import { Tensor } from './tensor'; import { DataType, DataTypeMap, FlatVector, NamedTensorMap, RecursiveArray, RegularArray, TensorContainer, TypedArray } from './types'; export declare function shuffle(array: any[] | Uint32Array | Int32Array | Float32Array): void; export declare function clamp(min: number, x: number, max: number): number; export declare function randUniform(a: number, b: number): number; export declare function distSquared(a: FlatVector, b: FlatVector): number; export declare function assert(expr: boolean, msg: string): void; export declare function assertShapesMatch(shapeA: number[], shapeB: number[], errorMessagePrefix?: string): void; export declare function assertTypesMatch(a: Tensor, b: Tensor): void; export declare function flatten>(arr: T | RecursiveArray, ret?: T[]): T[]; export declare function inferShape(val: TypedArray | number | boolean | RegularArray | RegularArray): number[]; export declare function sizeFromShape(shape: number[]): number; export declare function isScalarShape(shape: number[]): boolean; export declare function arraysEqual(n1: FlatVector, n2: FlatVector): boolean; export declare function isInt(a: number): boolean; export declare function tanh(x: number): number; export declare function sizeToSquarishShape(size: number): [number, number]; export declare function createShuffledIndices(n: number): Uint32Array; export declare function rightPad(a: string, size: number): string; export declare function repeatedTry(checkFn: () => boolean, delayFn?: (counter: number) => number, maxCounter?: number): Promise; export declare function getQueryParams(queryString: string): { [key: string]: string; }; export declare function inferFromImplicitShape(shape: number[], size: number): number[]; export declare const NAN_INT32: number; export declare const NAN_BOOL = 255; export declare const NAN_FLOAT32: number; export declare function getNaN(dtype: DataType): number; export declare function isValNaN(val: number, dtype: DataType): boolean; export declare function squeezeShape(shape: number[], axis?: number[]): { newShape: number[]; keptDims: number[]; }; export declare function getTypedArrayFromDType(dtype: D, size: number): DataTypeMap[D]; export declare function isTensorInList(tensor: Tensor, tensorList: Tensor[]): boolean; export declare function checkForNaN(vals: DataTypeMap[D], dtype: D, name: string): void; export declare function flattenNameArrayMap(nameArrayMap: Tensor | NamedTensorMap, keys?: string[]): Tensor[]; export declare function unflattenToNameArrayMap(keys: string[], flatArrays: Tensor[]): NamedTensorMap; export declare function hasEncodingLoss(oldType: DataType, newType: DataType): boolean; export declare function copyTypedArray(array: DataTypeMap[D] | number[] | boolean[], dtype: D): DataTypeMap[D]; export declare function isTypedArray(a: TypedArray | number | boolean | RegularArray | RegularArray): boolean; export declare function bytesPerElement(dtype: DataType): number; export declare function isFunction(f: Function): boolean; export declare function extractTensorsFromContainer(result: TensorContainer): Tensor[]; export declare function extractTensorsFromAny(result: any): Tensor[];