10 lines
1.1 KiB
Bash
10 lines
1.1 KiB
Bash
R=400
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E=graph_exp
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P=mini_graph_dc
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D=0
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s=12345
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mkdir $E/s$s
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CUDA_VISIBLE_DEVICES=$D python federatedscope/main.py --cfg scripts/example_configs/pfedhpo/$P/pfedhpo.yaml --client_cfg federatedscope/gfl/baseline/mini_graph_dc/fedavg_per_client.yaml hpo.pfedhpo.train_fl True hpo.pfedhpo.train_anchor True federate.sample_client_rate 1.0 federate.total_round_num $R seed $s outdir $E/s$s hpo.working_folder $E/s$s/working device 0
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CUDA_VISIBLE_DEVICES=$D python federatedscope/main.py --cfg scripts/example_configs/pfedhpo/$P/pfedhpo.yaml --client_cfg federatedscope/gfl/baseline/mini_graph_dc/fedavg_per_client.yaml hpo.pfedhpo.train_fl False hpo.pfedhpo.target_fl_total_round $R seed $s outdir $E/s$s hpo.working_folder $E/s$s/working device 0
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CUDA_VISIBLE_DEVICES=$D python federatedscope/main.py --cfg scripts/example_configs/pfedhpo/$P/pfedhpo.yaml --client_cfg federatedscope/gfl/baseline/mini_graph_dc/fedavg_per_client.yaml hpo.pfedhpo.train_fl True federate.total_round_num $R seed $s outdir $E/s$s hpo.working_folder $E/s$s/working device 0
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#rm -rf $E/s$s/working/temp_model_round_* |