Source code for alibi_detect.saving.validate

import warnings

from alibi_detect.saving.schemas import (
from alibi_detect.version import __version__

[docs] def validate_config(cfg: dict, resolved: bool = False) -> dict: """ Validates a detector config dict by passing the dict to the detector's pydantic model schema. Parameters ---------- cfg The detector config dict. resolved Whether the config is resolved or not. For example, if resolved=True, `x_ref` is expected to be a np.ndarray, wheras if resolved=False, `x_ref` is expected to be a str. Returns ------- The validated config dict, with missing fields set to their default values. """ # Get detector name and meta if 'name' in cfg: detector_name = cfg['name'] else: raise ValueError('`name` missing from config.toml.') # Validate detector specific config if detector_name in DETECTOR_CONFIGS.keys(): if resolved: cfg = DETECTOR_CONFIGS_RESOLVED[detector_name](**cfg).dict() else: cfg = DETECTOR_CONFIGS[detector_name](**cfg).dict() else: raise ValueError(f'Loading the {detector_name} detector from a config.toml is not yet supported.') # Get meta data meta = cfg.get('meta') meta = {} if meta is None else meta # Needed because pydantic sets meta=None if it is missing from the config version_warning = meta.get('version_warning', False) version = meta.get('version', None) # Raise warning if config file already contains a version_warning if version_warning: warnings.warn('The config file appears to be have been generated from a detector which may have been ' 'loaded with a version mismatch. This may lead to breaking code or invalid results.') # check version if version is not None and version != __version__: warnings.warn(f'Config is from version {version} but current version is ' f'{__version__}. This may lead to breaking code or invalid results.') cfg['meta'].update({'version_warning': True}) return cfg