def test_whenInstanciatedWithPath_thenShouldLoadBPEmbModel(self):
with patch('deepparse.embeddings_models.bpemb_embeddings_model.BPEmb',
return_value=self.model) as loader:
self.embeddings_model = BPEmbEmbeddingsModel(lang="multi",
vs=100000,
dim=300)
loader.assert_called_with(lang="multi", vs=100000, dim=300)
def test_whenInstantiatedWithPath_thenShouldLoadBPEmbModel(self):
with patch(
"deepparse.embeddings_models.bpemb_embeddings_model.BPEmb",
return_value=self.model,
) as loader:
_ = BPEmbEmbeddingsModel(verbose=False)
loader.assert_called_with(lang="multi", vs=100000, dim=300)
def test_whenCalledToEmbed_thenShouldCallLoadedModel(self):
with patch('deepparse.embeddings_models.bpemb_embeddings_model.BPEmb',
return_value=self.model) as loader:
self.embeddings_model = BPEmbEmbeddingsModel(lang="multi",
vs=100000,
dim=300)
self.embeddings_model(self.a_word)
self.model.embed.assert_called_with(self.a_word)
def test_givenADimOf9_whenAskDimProperty_thenReturnProperDim(self):
with patch(
"deepparse.embeddings_models.bpemb_embeddings_model.BPEmb",
return_value=self.model,
):
embeddings_model = BPEmbEmbeddingsModel(verbose=False)
actual = embeddings_model.dim
expected = self.dim
self.assertEqual(actual, expected)
def test_whenCalledToEmbed_thenShouldCallLoadedModel(self):
with patch(
"deepparse.embeddings_models.bpemb_embeddings_model.BPEmb",
return_value=self.model,
):
embeddings_model = BPEmbEmbeddingsModel(verbose=False)
embeddings_model(self.a_word)
self.model.embed.assert_called_with(self.a_word)
def test_givenAWindowsOS_whenBPEmbModelCollateFnInDataLoaderNumWorkers2_thenWorkProperly(
self, ):
# we setup a smaller model for simplicity
model = BPEmbEmbeddingsModel(verbose=self.verbose)
data_transform = MockedDataTransform(model)
data_loader = DataLoader(
self.training_container,
collate_fn=data_transform.collate_fn,
batch_size=32,
num_workers=2,
)
dataset = []
for data in data_loader:
dataset.append(data)
self.assertGreater(len(dataset), 0)
def test_givenANotWindowsOS_whenBPEmbModelInit_thenLoadWithProperFunction(
self):
# we setup a smaller model for simplicity
model = BPEmbEmbeddingsModel(verbose=self.verbose)
self.assertIsInstance(model.model, BPEmb)