python run.py\
 --global-lr "${g_lr}"\
 --local-lr "1"\
 --run-id "qsgd_${g_lr}_${job_id}"\
 --logfile "../logs/qsgd_${g_lr}.txt"\
 --out "qsgd_${g_lr}.bin"\
 --algorithm "dcgd"\
 --rounds "10000"\
 --gpu "0"\
 --comment ""\
 --client-sampling-type "uniform"\
 --num-clients-per-round "10"\
 --global-optimiser "sgd"\
 --global-weight-decay "0.0"\
 --number-of-local-iters "1"\
 --run-local-steps\
 --batch-size "600"\
 --local-optimiser "sgd"\
 --local-weight-decay "0.0"\
 --dataset "${dataset}"\
 --loss "crossentropy"\
 --model "tv_resnet18"\
 --per-round-clean-torch-cache \
 --turn-off-batch-normalization-and-dropout \
 --use-pretrained \
 --train-last-layer \
 --metric "top_1_acc"\
 --global-regulizer "cvx_l2norm_square_div_2" \
 --global-regulizer-alpha "0.0001" \
 --checkpoint-dir "../check_points"\
 --do-not-save-eval-checkpoints \
 --data-path "../data/"\
 --log-gpu-usage\
 --num-workers-train "4"\
 --num-workers-test "4"\
 --deterministic\
 --manual-init-seed "123"\
 --manual-runtime-seed "1"\
 --group-name ""\
 --eval-every "100"\
 --eval-async-threads "0"\
 --save-async-threads "0"\
 --threadpool-for-local-opt "0"\
 --algorithm-options "internal_sgd:sgd-multi,tau:10%"\
 --client-compressor "randk:5%"\
 --extra-track "full_gradient_norm_train,full_objective_value_train,full_gradient_norm_val,full_objective_value_val"\
 --allow-use-nv-tensorcores\
 --initialize-shifts-policy "zero"\
 --sort-dataset-by-class-before-split \
 --wandb-key "${wandb_key}"\
 --wandb-project-name "${wandb_project}"\
 --loglevel "debug"\
 --logfilter ".*"
