config_cifar_wavelet.ini 887 B
[DATASET]
dataset_package = decentralizepy.datasets.CIFAR10
dataset_class = CIFAR10
model_class = LeNet
train_dir = /mnt/nfs/shared/CIFAR
test_dir = /mnt/nfs/shared/CIFAR
; python list of fractions below
sizes =
random_seed = 99
partition_niid = True
shards = 4
[OPTIMIZER_PARAMS]
optimizer_package = torch.optim
optimizer_class = SGD
lr = 0.001
[TRAIN_PARAMS]
training_package = decentralizepy.training.Training
training_class = Training
rounds = 65
full_epochs = False
batch_size = 8
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 = 0.5
wavelet=sym2
level= 4
accumulation = True
accumulate_averaging_changes = True