def test(self):
self.model.eval() # set to eval mode
self.model = self.model.to(device)
predictions = TestLanguageModel.prediction(
fixtures_pred['inp'], self.model) # get predictions
self.predictions.append(predictions)
generated_logits = TestLanguageModel.generation(
fixtures_gen, 10, self.model) # generated predictions for 10 words
generated_logits_test = TestLanguageModel.generation(
fixtures_gen_test, 10, self.model)
nll = test_prediction(predictions, fixtures_pred['out'])
generated = test_generation(fixtures_gen, generated_logits, vocab)
generated_test = test_generation(fixtures_gen_test,
generated_logits_test, vocab)
self.val_losses.append(nll)
self.generated.append(generated)
self.generated_test.append(generated_test)
self.generated_logits.append(generated_logits)
self.generated_logits_test.append(generated_logits_test)
# generate predictions for test data
predictions_test = TestLanguageModel.prediction(
fixtures_pred_test['inp'], self.model) # get predictions
self.predictions_test.append(predictions_test)
print('[VAL] Epoch [%d/%d] Loss: %.4f' %
(self.epochs + 1, self.max_epochs, nll))
return nll
def test(self):
# don't change these
self.model.eval() # set to eval mode
predictions = TestLanguageModel.prediction(
fixtures_pred['inp'], self.model) # get predictions
print(predictions.shape)
self.predictions.append(predictions)
nll = test_prediction(predictions, fixtures_pred['out'])
generated_logits = TestLanguageModel.generation(
fixtures_gen, 10, self.model) # predictions for 20 words
generated_logits_test = TestLanguageModel.generation(
fixtures_gen_test, 10, self.model) # predictions for 20 words
generated = test_generation(fixtures_gen, generated_logits, vocab)
generated_test = test_generation(fixtures_gen_test,
generated_logits_test, vocab)
self.val_losses.append(nll)
self.generated.append(generated)
self.generated_test.append(generated_test)
self.generated_logits.append(generated_logits)
self.generated_logits_test.append(generated_logits_test)
# generate predictions for test data
predictions_test = TestLanguageModel.prediction(
fixtures_pred_test['inp'], self.model) # get predictions
self.predictions_test.append(predictions_test)
print('[VAL] Epoch [%d/%d] NLL: %.4f' %
(self.epochs, self.max_epochs, nll))
return nll
def test(self):
self.model.eval() # set to eval mode
predictions = TestLanguageModel.prediction(
fixtures_pred['inp'], self.model) # get predictions
nll = test_prediction(predictions, fixtures_pred['out'])
print('[VAL] Epoch [%d/%d] NLL: %.4f' %
(self.epochs, self.max_epochs, nll))
return nll