model            : conv4_bn
dataset          : cifar10
data_root        : data
log_root         : log
model_root       : checkpoint
load_checkpoint  : ./model/default/model.pth
affix            : test
num_clients      : 100
schedulingsize   : 10
batch_size       : 64
comm_rounds      : 500
learning_rate    : 0.001
lr_decay         : 1
momentum         : 0.9
gpu              : 0
seed             : 1
alpha            : 0.2
th_coeff         : 0.002
mask             : 1
weight_decay     : 0.0
local_epoch      : 5
penalty_scheduler : 1
th_update        : 1
log_folder       : log\test
model_folder     : checkpoint\test
masked_Conv4_BN(
  (conv1): MaskedConv2d()
  (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (conv2): MaskedConv2d()
  (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (conv3): MaskedConv2d()
  (bn3): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (conv4): MaskedConv2d()
  (bn4): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (dense1): MaskedMLP()
  (bn5): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (dense2): MaskedMLP()
  (bn6): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (dense3): MaskedMLP()
)
------------------------------Epoch start------------------------------
round: 0, avg_acc: 14.812, avg_density: 1.000, spent: 24.91
------------------------------Epoch start------------------------------
round: 1, avg_acc: 18.179, avg_density: 1.000, spent: 16.48
------------------------------Epoch start------------------------------
round: 2, avg_acc: 23.885, avg_density: 1.000, spent: 21.59
------------------------------Epoch start------------------------------
