sagemaker.serve.detector.pickler

Save the object using cloudpickle

Functions

load_xgboost_from_json(model_save_path, ...)	Load xgboost model from json format
save_pkl(save_path, obj)	Save obj with cloudpickle under save_path
save_sklearn(model_path, model)	Save sklearn model using joblib serialization.
save_xgboost(save_path, xgb_model)	Save xgboost model to json format using save_model

sagemaker.serve.detector.pickler.load_xgboost_from_json(model_save_path: str, class_name: str)

Load xgboost model from json format

sagemaker.serve.detector.pickler.save_pkl(save_path: Path, obj: Any)

Save obj with cloudpickle under save_path

sagemaker.serve.detector.pickler.save_sklearn(model_path: str, model: object) → None

Save sklearn model using joblib serialization.

sagemaker.serve.detector.pickler.save_xgboost(save_path: Path, xgb_model: Any)

Save xgboost model to json format using save_model