from evalml.exceptions import PipelineScoreError
from evalml.utils.logger import get_logger
logger = get_logger(__file__)
[docs]def silent_error_callback(exception, traceback, automl, **kwargs):
"""No-op."""
[docs]def raise_error_callback(exception, traceback, automl, **kwargs):
"""Raises the exception thrown by the AutoMLSearch object. Also logs the exception as an error."""
logger.error(f'AutoML search raised a fatal exception: {str(exception)}')
logger.error("\n".join(traceback))
raise exception
[docs]def log_error_callback(exception, traceback, automl, **kwargs):
"""Logs the exception thrown as an error. Will not throw. This is the default behavior for AutoMLSearch."""
fold_num = kwargs.get('fold_num')
pipeline = kwargs.get('pipeline')
trace = "\n".join(traceback) if traceback else ""
if isinstance(exception, PipelineScoreError):
logger.info(f"\t\t\tFold {fold_num}: Encountered an error scoring the following objectives: {', '.join(exception.exceptions)}.")
logger.info(f"\t\t\tFold {fold_num}: The scores for these objectives will be replaced with nan.")
trace += f"\n{exception.message}"
else:
logger.info(f"\t\t\tFold {fold_num}: Encountered an error.")
logger.info(f"\t\t\tFold {fold_num}: All scores will be replaced with nan.")
logger.info(f"\t\t\tFold {fold_num}: Please check {logger.handlers[1].baseFilename} for the current hyperparameters and stack trace.")
logger.info(f"\t\t\tFold {fold_num}: Exception during automl search: {str(exception)}")
logger.debug(f"\t\t\tFold {fold_num}: Hyperparameters:\n\t{pipeline.hyperparameters}")
logger.debug(f"\t\t\tFold {fold_num}: Traceback:\n{trace}")