@hoff97/tensor-js/dist/lib/model/module.d.ts

PyTorch like deep learning inferrence library

import { Variable } from '../autograd/variable';
import Tensor from '../types';
import { Backend } from '../util/convert';
export declare type Mode = 'train' | 'inference';
/**
 * A module is a self contained unit that transforms
 * a list of inputs when forward is called.
 *
 * It can be in two modes, training and inference.
 * In training mode, gradients will be tracked, while
 * in inference mode, only the forward pass will be calculated
 */
export declare abstract class Module {
    backend: Backend;
    mode: Mode;
    abstract forward(inputs: Tensor<any>[]): Promise<Tensor<any>[]>;
    getSubModules(): Module[];
    getParameters(): Variable<any>[];
    toBackend(backend: Backend): Promise<void>;
    toCPU(): Promise<void>;
    toWASM(): Promise<void>;
    toGPU(): Promise<void>;
}