[DATASET]
dataset_package = decentralizepy.datasets.Shakespeare
dataset_class = Shakespeare
random_seed = 97
model_class = LSTM
train_dir = /mnt/nfs/shared/leaf/data/shakespeare_sub96/per_user_data/train
test_dir = /mnt/nfs/shared/leaf/data/shakespeare_sub96/data/test
; python list of fractions below
sizes =

[OPTIMIZER_PARAMS]
optimizer_package = torch.optim
optimizer_class = SGD
lr = 0.1

[TRAIN_PARAMS]
training_package = decentralizepy.training.Training
training_class = Training
rounds = 10
full_epochs = False
batch_size = 16
shuffle = True
loss_package = torch.nn
loss_class = CrossEntropyLoss

[COMMUNICATION]
comm_package = decentralizepy.communication.TCP
comm_class = TCP
addresses_filepath = ip_addr_6Machines.json

[SHARING]
sharing_package = decentralizepy.sharing.Wavelet
sharing_class = Wavelet
change_based_selection = True
alpha = 0.1
wavelet=sym2
level= 4
accumulation = True
accumulate_averaging_changes = True