code: def _partial_fit(self, evaluator, fold):
      partial_fit = functools.partial(evaluator.partial_fit, fold=fold)
      return self.__fit(partial_fit)
  
imports: import functools
  import tempfile
  import traceback
  import numpy
  import sklearn.datasets
  import sklearn.model_selection
  from numpy.linalg import LinAlgError
  from sklearn import preprocessing
  from autosklearn.automl_common.common.utils.backend import Backend
  from autosklearn.constants import BINARY_CLASSIFICATION, MULTICLASS_CLASSIFICATION, MULTILABEL_CLASSIFICATION, REGRESSION
  from autosklearn.data.xy_data_manager import XYDataManager
  from autosklearn.metrics import accuracy, balanced_accuracy, f1_macro, f1_micro, f1_weighted, log_loss, precision_macro, precision_micro, precision_weighted, recall_macro, recall_micro, recall_weighted
  from autosklearn.pipeline.util import get_dataset
  from autosklearn.util.data import convert_to_bin
  import unittest
label_desc: Use image node_id 3 for calling the BaseEvaluatorTest obj's underlying member method code with example usage: obj._partial_fit(evaluator, fold) and returns: self