62 lines
1.1 KiB
YAML
62 lines
1.1 KiB
YAML
use_gpu: True
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device: 3
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outdir: bo_rf_wrap_femnist_avg
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early_stop:
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patience: 100
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seed: 12345
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federate:
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mode: standalone
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total_round_num: 500
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sample_client_rate: 1.0
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share_local_model: True
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online_aggr: True
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use_diff: True
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data:
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root: data/
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type: femnist
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splits: [0.6,0.2,0.2]
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subsample: 0.05
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transform: [['ToTensor'], ['Normalize', {'mean': [0.1307], 'std': [0.3081]}]]
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dataloader:
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batch_size: 16
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model:
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type: convnet2
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hidden: 2048
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out_channels: 62
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dropout: 0.5
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train:
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batch_or_epoch: epoch
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local_update_steps: 1
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optimizer:
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lr: 0.01
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weight_decay: 0.0
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grad:
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grad_clip: 5.0
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criterion:
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type: CrossEntropyLoss
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trainer:
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type: cvtrainer
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eval:
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freq: 1
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metrics: ['acc', 'correct', 'f1']
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split: ['test', 'val', 'train']
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hpo:
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scheduler: wrap_bo_rf
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num_workers: 0
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init_cand_num: 100
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ss: 'scripts/example_configs/femnist/avg/ss.yaml'
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sha:
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budgets: [ 50, 50 ]
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elim_rate: 3
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iter: 50
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table:
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num: 27
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fedex:
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sched: 'aggressive'
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use: True
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diff: False
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eta0: -1.0
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gamma: 0.0
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metric: 'client_summarized_weighted_avg.val_avg_loss'
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working_folder: bo_rf_wrap_femnist_avg
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