예제 #1
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    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))
예제 #2
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 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 setup(self, model: ExplainerModel, persistence, **kwargs):
        CustomExplainer.setup(self,
                              model=model,
                              persistence=persistence,
                              **kwargs)

        # resolve explainer parameters to instance field
        self.args = CustomExplainerArgs(
            TemplatePartialDependenceExplainer._parameters)
        self.args.resolve_params(
            explainer_params=CustomExplainerArgs.json_str_to_dict(
                self.explainer_params_as_str))
예제 #4
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    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}")
예제 #6
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    def __init__(self):
        CustomExplainer.__init__(self)
        CustomDaiExplainer.__init__(self)

        self.args = None
예제 #7
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 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 setup(self, model, persistence, **kwargs):
     CustomExplainer.setup(self, model, persistence, **kwargs)
 def __init__(self):
     CustomExplainer.__init__(self)
     self.args = {}
 def __init__(self):
     CustomExplainer.__init__(self)
     CustomDaiExplainer.__init__(self)
     self.cat_variables = None
     self.mcle = None
    def setup(self, model, persistence, **kwargs):
        CustomExplainer.setup(self, model, persistence, **kwargs)

        self.logger.info(f"{self.display_name} explainer initialized")