def test_get_fit_requirements(self):
dataset_properties = {
'numerical_columns': [],
'categorical_columns': []
}
pipeline = TabularClassificationPipeline(
dataset_properties=dataset_properties)
fit_requirements = pipeline.get_fit_requirements()
# check if fit requirements is a list of FitRequirement named tuples
self.assertIsInstance(fit_requirements, list)
for requirement in fit_requirements:
self.assertIsInstance(requirement, FitRequirement)
def test_get_fit_requirements(self, fit_dictionary_tabular):
dataset_properties = {
'numerical_columns': [],
'categorical_columns': [],
'task_type': 'tabular_classification'
}
pipeline = TabularClassificationPipeline(
dataset_properties=dataset_properties)
fit_requirements = pipeline.get_fit_requirements()
# check if fit requirements is a list of FitRequirement named tuples
assert isinstance(fit_requirements, list)
for requirement in fit_requirements:
assert isinstance(requirement, FitRequirement)