code: def __init__(self, transform=None):
      self.transform = transform
  
imports: from copy import deepcopy
  from test.unit.input_convertors import _map_into_single_column
  import numpy
  import pandas
  import pytest
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.datasets import make_classification
  from fairlearn.postprocessing import ThresholdOptimizer
  from fairlearn.postprocessing._threshold_optimizer import BASE_ESTIMATOR_NONE_ERROR_MESSAGE, NOT_SUPPORTED_CONSTRAINTS_ERROR_MESSAGE
  from fairlearn.postprocessing._tradeoff_curve_utilities import DEGENERATE_LABELS_ERROR_MESSAGE
  from fairlearn.utils._input_validation import _LABELS_NOT_0_1_ERROR_MESSAGE, _MESSAGE_SENSITIVE_FEATURES_NONE, _MESSAGE_Y_NONE
  from .conftest import ExamplePredictor, X_ex, _get_predictions_by_sensitive_feature, candidate_A_transforms, candidate_X_transforms, candidate_Y_transforms, degenerate_labels_ex, is_invalid_transformation, labels_ex, scores_ex, sensitive_feature_names_ex1, sensitive_features_ex1
label_desc: Use image node_id 1 to create a new PassThroughPredictor object from inherited base classes: BaseEstimator with example: obj = PassThroughPredictor(transform)