def test_store_load(self):
x = np.array([[1, 0, 0], [0, 1, 1], [1, 1, 1], [0, 1, 1]])
y = {"default": np.array(['a', "b", "c", "a"])}
svm = SVM()
svm._fit(sparse.csr_matrix(x), y["default"])
path = EnvironmentSettings.root_path / "test/tmp/store_load_sklearn/"
details_path = EnvironmentSettings.root_path / "test/tmp/store_load_sklearn/details.yaml"
svm.store(path=path, details_path=details_path)
svm2 = SVM()
svm2.load(path=path, details_path=details_path)
shutil.rmtree(path)
def test_store(self):
x = np.array([[1, 0, 0], [0, 1, 1], [1, 1, 1], [0, 1, 1]])
y = {"default": np.array(['a', "b", "c", "a"])}
svm = SVM()
svm.fit(EncodedData(x, y), 'default')
path = EnvironmentSettings.root_path / "my_svm/"
svm.store(path)
self.assertTrue(os.path.isfile(path / "svm.pickle"))
with open(path / "svm.pickle", "rb") as file:
svm2 = pickle.load(file)
self.assertTrue(isinstance(svm2, SVC))
shutil.rmtree(path)
def test_store(self):
x = np.array([[1, 0, 0], [0, 1, 1], [1, 1, 1], [0, 1, 1]])
y = {"default": np.array(['a', "b", "c", "a"])}
svm = SVM()
svm._fit(sparse.csr_matrix(x), y["default"])
path = EnvironmentSettings.root_path / "test/tmp/storesklearn/"
svm.store(path)
self.assertTrue(os.path.isfile(path / "svm.pickle"))
with open(path / "svm.pickle", "rb") as file:
svm2 = pickle.load(file)
self.assertTrue(isinstance(svm2, SVC))
shutil.rmtree(path)