def test_get_all_params():
# not enough args
args = [
'--data_config', 'data.json',
'--model_config', 'model.json',
'--training_config', 'training.json']
with pytest.raises(ValueError):
utils.get_all_params(search_type='grid_search', args=args)
# too many args
args = [
'--data_config', 'data.json',
'--model_config', 'model.json',
'--training_config', 'training.json',
'--compute_config', 'compute.json',
'--model_class', 'ae']
with pytest.raises(ValueError):
utils.get_all_params(search_type='grid_search', args=args)
# correct args, substituted into sys.argv
data_config = os.path.join(
os.getcwd(), 'configs', 'data_default.json')
model_config = os.path.join(
os.getcwd(), 'configs', 'arhmm_jsons', 'arhmm_model.json')
training_config = os.path.join(
os.getcwd(), 'configs', 'arhmm_jsons', 'arhmm_training.json')
compute_config = os.path.join(
os.getcwd(), 'configs', 'arhmm_jsons', 'arhmm_compute.json')
args = [
'--data_config', data_config,
'--model_config', model_config,
'--training_config', training_config,
'--compute_config', compute_config]
old_sys_argv = sys.argv
sys.argv = [old_sys_argv[0]] + args
parser = utils.get_all_params(search_type='grid_search')
# test a couple args
assert parser.data_config == data_config
assert parser.model_config == model_config
assert parser.training_config == training_config
assert parser.compute_config == compute_config
save_file = os.path.join(version_dir, 'loss_training')
export_train_plots(hparams, 'train', loss_type='ll', save_file=save_file)
save_file = os.path.join(version_dir, 'loss_validation')
export_train_plots(hparams, 'val', loss_type='ll', save_file=save_file)
print('done')
# update hparams upon successful training
hparams['training_completed'] = True
export_hparams(hparams, exp)
# get rid of unneeded logging info
_clean_tt_dir(hparams)
if __name__ == '__main__':
hyperparams = get_all_params('grid_search')
if hyperparams.device == 'cuda' or hyperparams.device == 'gpu':
if hyperparams.device == 'gpu':
hyperparams.device = 'cuda'
gpu_ids = hyperparams.gpus_viz.split(';')
hyperparams.optimize_parallel_gpu(main, gpu_ids=gpu_ids)
elif hyperparams.device == 'cpu':
hyperparams.optimize_parallel_cpu(
main,
nb_trials=hyperparams.tt_n_cpu_trials,
nb_workers=hyperparams.tt_n_cpu_workers)