download=True,
transform=transform_svhn)
dataset_test = datasets.SVHN('../data/svhn',
split='test',
download=True,
transform=transform_svhn_test)
else:
exit('Error: unrecognized dataset')
dataset_valid = dataset_test
if args.iid == 'noniid_ssl' and args.dataset == 'cifar':
dict_users, dict_users_labeled, pseudo_label = noniid_ssl(
dataset_train, args.num_users, args.label_rate)
else:
dict_users, dict_users_labeled, pseudo_label = sample(
dataset_train, args.num_users, args.label_rate, args.iid)
if args.dataset == 'cifar':
net_glob = CNNCifar(args=args).to(args.device)
elif args.dataset == 'mnist':
net_glob = CNNMnist(args=args).to(args.device)
elif args.dataset == 'svhn':
net_glob = CNNCifar(args=args).to(args.device)
else:
exit('Error: unrecognized model')
print("\n Begin Train")
net_glob.train()
w_glob = net_glob.state_dict()
""" -- ------------------------------------------------------------------ -- Title: Explore data on sepsis patients -- Description: -- Start off on comparing mortality rates -- Followed by comparing teaching hospitals -- ------------------------------------------------------------------ """ import data.sampling as sampling import pandas as pd import csv #get sample population sample_eicu = sampling.sample(path="../data/raw/") sample_sepsis = sampling.sample(db="sepsis", path="../data/interim/") df_eicu = pd.Series.to_frame(sample_eicu) df_sepsis = pd.Series.to_frame(sample_sepsis)