39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
"""
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Custom exception types for the Model Manager.
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This module defines domain-specific exceptions used across the training
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workflow to convey additional context (e.g., flags indicating which steps
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completed successfully) without altering control flow semantics.
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"""
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class ModelTrainingError(Exception):
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"""
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Exception raised when the model training workflow fails.
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This exception carries flags indicating whether the model was trained
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and/or saved successfully, enabling the workflow to map errors to
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appropriate experiment statuses.
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"""
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def __init__(self, model_trained: bool, model_saved: bool, message: str | None = None):
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"""
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Initialize ModelTrainingError with training state flags.
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Args:
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model_trained: True if the training step completed successfully.
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model_saved: True if the model saving step completed successfully.
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message: Optional custom error message. If None, a default message
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including the state flags is generated.
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"""
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self.model_trained = model_trained
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self.model_saved = model_saved
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if message is None:
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message = (
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'Model training workflow failed '
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f'(model_trained={model_trained}, model_saved={model_saved})'
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)
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super().__init__(message)
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