class TestParallelTextClassifier(TestCase):
def setUp(self):
src_voc = Vocabulary()
trg_voc = Vocabulary()
for tok in "I am Philip".split():
src_voc[tok]
for tok in "私 は フィリップ です".split():
trg_voc[tok]
self.model = ParallelTextClassifier(Args(), src_voc, trg_voc, optimizer=optimizers.SGD())
self.src_voc = src_voc
self.trg_voc = trg_voc
def test_read_write(self):
model = "/tmp/chainer-test/text/model.temp"
X, Y = self.src_voc, self.trg_voc
# Train with 1 example
inp = np.array([[X["Philip"], X["I"]]], dtype=np.int32)
out = np.array([[Y["フィリップ"], Y["私"]]], dtype=np.int32)
self.model.train(inp, out)
# Save
serializer = ModelSerializer(model)
serializer.save(self.model)
# Load
model1 = ParallelTextClassifier(InitArgs(model))
# Check
self.assertModelEqual(self.model._model, model1._model)
