def load(model_type, model_dir): """Dispatcher function for loading.""" params = load_from_disk(Model.get_params_filename(model_dir)) if model_type in Model.registered_model_types: model = Model.registered_model_types[model_type]( model_type=params["model_type"], task_types=params["task_types"], model_params=params["model_params"]) model.load(model_dir) else: raise ValueError("model_type %s is not supported" % model_type) return model
def load(model_dir): """Dispatcher function for loading.""" params = load_from_disk(Model.get_params_filename(model_dir)) model_class = params["model_class"] if model_class in Model.registered_model_classes: model = Model.registered_model_classes[model_class]( task_types=params["task_types"], model_params=params["model_params"]) model.load(model_dir) else: model = Model.registered_model_classes["SklearnModel"]( model_instance=model_class, task_types=params["task_types"], model_params=params["model_params"]) model.load(model_dir) return model
def load(self, model_dir): """Loads sklearn model from joblib file on disk.""" self.raw_model = load_from_disk(Model.get_model_filename(model_dir))