def fed_learn_exp():
module = leap_functions.fl_fn
selector = "[age] > 50 and [bmi] < 25"
leap_fed_learn = leap_fn.FedLearnFunction()
leap_fed_learn.selector = selector
leap_fed_learn.get_model = module.get_model
leap_fed_learn.get_optimizer = module.get_optimizer
leap_fed_learn.get_criterion = module.get_criterion
leap_fed_learn.get_dataloader = module.get_dataloader
hyperparams = {
"lr": 1e-5,
"d_x": 2, # input dimension
"d_y": 1, # output dimension
"batch_size": 1,
"max_iters": 7,
"iters_per_epoch":1
}
leap_fed_learn.hyperparams = hyperparams
return leap_fed_learn
def fed_learn_exp():
module = leap_functions.fl_fn
selector = {
"type": codes.DEFAULT,
"useLocalData": True
}
leap_fed_learn = leap_fn.FedLearnFunction()
leap_fed_learn.selector = selector
leap_fed_learn.get_model = module.get_model
leap_fed_learn.get_optimizer = module.get_optimizer
leap_fed_learn.get_criterion = module.get_criterion
leap_fed_learn.get_dataloader = module.get_dataloader
hyperparams = {
"lr": 1e-5,
"d_x": 2, # input dimension
"d_y": 1, # output dimension
"batch_size": 1,
"max_iters": 7,
"iters_per_epoch":1
}
leap_fed_learn.hyperparams = hyperparams
return leap_fed_learn
import pickle
import api.leap as leap
import api.register.user.registration as user_reg
import api.leap_fn as leap_fn
import api.codes as codes
import api.local.functions as leap_functions
import random
import argparse
import numpy as np
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('num_sites', metavar='n', type=int)
args = parser.parse_args()
leap_fed_learn = leap_fn.FedLearnFunction()
selector = {"type": codes.DEFAULT, "useLocalData": True}
leap_fed_learn.selector = selector
module = leap_functions.log_reg
leap_fed_learn.get_model = module.get_model
leap_fed_learn.get_optimizer = module.get_optimizer
leap_fed_learn.get_criterion = module.get_criterion
leap_fed_learn.get_dataloader = module.get_dataloader
random.seed(1)
ids = list(range(1, 10001))
random_ids = random.sample(ids, 10000)
train_ids = random_ids[:8000]