def __init__()

in docker_images/sklearn/app/pipelines/common.py [0:0]

• 29 lines of code
• 12 McCabe index (conditional complexity)

    def __init__(self, model_id: str):
        cached_folder = snapshot_download(repo_id=model_id)
        self._load_warnings = []
        self._load_exception = None
        try:
            with open(Path(cached_folder) / "config.json") as f:
                # this is the default path for configuration of a scikit-learn
                # project. If the project is created using `skops`, it should have
                # this file.
                config = json.load(f)
        except Exception:
            config = dict()
            warnings.warn("`config.json` does not exist or is invalid.")

        self.model_file = (
            config.get("sklearn", {}).get("model", {}).get("file", DEFAULT_FILENAME)
        )
        self.model_format = config.get("sklearn", {}).get("model_format", "pickle")

        try:
            with warnings.catch_warnings(record=True) as record:
                if self.model_format == "pickle":
                    self.model = joblib.load(
                        open(Path(cached_folder) / self.model_file, "rb")
                    )
                elif self.model_format == "skops":
                    self.model = sio.load(
                        file=Path(cached_folder) / self.model_file, trusted=True
                    )
                if len(record) > 0:
                    # if there's a warning while loading the model, we save it so
                    # that it can be raised to the user when __call__ is called.
                    self._load_warnings += record

        except Exception as e:
            # if there is an exception while loading the model, we save it to
            # raise the write error when __call__ is called.
            self._load_exception = e
        # use column names from the config file if available, to give the data
        # to the model in the right order.
        self.columns = config.get("sklearn", {}).get("columns", None)