def main(args):
logger = Logger(args.output_dir)
args.logger = logger
trainer = Trainer(args)
evaluator = Evaluator(trainer)
for i_epoch in range(0, args.epoch + 1):
# train
log_dict = {
'i_epoch': i_epoch,
'train_losses': [], # per batch
'test_bleus': []
} # per sample
trainer.train_one_epoch(log_dict)
# evaluation and logging
logger.log('%d th epoch' % i_epoch)
evaluator.bleu(log_dict)
evaluator.sample_translation()
log_dict_mean = {
'i_epoch': log_dict['i_epoch'],
'train_loss': np.mean(log_dict['train_losses']),
'test_bleu': np.mean(log_dict['test_bleus'])
}
logger.dump(log_dict_mean)
trainer.save_best(log_dict_mean)
logger.log('-' * 10)
