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26 lines (25 loc) · 831 Bytes
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#!/usr/bin/env python
import h5py
import matplotlib.pyplot as plt
import numpy as np
import argparse
import importlib
import random
import os
from utils.plot_utils import *
import torch
torch.manual_seed(0)
if __name__ == "__main__": # plot for MNIST convex
numusers = 10
num_glob_iters = 800
dataset = "Mnist"
local_ep = [20]
lamda = [15]
learning_rate = [0.001]
beta = [1.0]
batch_size = [100]
K = [5]
personal_learning_rate = [0.001]
algorithms = ["pFedbayes"]
plot_summary_one_figure_mnist_Compare(num_users=numusers, loc_ep1=local_ep, Numb_Glob_Iters=num_glob_iters, lamb=lamda,
learning_rate=learning_rate, beta = beta, algorithms_list=algorithms, batch_size=batch_size, dataset=dataset, k = K, personal_learning_rate = personal_learning_rate)