def test_higher_order_2(self):
self.maxDiff = None
from lale.lib.sklearn import VotingClassifier as Vote
from lale.lib.sklearn import KNeighborsClassifier as KNN
from lale.lib.sklearn import PCA
from lale.lib.sklearn import LogisticRegression as LR
from lale.json_operator import from_json
operator = Vote(estimators=[('knn',KNN), ('pipeline',PCA()>>LR)],
voting='soft')
json_expected = {
'class': 'lale.lib.sklearn.voting_classifier.VotingClassifierImpl',
'state': 'trainable',
'operator': 'VotingClassifier',
'is_frozen_trainable': True,
'label': 'Vote',
'documentation_url': 'https://lale.readthedocs.io/en/latest/modules/lale.lib.sklearn.voting_classifier.html',
'hyperparams': {
'estimators': [
('knn', {'$ref': '../steps/knn'}),
('pipeline', {'$ref': '../steps/pipeline'})],
'voting': 'soft'},
'steps': {
'knn': {
'class': 'lale.lib.sklearn.k_neighbors_classifier.KNeighborsClassifierImpl',
'state': 'planned',
'operator': 'KNeighborsClassifier', 'label': 'KNN',
'documentation_url': 'https://lale.readthedocs.io/en/latest/modules/lale.lib.sklearn.k_neighbors_classifier.html'},
'pipeline': {
'class': 'lale.operators.PlannedPipeline',
'state': 'planned',
'edges': [['pca', 'lr']],
'steps': {
'pca': {
'class': 'lale.lib.sklearn.pca.PCAImpl',
'state': 'trainable',
'operator': 'PCA', 'label': 'PCA',
'documentation_url': 'https://lale.readthedocs.io/en/latest/modules/lale.lib.sklearn.pca.html',
'hyperparams': {},
'is_frozen_trainable': False},
'lr': {
'class': 'lale.lib.sklearn.logistic_regression.LogisticRegressionImpl',
'state': 'planned',
'operator': 'LogisticRegression', 'label': 'LR',
'documentation_url': 'https://lale.readthedocs.io/en/latest/modules/lale.lib.sklearn.logistic_regression.html'}}}}}
json = operator.to_json()
self.assertEqual(json, json_expected)
operator_2 = from_json(json)
json_2 = operator_2.to_json()
self.assertEqual(json, json_2)
def test_higher_order_2(self):
from lale.lib.sklearn import VotingClassifier as Vote
from lale.lib.sklearn import KNeighborsClassifier as KNN
from lale.lib.sklearn import PCA
from lale.lib.sklearn import LogisticRegression as LR
pipeline = Vote(estimators=[('knn', KNN), ('pipeline', PCA() >> LR)],
voting='soft')
expected = """from lale.lib.sklearn import VotingClassifier as Vote
from lale.lib.sklearn import KNeighborsClassifier as KNN
from lale.lib.sklearn import PCA
from lale.lib.sklearn import LogisticRegression as LR
import lale
lale.wrap_imported_operators()
pipeline = Vote(estimators=[('knn', KNN), ('pipeline', PCA() >> LR)], voting='soft')"""
self._roundtrip(expected, lale.pretty_print.to_string(pipeline))
def test_higher_order_2(self):
from lale.lib.sklearn import PCA
from lale.lib.sklearn import KNeighborsClassifier as KNN
from lale.lib.sklearn import LogisticRegression as LR
from lale.lib.sklearn import VotingClassifier as Vote
pipeline = Vote(estimators=[("knn", KNN), ("pipeline", PCA() >> LR)],
voting="soft")
expected = """from sklearn.ensemble import VotingClassifier as Vote
from sklearn.neighbors import KNeighborsClassifier as KNN
from sklearn.decomposition import PCA
from sklearn.linear_model import LogisticRegression as LR
import lale
lale.wrap_imported_operators()
pipeline = Vote(
estimators=[("knn", KNN), ("pipeline", PCA() >> LR)], voting="soft"
)"""
self._roundtrip(expected, lale.pretty_print.to_string(pipeline))
def test_higher_order_2(self):
self.maxDiff = None
from lale.json_operator import from_json
from lale.lib.sklearn import PCA
from lale.lib.sklearn import KNeighborsClassifier as KNN
from lale.lib.sklearn import LogisticRegression as LR
from lale.lib.sklearn import VotingClassifier as Vote
operator = Vote(
estimators=[("knn", KNN), ("pipeline", PCA() >> LR)], voting="soft"
)
json_expected = {
"class": Vote.class_name(),
"state": "trainable",
"operator": "VotingClassifier",
"is_frozen_trainable": True,
"label": "Vote",
"documentation_url": "https://lale.readthedocs.io/en/latest/modules/lale.lib.sklearn.voting_classifier.html",
"hyperparams": {
"estimators": [
("knn", {"$ref": "../steps/knn"}),
("pipeline", {"$ref": "../steps/pipeline"}),
],
"voting": "soft",
},
"steps": {
"knn": {
"class": KNN.class_name(),
"state": "planned",
"operator": "KNeighborsClassifier",
"label": "KNN",
"documentation_url": "https://lale.readthedocs.io/en/latest/modules/lale.lib.sklearn.k_neighbors_classifier.html",
},
"pipeline": {
"class": "lale.operators.PlannedPipeline",
"state": "planned",
"edges": [["pca", "lr"]],
"steps": {
"pca": {
"class": PCA.class_name(),
"state": "trainable",
"operator": "PCA",
"label": "PCA",
"documentation_url": "https://lale.readthedocs.io/en/latest/modules/lale.lib.sklearn.pca.html",
"hyperparams": {},
"is_frozen_trainable": False,
},
"lr": {
"class": LR.class_name(),
"state": "planned",
"operator": "LogisticRegression",
"label": "LR",
"documentation_url": "https://lale.readthedocs.io/en/latest/modules/lale.lib.sklearn.logistic_regression.html",
},
},
},
},
}
json = operator.to_json()
self.assertEqual(json, json_expected)
operator_2 = from_json(json)
json_2 = operator_2.to_json()
self.assertEqual(json, json_2)