federer/dist/src/coordinator/preprocess/datasplits.d.ts

Experiments in asynchronous federated learning and decentralized learning

/**
 * Given number of splits, the function determines fraction of data in each split.
 * Zipf's law is given by f(k;s;N) = (1/k**s)/ Summation{from=1}{to=N}(1/n**s)
 * @param N Number of splits
 * @param s the value of the exponent characterizing the distribution
 * @returns array of split fractions
 *
 */
export declare function zipf(N: number, s: number): number[];
/**
 *
 * @param size total number of samples to be split
 * @param numberOfBatches total number of batches to be formed
 * @param s exponent in the function
 * @returns sample size for each batch
 * @throws Error for s < 1 or size < 0 or numberOfBatches<0
 * @assumes batch size = 0 is okay since these batches are used in conjunction
 * with uniform batches
 *
 */
export declare function zipfSplits(size: number, numberOfBatches: number, s: number): number[];
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