Error "_catboost.CatBoostError: util/generic/maybe.cpp:4: TMaybe is empty"

[AsciiShell]

Problem: Catboost method "select_features" fails with custom metric
catboost version: 1.0.3
Operating System: 20.04.3 LTS (Focal Fossa)
CPU: Intel Xeon Processor (Icelake)
GPU: -

import sys
import numpy as np
import pandas as pd
import catboost
print(sys.version)
print('numpy', np.__version__)
print('pandas', pd.__version__)
print('catboost', catboost.__version__)

# from https://catboost.ai/en/docs/concepts/python-usages-examples#custom-loss-function-eval-metric
class LoglossMetric(object):
    def get_final_error(self, error, weight):
        return error / (weight + 1e-38)

    def is_max_optimal(self):
        return False

    def evaluate(self, approxes, target, weight):
        assert len(approxes) == 1
        assert len(target) == len(approxes[0])

        approx = approxes[0]

        error_sum = 0.0
        weight_sum = 0.0

        for i in range(len(approx)):
            e = np.exp(approx[i])
            p = e / (1 + e)
            w = 1.0 if weight is None else weight[i]
            weight_sum += w
            error_sum += -w * (target[i] * np.log(p) + (1 - target[i]) * np.log(1 - p))

        return error_sum, weight_sum

    
data  = pd.DataFrame({'A': [1, 2, 3, 4] * 100, 'B': [6, 7, 8, 9] * 100, 'target': [0, 1] * 200})
features = ['A', 'B']
train_pool = catboost.Pool(data[features], data['target'])

clf = catboost.CatBoostClassifier(iterations=2, eval_metric=LoglossMetric())
clf.fit(train_pool)

clf = catboost.CatBoostClassifier(iterations=2)
clf.select_features(train_pool, features_for_select=features, steps=1, num_features_to_select=1)

clf = catboost.CatBoostClassifier(iterations=2, eval_metric=LoglossMetric())
clf.select_features(train_pool, features_for_select=features, steps=1, num_features_to_select=1)

3.8.10 (default, Sep 28 2021, 16:10:42)
[GCC 9.3.0]
numpy 1.20.3
pandas 1.3.4
catboost 1.0.3
Learning rate set to 0.5
0:      learn: 0.3432238        total: 379ms    remaining: 379ms
1:      learn: 0.1999481        total: 379ms    remaining: 0us
Learning rate set to 0.5
Step #1 out of 1
0:      learn: 0.3432126        total: 415us    remaining: 415us
1:      learn: 0.1999658        total: 746us    remaining: 0us
Feature #0 eliminated
Train final model
0:      learn: 0.3432126        total: 304us    remaining: 304us
1:      learn: 0.1999658        total: 511us    remaining: 0us
Learning rate set to 0.5
Step #1 out of 1
Traceback (most recent call last):
  File "cb_bug2.py", line 48, in <module>
    clf.select_features(train_pool, features_for_select=features, steps=1, num_features_to_select=1)
  File "/home/asciishell/project/venv/lib/python3.8/site-packages/catboost/core.py", line 4017, in select_features
    summary = self._object._select_features(train_pool, test_pool, params)
  File "_catboost.pyx", line 5001, in _catboost._CatBoost._select_features
  File "_catboost.pyx", line 5015, in _catboost._CatBoost._select_features
_catboost.CatBoostError: util/generic/maybe.cpp:4: TMaybe is empty

[LyzhinIvan]

Custom eval metric is supported now in select_features.