federer/dist/src/experiments/mnist/coordinator/model.d.ts

Experiments in asynchronous federated learning and decentralized learning

import * as tf from "@tensorflow/tfjs-node";
import { OptimizerOptions } from "../../../coordinator";
export declare type MnistModelName = "2NN" | "CNN";
export interface MnistModelOptions {
    name: "2NN" | "CNN";
    optimizer: OptimizerOptions;
    numberOutputClasses: number;
}
/**
 * Gets a TensorFlow model to use on the MNIST dataset.
 *
 * @param model Name of the model to get
 *
 * @param numberOutputClasses Number of label classes to use for the output.
 * Setting this parameter is important: if we are running a small test
 * experiment, where we only have digits 0 and 1, the model should output a
 * one-hot vector of length two; in other words, the model should only be able
 * to predict digits that are a part of the experiment. For full experiments,
 * where we use the whole MNIST dataset, `numberOutputClasses` should be 10.
 */
export declare function createModel(options: MnistModelOptions): tf.Sequential;
//# sourceMappingURL=model.d.ts.map