from eICU_preprocessing.split_train_test import create_folder
from models.run_lstm import BaselineLSTM
from models.initialise_arguments import initialise_lstm_arguments
from models.final_experiment_scripts.best_hyperparameters import best_lstm
if __name__ == '__main__':
c = initialise_lstm_arguments()
c['exp_name'] = 'StandardLSTM'
c['dataset'] = 'MIMIC'
c['task'] = 'mortality'
c = best_lstm(c)
log_folder_path = create_folder('models/experiments/final/MIMIC/mortality',
c.exp_name)
baseline_lstm = BaselineLSTM(
config=c,
n_epochs=c.n_epochs,
name=c.exp_name,
base_dir=log_folder_path,
explogger_kwargs={'folder_format': '%Y-%m-%d_%H%M%S{run_number}'})
baseline_lstm.run()
import os
from models.run_lstm import BaselineLSTM
from models.initialise_arguments import initialise_lstm_arguments
from models.final_experiment_scripts.best_hyperparameters import best_lstm
if __name__ == '__main__':
c = initialise_lstm_arguments()
c['exp_name'] = 'StandardLSTM'
c['dataset'] = 'eICU'
c['task'] = 'multitask'
c = best_lstm(c)
log_folder_path = 'models/experiments/final/{}/{}/{}'.format(
c['dataset'], c['task'], c['exp_name'])
sub_directories = next(os.walk(log_folder_path))[1]
for sub_dir in sub_directories:
baseline_lstm = BaselineLSTM(
config=c,
n_epochs=c.n_epochs,
name=c.exp_name,
base_dir=log_folder_path,
explogger_kwargs={'folder_format': '%Y-%m-%d_%H%M%S{run_number}'},
resume='{}/{}'.format(log_folder_path, sub_dir))
baseline_lstm.run_test()