def test_cat_to_num_get_config_has_all_attributes():
block = blocks.CategoricalToNumerical()
config = block.get_config()
assert test_utils.get_func_args(
blocks.CategoricalToNumerical.__init__).issubset(config.keys())
def test_cat_to_num_build_return_tensor():
block = blocks.CategoricalToNumerical()
block.column_names = ["a"]
block.column_types = {"a": "num"}
outputs = block.build(keras_tuner.HyperParameters(),
tf.keras.Input(shape=(1, ), dtype=tf.string))
assert len(nest.flatten(outputs)) == 1
def test_cat_to_num_build_return_tensor():
block = blocks.CategoricalToNumerical()
block.column_names = ['a']
block.column_types = {'a': 'num'}
outputs = block.build(kerastuner.HyperParameters(),
tf.keras.Input(shape=(1, ), dtype=tf.string))
assert len(nest.flatten(outputs)) == 1
assert isinstance(nest.flatten(outputs)[0], tf.Tensor)
def test_cat_to_num_deserialize_to_cat_to_num():
serialized_block = blocks.serialize(blocks.CategoricalToNumerical())
block = blocks.deserialize(serialized_block)
assert isinstance(block, blocks.CategoricalToNumerical)