ml-basic/dist/types/layers/index.d.ts

Lightweight, zero dependency, machine learning library

import AveragePoolingLayer from "./average-pooling";
import ConvolutionalLayer, { ConvolutionalParams } from "./convolutional";
import DropoutLayer, { DropoutParams } from "./dropout";
import FullyConnectedLayer, { FullyConnectedParams } from "./fully-connected";
import { LoopParams } from "./loop";
import LSTMLayer from "./lstm";
import MaxPoolingLayer from "./max-pooling";
import { PoolingParams } from "./pooling";
import RecurrentLayer from "./recurrent";
type LayerParams<T extends {
    input: any;
}> = Omit<T, 'input'> & Partial<Pick<T, 'input'>>;
declare const Layers: {
    avgp: (args: LayerParams<PoolingParams>) => {
        Layer: typeof AveragePoolingLayer;
        args: LayerParams<PoolingParams>;
    };
    conv: (args: LayerParams<ConvolutionalParams>) => {
        Layer: typeof ConvolutionalLayer;
        args: LayerParams<ConvolutionalParams>;
    };
    fcon: (args: LayerParams<FullyConnectedParams>) => {
        Layer: typeof FullyConnectedLayer;
        args: LayerParams<FullyConnectedParams>;
    };
    maxp: (args: LayerParams<PoolingParams>) => {
        Layer: typeof MaxPoolingLayer;
        args: LayerParams<PoolingParams>;
    };
    recu: (args: LayerParams<LoopParams>) => {
        Layer: typeof RecurrentLayer;
        args: LayerParams<LoopParams>;
    };
    lstm: (args: LayerParams<LoopParams>) => {
        Layer: typeof LSTMLayer;
        args: LayerParams<LoopParams>;
    };
    drop: (args: LayerParams<DropoutParams>) => {
        Layer: typeof DropoutLayer;
        args: LayerParams<DropoutParams>;
    };
};
export type Layers = ReturnType<(typeof Layers)[keyof typeof Layers]>;
export default Layers;