def test_customize_schema(self):
from lale.lib.sklearn import LogisticRegression
pipeline = LogisticRegression.customize_schema(
solver={"enum": ["lbfgs", "liblinear"], "default": "liblinear"},
tol={
"type": "number",
"minimum": 0.00001,
"maximum": 0.1,
"default": 0.0001,
},
)(solver="lbfgs")
expected = """from sklearn.linear_model import LogisticRegression
import lale
lale.wrap_imported_operators()
pipeline = LogisticRegression.customize_schema(
solver={"enum": ["lbfgs", "liblinear"], "default": "liblinear"},
tol={
"type": "number",
"minimum": 1e-05,
"maximum": 0.1,
"default": 0.0001,
},
)(solver="lbfgs")"""
self._roundtrip(expected, pipeline.pretty_print(customize_schema=True))
def test_user_operator_in_toplevel_module(self):
import importlib
import os.path
import sys
import tempfile
with tempfile.NamedTemporaryFile(mode="w",
suffix=".py") as tmp_py_file:
file_contents = """import numpy as np
import lale.operators
class _MockClassifierImpl:
def __init__(self, int_hp=0):
self.int_hp = int_hp
def fit(self, X, y):
self.some_y = list(y)[0]
def predict(self, X):
return self.some_y
MockClassifier = lale.operators.make_operator(_MockClassifierImpl)
"""
tmp_py_file.write(file_contents)
tmp_py_file.flush()
dir_name = os.path.dirname(tmp_py_file.name)
old_pythonpath = sys.path
try:
sys.path.append(dir_name)
module_name = os.path.basename(tmp_py_file.name)[:-len(".py")]
module = importlib.import_module(module_name)
MockClf = getattr(module, "MockClassifier")
self.assertIsInstance(MockClf,
lale.operators.PlannedIndividualOp)
self.assertEqual(MockClf.name(), "MockClassifier")
pipeline = MockClf(int_hp=42)
expected = f"""from {module_name} import MockClassifier as MockClf
import lale
lale.wrap_imported_operators()
pipeline = MockClf(int_hp=42)"""
self._roundtrip(expected, pipeline.pretty_print())
finally:
sys.path = old_pythonpath