def _build_transforms(transforms: Union[Params, List[Params]]):
if isinstance(transforms, list):
transforms = [
RegistrableTransform.from_params(param) for param in transforms
]
else:
transforms = RegistrableTransform.from_params(transforms)
return transforms
def test_registrable_transform(self) -> None:
registered_list = set(
Registrable._registry[RegistrableTransform].keys())
assert registered_list == set([
"standard-scaler",
"min-max-scaler",
"label-encoder",
"logarithmer",
"flatten",
"hashname",
])
assert (RegistrableTransform.by_name("standard-scaler").__name__ ==
"StandardScaler")
assert RegistrableTransform.by_name(
"min-max-scaler").__name__ == "MinMaxScaler"
assert RegistrableTransform.by_name(
"label-encoder").__name__ == "LabelEncoder"
assert RegistrableTransform.by_name(
"logarithmer").__name__ == "Logarithmer"
assert RegistrableTransform.by_name(
"flatten").__name__ == "FlattenTransformer"
assert RegistrableTransform.by_name("hashname").__name__ == "HashName"
def test_flatten(self):
params = Params.from_file(self.FIXTURES_ROOT / "transforms" /
"preprocessing" / "flatten.jsonnet")
transform = RegistrableTransform.from_params(params=params)
assert isinstance(transform, FlattenTransformer)
def test_logarithmer(self):
params = Params.from_file(self.FIXTURES_ROOT / "transforms" /
"preprocessing" / "logarithmer.jsonnet")
transform = RegistrableTransform.from_params(params=params)
assert isinstance(transform, Logarithmer)
def test_min_max_scalar(self):
params = Params.from_file(self.FIXTURES_ROOT / "transforms" /
"preprocessing" / "min_max_scalar.jsonnet")
transform = RegistrableTransform.from_params(params=params)
assert isinstance(transform, MinMaxScaler)
def test_hash_name_from_params(self):
params = Params.from_file(self.FIXTURES_ROOT / "transforms" /
"hash_name" / "hash_name.jsonnet")
transform = RegistrableTransform.from_params(params=params)
assert isinstance(transform, HashName)