def test_whenInstanciatedWithPath_thenShouldLoadFasttextModel(self):
with patch(
'deepparse.embeddings_models.fasttext_embeddings_model.load_fasttext_embeddings',
return_value=self.model) as loader:
self.embeddings_model = FastTextEmbeddingsModel(self.a_path)
loader.assert_called_with(self.a_path)
def test_whenCalledToEmbed_thenShouldCallLoadedModel(self):
with patch("deepparse.embeddings_models.fasttext_embeddings_model.load_fasttext_embeddings",
return_value=self.model):
self.embeddings_model = FastTextEmbeddingsModel(self.a_path, verbose=self.verbose)
self.embeddings_model(self.a_word)
self.model.__getitem__.assert_called_with(self.a_word)
def test_whenInstantiatedWithPath_thenShouldLoadFasttextModel(self):
with patch(
"deepparse.embeddings_models.fasttext_embeddings_model.load_fasttext_embeddings",
return_value=self.model,
) as loader:
_ = FastTextEmbeddingsModel(self.a_path, verbose=self.verbose)
loader.assert_called_with(self.a_path)
def test_givenADimOf9Windows_whenAskDimProperty_thenReturnProperDim(self):
with patch(
"deepparse.embeddings_models.fasttext_embeddings_model.load_facebook_vectors",
return_value=self.model,
):
embeddings_model = FastTextEmbeddingsModel(self.a_path,
verbose=self.verbose)
actual = embeddings_model.dim
expected = self.dim
self.assertEqual(actual, expected)
def test_whenInstantiatedOnMacOS_thenShouldLoadFasttextModel(
self, platform_mock):
platform_mock.system().__eq__.return_value = False
with patch(
"deepparse.embeddings_models.fasttext_embeddings_model.load_fasttext_embeddings",
return_value=self.model,
) as loader:
with platform_mock:
self.embeddings_model = FastTextEmbeddingsModel(
self.a_path, verbose=self.verbose)
loader.assert_called_with(self.a_path)
def test_givenAWindowsOS_whenFasttextModelCollateFnInDataLoaderNumWorkers2_thenWorkProperly(
self,
):
model = FastTextEmbeddingsModel(self.a_fasttext_model_path, 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_givenAWindowsOS_whenFasttextModelCollateFnInDataLoaderForNotWindows_thenRaiseError(self, platform_mock):
platform_mock.system().__eq__.return_value = True
with platform_mock:
model = FastTextEmbeddingsModel(self.a_fasttext_model_path, verbose=self.verbose)
data_transform = MockedDataTransform(model)
data_loader = DataLoader(
self.training_container,
collate_fn=data_transform.collate_fn,
batch_size=32,
num_workers=0,
)
with self.assertRaises(TypeError):
for _ in data_loader:
pass
def test_givenAWindowsOS_whenFasttextModelCollateFnInDataLoaderEvenWithWindowsSetup_thenWorkProperly(
self, platform_mock
):
platform_mock.system().__eq__.return_value = True
with platform_mock:
model = FastTextEmbeddingsModel(self.a_fasttext_model_path, verbose=self.verbose)
data_transform = MockedDataTransform(model)
data_loader = DataLoader(
self.training_container,
collate_fn=data_transform.collate_fn,
batch_size=32,
num_workers=0,
)
dataset = []
for data in data_loader:
dataset.append(data)
self.assertGreater(len(dataset), 0)
def test_givenANotWindowsOS_whenFasttextModelInit_thenLoadWithProperFunction(self):
model = FastTextEmbeddingsModel(self.a_fasttext_model_path, verbose=self.verbose)
self.assertIsInstance(model.model, _FastText)