def test_assigned_ids(self):
search_space = search_space_reader.create_search_space(
"res/search_space/ml-plan-ul.json")
c1 = search_space.get_component_by_name(
"sklearn.pipeline.make_pipeline")
c2 = search_space.get_component_by_name("sklearn.pipeline.make_union")
components = [c1, c2]
used_ids = []
for component in components:
for ri in component.get_required_interfaces():
assert "id" in ri
assert ri["id"] not in used_ids
used_ids.append(ri["id"])
def __init__(self, search_config, optimizers):
self.config = search_config
self.search_space = create_search_space(
*self.config.search_space_files)
self.stop_event = Event()
self.graph_generator = MctsGraphGenerator(
self.search_space,
self.config.start_component_name,
optimizers,
self.config.pipeline_evaluator_class,
self.stop_event,
self.config.timeout_for_pipeline_evaluation,
self.config.data_x,
self.config.data_y,
self.config.seed,
self.config.numpy_random_state,
)
self.root_node = self.graph_generator.get_root_node()
self.random_selection = self.config.random_node_selection
from frankensteins_automl.search_space import search_space_reader
search_space = search_space_reader.create_search_space(
"res/search_space/scikit-learn-classifiers-tpot.json")
class TestSearchSpaceReader:
def test_component_retrievement(self):
component = search_space.get_component_by_name(
"sklearn.naive_bayes.GaussianNB")
assert component.get_name() == "sklearn.naive_bayes.GaussianNB"
def test_non_existing_component_retrievement(self):
assert search_space.get_component_by_name("abc.def.GHI") is None
def test_interface_retrievement(self):
providing_components = search_space.get_components_providing_interface(
"BaseLearner")
providing_components_names = []
for component in providing_components:
providing_components_names.append(component.get_name())
components = [
"sklearn.naive_bayes.GaussianNB",
"sklearn.naive_bayes.BernoulliNB",
"sklearn.naive_bayes.MultinomialNB",
"sklearn.tree.DecisionTreeClassifier",
"sklearn.ensemble.RandomForestClassifier",
"sklearn.ensemble.GradientBoostingClassifier",
"sklearn.neighbors.KNeighborsClassifier",
"sklearn.svm.LinearSVC",
]
from time import perf_counter
from frankensteins_automl.search_space.search_space_graph import (
SearchSpaceRestProblem, )
from frankensteins_automl.machine_learning.arff_reader import read_arff
from frankensteins_automl.machine_learning.pipeline.pipeline_evaluator import (
PipelineEvaluator, )
from frankensteins_automl.search_space.search_space_reader import (
create_search_space, )
search_space = create_search_space(
"res/search_space/ml-plan-ul.json",
"res/search_space/scikit-learn-classifiers-tpot.json",
"res/search_space/scikit-learn-preprocessors-tpot.json",
)
c1 = search_space.get_component_by_name("sklearn.pipeline.make_pipeline")
c2 = search_space.get_component_by_name("sklearn.preprocessing.Binarizer")
c3 = search_space.get_component_by_name("sklearn.tree.DecisionTreeClassifier")
required_interfaces = [
{
"interface": {
"name": "AbstractPreprocessor",
"construction_key": 0,
"id": c1.get_required_interfaces()[0]["id"],
},
"satisfied": True,
"component_id": "a3f1fa38-0979-11ea-ba87-309c23b50ce0",
"satisfied_with": "a3f20a5a-0979-11ea-ba87-309c23b50ce0",
},
{
"interface": {
"name": "BasicClassifier",
def test_non_json_path(self):
assert search_space_reader.create_search_space("README.md") is None
def test_non_string_path(self):
assert search_space_reader.create_search_space(123) is None
def test_json_parsing(self):
search_space = search_space_reader.create_search_space(
"res/search_space/ml-plan-ul.json")
assert isinstance(search_space, SearchSpace)
