alibi_detect.utils.frameworks

Constants

ERROR_TYPES

ERROR_TYPES: dict = {'prophet': 'prophet', 'tensorflow_probability': 'tensorflow', 'tensorflow': ...

has_tensorflow

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

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.

has_keops

has_keops: 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_BACKEND

HAS_BACKEND: dict = {'tensorflow': True, 'pytorch': True, 'sklearn': True, 'keops': True}

BackendValidator

Constructor

BackendValidator(self, backend_options: Dict[Optional[str], List[str]], construct_name: str)

Name	Type	Default	Description
backend_options	Dict[Optional[str], List[str]]		Dictionary from backend to list of dependencies that must be satisfied. The keys are the available options for the user and the values should be a list of dependencies that are checked via the HAS_BACKEND map defined in this module. An example of backend_options would be {'tensorflow': ['tensorflow'], 'pytorch': ['pytorch'], None: []}.This would mean 'tensorflow', 'pytorch' or None are available backend options. If the user passes a different backend they will receive and error listing the correct backends. In addition, if one of the dependencies in the backend_option values is missing for the specified backend the validator will issue an error message telling the user what dependency bucket to install.
construct_name	str		Name of the object that has a set of backends we need to verify.

Methods

verify_backend

verify_backend(backend: str)

Verifies backend choice.

Verifies backend is implemented and that the correct dependencies are installed for the requested backend. If the backend is not implemented or a dependency is missing then an error is issued.

Name	Type	Default	Description
backend	str		Choice of backend the user wishes to initialize the alibi-detect construct with. Must be one of the keys in the self.backend_options dictionary.

Framework

Inherits from: str, Enum

An enumeration.