clustering-tfjs/dist/tf-adapter.browser.d.ts

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

/**
 * Browser-specific TensorFlow.js adapter
 *
 * This module is used when building for browser environments.
 * It expects users to have loaded @tensorflow/tfjs separately.
 */
import type * as tfTypes from '@tensorflow/tfjs-core';
declare global {
    interface Window {
        tf: typeof tfTypes;
    }
}
export declare const tensor: typeof tfTypes.tensor;
export declare const tensor1d: typeof tfTypes.tensor1d;
export declare const tensor2d: typeof tfTypes.tensor2d;
export declare const tensor3d: typeof tfTypes.tensor3d;
export declare const tensor4d: typeof tfTypes.tensor4d;
export declare const tensor5d: typeof tfTypes.tensor5d;
export declare const tensor6d: typeof tfTypes.tensor6d;
export declare const variable: typeof tfTypes.variable;
export declare const scalar: typeof tfTypes.scalar;
export declare const zeros: typeof tfTypes.zeros;
export declare const ones: typeof tfTypes.ones;
export declare const zerosLike: typeof tfTypes.zerosLike;
export declare const onesLike: typeof tfTypes.onesLike;
export declare const fill: typeof tfTypes.fill;
export declare const range: typeof tfTypes.range;
export declare const linspace: typeof tfTypes.linspace;
export declare const add: typeof tfTypes.add;
export declare const sub: typeof tfTypes.sub;
export declare const mul: typeof tfTypes.mul;
export declare const div: typeof tfTypes.div;
export declare const pow: typeof tfTypes.pow;
export declare const sqrt: typeof tfTypes.sqrt;
export declare const square: typeof tfTypes.square;
export declare const abs: typeof tfTypes.abs;
export declare const neg: typeof tfTypes.neg;
export declare const sign: typeof tfTypes.sign;
export declare const round: typeof tfTypes.round;
export declare const floor: typeof tfTypes.floor;
export declare const ceil: typeof tfTypes.ceil;
export declare const sin: typeof tfTypes.sin;
export declare const cos: typeof tfTypes.cos;
export declare const tan: typeof tfTypes.tan;
export declare const asin: typeof tfTypes.asin;
export declare const acos: typeof tfTypes.acos;
export declare const atan: typeof tfTypes.atan;
export declare const sinh: typeof tfTypes.sinh;
export declare const cosh: typeof tfTypes.cosh;
export declare const tanh: typeof tfTypes.tanh;
export declare const elu: typeof tfTypes.elu;
export declare const relu: typeof tfTypes.relu;
export declare const selu: typeof tfTypes.selu;
export declare const leakyRelu: typeof tfTypes.leakyRelu;
export declare const prelu: typeof tfTypes.prelu;
export declare const softmax: typeof tfTypes.softmax;
export declare const matMul: typeof tfTypes.matMul;
export declare const dot: typeof tfTypes.dot;
export declare const outerProduct: typeof tfTypes.outerProduct;
export declare const transpose: typeof tfTypes.transpose;
export declare const norm: typeof tfTypes.norm;
export declare const mean: typeof tfTypes.mean;
export declare const sum: typeof tfTypes.sum;
export declare const min: typeof tfTypes.min;
export declare const max: typeof tfTypes.max;
export declare const prod: typeof tfTypes.prod;
export declare const cumsum: typeof tfTypes.cumsum;
export declare const all: typeof tfTypes.all;
export declare const any: typeof tfTypes.any;
export declare const argMax: typeof tfTypes.argMax;
export declare const argMin: typeof tfTypes.argMin;
export declare const slice: typeof tfTypes.slice;
export declare const concat: typeof tfTypes.concat;
export declare const stack: typeof tfTypes.stack;
export declare const unstack: typeof tfTypes.unstack;
export declare const split: typeof tfTypes.split;
export declare const gather: typeof tfTypes.gather;
export declare const reverse: typeof tfTypes.reverse;
export declare const cast: typeof tfTypes.cast;
export declare const reshape: typeof tfTypes.reshape;
export declare const squeeze: typeof tfTypes.squeeze;
export declare const expandDims: typeof tfTypes.expandDims;
export declare const equal: typeof tfTypes.equal;
export declare const greater: typeof tfTypes.greater;
export declare const greaterEqual: typeof tfTypes.greaterEqual;
export declare const less: typeof tfTypes.less;
export declare const lessEqual: typeof tfTypes.lessEqual;
export declare const logicalAnd: typeof tfTypes.logicalAnd;
export declare const logicalOr: typeof tfTypes.logicalOr;
export declare const logicalNot: typeof tfTypes.logicalNot;
export declare const where: typeof tfTypes.where;
export declare const eye: typeof tfTypes.eye;
export declare const diag: typeof tfTypes.diag;
export declare const unique: typeof tfTypes.unique;
export declare const tidy: typeof tfTypes.tidy;
export declare const dispose: typeof tfTypes.dispose;
export declare const keep: typeof tfTypes.keep;
export declare const memory: typeof tfTypes.memory;
export declare const backend: typeof tfTypes.backend;
export declare const env: typeof tfTypes.env;
export declare const ready: typeof tfTypes.ready;
export declare const setBackend: typeof tfTypes.setBackend;
export declare const getBackend: typeof tfTypes.getBackend;
export declare const grad: typeof tfTypes.grad;
export declare const grads: typeof tfTypes.grads;
export declare const customGrad: typeof tfTypes.customGrad;
export declare const valueAndGrad: typeof tfTypes.valueAndGrad;
export declare const valueAndGrads: typeof tfTypes.valueAndGrads;
export declare const variableGrads: typeof tfTypes.variableGrads;
export declare const topk: typeof tfTypes.topk;
export declare const scatterND: typeof tfTypes.scatterND;
export declare const Tensor: () => typeof tfTypes.Tensor;
export declare const image: () => {
    flipLeftRight: (image: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D) => import("@tensorflow/tfjs-core/dist/tensor").Tensor4D;
    grayscaleToRGB: <T extends import("@tensorflow/tfjs-core/dist/tensor").Tensor2D | import("@tensorflow/tfjs-core/dist/tensor").Tensor3D | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D | import("@tensorflow/tfjs-core/dist/tensor").Tensor5D | import("@tensorflow/tfjs-core/dist/tensor").Tensor6D>(image: import("@tensorflow/tfjs-core/dist/types").TensorLike | T) => T;
    resizeNearestNeighbor: <T_1 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor3D | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D>(images: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_1, size: [number, number], alignCorners?: boolean, halfPixelCenters?: boolean) => T_1;
    resizeBilinear: <T_2 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor3D | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D>(images: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_2, size: [number, number], alignCorners?: boolean, halfPixelCenters?: boolean) => T_2;
    rgbToGrayscale: <T_3 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor2D | import("@tensorflow/tfjs-core/dist/tensor").Tensor3D | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D | import("@tensorflow/tfjs-core/dist/tensor").Tensor5D | import("@tensorflow/tfjs-core/dist/tensor").Tensor6D>(image: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_3) => T_3;
    rotateWithOffset: (image: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D, radians: number, fillValue?: number | [number, number, number], center?: number | [number, number]) => import("@tensorflow/tfjs-core/dist/tensor").Tensor4D;
    cropAndResize: (image: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D, boxes: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, boxInd: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D, cropSize: [number, number], method?: "bilinear" | "nearest", extrapolationValue?: number) => import("@tensorflow/tfjs-core/dist/tensor").Tensor4D;
    nonMaxSuppression: (boxes: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, scores: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D, maxOutputSize: number, iouThreshold?: number, scoreThreshold?: number) => import("@tensorflow/tfjs-core/dist/tensor").Tensor1D;
    nonMaxSuppressionAsync: (boxes: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, scores: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D, maxOutputSize: number, iouThreshold?: number, scoreThreshold?: number) => Promise<import("@tensorflow/tfjs-core/dist/tensor").Tensor1D>;
    nonMaxSuppressionWithScore: (boxes: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, scores: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D, maxOutputSize: number, iouThreshold?: number, scoreThreshold?: number, softNmsSigma?: number) => import("@tensorflow/tfjs-core/dist/tensor_types").NamedTensorMap;
    nonMaxSuppressionWithScoreAsync: (boxes: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, scores: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D, maxOutputSize: number, iouThreshold?: number, scoreThreshold?: number, softNmsSigma?: number) => Promise<import("@tensorflow/tfjs-core/dist/tensor_types").NamedTensorMap>;
    nonMaxSuppressionPadded: (boxes: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, scores: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D, maxOutputSize: number, iouThreshold?: number, scoreThreshold?: number, padToMaxOutputSize?: boolean) => import("@tensorflow/tfjs-core/dist/tensor_types").NamedTensorMap;
    nonMaxSuppressionPaddedAsync: (boxes: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, scores: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D, maxOutputSize: number, iouThreshold?: number, scoreThreshold?: number, padToMaxOutputSize?: boolean) => Promise<import("@tensorflow/tfjs-core/dist/tensor_types").NamedTensorMap>;
    threshold: (image: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor3D, method?: string, inverted?: boolean, threshValue?: number) => import("@tensorflow/tfjs-core/dist/tensor").Tensor3D;
    transform: (image: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D, transforms: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, interpolation?: "bilinear" | "nearest", fillMode?: "reflect" | "nearest" | "constant" | "wrap", fillValue?: number, outputShape?: [number, number]) => import("@tensorflow/tfjs-core/dist/tensor").Tensor4D;
};
export declare const linalg: () => {
    bandPart: <T extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(a: import("@tensorflow/tfjs-core/dist/types").TensorLike | T, numLower: number | import("@tensorflow/tfjs-core/dist/tensor").Scalar, numUpper: number | import("@tensorflow/tfjs-core/dist/tensor").Scalar) => T;
    gramSchmidt: (xs: import("@tensorflow/tfjs-core/dist/tensor").Tensor2D | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D[]) => import("@tensorflow/tfjs-core/dist/tensor").Tensor2D | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D[];
    qr: (x: import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, fullMatrices?: boolean) => [import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>];
};
export declare const losses: () => {
    absoluteDifference: <T extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(labels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T, predictions: import("@tensorflow/tfjs-core/dist/types").TensorLike | T, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O;
    computeWeightedLoss: <T_1 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_1 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(losses: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_1, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_1;
    cosineDistance: <T_2 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_2 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(labels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_2, predictions: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_2, axis: number, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_2;
    hingeLoss: <T_3 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_3 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(labels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_3, predictions: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_3, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_3;
    huberLoss: <T_4 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_4 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(labels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_4, predictions: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_4, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, delta?: number, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_4;
    logLoss: <T_5 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_5 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(labels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_5, predictions: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_5, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, epsilon?: number, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_5;
    meanSquaredError: <T_6 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_6 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(labels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_6, predictions: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_6, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_6;
    sigmoidCrossEntropy: <T_7 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_7 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(multiClassLabels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_7, logits: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_7, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, labelSmoothing?: number, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_7;
    softmaxCrossEntropy: <T_8 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_8 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(onehotLabels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_8, logits: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_8, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, labelSmoothing?: number, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_8;
};
export declare const train: () => typeof tfTypes.OptimizerConstructors;
export declare const data: () => unknown;
export declare const browser: () => typeof tfTypes.browser;
export declare const util: () => typeof tfTypes.util;
export declare const io: () => typeof tfTypes.io;
export declare const sigmoid: typeof tfTypes.sigmoid;
export declare const log: typeof tfTypes.log;
export declare const exp: typeof tfTypes.exp;
export declare const maximum: typeof tfTypes.maximum;
export declare const minimum: typeof tfTypes.minimum;
export declare const clone: typeof tfTypes.clone;
export declare const print: typeof tfTypes.print;
export declare const pad: typeof tfTypes.pad;
export declare const notEqual: typeof tfTypes.notEqual;
export declare const logicalXor: typeof tfTypes.logicalXor;
export declare const batchNorm: typeof tfTypes.batchNorm;
export declare const localResponseNormalization: typeof tfTypes.localResponseNormalization;
export declare const separableConv2d: typeof tfTypes.separableConv2d;
export declare const depthwiseConv2d: typeof tfTypes.depthwiseConv2d;
export declare const conv1d: typeof tfTypes.conv1d;
export declare const conv2d: typeof tfTypes.conv2d;
export declare const conv2dTranspose: typeof tfTypes.conv2dTranspose;
export declare const conv3d: typeof tfTypes.conv3d;
export declare const conv3dTranspose: typeof tfTypes.conv3dTranspose;
export declare const maxPool: typeof tfTypes.maxPool;
export declare const avgPool: typeof tfTypes.avgPool;
export declare const pool: typeof tfTypes.pool;
export declare const maxPool3d: typeof tfTypes.maxPool3d;
export declare const avgPool3d: typeof tfTypes.avgPool3d;
export declare const complex: typeof tfTypes.complex;
export declare const real: typeof tfTypes.real;
export declare const imag: typeof tfTypes.imag;
export declare const fft: typeof tfTypes.fft;
export declare const ifft: typeof tfTypes.ifft;
export declare const rfft: typeof tfTypes.rfft;
export declare const irfft: typeof tfTypes.irfft;
export declare const booleanMaskAsync: typeof tfTypes.booleanMaskAsync;
export declare const randomNormal: typeof tfTypes.randomNormal;
export declare const randomUniform: typeof tfTypes.randomUniform;
export declare const multinomial: typeof tfTypes.multinomial;
export declare const randomGamma: typeof tfTypes.randomGamma;
declare const _default: {
    tensor: typeof tfTypes.tensor;
    tensor1d: typeof tfTypes.tensor1d;
    tensor2d: typeof tfTypes.tensor2d;
    tensor3d: typeof tfTypes.tensor3d;
    tensor4d: typeof tfTypes.tensor4d;
    tensor5d: typeof tfTypes.tensor5d;
    tensor6d: typeof tfTypes.tensor6d;
    variable: typeof tfTypes.variable;
    scalar: typeof tfTypes.scalar;
    zeros: typeof tfTypes.zeros;
    ones: typeof tfTypes.ones;
    zerosLike: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    onesLike: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    fill: typeof tfTypes.fill;
    range: typeof tfTypes.range;
    linspace: typeof tfTypes.linspace;
    add: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    sub: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    mul: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    div: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    pow: <T extends tfTypes.Tensor>(base: tfTypes.Tensor | tfTypes.TensorLike, exp: tfTypes.Tensor | tfTypes.TensorLike) => T;
    sqrt: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    square: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    abs: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    neg: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    sign: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    round: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    floor: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    ceil: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    sin: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    cos: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    tan: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    asin: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    acos: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    atan: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    sinh: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    cosh: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    tanh: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    elu: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    relu: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    selu: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    leakyRelu: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike, alpha?: number) => T;
    prelu: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike, alpha: T | tfTypes.TensorLike) => T;
    softmax: <T extends tfTypes.Tensor>(logits: T | tfTypes.TensorLike, dim?: number) => T;
    matMul: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike, transposeA?: boolean, transposeB?: boolean) => T;
    dot: (t1: tfTypes.Tensor | tfTypes.TensorLike, t2: tfTypes.Tensor | tfTypes.TensorLike) => tfTypes.Tensor;
    outerProduct: (v1: tfTypes.Tensor1D | tfTypes.TensorLike, v2: tfTypes.Tensor1D | tfTypes.TensorLike) => tfTypes.Tensor2D;
    transpose: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike, perm?: number[], conjugate?: boolean) => T;
    norm: (x: tfTypes.Tensor | tfTypes.TensorLike, ord?: number | "euclidean" | "fro", axis?: number | number[], keepDims?: boolean) => tfTypes.Tensor;
    mean: <T extends tfTypes.Tensor>(x: tfTypes.Tensor | tfTypes.TensorLike, axis?: number | number[], keepDims?: boolean) => T;
    sum: <T extends tfTypes.Tensor>(x: tfTypes.Tensor | tfTypes.TensorLike, axis?: number | number[], keepDims?: boolean) => T;
    min: <T extends tfTypes.Tensor>(x: tfTypes.Tensor | tfTypes.TensorLike, axis?: number | number[], keepDims?: boolean) => T;
    max: <T extends tfTypes.Tensor>(x: tfTypes.Tensor | tfTypes.TensorLike, axis?: number | number[], keepDims?: boolean) => T;
    prod: <T extends tfTypes.Tensor>(x: tfTypes.Tensor | tfTypes.TensorLike, axis?: number | number[], keepDims?: boolean) => T;
    cumsum: <T extends tfTypes.Tensor>(x: tfTypes.Tensor | tfTypes.TensorLike, axis?: number, exclusive?: boolean, reverse?: boolean) => T;
    all: <T extends tfTypes.Tensor>(x: tfTypes.Tensor | tfTypes.TensorLike, axis?: number | number[], keepDims?: boolean) => T;
    any: <T extends tfTypes.Tensor>(x: tfTypes.Tensor | tfTypes.TensorLike, axis?: number | number[], keepDims?: boolean) => T;
    argMax: <T extends tfTypes.Tensor>(x: tfTypes.Tensor | tfTypes.TensorLike, axis?: number) => T;
    argMin: <T extends tfTypes.Tensor>(x: tfTypes.Tensor | tfTypes.TensorLike, axis?: number) => T;
    slice: <R extends tfTypes.Rank, T extends tfTypes.Tensor<R>>(x: T | tfTypes.TensorLike, begin: number | number[], size?: number | number[]) => T;
    concat: <T extends tfTypes.Tensor>(tensors: Array<T | tfTypes.TensorLike>, axis?: number) => T;
    stack: <T extends tfTypes.Tensor>(tensors: Array<T | tfTypes.TensorLike>, axis?: number) => tfTypes.Tensor;
    unstack: (x: tfTypes.Tensor | tfTypes.TensorLike, axis?: number) => tfTypes.Tensor[];
    split: <T extends tfTypes.Tensor>(x: tfTypes.Tensor | tfTypes.TensorLike, numOrSizeSplits: number[] | number, axis?: number) => T[];
    gather: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike, indices: tfTypes.Tensor | tfTypes.TensorLike, axis?: number, batchDims?: number) => T;
    reverse: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike, axis?: number | number[]) => T;
    cast: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike, dtype: tfTypes.DataType) => T;
    reshape: <R extends tfTypes.Rank>(x: tfTypes.Tensor | tfTypes.TensorLike, shape: tfTypes.ShapeMap[R]) => tfTypes.Tensor<R>;
    squeeze: <T extends tfTypes.Tensor>(x: tfTypes.Tensor | tfTypes.TensorLike, axis?: number[]) => T;
    expandDims: <T extends tfTypes.Tensor>(x: tfTypes.Tensor | tfTypes.TensorLike, axis?: number) => T;
    equal: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    greater: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    greaterEqual: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    less: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    lessEqual: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    logicalAnd: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    logicalOr: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    logicalNot: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    where: <T extends tfTypes.Tensor>(condition: tfTypes.Tensor | tfTypes.TensorLike, a: T | tfTypes.TensorLike, b: T | tfTypes.TensorLike) => T;
    eye: (numRows: number, numColumns?: number, batchShape?: [number] | [number, number] | [number, number, number] | [number, number, number, number], dtype?: tfTypes.DataType) => tfTypes.Tensor2D;
    diag: (x: tfTypes.Tensor) => tfTypes.Tensor;
    unique: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike, axis?: number) => {
        values: T;
        indices: tfTypes.Tensor1D;
    };
    tidy: typeof tfTypes.tidy;
    dispose: typeof tfTypes.dispose;
    keep: typeof tfTypes.keep;
    memory: typeof tfTypes.memory;
    backend: typeof tfTypes.backend;
    env: typeof tfTypes.env;
    ready: typeof tfTypes.ready;
    setBackend: typeof tfTypes.setBackend;
    getBackend: typeof tfTypes.getBackend;
    grad: typeof tfTypes.grad;
    grads: typeof tfTypes.grads;
    customGrad: typeof tfTypes.customGrad;
    valueAndGrad: typeof tfTypes.valueAndGrad;
    valueAndGrads: typeof tfTypes.valueAndGrads;
    variableGrads: typeof tfTypes.variableGrads;
    topk: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike, k?: number, sorted?: boolean) => {
        values: T;
        indices: T;
    };
    scatterND: <R extends tfTypes.Rank>(indices: tfTypes.Tensor | tfTypes.TensorLike, updates: tfTypes.Tensor | tfTypes.TensorLike, shape: tfTypes.ShapeMap[R]) => tfTypes.Tensor<R>;
    Tensor: () => typeof tfTypes.Tensor;
    image: () => {
        flipLeftRight: (image: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D) => import("@tensorflow/tfjs-core/dist/tensor").Tensor4D;
        grayscaleToRGB: <T extends import("@tensorflow/tfjs-core/dist/tensor").Tensor2D | import("@tensorflow/tfjs-core/dist/tensor").Tensor3D | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D | import("@tensorflow/tfjs-core/dist/tensor").Tensor5D | import("@tensorflow/tfjs-core/dist/tensor").Tensor6D>(image: import("@tensorflow/tfjs-core/dist/types").TensorLike | T) => T;
        resizeNearestNeighbor: <T_1 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor3D | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D>(images: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_1, size: [number, number], alignCorners?: boolean, halfPixelCenters?: boolean) => T_1;
        resizeBilinear: <T_2 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor3D | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D>(images: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_2, size: [number, number], alignCorners?: boolean, halfPixelCenters?: boolean) => T_2;
        rgbToGrayscale: <T_3 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor2D | import("@tensorflow/tfjs-core/dist/tensor").Tensor3D | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D | import("@tensorflow/tfjs-core/dist/tensor").Tensor5D | import("@tensorflow/tfjs-core/dist/tensor").Tensor6D>(image: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_3) => T_3;
        rotateWithOffset: (image: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D, radians: number, fillValue?: number | [number, number, number], center?: number | [number, number]) => import("@tensorflow/tfjs-core/dist/tensor").Tensor4D;
        cropAndResize: (image: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D, boxes: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, boxInd: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D, cropSize: [number, number], method?: "bilinear" | "nearest", extrapolationValue?: number) => import("@tensorflow/tfjs-core/dist/tensor").Tensor4D;
        nonMaxSuppression: (boxes: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, scores: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D, maxOutputSize: number, iouThreshold?: number, scoreThreshold?: number) => import("@tensorflow/tfjs-core/dist/tensor").Tensor1D;
        nonMaxSuppressionAsync: (boxes: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, scores: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D, maxOutputSize: number, iouThreshold?: number, scoreThreshold?: number) => Promise<import("@tensorflow/tfjs-core/dist/tensor").Tensor1D>;
        nonMaxSuppressionWithScore: (boxes: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, scores: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D, maxOutputSize: number, iouThreshold?: number, scoreThreshold?: number, softNmsSigma?: number) => import("@tensorflow/tfjs-core/dist/tensor_types").NamedTensorMap;
        nonMaxSuppressionWithScoreAsync: (boxes: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, scores: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D, maxOutputSize: number, iouThreshold?: number, scoreThreshold?: number, softNmsSigma?: number) => Promise<import("@tensorflow/tfjs-core/dist/tensor_types").NamedTensorMap>;
        nonMaxSuppressionPadded: (boxes: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, scores: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D, maxOutputSize: number, iouThreshold?: number, scoreThreshold?: number, padToMaxOutputSize?: boolean) => import("@tensorflow/tfjs-core/dist/tensor_types").NamedTensorMap;
        nonMaxSuppressionPaddedAsync: (boxes: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, scores: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D, maxOutputSize: number, iouThreshold?: number, scoreThreshold?: number, padToMaxOutputSize?: boolean) => Promise<import("@tensorflow/tfjs-core/dist/tensor_types").NamedTensorMap>;
        threshold: (image: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor3D, method?: string, inverted?: boolean, threshValue?: number) => import("@tensorflow/tfjs-core/dist/tensor").Tensor3D;
        transform: (image: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor4D, transforms: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor2D, interpolation?: "bilinear" | "nearest", fillMode?: "reflect" | "nearest" | "constant" | "wrap", fillValue?: number, outputShape?: [number, number]) => import("@tensorflow/tfjs-core/dist/tensor").Tensor4D;
    };
    linalg: () => {
        bandPart: <T extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(a: import("@tensorflow/tfjs-core/dist/types").TensorLike | T, numLower: number | import("@tensorflow/tfjs-core/dist/tensor").Scalar, numUpper: number | import("@tensorflow/tfjs-core/dist/tensor").Scalar) => T;
        gramSchmidt: (xs: import("@tensorflow/tfjs-core/dist/tensor").Tensor2D | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D[]) => import("@tensorflow/tfjs-core/dist/tensor").Tensor2D | import("@tensorflow/tfjs-core/dist/tensor").Tensor1D[];
        qr: (x: import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, fullMatrices?: boolean) => [import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>];
    };
    losses: () => {
        absoluteDifference: <T extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(labels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T, predictions: import("@tensorflow/tfjs-core/dist/types").TensorLike | T, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O;
        computeWeightedLoss: <T_1 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_1 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(losses: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_1, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_1;
        cosineDistance: <T_2 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_2 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(labels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_2, predictions: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_2, axis: number, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_2;
        hingeLoss: <T_3 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_3 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(labels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_3, predictions: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_3, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_3;
        huberLoss: <T_4 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_4 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(labels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_4, predictions: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_4, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, delta?: number, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_4;
        logLoss: <T_5 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_5 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(labels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_5, predictions: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_5, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, epsilon?: number, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_5;
        meanSquaredError: <T_6 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_6 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(labels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_6, predictions: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_6, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_6;
        sigmoidCrossEntropy: <T_7 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_7 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(multiClassLabels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_7, logits: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_7, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, labelSmoothing?: number, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_7;
        softmaxCrossEntropy: <T_8 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, O_8 extends import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>>(onehotLabels: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_8, logits: import("@tensorflow/tfjs-core/dist/types").TensorLike | T_8, weights?: import("@tensorflow/tfjs-core/dist/types").TensorLike | import("@tensorflow/tfjs-core/dist/tensor").Tensor<import("@tensorflow/tfjs-core/dist/types").Rank>, labelSmoothing?: number, reduction?: import("@tensorflow/tfjs-core/dist/base").Reduction) => O_8;
    };
    train: () => typeof tfTypes.OptimizerConstructors;
    data: () => unknown;
    browser: () => typeof tfTypes.browser;
    util: () => typeof tfTypes.util;
    io: () => typeof tfTypes.io;
    sigmoid: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    log: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    exp: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    maximum: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    minimum: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    clone: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike) => T;
    print: typeof tfTypes.print;
    pad: <T extends tfTypes.Tensor>(x: T | tfTypes.TensorLike, paddings: Array<[number, number]>, constantValue?: number) => T;
    notEqual: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    logicalXor: <T extends tfTypes.Tensor>(a: tfTypes.Tensor | tfTypes.TensorLike, b: tfTypes.Tensor | tfTypes.TensorLike) => T;
    batchNorm: <R extends tfTypes.Rank>(x: tfTypes.Tensor<R> | tfTypes.TensorLike, mean: tfTypes.Tensor<R> | tfTypes.Tensor1D | tfTypes.TensorLike, variance: tfTypes.Tensor<R> | tfTypes.Tensor1D | tfTypes.TensorLike, offset?: tfTypes.Tensor<R> | tfTypes.Tensor1D | tfTypes.TensorLike, scale?: tfTypes.Tensor<R> | tfTypes.Tensor1D | tfTypes.TensorLike, varianceEpsilon?: number) => tfTypes.Tensor<R>;
    localResponseNormalization: <T extends tfTypes.Tensor3D | tfTypes.Tensor4D>(x: T | tfTypes.TensorLike, depthRadius?: number, bias?: number, alpha?: number, beta?: number) => T;
    separableConv2d: <T extends tfTypes.Tensor3D | tfTypes.Tensor4D>(x: T | tfTypes.TensorLike, depthwiseFilter: tfTypes.Tensor4D | tfTypes.TensorLike, pointwiseFilter: tfTypes.Tensor4D | tfTypes.TensorLike, strides: [number, number] | number, pad: "valid" | "same", dilation?: [number, number] | number, dataFormat?: "NHWC" | "NCHW") => T;
    depthwiseConv2d: <T extends tfTypes.Tensor3D | tfTypes.Tensor4D>(x: T | tfTypes.TensorLike, filter: tfTypes.Tensor4D | tfTypes.TensorLike, strides: [number, number] | number, pad: "valid" | "same" | number | tfTypes.backend_util.ExplicitPadding, dataFormat?: "NHWC" | "NCHW", dilations?: [number, number] | number, dimRoundingMode?: "floor" | "round" | "ceil") => T;
    conv1d: <T extends tfTypes.Tensor2D | tfTypes.Tensor3D>(x: T | tfTypes.TensorLike, filter: tfTypes.Tensor3D | tfTypes.TensorLike, stride: number, pad: "valid" | "same" | number | tfTypes.backend_util.ExplicitPadding, dataFormat?: "NWC" | "NCW", dilation?: number, dimRoundingMode?: "floor" | "round" | "ceil") => T;
    conv2d: <T extends tfTypes.Tensor3D | tfTypes.Tensor4D>(x: T | tfTypes.TensorLike, filter: tfTypes.Tensor4D | tfTypes.TensorLike, strides: [number, number] | number, pad: "valid" | "same" | number | tfTypes.backend_util.ExplicitPadding, dataFormat?: "NHWC" | "NCHW", dilations?: [number, number] | number, dimRoundingMode?: "floor" | "round" | "ceil") => T;
    conv2dTranspose: <T extends tfTypes.Tensor3D | tfTypes.Tensor4D>(x: T | tfTypes.TensorLike, filter: tfTypes.Tensor4D | tfTypes.TensorLike, outputShape: [number, number, number, number] | [number, number, number], strides: [number, number] | number, pad: "valid" | "same" | number | tfTypes.backend_util.ExplicitPadding, dimRoundingMode?: "floor" | "round" | "ceil") => T;
    conv3d: <T extends tfTypes.Tensor4D | tfTypes.Tensor5D>(x: T | tfTypes.TensorLike, filter: tfTypes.Tensor5D | tfTypes.TensorLike, strides: [number, number, number] | number, pad: "valid" | "same", dataFormat?: "NDHWC" | "NCDHW", dilations?: [number, number, number] | number) => T;
    conv3dTranspose: <T extends tfTypes.Tensor4D | tfTypes.Tensor5D>(x: T | tfTypes.TensorLike, filter: tfTypes.Tensor5D | tfTypes.TensorLike, outputShape: [number, number, number, number, number] | [number, number, number, number], strides: [number, number, number] | number, pad: "valid" | "same") => T;
    maxPool: <T extends tfTypes.Tensor3D | tfTypes.Tensor4D>(x: T | tfTypes.TensorLike, filterSize: [number, number] | number, strides: [number, number] | number, pad: "valid" | "same" | number | tfTypes.backend_util.ExplicitPadding, dimRoundingMode?: "floor" | "round" | "ceil") => T;
    avgPool: <T extends tfTypes.Tensor3D | tfTypes.Tensor4D>(x: T | tfTypes.TensorLike, filterSize: [number, number] | number, strides: [number, number] | number, pad: "valid" | "same" | number | tfTypes.backend_util.ExplicitPadding, dimRoundingMode?: "floor" | "round" | "ceil") => T;
    pool: <T extends tfTypes.Tensor3D | tfTypes.Tensor4D>(input: T | tfTypes.TensorLike, windowShape: [number, number] | number, poolingType: "avg" | "max", pad: "valid" | "same" | number | tfTypes.backend_util.ExplicitPadding, dilations?: [number, number] | number, strides?: [number, number] | number, dimRoundingMode?: "floor" | "round" | "ceil") => T;
    maxPool3d: <T extends tfTypes.Tensor4D | tfTypes.Tensor5D>(x: T | tfTypes.TensorLike, filterSize: [number, number, number] | number, strides: [number, number, number] | number, pad: "valid" | "same" | number, dimRoundingMode?: "floor" | "round" | "ceil", dataFormat?: "NDHWC" | "NCDHW") => T;
    avgPool3d: <T extends tfTypes.Tensor4D | tfTypes.Tensor5D>(x: T | tfTypes.TensorLike, filterSize: [number, number, number] | number, strides: [number, number, number] | number, pad: "valid" | "same" | number, dimRoundingMode?: "floor" | "round" | "ceil", dataFormat?: "NDHWC" | "NCDHW") => T;
    complex: <T extends tfTypes.Tensor>(real: T | tfTypes.TensorLike, imag: T | tfTypes.TensorLike) => T;
    real: <T extends tfTypes.Tensor>(input: T | tfTypes.TensorLike) => T;
    imag: <T extends tfTypes.Tensor>(input: T | tfTypes.TensorLike) => T;
    fft: (input: tfTypes.Tensor) => tfTypes.Tensor;
    ifft: (input: tfTypes.Tensor) => tfTypes.Tensor;
    rfft: (input: tfTypes.Tensor, fftLength?: number) => tfTypes.Tensor;
    irfft: (input: tfTypes.Tensor) => tfTypes.Tensor;
    booleanMaskAsync: (tensor: tfTypes.Tensor | tfTypes.TensorLike, mask: tfTypes.Tensor | tfTypes.TensorLike, axis?: number) => Promise<tfTypes.Tensor>;
    randomNormal: <R extends tfTypes.Rank>(shape: tfTypes.ShapeMap[R], mean?: number, stdDev?: number, dtype?: "float32" | "int32", seed?: number) => tfTypes.Tensor<R>;
    randomUniform: <R extends tfTypes.Rank>(shape: tfTypes.ShapeMap[R], minval?: number, maxval?: number, dtype?: tfTypes.DataType, seed?: number | string) => tfTypes.Tensor<R>;
    multinomial: (logits: tfTypes.Tensor1D | tfTypes.Tensor2D | tfTypes.TensorLike, numSamples: number, seed?: number, normalized?: boolean) => tfTypes.Tensor1D | tfTypes.Tensor2D;
    randomGamma: <R extends tfTypes.Rank>(shape: tfTypes.ShapeMap[R], alpha: number, beta?: number, dtype?: "float32" | "int32", seed?: number) => tfTypes.Tensor<R>;
};
export default _default;
//# sourceMappingURL=tf-adapter.browser.d.ts.map