@tensorflow/tfjs-core/dist/util.d.ts

Hardware-accelerated JavaScript library for machine intelligence

import { DataType, DataTypeMap, FlatVector, NumericDataType, RecursiveArray, TensorLike, 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 nearestLargerEven(val: number): number;
export declare function sum(arr: 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 | (() => string)): void;
export declare function assertShapesMatch(shapeA: number[], shapeB: number[], errorMessagePrefix?: string): void;
export declare function assertNonNull(a: TensorLike): void;
export declare function flatten<T extends number | boolean | string | Promise<number> | TypedArray>(arr: T | RecursiveArray<T>, ret?: T[]): T[];
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<void>;
export declare function inferFromImplicitShape(shape: number[], size: number): number[];
export declare function parseAxisParam(axis: number | number[], shape: number[]): number[];
export declare function squeezeShape(shape: number[], axis?: number[]): {
    newShape: number[];
    keptDims: number[];
};
export declare function getTypedArrayFromDType<D extends NumericDataType>(dtype: D, size: number): DataTypeMap[D];
export declare function getArrayFromDType<D extends DataType>(dtype: D, size: number): DataTypeMap[D];
export declare function checkComputationForErrors<D extends DataType>(vals: DataTypeMap[D], dtype: D, name: string): void;
export declare function checkConversionForErrors<D extends DataType>(vals: DataTypeMap[D] | number[], dtype: D): void;
export declare function hasEncodingLoss(oldType: DataType, newType: DataType): boolean;
export declare function isTypedArray(a: {}): a is Float32Array | Int32Array | Uint8Array;
export declare function bytesPerElement(dtype: DataType): number;
export declare function bytesFromStringArray(arr: string[]): number;
export declare function isString(value: {}): value is string;
export declare function isBoolean(value: {}): boolean;
export declare function isNumber(value: {}): boolean;
export declare function inferDtype(values: TensorLike): DataType;
export declare function isFunction(f: Function): boolean;
export declare function nearestDivisor(size: number, start: number): number;
export declare function computeStrides(shape: number[]): number[];
export declare function toTypedArray(a: TensorLike, dtype: DataType, debugMode: boolean): TypedArray;
export declare function toNestedArray(shape: number[], a: TypedArray): any[];
export declare function makeOnesTypedArray<D extends DataType>(size: number, dtype: D): DataTypeMap[D];
export declare function makeZerosTypedArray<D extends DataType>(size: number, dtype: D): DataTypeMap[D];
export declare function now(): number;
export declare function monitorPromisesProgress<D extends DataType>(promises: Array<Promise<D | Function | {} | void>>, onProgress: Function, startFraction?: number, endFraction?: number): Promise<(void | {} | Function | D)[]>;