clustering-tfjs/dist/tf-adapter.browser.js

High-performance TypeScript clustering algorithms (K-Means, Spectral, Agglomerative) with TensorFlow.js acceleration and scikit-learn compatibility

"use strict";
/**
 * Browser-specific TensorFlow.js adapter
 *
 * This module is used when building for browser environments.
 * It expects users to have loaded @tensorflow/tfjs separately.
 */
Object.defineProperty(exports, "__esModule", { value: true });
exports.mean = exports.norm = exports.transpose = exports.outerProduct = exports.dot = exports.matMul = exports.softmax = exports.prelu = exports.leakyRelu = exports.selu = exports.relu = exports.elu = exports.tanh = exports.cosh = exports.sinh = exports.atan = exports.acos = exports.asin = exports.tan = exports.cos = exports.sin = exports.ceil = exports.floor = exports.round = exports.sign = exports.neg = exports.abs = exports.square = exports.sqrt = exports.pow = exports.div = exports.mul = exports.sub = exports.add = exports.linspace = exports.range = exports.fill = exports.onesLike = exports.zerosLike = exports.ones = exports.zeros = exports.scalar = exports.variable = exports.tensor6d = exports.tensor5d = exports.tensor4d = exports.tensor3d = exports.tensor2d = exports.tensor1d = exports.tensor = void 0;
exports.Tensor = exports.scatterND = exports.topk = exports.variableGrads = exports.valueAndGrads = exports.valueAndGrad = exports.customGrad = exports.grads = exports.grad = exports.getBackend = exports.setBackend = exports.ready = exports.env = exports.backend = exports.memory = exports.keep = exports.dispose = exports.tidy = exports.unique = exports.diag = exports.eye = exports.where = exports.logicalNot = exports.logicalOr = exports.logicalAnd = exports.lessEqual = exports.less = exports.greaterEqual = exports.greater = exports.equal = exports.expandDims = exports.squeeze = exports.reshape = exports.cast = exports.reverse = exports.gather = exports.split = exports.unstack = exports.stack = exports.concat = exports.slice = exports.argMin = exports.argMax = exports.any = exports.all = exports.cumsum = exports.prod = exports.max = exports.min = exports.sum = void 0;
exports.randomGamma = exports.multinomial = exports.randomUniform = exports.randomNormal = exports.booleanMaskAsync = exports.irfft = exports.rfft = exports.ifft = exports.fft = exports.imag = exports.real = exports.complex = exports.avgPool3d = exports.maxPool3d = exports.pool = exports.avgPool = exports.maxPool = exports.conv3dTranspose = exports.conv3d = exports.conv2dTranspose = exports.conv2d = exports.conv1d = exports.depthwiseConv2d = exports.separableConv2d = exports.localResponseNormalization = exports.batchNorm = exports.logicalXor = exports.notEqual = exports.pad = exports.print = exports.clone = exports.minimum = exports.maximum = exports.exp = exports.log = exports.sigmoid = exports.io = exports.util = exports.browser = exports.data = exports.train = exports.losses = exports.linalg = exports.image = void 0;
// Function to get tf from global
function getTf() {
    if (typeof window !== 'undefined' && window.tf) {
        return window.tf;
    }
    throw new Error('TensorFlow.js not found. Please load it before using this library.');
}
// Re-export all tf functions, properly typed
const tf = new Proxy({}, {
    get(_target, prop) {
        const tfInstance = getTf();
        return tfInstance[prop];
    }
});
// Export commonly used functions for better tree-shaking
const tensor = (...args) => tf.tensor(...args);
exports.tensor = tensor;
const tensor1d = (...args) => tf.tensor1d(...args);
exports.tensor1d = tensor1d;
const tensor2d = (...args) => tf.tensor2d(...args);
exports.tensor2d = tensor2d;
const tensor3d = (...args) => tf.tensor3d(...args);
exports.tensor3d = tensor3d;
const tensor4d = (...args) => tf.tensor4d(...args);
exports.tensor4d = tensor4d;
const tensor5d = (...args) => tf.tensor5d(...args);
exports.tensor5d = tensor5d;
const tensor6d = (...args) => tf.tensor6d(...args);
exports.tensor6d = tensor6d;
const variable = (...args) => tf.variable(...args);
exports.variable = variable;
const scalar = (...args) => tf.scalar(...args);
exports.scalar = scalar;
const zeros = (...args) => tf.zeros(...args);
exports.zeros = zeros;
const ones = (...args) => tf.ones(...args);
exports.ones = ones;
const zerosLike = (...args) => tf.zerosLike(...args);
exports.zerosLike = zerosLike;
const onesLike = (...args) => tf.onesLike(...args);
exports.onesLike = onesLike;
const fill = (...args) => tf.fill(...args);
exports.fill = fill;
const range = (...args) => tf.range(...args);
exports.range = range;
const linspace = (...args) => tf.linspace(...args);
exports.linspace = linspace;
// Math operations
const add = (...args) => tf.add(...args);
exports.add = add;
const sub = (...args) => tf.sub(...args);
exports.sub = sub;
const mul = (...args) => tf.mul(...args);
exports.mul = mul;
const div = (...args) => tf.div(...args);
exports.div = div;
const pow = (...args) => tf.pow(...args);
exports.pow = pow;
const sqrt = (...args) => tf.sqrt(...args);
exports.sqrt = sqrt;
const square = (...args) => tf.square(...args);
exports.square = square;
const abs = (...args) => tf.abs(...args);
exports.abs = abs;
const neg = (...args) => tf.neg(...args);
exports.neg = neg;
const sign = (...args) => tf.sign(...args);
exports.sign = sign;
const round = (...args) => tf.round(...args);
exports.round = round;
const floor = (...args) => tf.floor(...args);
exports.floor = floor;
const ceil = (...args) => tf.ceil(...args);
exports.ceil = ceil;
const sin = (...args) => tf.sin(...args);
exports.sin = sin;
const cos = (...args) => tf.cos(...args);
exports.cos = cos;
const tan = (...args) => tf.tan(...args);
exports.tan = tan;
const asin = (...args) => tf.asin(...args);
exports.asin = asin;
const acos = (...args) => tf.acos(...args);
exports.acos = acos;
const atan = (...args) => tf.atan(...args);
exports.atan = atan;
const sinh = (...args) => tf.sinh(...args);
exports.sinh = sinh;
const cosh = (...args) => tf.cosh(...args);
exports.cosh = cosh;
const tanh = (...args) => tf.tanh(...args);
exports.tanh = tanh;
const elu = (...args) => tf.elu(...args);
exports.elu = elu;
const relu = (...args) => tf.relu(...args);
exports.relu = relu;
const selu = (...args) => tf.selu(...args);
exports.selu = selu;
const leakyRelu = (...args) => tf.leakyRelu(...args);
exports.leakyRelu = leakyRelu;
const prelu = (...args) => tf.prelu(...args);
exports.prelu = prelu;
const softmax = (...args) => tf.softmax(...args);
exports.softmax = softmax;
// Linear algebra
const matMul = (...args) => tf.matMul(...args);
exports.matMul = matMul;
const dot = (...args) => tf.dot(...args);
exports.dot = dot;
const outerProduct = (...args) => tf.outerProduct(...args);
exports.outerProduct = outerProduct;
const transpose = (...args) => tf.transpose(...args);
exports.transpose = transpose;
const norm = (...args) => tf.norm(...args);
exports.norm = norm;
// Reduction
const mean = (...args) => tf.mean(...args);
exports.mean = mean;
const sum = (...args) => tf.sum(...args);
exports.sum = sum;
const min = (...args) => tf.min(...args);
exports.min = min;
const max = (...args) => tf.max(...args);
exports.max = max;
const prod = (...args) => tf.prod(...args);
exports.prod = prod;
const cumsum = (...args) => tf.cumsum(...args);
exports.cumsum = cumsum;
const all = (...args) => tf.all(...args);
exports.all = all;
const any = (...args) => tf.any(...args);
exports.any = any;
const argMax = (...args) => tf.argMax(...args);
exports.argMax = argMax;
const argMin = (...args) => tf.argMin(...args);
exports.argMin = argMin;
// Manipulation
const slice = (...args) => tf.slice(...args);
exports.slice = slice;
const concat = (...args) => tf.concat(...args);
exports.concat = concat;
const stack = (...args) => tf.stack(...args);
exports.stack = stack;
const unstack = (...args) => tf.unstack(...args);
exports.unstack = unstack;
const split = (...args) => tf.split(...args);
exports.split = split;
const gather = (...args) => tf.gather(...args);
exports.gather = gather;
const reverse = (...args) => tf.reverse(...args);
exports.reverse = reverse;
const cast = (...args) => tf.cast(...args);
exports.cast = cast;
const reshape = (...args) => tf.reshape(...args);
exports.reshape = reshape;
const squeeze = (...args) => tf.squeeze(...args);
exports.squeeze = squeeze;
const expandDims = (...args) => tf.expandDims(...args);
exports.expandDims = expandDims;
// Logical
const equal = (...args) => tf.equal(...args);
exports.equal = equal;
const greater = (...args) => tf.greater(...args);
exports.greater = greater;
const greaterEqual = (...args) => tf.greaterEqual(...args);
exports.greaterEqual = greaterEqual;
const less = (...args) => tf.less(...args);
exports.less = less;
const lessEqual = (...args) => tf.lessEqual(...args);
exports.lessEqual = lessEqual;
const logicalAnd = (...args) => tf.logicalAnd(...args);
exports.logicalAnd = logicalAnd;
const logicalOr = (...args) => tf.logicalOr(...args);
exports.logicalOr = logicalOr;
const logicalNot = (...args) => tf.logicalNot(...args);
exports.logicalNot = logicalNot;
const where = (...args) => tf.where(...args);
exports.where = where;
// Special tensors
const eye = (...args) => tf.eye(...args);
exports.eye = eye;
const diag = (...args) => tf.diag(...args);
exports.diag = diag;
const unique = (...args) => tf.unique(...args);
exports.unique = unique;
// Utility
const tidy = (...args) => tf.tidy(...args);
exports.tidy = tidy;
const dispose = (...args) => tf.dispose(...args);
exports.dispose = dispose;
const keep = (...args) => tf.keep(...args);
exports.keep = keep;
const memory = () => tf.memory();
exports.memory = memory;
const backend = () => tf.backend();
exports.backend = backend;
const env = () => tf.env();
exports.env = env;
const ready = () => tf.ready();
exports.ready = ready;
const setBackend = (...args) => tf.setBackend(...args);
exports.setBackend = setBackend;
const getBackend = () => tf.getBackend();
exports.getBackend = getBackend;
// Advanced
const grad = (...args) => tf.grad(...args);
exports.grad = grad;
const grads = (...args) => tf.grads(...args);
exports.grads = grads;
const customGrad = (...args) => tf.customGrad(...args);
exports.customGrad = customGrad;
const valueAndGrad = (...args) => tf.valueAndGrad(...args);
exports.valueAndGrad = valueAndGrad;
const valueAndGrads = (...args) => tf.valueAndGrads(...args);
exports.valueAndGrads = valueAndGrads;
const variableGrads = (...args) => tf.variableGrads(...args);
exports.variableGrads = variableGrads;
// Scatter
const topk = (...args) => tf.topk(...args);
exports.topk = topk;
const scatterND = (...args) => tf.scatterND(...args);
exports.scatterND = scatterND;
// Globals/Types - Access from runtime tf object
const Tensor = () => getTf().Tensor;
exports.Tensor = Tensor;
// Namespaces - return functions to avoid immediate evaluation
const image = () => getTf().image;
exports.image = image;
const linalg = () => getTf().linalg;
exports.linalg = linalg;
const losses = () => getTf().losses;
exports.losses = losses;
const train = () => getTf().train;
exports.train = train;
// data namespace is not in @tensorflow/tfjs-core, only in full tfjs
// Return type is unknown since data namespace types aren't in core
const data = () => {
    const tfInstance = getTf();
    if ('data' in tfInstance) {
        return tfInstance.data;
    }
    throw new Error('TensorFlow.js data API not available. Please load @tensorflow/tfjs instead of @tensorflow/tfjs-core');
};
exports.data = data;
const browser = () => getTf().browser;
exports.browser = browser;
const util = () => getTf().util;
exports.util = util;
const io = () => getTf().io;
exports.io = io;
// Additional functions that might be needed - export them
const sigmoid = (...args) => tf.sigmoid(...args);
exports.sigmoid = sigmoid;
const log = (...args) => tf.log(...args);
exports.log = log;
const exp = (...args) => tf.exp(...args);
exports.exp = exp;
const maximum = (...args) => tf.maximum(...args);
exports.maximum = maximum;
const minimum = (...args) => tf.minimum(...args);
exports.minimum = minimum;
const clone = (...args) => tf.clone(...args);
exports.clone = clone;
const print = (...args) => tf.print(...args);
exports.print = print;
const pad = (...args) => tf.pad(...args);
exports.pad = pad;
const notEqual = (...args) => tf.notEqual(...args);
exports.notEqual = notEqual;
const logicalXor = (...args) => tf.logicalXor(...args);
exports.logicalXor = logicalXor;
const batchNorm = (...args) => tf.batchNorm(...args);
exports.batchNorm = batchNorm;
const localResponseNormalization = (...args) => tf.localResponseNormalization(...args);
exports.localResponseNormalization = localResponseNormalization;
const separableConv2d = (...args) => tf.separableConv2d(...args);
exports.separableConv2d = separableConv2d;
const depthwiseConv2d = (...args) => tf.depthwiseConv2d(...args);
exports.depthwiseConv2d = depthwiseConv2d;
const conv1d = (...args) => tf.conv1d(...args);
exports.conv1d = conv1d;
const conv2d = (...args) => tf.conv2d(...args);
exports.conv2d = conv2d;
const conv2dTranspose = (...args) => tf.conv2dTranspose(...args);
exports.conv2dTranspose = conv2dTranspose;
const conv3d = (...args) => tf.conv3d(...args);
exports.conv3d = conv3d;
const conv3dTranspose = (...args) => tf.conv3dTranspose(...args);
exports.conv3dTranspose = conv3dTranspose;
const maxPool = (...args) => tf.maxPool(...args);
exports.maxPool = maxPool;
const avgPool = (...args) => tf.avgPool(...args);
exports.avgPool = avgPool;
const pool = (...args) => tf.pool(...args);
exports.pool = pool;
const maxPool3d = (...args) => tf.maxPool3d(...args);
exports.maxPool3d = maxPool3d;
const avgPool3d = (...args) => tf.avgPool3d(...args);
exports.avgPool3d = avgPool3d;
const complex = (...args) => tf.complex(...args);
exports.complex = complex;
const real = (...args) => tf.real(...args);
exports.real = real;
const imag = (...args) => tf.imag(...args);
exports.imag = imag;
const fft = (...args) => tf.fft(...args);
exports.fft = fft;
const ifft = (...args) => tf.ifft(...args);
exports.ifft = ifft;
const rfft = (...args) => tf.rfft(...args);
exports.rfft = rfft;
const irfft = (...args) => tf.irfft(...args);
exports.irfft = irfft;
const booleanMaskAsync = (...args) => tf.booleanMaskAsync(...args);
exports.booleanMaskAsync = booleanMaskAsync;
const randomNormal = (...args) => tf.randomNormal(...args);
exports.randomNormal = randomNormal;
const randomUniform = (...args) => tf.randomUniform(...args);
exports.randomUniform = randomUniform;
const multinomial = (...args) => tf.multinomial(...args);
exports.multinomial = multinomial;
const randomGamma = (...args) => tf.randomGamma(...args);
exports.randomGamma = randomGamma;
// Default export as namespace
exports.default = {
    // Export all our typed functions
    tensor: exports.tensor,
    tensor1d: exports.tensor1d,
    tensor2d: exports.tensor2d,
    tensor3d: exports.tensor3d,
    tensor4d: exports.tensor4d,
    tensor5d: exports.tensor5d,
    tensor6d: exports.tensor6d,
    variable: exports.variable,
    scalar: exports.scalar,
    zeros: exports.zeros,
    ones: exports.ones,
    zerosLike: exports.zerosLike,
    onesLike: exports.onesLike,
    fill: exports.fill,
    range: exports.range,
    linspace: exports.linspace,
    add: exports.add,
    sub: exports.sub,
    mul: exports.mul,
    div: exports.div,
    pow: exports.pow,
    sqrt: exports.sqrt,
    square: exports.square,
    abs: exports.abs,
    neg: exports.neg,
    sign: exports.sign,
    round: exports.round,
    floor: exports.floor,
    ceil: exports.ceil,
    sin: exports.sin,
    cos: exports.cos,
    tan: exports.tan,
    asin: exports.asin,
    acos: exports.acos,
    atan: exports.atan,
    sinh: exports.sinh,
    cosh: exports.cosh,
    tanh: exports.tanh,
    elu: exports.elu,
    relu: exports.relu,
    selu: exports.selu,
    leakyRelu: exports.leakyRelu,
    prelu: exports.prelu,
    softmax: exports.softmax,
    matMul: exports.matMul,
    dot: exports.dot,
    outerProduct: exports.outerProduct,
    transpose: exports.transpose,
    norm: exports.norm,
    mean: exports.mean,
    sum: exports.sum,
    min: exports.min,
    max: exports.max,
    prod: exports.prod,
    cumsum: exports.cumsum,
    all: exports.all,
    any: exports.any,
    argMax: exports.argMax,
    argMin: exports.argMin,
    slice: exports.slice,
    concat: exports.concat,
    stack: exports.stack,
    unstack: exports.unstack,
    split: exports.split,
    gather: exports.gather,
    reverse: exports.reverse,
    cast: exports.cast,
    reshape: exports.reshape,
    squeeze: exports.squeeze,
    expandDims: exports.expandDims,
    equal: exports.equal,
    greater: exports.greater,
    greaterEqual: exports.greaterEqual,
    less: exports.less,
    lessEqual: exports.lessEqual,
    logicalAnd: exports.logicalAnd,
    logicalOr: exports.logicalOr,
    logicalNot: exports.logicalNot,
    where: exports.where,
    eye: exports.eye,
    diag: exports.diag,
    unique: exports.unique,
    tidy: exports.tidy,
    dispose: exports.dispose,
    keep: exports.keep,
    memory: exports.memory,
    backend: exports.backend,
    env: exports.env,
    ready: exports.ready,
    setBackend: exports.setBackend,
    getBackend: exports.getBackend,
    grad: exports.grad,
    grads: exports.grads,
    customGrad: exports.customGrad,
    valueAndGrad: exports.valueAndGrad,
    valueAndGrads: exports.valueAndGrads,
    variableGrads: exports.variableGrads,
    topk: exports.topk,
    scatterND: exports.scatterND,
    Tensor: exports.Tensor,
    image: exports.image,
    linalg: exports.linalg,
    losses: exports.losses,
    train: exports.train,
    data: exports.data,
    browser: exports.browser,
    util: exports.util,
    io: exports.io,
    // Additional
    sigmoid: exports.sigmoid,
    log: exports.log,
    exp: exports.exp,
    maximum: exports.maximum,
    minimum: exports.minimum,
    clone: exports.clone,
    print: exports.print,
    pad: exports.pad,
    notEqual: exports.notEqual,
    logicalXor: exports.logicalXor,
    batchNorm: exports.batchNorm,
    localResponseNormalization: exports.localResponseNormalization,
    separableConv2d: exports.separableConv2d,
    depthwiseConv2d: exports.depthwiseConv2d,
    conv1d: exports.conv1d,
    conv2d: exports.conv2d,
    conv2dTranspose: exports.conv2dTranspose,
    conv3d: exports.conv3d,
    conv3dTranspose: exports.conv3dTranspose,
    maxPool: exports.maxPool,
    avgPool: exports.avgPool,
    pool: exports.pool,
    maxPool3d: exports.maxPool3d,
    avgPool3d: exports.avgPool3d,
    complex: exports.complex,
    real: exports.real,
    imag: exports.imag,
    fft: exports.fft,
    ifft: exports.ifft,
    rfft: exports.rfft,
    irfft: exports.irfft,
    booleanMaskAsync: exports.booleanMaskAsync,
    randomNormal: exports.randomNormal,
    randomUniform: exports.randomUniform,
    multinomial: exports.multinomial,
    randomGamma: exports.randomGamma,
};