def test_train_and_score_pipelines_error(mock_fit, mock_score,
dummy_binary_pipeline_class,
X_y_binary, caplog):
X, y = X_y_binary
mock_score.side_effect = Exception('yeet')
automl = AutoMLSearch(X_train=X,
y_train=y,
problem_type='binary',
max_time=1,
max_batches=1,
allowed_pipelines=[dummy_binary_pipeline_class({})])
pipeline = dummy_binary_pipeline_class({})
job_log = JobLogger()
result = evaluate_pipeline(pipeline,
automl,
automl.X_train,
automl.y_train,
logger=job_log)
evaluation_result, job_log = result.get("scores"), result.get("logger")
logger = get_logger(__file__)
job_log.write_to_logger(logger)
assert mock_fit.call_count == automl.data_splitter.get_n_splits()
assert mock_score.call_count == automl.data_splitter.get_n_splits()
assert evaluation_result.get('training_time') is not None
assert np.isnan(evaluation_result.get('cv_score_mean'))
pd.testing.assert_series_equal(evaluation_result.get('cv_scores'),
pd.Series([np.nan] * 3))
for i in range(automl.data_splitter.get_n_splits()):
assert np.isnan(evaluation_result['cv_data'][i]['all_objective_scores']
['Log Loss Binary'])
assert 'yeet' in caplog.text
def test_job_logger_warning_and_error_messages(caplog):
job_log = JobLogger()
job_log.warning("This is a warning!")
job_log.error("This is an error!")
logger = get_logger(__file__)
job_log.write_to_logger(logger)
assert "This is a warning!" in caplog.text
assert "This is an error!" in caplog.text
import warnings
from collections import namedtuple
from functools import reduce
import numpy as np
import pandas as pd
import woodwork as ww
from sklearn.utils import check_random_state
from evalml.exceptions import (
EnsembleMissingPipelinesError,
MissingComponentError
)
from evalml.utils import get_logger
logger = get_logger(__file__)
def import_or_raise(library, error_msg=None, warning=False):
"""Attempts to import the requested library by name.
If the import fails, raises an ImportError or warning.
Arguments:
library (str): the name of the library
error_msg (str): error message to return if the import fails
warning (bool): if True, import_or_raise gives a warning instead of ImportError. Defaults to False.
"""
try:
return importlib.import_module(library)
except ImportError:
if error_msg is None:
