validmind.errors

This module contains all the custom errors that are used in the ValidMind Library.

The following base errors are defined for others:

Base errors

BaseError

classBaseError(Exception):

Common base class for all non-exit exceptions.

BaseError

BaseError(message='')

description

defdescription(self,*args,**kwargs):

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  • builtins.BaseException with_traceback, add_note

APIRequestError

classAPIRequestError(BaseError):

Generic error for API request errors that are not known.

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API errors

InvalidAPICredentialsError

classInvalidAPICredentialsError(APIRequestError):

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MissingAPICredentialsError

classMissingAPICredentialsError(BaseError):

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Model errors

InvalidXGBoostTrainedModelError

classInvalidXGBoostTrainedModelError(BaseError):

When an invalid XGBoost trained model is used when calling init_r_model.

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MissingModelIdError

classMissingModelIdError(BaseError):

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MissingOrInvalidModelPredictFnError

classMissingOrInvalidModelPredictFnError(BaseError):

When the PyTorch model is missing a predict function or its predict method does not have the expected arguments.

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UnsupportedModelError

classUnsupportedModelError(BaseError):

When an unsupported model is used.

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UnsupportedModelForSHAPError

classUnsupportedModelForSHAPError(BaseError):

When an unsupported model is used for SHAP importance.

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UnsupportedRModelError

classUnsupportedRModelError(BaseError):

When an unsupported R model is used.

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Test errors

GetTestSuiteError

classGetTestSuiteError(BaseError):

When the test suite could not be found.

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InitializeTestSuiteError

classInitializeTestSuiteError(BaseError):

When the test suite was found but could not be initialized.

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InvalidTestParametersError

classInvalidTestParametersError(BaseError):

When invalid parameters are provided for the test.

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InvalidTestResultsError

classInvalidTestResultsError(APIRequestError):

When an invalid test results object is sent to the API.

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LoadTestError

classLoadTestError(BaseError):

Exception raised when an error occurs while loading a test.

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MissingRequiredTestInputError

classMissingRequiredTestInputError(BaseError):

When a required test context variable is missing.

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SkipTestError

classSkipTestError(BaseError):

Useful error to throw when a test cannot be executed.

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TestInputInvalidDatasetError

classTestInputInvalidDatasetError(BaseError):

When an invalid dataset is used in a test context.

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Input validation errors

InvalidXGBoostTrainedModelError

classInvalidXGBoostTrainedModelError(BaseError):

When an invalid XGBoost trained model is used when calling init_r_model.

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MissingModelIdError

classMissingModelIdError(BaseError):

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MissingOrInvalidModelPredictFnError

classMissingOrInvalidModelPredictFnError(BaseError):

When the PyTorch model is missing a predict function or its predict method does not have the expected arguments.

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InvalidTestParametersError

classInvalidTestParametersError(BaseError):

When invalid parameters are provided for the test.

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InvalidTestResultsError

classInvalidTestResultsError(APIRequestError):

When an invalid test results object is sent to the API.

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MissingRequiredTestInputError

classMissingRequiredTestInputError(BaseError):

When a required test context variable is missing.

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InvalidAPICredentialsError

classInvalidAPICredentialsError(APIRequestError):

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InvalidContentIdPrefixError

classInvalidContentIdPrefixError(APIRequestError):

When an invalid text content_id is sent to the API.

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InvalidInputError

classInvalidInputError(BaseError):

When an invalid input object is provided.

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InvalidMetricResultsError

classInvalidMetricResultsError(APIRequestError):

When an invalid metric results object is sent to the API.

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InvalidProjectError

classInvalidProjectError(APIRequestError):

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InvalidRequestBodyError

classInvalidRequestBodyError(APIRequestError):

When a POST/PUT request is made with an invalid request body.

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InvalidTextObjectError

classInvalidTextObjectError(APIRequestError):

When an invalid Metadata (Text) object is sent to the API.

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InvalidValueFormatterError

classInvalidValueFormatterError(BaseError):

When an invalid value formatter is provided when serializing results.

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MissingAPICredentialsError

classMissingAPICredentialsError(BaseError):

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MissingCacheResultsArgumentsError

classMissingCacheResultsArgumentsError(BaseError):

When the cache_results function is missing arguments.

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MissingClassLabelError

classMissingClassLabelError(BaseError):

When the one or more class labels are missing from provided dataset targets.

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MissingDependencyError

classMissingDependencyError(BaseError):

When a required dependency is missing.

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MissingDocumentationTemplate

classMissingDocumentationTemplate(BaseError):

When the client config is missing the documentation template.

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MissingRExtrasError

classMissingRExtrasError(BaseError):

When the R extras have not been installed.

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MissingTextContentIdError

classMissingTextContentIdError(APIRequestError):

When a Text object is sent to the API without a content_id.

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MissingTextContentsError

classMissingTextContentsError(APIRequestError):

When a Text object is sent to the API without a "text" attribute.

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Unsupported feature errors

UnsupportedModelError

classUnsupportedModelError(BaseError):

When an unsupported model is used.

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UnsupportedModelForSHAPError

classUnsupportedModelForSHAPError(BaseError):

When an unsupported model is used for SHAP importance.

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UnsupportedRModelError

classUnsupportedRModelError(BaseError):

When an unsupported R model is used.

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UnsupportedColumnTypeError

classUnsupportedColumnTypeError(BaseError):

When an unsupported column type is found on a dataset.

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UnsupportedDatasetError

classUnsupportedDatasetError(BaseError):

When an unsupported dataset is used.

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UnsupportedFigureError

classUnsupportedFigureError(BaseError):

When an unsupported figure object is constructed.

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