code: def __init__(self, max_levels=None):
      self._feature_map = (
          OrderedDict()
      )  # key: feature_name, value: feature_type
      self.labels = OrderedDict()
      self.cat_cols = []
      self.other_cols = []
      self.ohe_encs = None
      self.max_levels = max_levels
  
file_path: autogluon/tabular/src/autogluon/tabular/models/xgboost/xgboost_utils.py
imports: from collections import OrderedDict
  import numpy
  from scipy.sparse import csr_matrix, hstack
  from sklearn.base import BaseEstimator, TransformerMixin
  from autogluon.core.constants import BINARY, MULTICLASS, REGRESSION, SOFTCLASS
  from ..tabular_nn.utils.categorical_encoders import OneHotMergeRaresHandleUnknownEncoder
label_desc: Use image node_id 1 to create a new OheFeatureGenerator object from inherited base classes: BaseEstimator, TransformerMixin with example: obj = OheFeatureGenerator(max_levels)