run_stage4_experiments.sh 1.52 KB
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#!/bin/bash
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core_number=14
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walltime=1:00
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seeds='1 2 3 4 5 6 7'
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for dataset in california_housing
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#for dataset in kin8nm
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#for dataset in gamma
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#for dataset in breast_cancer diabetes diamonds california_housing boston linnerud steel-plates kr-vs-kp digits iris kin8nm lfw_pairs linnerud olivetti_faces wine spambase gamma
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do
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    oarsub -p "(gpu is null)" -n "$dataset base" -l /core=$core_number,walltime=1:00 "conda activate test_env && python code/train.py --dataset_name=$dataset --seeds $seeds --extraction_strategy=none --save_experiment_configuration 4 none_with_params --extracted_forest_size_stop=1 --extracted_forest_size_samples=30 --experiment_id=1 --models_dir=models/$dataset/stage4 --subsets_used train+dev,train+dev"
    oarsub -p "(gpu is null)" -n "$dataset random" -l /core=$core_number,walltime=1:00 "conda activate test_env && python code/train.py --dataset_name=$dataset --seeds $seeds --extraction_strategy=random --save_experiment_configuration 4 random_with_params --extracted_forest_size_stop=1 --extracted_forest_size_samples=30 --experiment_id=2 --models_dir=models/$dataset/stage4 --subsets_used train+dev,train+dev"
    oarsub -p "(gpu is null)" -n "$dataset omp" -l /core=$core_number,walltime=1:00 "conda activate test_env && python code/train.py --dataset_name=$dataset --seeds $seeds --extraction_strategy=omp --save_experiment_configuration 4 omp_with_params --extracted_forest_size_stop=1 --extracted_forest_size_samples=30 --experiment_id=3 --models_dir=models/$dataset/stage4 --subsets_used train+dev,train+dev"
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done