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run_trains.sh
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#!/bin/bash
#### new datasets for training ###
# dataset internal
#python main_train.py --config config_lstm.json --dataset "/data/track-ml/eramia/results/eta_n0.5-0.5_phi_n0.5-0.5.csv" --cylindrical False
#python main_train.py --config config_lstm.json --dataset "/data/track-ml/eramia/results/eta_n0.5-0.5_phi_n0.5-0.5.csv" --cylindrical True
# dataset intermediary
#python main_train.py --config config_lstm.json --dataset "/data/track-ml/eramia/results/eta_0.0-1.0_phi_0.0-1.0.csv" --cylindrical False
#python main_train.py --config config_lstm.json --dataset "/data/track-ml/eramia/results/eta_0.0-1.0_phi_0.0-1.0.csv" --cylindrical True
# dataset external
#python main_train.py --config config_lstm.json --dataset "/data/track-ml/eramia/dataset/eta_n0.5-0.5_phi_ninf-pinf.csv" --cylindrical True
#python main_train.py --config config_lstm.json --dataset "/data/track-ml/eramia/dataset/eta_n0.5-0.5_phi_ninf-pinf.csv" --cylindrical False
# dataset internal with two configurations and models differents
python main_train.py --config config_cnn_parallel_internal.json --dataset "dataset/eta_n0.5-0.5_phi_n0.5-0.5_internal_short1.csv" --cylindrical True --load False
python main_train.py --config config_cnn_internal.json --dataset "dataset/eta_n0.5-0.5_phi_n0.5-0.5_internal_short1.csv" --cylindrical True --load False