@ai-on-browser/data-analysis-models/lib/util/tensor.d.ts

Data analysis model package without any dependencies

/**
 * Tensor class
 */
export default class Tensor {
    /**
     * Returns a tensor filled with 0.
     * @overload
     * @param {...number} size Sizes for each dimension
     * @returns {Tensor} Tensor filled with 0
     */
    static zeros(...size: number[]): Tensor;
    /**
     * Returns a tensor filled with 0.
     * @overload
     * @param {number[]} size Sizes for each dimension
     * @returns {Tensor} Tensor filled with 0
     */
    static zeros(size: number[]): Tensor;
    /**
     * Returns a tensor filled with 1.
     * @overload
     * @param {...number} size Sizes for each dimension
     * @returns {Tensor} Tensor filled with 1
     */
    static ones(...size: number[]): Tensor;
    /**
     * Returns a tensor filled with 1.
     * @overload
     * @param {number[]} size Sizes for each dimension
     * @returns {Tensor} Tensor filled with 1
     */
    static ones(size: number[]): Tensor;
    /**
     * Returns a tensor initialized uniform random values.
     * @param {number[]} size Sizes for each dimension
     * @param {number} [min] Minimum value of the Tensor
     * @param {number} [max] Maximum value of the Tensor
     * @returns {Tensor} Tensor initialized uniform random values
     */
    static random(size: number[], min?: number, max?: number): Tensor;
    /**
     * Returns a tensor initialized normal random values.
     * @param {number[]} size Sizes for each dimension
     * @param {number} [myu] Mean value of the Tensor
     * @param {number} [sigma] Variance value of the Tensor
     * @returns {Tensor} Tensor initialized normal random values
     */
    static randn(size: number[], myu?: number, sigma?: number): Tensor;
    /**
     * Returns a tensor from some value.
     * @param {Tensor | Matrix | Array<number> | number} arr Original values
     * @returns {Tensor} Tensor from some value
     */
    static fromArray(arr: Tensor | Matrix | Array<number> | number): Tensor;
    /**
     * @param {number[]} size Sizes for each dimension
     * @param {number | number[]} [value] Initial values
     */
    constructor(size: number[], value?: number | number[]);
    /** @private */
    private _size;
    /** @private */
    private _length;
    /** @private */
    private _value;
    /** @private */
    private _offset;
    /**
     * Dimension of the tensor.
     * @type {number}
     */
    get dimension(): number;
    /**
     * Sizes of the tensor.
     * @type {number[]}
     */
    get sizes(): number[];
    /**
     * Number of all elements in the tensor.
     * @type {number}
     */
    get length(): number;
    /**
     * Elements in the tensor.
     * @type {number[]}
     */
    get value(): number[];
    /**
     * Returns a nested array represented this tensor.
     * @returns {Array<number>} Nested array
     */
    toArray(): Array<number>;
    /**
     * Returns a string represented this tensor.
     * @returns {string} String represented this tensor
     */
    toString(): string;
    /**
     * Returns a Matrix if the dimension of this tensor is 2.
     * @returns {Matrix} Matrix
     * @throws {MatrixException} If the dimension of this tensor is not 2.
     */
    toMatrix(): Matrix;
    /**
     * Returns the only element.
     * @returns {number} The only element
     */
    toScaler(): number;
    _to_position(...i: any[]): number;
    _to_index(p: any): any[];
    /**
     * Returns a copy of this tensor.
     * @returns {Tensor} Copied tensor
     */
    copy(): Tensor;
    /**
     * Returns this tensor is equals to the others.
     * @param {*} other Check tensor
     * @returns {boolean} `true` if equal
     */
    equals(other: any): boolean;
    /**
     * Returns value at the index position.
     * @overload
     * @param  {...number} i Index values
     * @returns {number} The value
     */
    at(...i: number[]): number;
    /**
     * Returns value at the index position.
     * @overload
     * @param  {number[]} i Index values
     * @returns {number} The value
     */
    at(i: number[]): number;
    /**
     * Returns tensor at the index position.
     * @overload
     * @param  {...number} i Index values
     * @returns {Tensor} Sub tensor
     */
    index(...i: number[]): Tensor;
    /**
     * Returns tensor at the index position.
     * @overload
     * @param  {number[]} i Index values
     * @returns {Tensor} Sub tensor
     */
    index(i: number[]): Tensor;
    /**
     * Set the value at the specific position.
     * @param {number | number[]} i Index values
     * @param {number} value Set value
     */
    set(i: number | number[], value: number): void;
    /**
     * Returns the sub-tensor corresponding to position i in the first dimension of this.
     * @param {number | number[]} idx Select index value(s)
     * @param {number} [axis] Axis
     * @returns {Tensor} Selected tensor
     */
    select(idx: number | number[], axis?: number): Tensor;
    /**
     * Returns a tensor sliced by first dimension.
     * @param {number} from Start index
     * @param {number} to End index
     * @param {number} [axis] Axis
     * @returns {Tensor} Sliced tensor
     */
    slice(from: number, to: number, axis?: number): Tensor;
    /**
     * Fill in all the elements with the value.
     * @param {number} value Filled value
     */
    fill(value: number): void;
    /**
     * Iterate over all the elements and replace the value.
     * @param {function (number, number[], Tensor): number} cb Mapping function
     */
    map(cb: (arg0: number, arg1: number[], arg2: Tensor) => number): void;
    /**
     * Iterate over all the elements.
     * @param {function (number, number[], Tensor): void} cb Callback function
     */
    forEach(cb: (arg0: number, arg1: number[], arg2: Tensor) => void): void;
    /**
     * Returns a tensor transposed along the axis.
     * @param {...number} axises Selected axises
     * @returns {Tensor} Transposed tensor
     */
    /**
     * Returns a tensor transposed along the axis.
     * @param {number[]} axises Selected axises
     * @returns {Tensor} Transposed tensor
     */
    /**
     * @param {...number | number[]} axises Selected axises
     * @returns {Tensor} Transposed tensor
     */
    transpose(...axises: (number | number[])[]): Tensor;
    /**
     * Flip values along the axis.
     * @param {number} [axis] Axis to be flipped
     */
    flip(axis?: number): void;
    /**
     * Shuffle along the axis.
     * @param {number} [axis] Axis
     */
    shuffle(axis?: number): void;
    /**
     * Resize this tensor.
     * @param {number[]} sizes New sizes
     * @param {number} [init] Value of the extended region
     */
    resize(sizes: number[], init?: number): void;
    /**
     * Reshape this as the sizes.
     * @overload
     * @param {...number} sizes New sizes for each dimension
     */
    reshape(...sizes: number[]): any;
    /**
     * Reshape this as the sizes.
     * @overload
     * @param {number[]} sizes New sizes for each dimension
     */
    reshape(sizes: number[]): any;
    /**
     * Repeat the elements n times along the axis this.
     * @overload
     * @param {number} n Repeated count
     * @param {number} [axis] Axis to be repeated
     */
    repeat(n: number, axis?: number): any;
    /**
     * Repeat the elements n times along the axis this.
     * @overload
     * @param {number[]} n Repeated counts of each axis
     */
    repeat(n: number[]): any;
    /**
     * Concatenate this and t.
     * @param {Tensor} t Concatenate tensor
     * @param {number} [axis] Axis to be concatenated
     */
    concat(t: Tensor, axis?: number): void;
    /**
     * Returns a tensor reduced along all element with the callback function.
     * @overload
     * @param {function (number, number, number[], Tensor): number} cb Reducing function
     * @param {*} [init] Initial value
     * @returns {number} Reduced tensor or value
     */
    reduce(cb: (arg0: number, arg1: number, arg2: number[], arg3: Tensor) => number, init?: any): number;
    /**
     * Returns a tensor reduced along the axis with the callback function.
     * @overload
     * @param {function (number, number, number[], Tensor): number} cb Reducing function
     * @param {*} init Initial value
     * @param {number | number[]} axis Axis to be reduced. If negative, reduce along all elements.
     * @param {boolean} [keepdims] Keep dimensions or not.
     * @returns {Tensor | number} Reduced tensor or value
     */
    reduce(cb: (arg0: number, arg1: number, arg2: number[], arg3: Tensor) => number, init: any, axis: number | number[], keepdims?: boolean): Tensor | number;
    /**
     * Apply function for all elements with broadcasting.
     * @param {Tensor | Matrix | number} o Applied value
     * @param {function (number, number): number} fn Applied function
     */
    broadcastOperate(o: Tensor | Matrix | number, fn: (arg0: number, arg1: number) => number): void;
    /**
     * Apply function to the position.
     * @param {number | number[]} i Index values
     * @param {function (number): number} [fn] Applied function
     * @returns {number} Old value
     */
    operateAt(i: number | number[], fn?: (arg0: number) => number): number;
    /**
     * Returns a tensor product value.
     * @param {Matrix} o Right matrix
     * @returns {Tensor} Producted tensor
     */
    dot(o: Matrix): Tensor;
    /**
     * Iterate over the elements.
     * @yields {number}
     */
    [Symbol.iterator](): Generator<any, void, undefined>;
}
import Matrix from './matrix.js';