| from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint | |
| from warnings import filterwarnings | |
| filterwarnings('ignore') | |
| """ Trainer """ | |
| async def train(dict configuration, X_train, y_train, X_test, y_test): | |
| cdef object early_stopping = EarlyStopping( | |
| monitor = 'val_loss', | |
| patience = 5, | |
| mode = 'min' | |
| ) | |
| cdef object model_checkpoint = ModelCheckpoint( | |
| filepath = configuration['model_file'], | |
| save_best_only = True, | |
| monitor = 'val_loss', | |
| mode = 'min' | |
| ) | |
| cdef object history = configuration['model'].fit( | |
| X_train, y_train, | |
| epochs = configuration['epochs'], | |
| batch_size = configuration['batch_size'], | |
| validation_data = (X_test, y_test), | |
| callbacks = [ early_stopping, model_checkpoint ] | |
| ) | |
| return history | |