federer/dist/src/coordinator/preprocess/distribution-stats.d.ts

Experiments in asynchronous federated learning and decentralized learning

import * as tf from "@tensorflow/tfjs-node";
export interface DataDistributionStats {
    /**
     * 2D Tensor of shape `[clientLabels.length, numberLabelClasses]`
     * mapping each client to the number of labels that it holds, for each
     * different label. For example, a tensor containing `[[1, 10], [20, 2]]`
     * means client 0 has 1 item with label 0 and 10 items with label 1, and
     * client 1 has 20 items with label 0 and 2 items with label 1.
     */
    distributionMatrix: tf.Tensor2D;
}
/**
 * Computes statistics on the distribution of data that is produced by a
 * preprocessing pipeline.
 *
 * @param clientLabels Labels in the sharded client datasets. These should be in
 * numerical format, not one-hot encoded.
 * @param numberLabelClasses Number of labels that exist in total
 */
export declare function dataDistributionStats(clientLabels: tf.Tensor1D[], numberLabelClasses: number): DataDistributionStats;
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