Exemplos de best_lstm em Python

Exemplo n.º 1

Arquivo: channel_wise_lstm.py Projeto: medical-projects/TPC-LoS-prediction

def get_hyperparam_config(dataset):

    c = initialise_lstm_arguments()
    c['mode'] = 'train'
    c['exp_name'] = 'ChannelwiseLSTM'
    if dataset == 'MIMIC':
        c['no_diag'] = True
    c['dataset'] = dataset
    c = best_lstm(
        c)  # get best hyperparams from standard LSTM for this dataset
    c['channelwise'] = True

    hidden_size_choice = list(
        int(x) for x in np.logspace(np.log2(4), np.log2(16), base=2, num=6))
    c['hidden_size'] = random.choice(hidden_size_choice)

    return c

Exemplo n.º 2

Arquivo: standard_lstm.py Projeto: medical-projects/TPC-LoS-prediction

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()