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))
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))
