def test_get_loaded_booster(model_info):
"""Test model loading
'pickled_model' directory has a model dumped using pickle module
'saved_booster' directory has a model saved using booster.save_model()
"""
model_dir_name, model_format = model_info
model_dir = os.path.join(RESOURCES_PATH, 'models', model_dir_name)
loaded_booster, loaded_model_format = serve_utils.get_loaded_booster(model_dir)
assert loaded_model_format == model_format
def default_model_fn(self, model_dir):
"""Load a model. For XGBoost Framework, a default function to load a model is not provided.
Users should provide customized model_fn() in script.
Args:
model_dir: a directory where model is saved.
Returns:
A XGBoost model.
XGBoost model format type.
"""
try:
booster, format = serve_utils.get_loaded_booster(model_dir)
except Exception as e:
raise ModelLoadInferenceError("Unable to load model: {}".format(str(e)))
return booster, format
def load_model(cls):
if cls.booster is None:
cls.booster, cls.format = serve_utils.get_loaded_booster(
ScoringService.MODEL_PATH)
return cls.format
def load_model(cls, ensemble=True):
if cls.booster is None:
cls.booster, cls.format = serve_utils.get_loaded_booster(ScoringService.MODEL_PATH, ensemble)
cls.get_config_json()
return cls.format