use_gpu: True
outdir: exp
device: 0
early_stop:
  patience: 0
federate:
  mode: standalone
  total_round_num: 10000
  client_num: 100
  sample_client_num: 5
  make_global_eval: True
  merge_test_data: True
fedopt:
  use: True
  optimizer:
    lr: 1.0
    weight_decay: 0.0
    momentum: 0.0
  annealing: True
data:
  root: data/
  type: 'CIFAR10@torchvision'
  splits: [1.0,0.0,0.0]
  num_workers: 0
  transform: [['RandomCrop', {'size': 32, 'padding': 4}], ['RandomHorizontalFlip'], ['ToTensor'], ['Normalize', {'mean': [0.4914, 0.4822, 0.4465], 'std': [0.2023, 0.1994, 0.2010]}]]
  test_transform: [['ToTensor'], ['Normalize', {'mean': [0.4914, 0.4822, 0.4465], 'std': [0.2023, 0.1994, 0.2010]}]]
  args: [{'download': True}]
  splitter: 'fedsam_cifar10_splitter'
  splitter_args: [{'alpha': 0.05}]
dataloader:
  batch_size: 64
model:
  type: fedsam_conv2
  out_channels: 10
  dropout: 0.0
criterion:
  type: CrossEntropyLoss
trainer:
  type: local_entropy_trainer
  local_entropy:
    gamma: 0.03
    inc_factor: 1.0001
    eps: 0.0001
    alpha: 0.75
train:
  batch_or_epoch: 'epoch'
  optimizer:
    lr: 0.1
    weight_decay: 0.0
    momentum: 0.0
eval:
  freq: 100
  metrics: ['acc', 'correct']
  best_res_update_round_wise_key: test_acc
  count_flops: False
hpo:
  scheduler: bo_gp
  num_workers: 0
  ss: 'scripts/wide_valley_exp_scripts/search_space_for_fedentsgd.yaml'
  sha:
    budgets: [10000, 10000]
    iter: 400
  metric: server_global_eval.test_acc
  working_folder: bo_gp_fedentsgd