def setUp(self):
self.init_param = InitParam()
self.boosting_tree_param = HeteroSecureBoostParam()
self.config_dict = \
{"HeteroSecureBoostParam": {
"init_param": {"init_method": "test_init", "fit_intercept": False},
"tree_param": {"criterion_method": "test_decisiontree"},
"task_type": "test_boostingtree",
"test_variable": "test"}
}
def test_initializer(self):
initializer = Initializer()
data_shape = 10
init_param_obj = InitParam(init_method=consts.RANDOM_NORMAL,
init_const=20,
fit_intercept=False
)
model = initializer.init_model(model_shape=data_shape, init_params=init_param_obj)
model_shape = np.array(model).shape
self.assertTrue(model_shape == (10,))
def setUp(self):
self.init_param = InitParam()
self.boosting_tree_param = BoostingTreeParam()
import json
import time
config_dict = \
{"InitParam": {"init_method": "test_init", "fit_intercept": False},
"DecisionTreeParam": {"criterion_method": "test_decisiontree"},
"BoostingTreeParam": {"task_type": "test_boostingtree"}}
config_json = json.dumps(config_dict)
timeid = int(time.time() * 1000)
self.config_path = "param_config_test." + str(timeid)
with open(self.config_path, "w") as fout:
fout.write(config_json)
def test_directly_extract(self):
init_param = InitParam()
extractor = ParamExtract()
init_param = extractor.parse_param_from_config(init_param,
self.config_path)
self.assertTrue(init_param.init_method == "test_init")