a.Oa);a.Pa=b(a.Pa);a.__cxa_get_exception_ptr=c(a.__cxa_get_exception_ptr);return a}f.stackSave=()=>Tb();f.stackRestore=a=>U(a);
|
||||
f.stackAlloc=a=>Ub(a);f.setValue=function(a,b,c="i8"){c.endsWith("*")&&(c="*");switch(c){case "i1":D()[a>>>0]=b;break;case "i8":D()[a>>>0]=b;break;case "i16":ta()[a>>>1>>>0]=b;break;case "i32":G()[a>>>2>>>0]=b;break;case "i64":C[a>>>3]=BigInt(b);break;case "float":va()[a>>>2>>>0]=b;break;case "double":I()[a>>>3>>>0]=b;break;case "*":H()[a>>>2>>>0]=b;break;default:O(`invalid type for setValue: ${c}`)}};
|
||||
f.getValue=function(a,b="i8"){b.endsWith("*")&&(b="*");switch(b){case "i1":return D()[a>>>0];case "i8":return D()[a>>>0];case "i16":return ta()[a>>>1>>>0];case "i32":return G()[a>>>2>>>0];case "i64":return C[a>>>3];case "float":return va()[a>>>2>>>0];case "double":return I()[a>>>3>>>0];case "*":return H()[a>>>2>>>0];default:O(`invalid type for getValue: ${b}`)}};f.UTF8ToString=Lb;f.stringToUTF8=X;
|
||||
f.lengthBytesUTF8=a=>{for(var b=0,c=0;c<a.length;++c){var d=a.charCodeAt(c);127>=d?b++:2047>=d?b+=2:55296<=d&&57343>=d?(b+=4,++c):b+=3}return b};function Bc(){if(0<M)N=Bc;else if(m)aa(f),Fa();else{for(;0<Pb.length;)Pb.shift()(f);0<M?N=Bc:(f.calledRun=!0,z||(Fa(),aa(f)))}}Bc();f.PTR_SIZE=4;moduleRtn=ca;
|
||||
|
||||
|
||||
return moduleRtn;
|
||||
}
|
||||
);
|
||||
})();
|
||||
export default ortWasmThreaded;
|
||||
var isPthread = globalThis.self?.name?.startsWith('em-pthread');
|
||||
var isNode = typeof globalThis.process?.versions?.node == 'string';
|
||||
if (isNode) isPthread = (await import('worker_threads')).workerData === 'em-pthread';
|
||||
|
||||
// When running as a pthread, construct a new instance on startup
|
||||
isPthread && ortWasmThreaded();
|
||||
Binary file not shown.
@@ -0,0 +1,324 @@
|
||||
let wasm;
|
||||
|
||||
const cachedTextDecoder = (typeof TextDecoder !== 'undefined' ? new TextDecoder('utf-8', { ignoreBOM: true, fatal: true }) : { decode: () => { throw Error('TextDecoder not available') } } );
|
||||
|
||||
if (typeof TextDecoder !== 'undefined') { cachedTextDecoder.decode(); };
|
||||
|
||||
let cachedUint8ArrayMemory0 = null;
|
||||
|
||||
function getUint8ArrayMemory0() {
|
||||
if (cachedUint8ArrayMemory0 === null || cachedUint8ArrayMemory0.byteLength === 0) {
|
||||
cachedUint8ArrayMemory0 = new Uint8Array(wasm.memory.buffer);
|
||||
}
|
||||
return cachedUint8ArrayMemory0;
|
||||
}
|
||||
|
||||
function getStringFromWasm0(ptr, len) {
|
||||
ptr = ptr >>> 0;
|
||||
return cachedTextDecoder.decode(getUint8ArrayMemory0().subarray(ptr, ptr + len));
|
||||
}
|
||||
|
||||
let WASM_VECTOR_LEN = 0;
|
||||
|
||||
const cachedTextEncoder = (typeof TextEncoder !== 'undefined' ? new TextEncoder('utf-8') : { encode: () => { throw Error('TextEncoder not available') } } );
|
||||
|
||||
const encodeString = (typeof cachedTextEncoder.encodeInto === 'function'
|
||||
? function (arg, view) {
|
||||
return cachedTextEncoder.encodeInto(arg, view);
|
||||
}
|
||||
: function (arg, view) {
|
||||
const buf = cachedTextEncoder.encode(arg);
|
||||
view.set(buf);
|
||||
return {
|
||||
read: arg.length,
|
||||
written: buf.length
|
||||
};
|
||||
});
|
||||
|
||||
function passStringToWasm0(arg, malloc, realloc) {
|
||||
|
||||
if (realloc === undefined) {
|
||||
const buf = cachedTextEncoder.encode(arg);
|
||||
const ptr = malloc(buf.length, 1) >>> 0;
|
||||
getUint8ArrayMemory0().subarray(ptr, ptr + buf.length).set(buf);
|
||||
WASM_VECTOR_LEN = buf.length;
|
||||
return ptr;
|
||||
}
|
||||
|
||||
let len = arg.length;
|
||||
let ptr = malloc(len, 1) >>> 0;
|
||||
|
||||
const mem = getUint8ArrayMemory0();
|
||||
|
||||
let offset = 0;
|
||||
|
||||
for (; offset < len; offset++) {
|
||||
const code = arg.charCodeAt(offset);
|
||||
if (code > 0x7F) break;
|
||||
mem[ptr + offset] = code;
|
||||
}
|
||||
|
||||
if (offset !== len) {
|
||||
if (offset !== 0) {
|
||||
arg = arg.slice(offset);
|
||||
}
|
||||
ptr = realloc(ptr, len, len = offset + arg.length * 3, 1) >>> 0;
|
||||
const view = getUint8ArrayMemory0().subarray(ptr + offset, ptr + len);
|
||||
const ret = encodeString(arg, view);
|
||||
|
||||
offset += ret.written;
|
||||
ptr = realloc(ptr, len, offset, 1) >>> 0;
|
||||
}
|
||||
|
||||
WASM_VECTOR_LEN = offset;
|
||||
return ptr;
|
||||
}
|
||||
|
||||
let cachedDataViewMemory0 = null;
|
||||
|
||||
function getDataViewMemory0() {
|
||||
if (cachedDataViewMemory0 === null || cachedDataViewMemory0.buffer.detached === true || (cachedDataViewMemory0.buffer.detached === undefined && cachedDataViewMemory0.buffer !== wasm.memory.buffer)) {
|
||||
cachedDataViewMemory0 = new DataView(wasm.memory.buffer);
|
||||
}
|
||||
return cachedDataViewMemory0;
|
||||
}
|
||||
|
||||
export function main() {
|
||||
wasm.main();
|
||||
}
|
||||
|
||||
let cachedFloat32ArrayMemory0 = null;
|
||||
|
||||
function getFloat32ArrayMemory0() {
|
||||
if (cachedFloat32ArrayMemory0 === null || cachedFloat32ArrayMemory0.byteLength === 0) {
|
||||
cachedFloat32ArrayMemory0 = new Float32Array(wasm.memory.buffer);
|
||||
}
|
||||
return cachedFloat32ArrayMemory0;
|
||||
}
|
||||
|
||||
function passArrayF32ToWasm0(arg, malloc) {
|
||||
const ptr = malloc(arg.length * 4, 4) >>> 0;
|
||||
getFloat32ArrayMemory0().set(arg, ptr / 4);
|
||||
WASM_VECTOR_LEN = arg.length;
|
||||
return ptr;
|
||||
}
|
||||
|
||||
function getArrayF32FromWasm0(ptr, len) {
|
||||
ptr = ptr >>> 0;
|
||||
return getFloat32ArrayMemory0().subarray(ptr / 4, ptr / 4 + len);
|
||||
}
|
||||
|
||||
const SIMDMathFinalization = (typeof FinalizationRegistry === 'undefined')
|
||||
? { register: () => {}, unregister: () => {} }
|
||||
: new FinalizationRegistry(ptr => wasm.__wbg_simdmath_free(ptr >>> 0, 1));
|
||||
|
||||
export class SIMDMath {
|
||||
|
||||
__destroy_into_raw() {
|
||||
const ptr = this.__wbg_ptr;
|
||||
this.__wbg_ptr = 0;
|
||||
SIMDMathFinalization.unregister(this);
|
||||
return ptr;
|
||||
}
|
||||
|
||||
free() {
|
||||
const ptr = this.__destroy_into_raw();
|
||||
wasm.__wbg_simdmath_free(ptr, 0);
|
||||
}
|
||||
constructor() {
|
||||
const ret = wasm.simdmath_new();
|
||||
this.__wbg_ptr = ret >>> 0;
|
||||
SIMDMathFinalization.register(this, this.__wbg_ptr, this);
|
||||
return this;
|
||||
}
|
||||
/**
|
||||
* @param {Float32Array} vec_a
|
||||
* @param {Float32Array} vec_b
|
||||
* @returns {number}
|
||||
*/
|
||||
cosine_similarity(vec_a, vec_b) {
|
||||
const ptr0 = passArrayF32ToWasm0(vec_a, wasm.__wbindgen_malloc);
|
||||
const len0 = WASM_VECTOR_LEN;
|
||||
const ptr1 = passArrayF32ToWasm0(vec_b, wasm.__wbindgen_malloc);
|
||||
const len1 = WASM_VECTOR_LEN;
|
||||
const ret = wasm.simdmath_cosine_similarity(this.__wbg_ptr, ptr0, len0, ptr1, len1);
|
||||
return ret;
|
||||
}
|
||||
/**
|
||||
* @param {Float32Array} vectors
|
||||
* @param {Float32Array} query
|
||||
* @param {number} vector_dim
|
||||
* @returns {Float32Array}
|
||||
*/
|
||||
batch_similarity(vectors, query, vector_dim) {
|
||||
const ptr0 = passArrayF32ToWasm0(vectors, wasm.__wbindgen_malloc);
|
||||
const len0 = WASM_VECTOR_LEN;
|
||||
const ptr1 = passArrayF32ToWasm0(query, wasm.__wbindgen_malloc);
|
||||
const len1 = WASM_VECTOR_LEN;
|
||||
const ret = wasm.simdmath_batch_similarity(this.__wbg_ptr, ptr0, len0, ptr1, len1, vector_dim);
|
||||
var v3 = getArrayF32FromWasm0(ret[0], ret[1]).slice();
|
||||
wasm.__wbindgen_free(ret[0], ret[1] * 4, 4);
|
||||
return v3;
|
||||
}
|
||||
/**
|
||||
* @param {Float32Array} vectors_a
|
||||
* @param {Float32Array} vectors_b
|
||||
* @param {number} vector_dim
|
||||
* @returns {Float32Array}
|
||||
*/
|
||||
similarity_matrix(vectors_a, vectors_b, vector_dim) {
|
||||
const ptr0 = passArrayF32ToWasm0(vectors_a, wasm.__wbindgen_malloc);
|
||||
const len0 = WASM_VECTOR_LEN;
|
||||
const ptr1 = passArrayF32ToWasm0(vectors_b, wasm.__wbindgen_malloc);
|
||||
const len1 = WASM_VECTOR_LEN;
|
||||
const ret = wasm.simdmath_similarity_matrix(this.__wbg_ptr, ptr0, len0, ptr1, len1, vector_dim);
|
||||
var v3 = getArrayF32FromWasm0(ret[0], ret[1]).slice();
|
||||
wasm.__wbindgen_free(ret[0], ret[1] * 4, 4);
|
||||
return v3;
|
||||
}
|
||||
}
|
||||
|
||||
async function __wbg_load(module, imports) {
|
||||
if (typeof Response === 'function' && module instanceof Response) {
|
||||
if (typeof WebAssembly.instantiateStreaming === 'function') {
|
||||
try {
|
||||
return await WebAssembly.instantiateStreaming(module, imports);
|
||||
|
||||
} catch (e) {
|
||||
if (module.headers.get('Content-Type') != 'application/wasm') {
|
||||
console.warn("`WebAssembly.instantiateStreaming` failed because your server does not serve Wasm with `application/wasm` MIME type. Falling back to `WebAssembly.instantiate` which is slower. Original error:\n", e);
|
||||
|
||||
} else {
|
||||
throw e;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const bytes = await module.arrayBuffer();
|
||||
return await WebAssembly.instantiate(bytes, imports);
|
||||
|
||||
} else {
|
||||
const instance = await WebAssembly.instantiate(module, imports);
|
||||
|
||||
if (instance instanceof WebAssembly.Instance) {
|
||||
return { instance, module };
|
||||
|
||||
} else {
|
||||
return instance;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
function __wbg_get_imports() {
|
||||
const imports = {};
|
||||
imports.wbg = {};
|
||||
imports.wbg.__wbg_error_7534b8e9a36f1ab4 = function(arg0, arg1) {
|
||||
let deferred0_0;
|
||||
let deferred0_1;
|
||||
try {
|
||||
deferred0_0 = arg0;
|
||||
deferred0_1 = arg1;
|
||||
console.error(getStringFromWasm0(arg0, arg1));
|
||||
} finally {
|
||||
wasm.__wbindgen_free(deferred0_0, deferred0_1, 1);
|
||||
}
|
||||
};
|
||||
imports.wbg.__wbg_new_8a6f238a6ece86ea = function() {
|
||||
const ret = new Error();
|
||||
return ret;
|
||||
};
|
||||
imports.wbg.__wbg_stack_0ed75d68575b0f3c = function(arg0, arg1) {
|
||||
const ret = arg1.stack;
|
||||
const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_malloc, wasm.__wbindgen_realloc);
|
||||
const len1 = WASM_VECTOR_LEN;
|
||||
getDataViewMemory0().setInt32(arg0 + 4 * 1, len1, true);
|
||||
getDataViewMemory0().setInt32(arg0 + 4 * 0, ptr1, true);
|
||||
};
|
||||
imports.wbg.__wbindgen_init_externref_table = function() {
|
||||
const table = wasm.__wbindgen_export_3;
|
||||
const offset = table.grow(4);
|
||||
table.set(0, undefined);
|
||||
table.set(offset + 0, undefined);
|
||||
table.set(offset + 1, null);
|
||||
table.set(offset + 2, true);
|
||||
table.set(offset + 3, false);
|
||||
;
|
||||
};
|
||||
imports.wbg.__wbindgen_throw = function(arg0, arg1) {
|
||||
throw new Error(getStringFromWasm0(arg0, arg1));
|
||||
};
|
||||
|
||||
return imports;
|
||||
}
|
||||
|
||||
function __wbg_init_memory(imports, memory) {
|
||||
|
||||
}
|
||||
|
||||
function __wbg_finalize_init(instance, module) {
|
||||
wasm = instance.exports;
|
||||
__wbg_init.__wbindgen_wasm_module = module;
|
||||
cachedDataViewMemory0 = null;
|
||||
cachedFloat32ArrayMemory0 = null;
|
||||
cachedUint8ArrayMemory0 = null;
|
||||
|
||||
|
||||
wasm.__wbindgen_start();
|
||||
return wasm;
|
||||
}
|
||||
|
||||
function initSync(module) {
|
||||
if (wasm !== undefined) return wasm;
|
||||
|
||||
|
||||
if (typeof module !== 'undefined') {
|
||||
if (Object.getPrototypeOf(module) === Object.prototype) {
|
||||
({module} = module)
|
||||
} else {
|
||||
console.warn('using deprecated parameters for `initSync()`; pass a single object instead')
|
||||
}
|
||||
}
|
||||
|
||||
const imports = __wbg_get_imports();
|
||||
|
||||
__wbg_init_memory(imports);
|
||||
|
||||
if (!(module instanceof WebAssembly.Module)) {
|
||||
module = new WebAssembly.Module(module);
|
||||
}
|
||||
|
||||
const instance = new WebAssembly.Instance(module, imports);
|
||||
|
||||
return __wbg_finalize_init(instance, module);
|
||||
}
|
||||
|
||||
async function __wbg_init(module_or_path) {
|
||||
if (wasm !== undefined) return wasm;
|
||||
|
||||
|
||||
if (typeof module_or_path !== 'undefined') {
|
||||
if (Object.getPrototypeOf(module_or_path) === Object.prototype) {
|
||||
({module_or_path} = module_or_path)
|
||||
} else {
|
||||
console.warn('using deprecated parameters for the initialization function; pass a single object instead')
|
||||
}
|
||||
}
|
||||
|
||||
if (typeof module_or_path === 'undefined') {
|
||||
module_or_path = new URL('simd_math_bg.wasm', import.meta.url);
|
||||
}
|
||||
const imports = __wbg_get_imports();
|
||||
|
||||
if (typeof module_or_path === 'string' || (typeof Request === 'function' && module_or_path instanceof Request) || (typeof URL === 'function' && module_or_path instanceof URL)) {
|
||||
module_or_path = fetch(module_or_path);
|
||||
}
|
||||
|
||||
__wbg_init_memory(imports);
|
||||
|
||||
const { instance, module } = await __wbg_load(await module_or_path, imports);
|
||||
|
||||
return __wbg_finalize_init(instance, module);
|
||||
}
|
||||
|
||||
export { initSync };
|
||||
export default __wbg_init;
|
||||
Binary file not shown.
@@ -0,0 +1,384 @@
|
||||
/* eslint-disable */
|
||||
// js/similarity.worker.js
|
||||
importScripts('../libs/ort.min.js'); // 调整路径以匹配您的文件结构
|
||||
|
||||
// 全局Worker状态
|
||||
let session = null;
|
||||
let modelPathInternal = null;
|
||||
let ortEnvConfigured = false;
|
||||
let sessionOptions = null;
|
||||
let modelInputNames = null; // 存储模型的输入名称
|
||||
|
||||
// 复用的 TypedArray 缓冲区，减少内存分配
|
||||
let reusableBuffers = {
|
||||
inputIds: null,
|
||||
attentionMask: null,
|
||||
tokenTypeIds: null,
|
||||
};
|
||||
|
||||
// 性能统计
|
||||
let workerStats = {
|
||||
totalInferences: 0,
|
||||
totalInferenceTime: 0,
|
||||
averageInferenceTime: 0,
|
||||
memoryAllocations: 0,
|
||||
};
|
||||
|
||||
// 配置 ONNX Runtime 环境 (仅一次)
|
||||
function configureOrtEnv(numThreads = 1, executionProviders = ['wasm']) {
|
||||
if (ortEnvConfigured) return;
|
||||
try {
|
||||
ort.env.wasm.numThreads = numThreads;
|
||||
ort.env.wasm.simd = true; // 尽可能启用SIMD
|
||||
ort.env.wasm.proxy = false; // 在Worker中，通常不需要代理
|
||||
ort.env.logLevel = 'warning'; // 'verbose', 'info', 'warning', 'error', 'fatal'
|
||||
ortEnvConfigured = true;
|
||||
|
||||
sessionOptions = {
|
||||
executionProviders: executionProviders,
|
||||
graphOptimizationLevel: 'all',
|
||||
enableCpuMemArena: true,
|
||||
enableMemPattern: true,
|
||||
// executionMode: 'sequential' // 在worker内部通常是顺序执行一个任务
|
||||
};
|
||||
} catch (error) {
|
||||
console.error('Worker: Failed to configure ORT environment', error);
|
||||
throw error; // 抛出错误，让主线程知道
|
||||
}
|
||||
}
|
||||
|
||||
async function initializeModel(modelPathOrData, numThreads, executionProviders) {
|
||||
try {
|
||||
configureOrtEnv(numThreads, executionProviders); // 确保环境已配置
|
||||
|
||||
if (!modelPathOrData) {
|
||||
throw new Error('Worker: Model path or data is not provided.');
|
||||
}
|
||||
|
||||
// Check if input is ArrayBuffer (cached model data) or string (URL path)
|
||||
if (modelPathOrData instanceof ArrayBuffer) {
|
||||
console.log(
|
||||
`Worker: Initializing model from cached ArrayBuffer (${modelPathOrData.byteLength} bytes)`,
|
||||
);
|
||||
session = await ort.InferenceSession.create(modelPathOrData, sessionOptions);
|
||||
modelPathInternal = '[Cached ArrayBuffer]'; // For debugging purposes
|
||||
} else {
|
||||
console.log(`Worker: Initializing model from URL: ${modelPathOrData}`);
|
||||
modelPathInternal = modelPathOrData; // 存储模型路径以备调试或重载（如果需要）
|
||||
session = await ort.InferenceSession.create(modelPathInternal, sessionOptions);
|
||||
}
|
||||
|
||||
// 获取模型的输入名称，用于判断是否需要token_type_ids
|
||||
modelInputNames = session.inputNames;
|
||||
console.log(`Worker: ONNX session created successfully for model: ${modelPathInternal}`);
|
||||
console.log(`Worker: Model input names:`, modelInputNames);
|
||||
|
||||
return { status: 'success', message: 'Model initialized' };
|
||||
} catch (error) {
|
||||
console.error(`Worker: Model initialization failed:`, error);
|
||||
session = null; // 清理session以防部分初始化
|
||||
modelInputNames = null;
|
||||
// 将错误信息序列化，因为Error对象本身可能无法直接postMessage
|
||||
throw new Error(`Worker: Model initialization failed - ${error.message}`);
|
||||
}
|
||||
}
|
||||
|
||||
// 优化的缓冲区管理函数
|
||||
function getOrCreateBuffer(name, requiredLength, type = BigInt64Array) {
|
||||
if (!reusableBuffers[name] || reusableBuffers[name].length < requiredLength) {
|
||||
reusableBuffers[name] = new type(requiredLength);
|
||||
workerStats.memoryAllocations++;
|
||||
}
|
||||
return reusableBuffers[name];
|
||||
}
|
||||
|
||||
// 优化的批处理推理函数
|
||||
async function runBatchInference(batchData) {
|
||||
if (!session) {
|
||||
throw new Error("Worker: Session not initialized. Call 'initializeModel' first.");
|
||||
}
|
||||
|
||||
const startTime = performance.now();
|
||||
|
||||
try {
|
||||
const feeds = {};
|
||||
const batchSize = batchData.dims.input_ids[0];
|
||||
const seqLength = batchData.dims.input_ids[1];
|
||||
|
||||
// 优化：复用缓冲区，减少内存分配
|
||||
const inputIdsLength = batchData.input_ids.length;
|
||||
const attentionMaskLength = batchData.attention_mask.length;
|
||||
|
||||
// 复用或创建 BigInt64Array 缓冲区
|
||||
const inputIdsBuffer = getOrCreateBuffer('inputIds', inputIdsLength);
|
||||
const attentionMaskBuffer = getOrCreateBuffer('attentionMask', attentionMaskLength);
|
||||
|
||||
// 批量填充数据（避免 map 操作）
|
||||
for (let i = 0; i < inputIdsLength; i++) {
|
||||
inputIdsBuffer[i] = BigInt(batchData.input_ids[i]);
|
||||
}
|
||||
for (let i = 0; i < attentionMaskLength; i++) {
|
||||
attentionMaskBuffer[i] = BigInt(batchData.attention_mask[i]);
|
||||
}
|
||||
|
||||
feeds['input_ids'] = new ort.Tensor(
|
||||
'int64',
|
||||
inputIdsBuffer.slice(0, inputIdsLength),
|
||||
batchData.dims.input_ids,
|
||||
);
|
||||
feeds['attention_mask'] = new ort.Tensor(
|
||||
'int64',
|
||||
attentionMaskBuffer.slice(0, attentionMaskLength),
|
||||
batchData.dims.attention_mask,
|
||||
);
|
||||
|
||||
// 处理 token_type_ids - 只有当模型需要时才提供
|
||||
if (modelInputNames && modelInputNames.includes('token_type_ids')) {
|
||||
if (batchData.token_type_ids && batchData.dims.token_type_ids) {
|
||||
const tokenTypeIdsLength = batchData.token_type_ids.length;
|
||||
const tokenTypeIdsBuffer = getOrCreateBuffer('tokenTypeIds', tokenTypeIdsLength);
|
||||
|
||||
for (let i = 0; i < tokenTypeIdsLength; i++) {
|
||||
tokenTypeIdsBuffer[i] = BigInt(batchData.token_type_ids[i]);
|
||||
}
|
||||
|
||||
feeds['token_type_ids'] = new ort.Tensor(
|
||||
'int64',
|
||||
tokenTypeIdsBuffer.slice(0, tokenTypeIdsLength),
|
||||
batchData.dims.token_type_ids,
|
||||
);
|
||||
} else {
|
||||
// 创建默认的全零 token_type_ids
|
||||
const tokenTypeIdsBuffer = getOrCreateBuffer('tokenTypeIds', inputIdsLength);
|
||||
tokenTypeIdsBuffer.fill(0n, 0, inputIdsLength);
|
||||
|
||||
feeds['token_type_ids'] = new ort.Tensor(
|
||||
'int64',
|
||||
tokenTypeIdsBuffer.slice(0, inputIdsLength),
|
||||
batchData.dims.input_ids,
|
||||
);
|
||||
}
|
||||
} else {
|
||||
console.log('Worker: Skipping token_type_ids as model does not require it');
|
||||
}
|
||||
|
||||
// 执行批处理推理
|
||||
const results = await session.run(feeds);
|
||||
const outputTensor = results.last_hidden_state || results[Object.keys(results)[0]];
|
||||
|
||||
// 使用 Transferable Objects 优化数据传输
|
||||
const outputData = new Float32Array(outputTensor.data);
|
||||
|
||||
// 更新统计信息
|
||||
workerStats.totalInferences += batchSize; // 批处理计算多个推理
|
||||
const inferenceTime = performance.now() - startTime;
|
||||
workerStats.totalInferenceTime += inferenceTime;
|
||||
workerStats.averageInferenceTime = workerStats.totalInferenceTime / workerStats.totalInferences;
|
||||
|
||||
return {
|
||||
status: 'success',
|
||||
output: {
|
||||
data: outputData,
|
||||
dims: outputTensor.dims,
|
||||
batchSize: batchSize,
|
||||
seqLength: seqLength,
|
||||
},
|
||||
transferList: [outputData.buffer],
|
||||
stats: {
|
||||
inferenceTime,
|
||||
totalInferences: workerStats.totalInferences,
|
||||
averageInferenceTime: workerStats.averageInferenceTime,
|
||||
memoryAllocations: workerStats.memoryAllocations,
|
||||
batchSize: batchSize,
|
||||
},
|
||||
};
|
||||
} catch (error) {
|
||||
console.error('Worker: Batch inference failed:', error);
|
||||
throw new Error(`Worker: Batch inference failed - ${error.message}`);
|
||||
}
|
||||
}
|
||||
|
||||
async function runInference(inputData) {
|
||||
if (!session) {
|
||||
throw new Error("Worker: Session not initialized. Call 'initializeModel' first.");
|
||||
}
|
||||
|
||||
const startTime = performance.now();
|
||||
|
||||
try {
|
||||
const feeds = {};
|
||||
|
||||
// 优化：复用缓冲区，减少内存分配
|
||||
const inputIdsLength = inputData.input_ids.length;
|
||||
const attentionMaskLength = inputData.attention_mask.length;
|
||||
|
||||
// 复用或创建 BigInt64Array 缓冲区
|
||||
const inputIdsBuffer = getOrCreateBuffer('inputIds', inputIdsLength);
|
||||
const attentionMaskBuffer = getOrCreateBuffer('attentionMask', attentionMaskLength);
|
||||
|
||||
// 填充数据（避免 map 操作）
|
||||
for (let i = 0; i < inputIdsLength; i++) {
|
||||
inputIdsBuffer[i] = BigInt(inputData.input_ids[i]);
|
||||
}
|
||||
for (let i = 0; i < attentionMaskLength; i++) {
|
||||
attentionMaskBuffer[i] = BigInt(inputData.attention_mask[i]);
|
||||
}
|
||||
|
||||
feeds['input_ids'] = new ort.Tensor(
|
||||
'int64',
|
||||
inputIdsBuffer.slice(0, inputIdsLength),
|
||||
inputData.dims.input_ids,
|
||||
);
|
||||
feeds['attention_mask'] = new ort.Tensor(
|
||||
'int64',
|
||||
attentionMaskBuffer.slice(0, attentionMaskLength),
|
||||
inputData.dims.attention_mask,
|
||||
);
|
||||
|
||||
// 处理 token_type_ids - 只有当模型需要时才提供
|
||||
if (modelInputNames && modelInputNames.includes('token_type_ids')) {
|
||||
if (inputData.token_type_ids && inputData.dims.token_type_ids) {
|
||||
const tokenTypeIdsLength = inputData.token_type_ids.length;
|
||||
const tokenTypeIdsBuffer = getOrCreateBuffer('tokenTypeIds', tokenTypeIdsLength);
|
||||
|
||||
for (let i = 0; i < tokenTypeIdsLength; i++) {
|
||||
tokenTypeIdsBuffer[i] = BigInt(inputData.token_type_ids[i]);
|
||||
}
|
||||
|
||||
feeds['token_type_ids'] = new ort.Tensor(
|
||||
'int64',
|
||||
tokenTypeIdsBuffer.slice(0, tokenTypeIdsLength),
|
||||
inputData.dims.token_type_ids,
|
||||
);
|
||||
} else {
|
||||
// 创建默认的全零 token_type_ids
|
||||
const tokenTypeIdsBuffer = getOrCreateBuffer('tokenTypeIds', inputIdsLength);
|
||||
tokenTypeIdsBuffer.fill(0n, 0, inputIdsLength);
|
||||
|
||||
feeds['token_type_ids'] = new ort.Tensor(
|
||||
'int64',
|
||||
tokenTypeIdsBuffer.slice(0, inputIdsLength),
|
||||
inputData.dims.input_ids,
|
||||
);
|
||||
}
|
||||
} else {
|
||||
console.log('Worker: Skipping token_type_ids as model does not require it');
|
||||
}
|
||||
|
||||
const results = await session.run(feeds);
|
||||
const outputTensor = results.last_hidden_state || results[Object.keys(results)[0]];
|
||||
|
||||
// 使用 Transferable Objects 优化数据传输
|
||||
const outputData = new Float32Array(outputTensor.data);
|
||||
|
||||
// 更新统计信息
|
||||
workerStats.totalInferences++;
|
||||
const inferenceTime = performance.now() - startTime;
|
||||
workerStats.totalInferenceTime += inferenceTime;
|
||||
workerStats.averageInferenceTime = workerStats.totalInferenceTime / workerStats.totalInferences;
|
||||
|
||||
return {
|
||||
status: 'success',
|
||||
output: {
|
||||
data: outputData, // 直接返回 Float32Array
|
||||
dims: outputTensor.dims,
|
||||
},
|
||||
transferList: [outputData.buffer], // 标记为可转移对象
|
||||
stats: {
|
||||
inferenceTime,
|
||||
totalInferences: workerStats.totalInferences,
|
||||
averageInferenceTime: workerStats.averageInferenceTime,
|
||||
memoryAllocations: workerStats.memoryAllocations,
|
||||
},
|
||||
};
|
||||
} catch (error) {
|
||||
console.error('Worker: Inference failed:', error);
|
||||
throw new Error(`Worker: Inference failed - ${error.message}`);
|
||||
}
|
||||
}
|
||||
|
||||
self.onmessage = async (event) => {
|
||||
const { id, type, payload } = event.data;
|
||||
|
||||
try {
|
||||
switch (type) {
|
||||
case 'init':
|
||||
// Support both modelPath (URL string) and modelData (ArrayBuffer)
|
||||
const modelInput = payload.modelData || payload.modelPath;
|
||||
await initializeModel(modelInput, payload.numThreads, payload.executionProviders);
|
||||
self.postMessage({ id, type: 'init_complete', status: 'success' });
|
||||
break;
|
||||
case 'infer':
|
||||
const result = await runInference(payload);
|
||||
// 使用 Transferable Objects 优化数据传输
|
||||
self.postMessage(
|
||||
{
|
||||
id,
|
||||
type: 'infer_complete',
|
||||
status: 'success',
|
||||
payload: result.output,
|
||||
stats: result.stats,
|
||||
},
|
||||
result.transferList || [],
|
||||
);
|
||||
break;
|
||||
case 'batchInfer':
|
||||
const batchResult = await runBatchInference(payload);
|
||||
// 使用 Transferable Objects 优化数据传输
|
||||
self.postMessage(
|
||||
{
|
||||
id,
|
||||
type: 'batchInfer_complete',
|
||||
status: 'success',
|
||||
payload: batchResult.output,
|
||||
stats: batchResult.stats,
|
||||
},
|
||||
batchResult.transferList || [],
|
||||
);
|
||||
break;
|
||||
case 'getStats':
|
||||
self.postMessage({
|
||||
id,
|
||||
type: 'stats_complete',
|
||||
status: 'success',
|
||||
payload: workerStats,
|
||||
});
|
||||
break;
|
||||
case 'clearBuffers':
|
||||
// 清理缓冲区，释放内存
|
||||
reusableBuffers = {
|
||||
inputIds: null,
|
||||
attentionMask: null,
|
||||
tokenTypeIds: null,
|
||||
};
|
||||
workerStats.memoryAllocations = 0;
|
||||
self.postMessage({
|
||||
id,
|
||||
type: 'clear_complete',
|
||||
status: 'success',
|
||||
payload: { message: 'Buffers cleared' },
|
||||
});
|
||||
break;
|
||||
default:
|
||||
console.warn(`Worker: Unknown message type: ${type}`);
|
||||
self.postMessage({
|
||||
id,
|
||||
type: 'error',
|
||||
status: 'error',
|
||||
payload: { message: `Unknown message type: ${type}` },
|
||||
});
|
||||
}
|
||||
} catch (error) {
|
||||
// 确保将错误作为普通对象发送，因为Error对象本身可能无法正确序列化
|
||||
self.postMessage({
|
||||
id,
|
||||
type: `${type}_error`, // 如 'init_error' 或 'infer_error'
|
||||
status: 'error',
|
||||
payload: {
|
||||
message: error.message,
|
||||
stack: error.stack, // 可选，用于调试
|
||||
name: error.name,
|
||||
},
|
||||
});
|
||||
}
|
||||
};
|
||||
Reference in New Issue
Block a user