def _calc_and_save_train_metrics(nn_model, train_subset, avg_loss):
train_metrics = dict()
train_metrics['train_perplexity'] = calculate_model_mean_perplexity(nn_model, train_subset)
train_metrics['train_loss'] = avg_loss
save_metrics(train_metrics)
_logger.info('Current train perplexity: %s' % train_metrics['train_perplexity'])
return train_metrics
def _calc_and_save_val_metrics(nn_model,
context_sensitive_val_subset,
context_free_val,
prediction_mode=PREDICTION_MODE_FOR_TESTS):
val_metrics = calculate_and_log_val_metrics(nn_model, context_sensitive_val_subset, context_free_val,
prediction_mode)
save_metrics(val_metrics)
return val_metrics