> For the complete documentation index, see [llms.txt](https://docs.seldon.ai/alibi-detect/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.seldon.ai/alibi-detect/api-reference/saving/loading.md). # alibi\_detect.saving.loading ## Constants ### `TYPE_CHECKING` ```python TYPE_CHECKING: bool = False ``` bool(x) -> bool Returns True when the argument x is true, False otherwise. The builtins True and False are the only two instances of the class bool. The class bool is a subclass of the class int, and cannot be subclassed. ### `has_tensorflow` ```python has_tensorflow: bool = True ``` bool(x) -> bool Returns True when the argument x is true, False otherwise. The builtins True and False are the only two instances of the class bool. The class bool is a subclass of the class int, and cannot be subclassed. ### `has_pytorch` ```python has_pytorch: bool = True ``` bool(x) -> bool Returns True when the argument x is true, False otherwise. The builtins True and False are the only two instances of the class bool. The class bool is a subclass of the class int, and cannot be subclassed. ### `supported_models_tf` ```python supported_models_tf: tuple = (,) ``` Built-in immutable sequence. If no argument is given, the constructor returns an empty tuple. If iterable is specified the tuple is initialized from iterable's items. If the argument is a tuple, the return value is the same object. ### `supported_models_torch` ```python supported_models_torch: tuple = (,) ``` Built-in immutable sequence. If no argument is given, the constructor returns an empty tuple. If iterable is specified the tuple is initialized from iterable's items. If the argument is a tuple, the return value is the same object. ### `STATE_PATH` ```python STATE_PATH: str = 'state/' ``` str(object='') -> str str(bytes\_or\_buffer\[, encoding\[, errors]]) -> str Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.**str**() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'. ### `logger` ```python logger: logging.Logger = ``` Instances of the Logger class represent a single logging channel. A "logging channel" indicates an area of an application. Exactly how an "area" is defined is up to the application developer. Since an application can have any number of areas, logging channels are identified by a unique string. Application areas can be nested (e.g. an area of "input processing" might include sub-areas "read CSV files", "read XLS files" and "read Gnumeric files"). To cater for this natural nesting, channel names are organized into a namespace hierarchy where levels are separated by periods, much like the Java or Python package namespace. So in the instance given above, channel names might be "input" for the upper level, and "input.csv", "input.xls" and "input.gnu" for the sub-levels. There is no arbitrary limit to the depth of nesting. ### `FIELDS_TO_RESOLVE` ```python FIELDS_TO_RESOLVE: list = [['preprocess_fn', 'src'], ['preprocess_fn', 'model'], ['preprocess_fn', 'emb... ``` Built-in mutable sequence. If no argument is given, the constructor creates a new empty list. The argument must be an iterable if specified. ### `FIELDS_TO_DTYPE` ```python FIELDS_TO_DTYPE: list = [['preprocess_fn', 'dtype']] ``` Built-in mutable sequence. If no argument is given, the constructor creates a new empty list. The argument must be an iterable if specified. ## Functions ### `load_detector` ```python load_detector(filepath: Union[str, os.PathLike], enable_unsafe_loading: bool = False, kwargs) -> Union[alibi_detect.base.Detector, alibi_detect.base.ConfigurableDetector] ``` Load outlier, drift or adversarial detector. | Name | Type | Default | Description | | ----------------------- | ------------------------- | ------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `filepath` | `Union[str, os.PathLike]` | | Load directory. | | `enable_unsafe_loading` | `bool` | `False` | Sets allow\_pickle=True when a np.ndarray is loaded from a .npy file referenced in the detector config. Needed if you have to load objects. Only applied if the filepath is config.toml or a directory containing a config.toml. It has security implications: . | **Returns** * Type: `Union[alibi_detect.base.Detector, alibi_detect.base.ConfigurableDetector]` ### `read_config` ```python read_config(filepath: Union[os.PathLike, str]) -> dict ``` This function reads a detector toml config file and returns a dict specifying the detector. | Name | Type | Default | Description | | ---------- | ------------------------- | ------- | ------------------------------------- | | `filepath` | `Union[os.PathLike, str]` | | The filepath to the config.toml file. | **Returns** * Type: `dict` ### `resolve_config` ```python resolve_config(cfg: dict, config_dir: Optional[pathlib.Path], enable_unsafe_loading: bool = False) -> dict ``` Resolves artefacts in a config dict. For example x\_ref='x\_ref.npy' is resolved by loading the np.ndarray from the .npy file. For a list of fields that are resolved, see . | Name | Type | Default | Description | | ----------------------- | ------------------------ | ------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | `cfg` | `dict` | | The unresolved config dict. | | `config_dir` | `Optional[pathlib.Path]` | | Filepath to directory the `config.toml` is located in. Only required if different from the runtime directory, and artefacts are specified with filepaths relative to the config.toml file. | | `enable_unsafe_loading` | `bool` | `False` | If set to true, allow\_pickle=True is set in np.load(). Needed if you have to load objects. It has security implications: | **Returns** * Type: `dict` --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.seldon.ai/alibi-detect/api-reference/saving/loading.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.