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run_figure15.sh
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run_figure15.sh
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#!/bin/bash
# caltech_birds2011
python3 profiler.py --model_name resnet50 \
--num_classes 200
python3 main.py --model_name resnet50 \
--dataset_name caltech_birds2011 \
--train_type elastic_training \
--run_name CUB200_ElasticTrainer
python3 main.py --model_name resnet50 \
--dataset_name caltech_birds2011 \
--train_type full_training \
--run_name CUB200_Full_training
python3 main.py --model_name resnet50 \
--dataset_name caltech_birds2011 \
--train_type traditional_tl_training \
--run_name CUB200_Traditional_TL
python3 main.py --model_name resnet50 \
--dataset_name caltech_birds2011 \
--train_type bn_plus_bias_training \
--run_name CUB200_BN+Bias
python3 plot_curves.py --x_tag wall_time \
--y_tag test/accuracy \
--single False \
--elastic_trainer_path CUB200_ElasticTrainer \
--full_training_path CUB200_Full_training \
--traditional_tl_path CUB200_Traditional_TL \
--bn_plus_bias_path CUB200_BN+Bias \
--figure_id 1 \
--figure_name Figure_15_a.pdf
python3 plot_curves.py --x_tag wall_time \
--y_tag test/classification_loss \
--single False \
--elastic_trainer_path CUB200_ElasticTrainer \
--full_training_path CUB200_Full_training \
--traditional_tl_path CUB200_Traditional_TL \
--bn_plus_bias_path CUB200_BN+Bias \
--figure_id 2 \
--figure_name Figure_15_d.pdf
# oxford_iiit_pet
python3 profiler.py --model_name resnet50 \
--num_classes 37
python3 main.py --model_name resnet50 \
--dataset_name oxford_iiit_pet \
--train_type elastic_training \
--run_name PET37_ElasticTrainer
python3 main.py --model_name resnet50 \
--dataset_name oxford_iiit_pet \
--train_type full_training \
--run_name PET37_Full_training
python3 main.py --model_name resnet50 \
--dataset_name oxford_iiit_pet \
--train_type traditional_tl_training \
--run_name PET37_Traditional_TL
python3 main.py --model_name resnet50 \
--dataset_name oxford_iiit_pet \
--train_type bn_plus_bias_training \
--run_name PET37_BN+Bias
python3 plot_curves.py --x_tag wall_time \
--y_tag test/accuracy \
--single False \
--elastic_trainer_path PET37_ElasticTrainer \
--full_training_path PET37_Full_training \
--traditional_tl_path PET37_Traditional_TL \
--bn_plus_bias_path PET37_BN+Bias \
--figure_id 3 \
--figure_name Figure_15_b.pdf
python3 plot_curves.py --x_tag wall_time \
--y_tag test/classification_loss \
--single False \
--elastic_trainer_path PET37_ElasticTrainer \
--full_training_path PET37_Full_training \
--traditional_tl_path PET37_Traditional_TL \
--bn_plus_bias_path PET37_BN+Bias \
--figure_id 4 \
--figure_name Figure_15_e.pdf
# stanford_dogs
python3 profiler.py --model_name resnet50 \
--num_classes 120
python3 main.py --model_name resnet50 \
--dataset_name stanford_dogs \
--train_type elastic_training \
--run_name DOG120_ElasticTrainer
python3 main.py --model_name resnet50 \
--dataset_name stanford_dogs \
--train_type full_training \
--run_name DOG120_Full_training
python3 main.py --model_name resnet50 \
--dataset_name stanford_dogs \
--train_type traditional_tl_training \
--run_name DOG120_Traditional_TL
python3 main.py --model_name resnet50 \
--dataset_name stanford_dogs \
--train_type bn_plus_bias_training \
--run_name DOG120_BN+Bias
python3 plot_curves.py --x_tag wall_time \
--y_tag test/accuracy \
--single False \
--elastic_trainer_path DOG120_ElasticTrainer \
--full_training_path DOG120_Full_training \
--traditional_tl_path DOG120_Traditional_TL \
--bn_plus_bias_path DOG120_BN+Bias \
--figure_id 5 \
--figure_name Figure_15_c.pdf
python3 plot_curves.py --x_tag wall_time \
--y_tag test/classification_loss \
--single False \
--elastic_trainer_path DOG120_ElasticTrainer \
--full_training_path DOG120_Full_training \
--traditional_tl_path DOG120_Traditional_TL \
--bn_plus_bias_path DOG120_BN+Bias \
--figure_id 6 \
--figure_name Figure_15_f.pdf