/**
 * Exception for neuralnetwork layer class
 */
export class NeuralnetworkLayerException extends Error {
    /**
     * @param {string} message Error message
     * @param {*} value Some value
     */
    constructor(message: string, value: any);
    value: any;
}
/**
 * Neuralnetwork layer
 */
export default class Layer {
    /**
     * Returns layer from JSON.
     * @param {import("./index").PlainLayerObject} obj Object represented a layer
     * @returns {Layer} Layer
     */
    static fromObject(obj: import("./index").PlainLayerObject): Layer;
    /**
     * Regist layer class.
     * @param {string} [name] Name of the layer
     * @param {Layer} [cls] Layer class
     */
    static registLayer(name?: string, cls?: Layer): void;
    /**
     * @param {object} obj Config
     */
    constructor({}: object);
    /**
     * List of names of other layers dependent on this layer.
     * @type {string[]}
     */
    get dependentLayers(): string[];
    /**
     * Bind pre-condition values.
     * @param {object} values Binding object
     * @param {Matrix | Tensor | {[key: string]: Matrix | Tensor}} values.input Input data for neuralnetwork
     * @param {Matrix} [values.supervisor] Supervisor data
     * @param {number} values.n Data count
     * @param {*} values.rest Some other values
     */
    bind(values: {
        input: Matrix | Tensor | {
            [key: string]: Matrix | Tensor;
        };
        supervisor?: Matrix;
        n: number;
        rest: any;
    }): void;
    /**
     * Returns calculated values.
     * @param {...(Matrix | Tensor)} x Input values
     * @returns {Matrix | Tensor | Array<Matrix | Tensor>} Output values
     */
    calc(...x: (Matrix | Tensor)[]): Matrix | Tensor | Array<Matrix | Tensor>;
    /**
     * Returns gradient values.
     * @param {...(Matrix | Tensor)} bo Input value of backpropagation
     * @returns {Matrix | Tensor | Array<Matrix | Tensor>} Output value of backpropagation
     */
    grad(...bo: (Matrix | Tensor)[]): Matrix | Tensor | Array<Matrix | Tensor>;
    /**
     * Update parameters.
     * @param {{lr: number, delta: (function (string, Matrix): Matrix)}} optimizer Optimizer for this layer
     */
    update(optimizer: {
        lr: number;
        delta: ((arg0: string, arg1: Matrix) => Matrix);
    }): void;
    /**
     * Returns object of this layer.
     * @returns {import("./index").PlainLayerObject} Object represented this layer
     */
    toObject(): import("./index").PlainLayerObject;
}
/**
 * Base class for Flow-based generative model
 */
export class FlowLayer extends Layer {
    /**
     * Returns inverse values.
     * @param {...(Matrix | Tensor)} y Input value of inverse calculation
     * @returns {Matrix | Tensor | Array<Matrix | Tensor>} Output value of inverse calculation
     */
    inverse(...y: (Matrix | Tensor)[]): Matrix | Tensor | Array<Matrix | Tensor>;
    /**
     * Returns determinant of the Jacobian.
     * @returns {number} Determinant of the Jacobian
     */
    jacobianDeterminant(): number;
}
import Matrix from '../../../util/matrix.js';
import Tensor from '../../../util/tensor.js';