code: def _get_performance_array(
      self, X: list[Config[ModelConfig]]
  ) -> npt.NDArray[np.float32]:
      return np.array(
          [
              self.tracker.get_performance(
                  Config(SeasonalNaiveModelConfig(), x.dataset)
              ).ncrps.mean
              for x in X
          ]
      )[:, None]
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from typing import Any, cast, Dict, List, Optional, Set, Union
  import numpy
  import numpy.typing
  import pandas
  from sklearn.base import TransformerMixin
  from sklearn.feature_extraction import DictVectorizer
  from sklearn.impute import SimpleImputer
  from sklearn.pipeline import make_pipeline, make_union
  from sklearn.preprocessing import MinMaxScaler, PowerTransformer, StandardScaler
  from tsbench.config import Config, EnsembleConfig, MODEL_REGISTRY, ModelConfig, TrainConfig
  from tsbench.config.model.models import SeasonalNaiveModelConfig
  from tsbench.evaluations.tracking import ModelTracker
label_desc: Use image node_id 5 for calling the SeasonalNaivePerformanceEncoder obj's underlying member method code with example usage: obj._get_performance_array(X) and returns: np