def setup(self, model, persistence, **e_params):
CustomExplainer.setup(self, model, persistence, **e_params)
CustomDaiExplainer.setup(self, **e_params)
# resolve explainer parameters to instance attributes
self.args = CustomExplainerArgs(ExampleParamsExplainer._parameters)
self.args.resolve_params(
explainer_params=CustomExplainerArgs.json_str_to_dict(
self.explainer_params_as_str))
def setup(self, model, persistence, key = None, params = None, **explainer_params):
CustomExplainer.setup(self, model, persistence, key, params, **explainer_params)
CustomDaiExplainer.setup(self, **explainer_params)
self.args = CustomExplainerArgs(ALEExplainer._parameters)
self.args.resolve_params(
explainer_params=CustomExplainerArgs.json_str_to_dict(
self.explainer_params_as_str
)
)
self.cfg_bins = self.args.get("bins")
self.cfg_feature_bins = json.loads(str(self.args.get("feature_bins")))
def check_compatibility(
self,
params: Optional[CommonExplainerParameters] = None,
**explainer_params,
) -> bool:
CustomExplainer.check_compatibility(self, params, **explainer_params)
CustomDaiExplainer.check_compatibility(self, params,
**explainer_params)
# explainer can explain only dataset with less than 1M rows (without sampling)
if self.dataset_entity.row_count > 1_000_000:
# not supported
return False
return True
def setup(self, model, persistence, **e_params):
CustomExplainer.setup(self, model, persistence, **e_params)
CustomDaiExplainer.setup(self, **e_params)
self.logger.info("setup() method parameters:")
self.logger.info(f" {e_params}")
self.logger.info("explainer metadata:")
self.logger.info(f" display name: {self._display_name}")
self.logger.info(f" description: {self._description}")
self.logger.info(f" keywords: {self._keywords}")
self.logger.info(f" IID: {self._iid}")
self.logger.info(f" TS: {self._time_series}")
self.logger.info(f" image: {self._image}")
self.logger.info(f" regression: {self._regression}")
self.logger.info(f" binomial: {self._binary}")
self.logger.info(f" multinomial: {self._multiclass}")
self.logger.info(f" global: {self._global_explanation}")
self.logger.info(f" local: {self._local_explanation}")
self.logger.info(f" explanation types: {self._explanation_types}")
self.logger.info(
f" optional e. types: {self._optional_explanation_types}")
self.logger.info(f" parameters: {self._parameters}")
self.logger.info(
f" not standalone: {self._requires_predict_method}")
self.logger.info(f" Python deps: {self._modules_needed_by_name}")
self.logger.info(f" explainer deps: {self._depends_on}")
self.logger.info(f" priority: {self._priority}")
self.logger.info("explainer instance attributes:")
self.logger.info(f" explainer params: {self.explainer_params}")
self.logger.info(f" common params: {self.params}")
self.logger.info(f" DAI params: {self.dai_params}")
self.logger.info(f" explainer deps: {self.explainer_deps}")
self.logger.info(f" model with predict method: {self.model}")
self.logger.info(f" features used by model: {self.used_features}")
self.logger.info(f" target labels: {self.labels}")
self.logger.info(f" number of target labels: {self.num_labels}")
self.logger.info(f" persistence: {self.persistence}")
self.logger.info(f" MLI key: {self.mli_key}")
self.logger.info(f" DAI username: {self.dai_username}")
self.logger.info(f" model entity: {self.model_entity}")
self.logger.info(f" dataset entity: {self.dataset_entity}")
self.logger.info(
f" validation dataset entity: {self.validset_entity}")
self.logger.info(f" test dataset entity: {self.testset_entity}")
self.logger.info(f" sanitization map: {self.sanitization_map}")
self.logger.info(f" enable MOJO: {self.enable_mojo}")
self.logger.info(f" Driverless AI configuration: {self.config}")
def __init__(self):
CustomExplainer.__init__(self)
CustomDaiExplainer.__init__(self)
self.args = None
def __init__(self):
CustomExplainer.__init__(self)
CustomDaiExplainer.__init__(self)
def setup(self, model, persistence, **e_params):
CustomExplainer.setup(self, model, persistence, **e_params)
CustomDaiExplainer.setup(self, **e_params)
def __init__(self):
CustomExplainer.__init__(self)
CustomDaiExplainer.__init__(self)
self.cat_variables = None
self.mcle = None