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 __init__(self):
super(BaseLinearModel, self).__init__()
# attribute:
self.n_iter_ = 0
self.classes_ = None
self.feature_shape = None
self.gradient_operator = None
self.initializer = Initializer()
self.transfer_variable = None
self.loss_history = []
self.is_converged = False
self.header = None
self.model_name = 'toSet'
self.model_param_name = 'toSet'
self.model_meta_name = 'toSet'
self.role = ''
self.mode = ''
self.schema = {}
self.cipher_operator = None
self.model_weights = None
self.validation_freqs = None
self.need_one_vs_rest = False
self.need_call_back_loss = True
self.init_param_obj = None
self.validation_strategy = None
def __init__(self):
super(BaseFactorizationMachine, self).__init__()
# attribute:
self.initializer = Initializer()
self.model_name = 'FactorizationMachine'
self.model_param_name = 'FactorizationMachineParam'
self.model_meta_name = 'FactorizationMachineMeta'
self.n_iter_ = 0
self.classes_ = None
self.feature_shape = None
self.gradient_operator = None
self.transfer_variable = None
self.loss_history = []
self.is_converged = False
self.header = None
self.role = ''
self.mode = ''
self.schema = {}
self.cipher_operator = None
self.model_weights = None
self.validation_freqs = None
# one_ve_rest parameter
self.in_one_vs_rest = False
self.need_one_vs_rest = None
self.one_vs_rest_classes = []
self.one_vs_rest_obj = None
def __init__(self):
super(BaseLogisticRegression, self).__init__()
# attribute:
self.initializer = Initializer()
self.model_name = 'LogisticRegression'
self.model_param_name = 'LogisticRegressionParam'
self.model_meta_name = 'LogisticRegressionMeta'
# one_ve_rest parameter
self.need_one_vs_rest = None
self.one_vs_rest_classes = []
self.one_vs_rest_obj = None
def __init__(self):
super(BaseLinearRegression, self).__init__()
self.model_param = LinearParam()
# attribute:
self.n_iter_ = 0
self.feature_shape = None
self.gradient_operator = None
self.initializer = Initializer()
self.transfer_variable = None
self.loss_history = []
self.is_converged = False
self.header = None
self.model_name = 'LinearRegression'
self.model_param_name = 'LinearRegressionParam'
self.model_meta_name = 'LinearRegressionMeta'
self.role = ''
self.mode = ''
self.schema = {}
self.cipher_operator = PaillierEncrypt()