torch.manual_seed(config.seed); np.random.seed(config.seed)
# Initialize model
model = LanguageModel(config=config) #CTCModel(config=config)
print(model)
# Generate datasets
train_dataset, valid_dataset, test_dataset = get_text_datasets(config)
trainer = Trainer(model=model, config=config)
if restart: trainer.load_checkpoint()
# Train the final model
if train:
for epoch in range(config.num_epochs):
print("========= Epoch %d of %d =========" % (epoch+1, config.num_epochs))
train_loss = trainer.train(train_dataset)
model = model.cpu()
valid_loss = trainer.test(valid_dataset, set="valid")
if torch.cuda.is_available(): model = model.cuda()
print("========= Results: epoch %d of %d =========" % (epoch+1, config.num_epochs))
print("train loss: %.2f| valid loss: %.2f\n" % (train_loss, valid_loss) )
trainer.save_checkpoint()
trainer.load_best_model()
test_loss = trainer.test(test_dataset, set="test")
print("========= Test results =========")
print("test loss: %.2f \n" % (test_WER, test_loss) )
trainer.save_checkpoint(WER=valid_WER_surprisal,
sampling_method="surprisal")
print("========= Results: epoch %d of %d =========" %
(epoch + 1, config.num_epochs))
print("train WER: %.2f| train loss: %.2f| train FLOPs: %d" %
(train_WER * 100, train_loss, train_FLOPs_mean))
print(
"valid WER: %.2f| valid loss: %.2f| valid FLOPs: %d (random sampling)"
% (valid_WER_random * 100, valid_loss_random,
valid_FLOPs_mean_random))
print(
"valid WER: %.2f| valid loss: %.2f| valid FLOPs: %d (surprisal sampling)\n"
% (valid_WER_surprisal * 100, valid_loss_surprisal,
valid_FLOPs_mean_surprisal))
trainer.load_best_model(sampling_method="random")
model.sample_based_on_surprisal_during_testing = False
test_WER_random, test_loss_random, test_FLOPs_mean_random, test_FLOPs_std_random = trainer.test(
test_dataset, set="test")
trainer.load_best_model(sampling_method="surprisal")
model.sample_based_on_surprisal_during_testing = True
test_WER_surprisal, test_loss_surprisal, test_FLOPs_mean_surprisal, test_FLOPs_std_surprisal = trainer.test(
test_dataset, set="test")
print("========= Test results =========")
print("test WER: %.2f| test loss: %.2f| test FLOPs: %d (random sampling)" %
(test_WER_random * 100, test_loss_random, test_FLOPs_mean_random))
print(
"test WER: %.2f| test loss: %.2f| test FLOPs: %d (surprisal sampling)\n"
% (test_WER_surprisal * 100, test_loss_surprisal,
test_FLOPs_mean_surprisal))
