def test_make_classification(self):
X, y = make_classification(random_state=42)
pipe = PipelineCache([('pca', PCA(2)),
('lr', LogisticRegression())],
'cache__')
pipe.fit(X, y)
cache = MLCache.get_cache('cache__')
self.assertEqual(len(cache), 1)
key = list(cache.keys())[0]
self.assertIn("[('X',", key)
self.assertIn("('copy', 'True')", key)
MLCache.remove_cache('cache__')
def test_make_classification(self):
X, y = make_classification(random_state=42)
pipe0 = Pipeline([('pca', PCA(2)), ('lr', LogisticRegression())])
pipe = PipelineCache([('pca', PCA(2)), ('lr', LogisticRegression())],
'cache__')
if hasattr(pipe0, '_check_fit_params'):
pars0 = pipe0._check_fit_params() # pylint: disable=W0212,E1101
pars1 = pipe._check_fit_params() # pylint: disable=W0212,E1101
self.assertEqual(pars0, pars1)
pipe0.fit(X, y)
pipe.fit(X, y)
cache = MLCache.get_cache('cache__')
self.assertEqual(len(cache), 1)
key = list(cache.keys())[0]
self.assertIn("[('X',", key)
self.assertIn("('copy', 'True')", key)
MLCache.remove_cache('cache__')