[docs]class MethodPropertyNotFoundError(Exception):
"""Exception to raise when a class is does not have an expected method or property."""
pass
[docs]class PipelineNotFoundError(Exception):
"""An exception raised when a particular pipeline is not found in automl search results"""
pass
[docs]class ObjectiveNotFoundError(Exception):
"""Exception to raise when specified objective does not exist."""
pass
[docs]class MissingComponentError(Exception):
"""An exception raised when a component is not found in all_components()"""
pass
[docs]class ComponentNotYetFittedError(Exception):
"""An exception to be raised when predict/predict_proba/transform is called on a component without fitting first."""
pass
[docs]class PipelineNotYetFittedError(Exception):
"""An exception to be raised when predict/predict_proba/transform is called on a pipeline without fitting first."""
pass
[docs]class AutoMLSearchException(Exception):
"""Exception raised when all pipelines in an automl batch return a score of NaN for the primary objective."""
pass
[docs]class EnsembleMissingPipelinesError(Exception):
"""An exception raised when an ensemble is missing `estimators` (list) as a parameter."""
pass
[docs]class PipelineScoreError(Exception):
"""An exception raised when a pipeline errors while scoring any objective in a list of objectives.
Arguments:
exceptions (dict): A dictionary mapping an objective name (str) to a tuple of the form (exception, traceback).
All of the objectives that errored will be stored here.
scored_successfully (dict): A dictionary mapping an objective name (str) to a score value. All of the objectives
that did not error will be stored here.
"""
def __init__(self, exceptions, scored_successfully):
self.exceptions = exceptions
self.scored_successfully = scored_successfully
# Format the traceback message
exception_list = []
for objective, (exception, tb) in exceptions.items():
exception_list.append(
f"{objective} encountered {str(exception.__class__.__name__)} with message ({str(exception)}):\n"
)
exception_list.extend(tb)
message = "\n".join(exception_list)
self.message = message
super().__init__(message)
[docs]class DataCheckInitError(Exception):
"""Exception raised when a data check can't initialize with the parameters given."""
[docs]class NullsInColumnWarning(UserWarning):
"""Warning thrown when there are null values in the column of interest"""
class ObjectiveCreationError(Exception):
"""Exception when get_objective tries to instantiate an objective and required args are not provided."""
class NoPositiveLabelException(Exception):
"""Exception when a particular classification label for the 'positive' class cannot be found in the column index or unique values"""