code: def fit(self, X, y):
      if isinstance(X, DataFrame):
          X = X.to_numpy(dtype=np.float32)
      else:
          X = X.astype(np.float32)
      if not X.flags["C_CONTIGUOUS"]:
          X = np.ascontiguousarray(X)
      d = X.shape[1]
      self.index = self.faiss.index_factory(
          d, self.index_factory_string
      )
      self.y = np.array(y)
      self.index.train(X)
      self.index.add(X)
      return self
  
imports: import logging
  import numpy
  from pandas import DataFrame
  from scipy.stats import mode
  from sklearn.utils.extmath import weighted_mode
  from autogluon.common.utils.try_import import try_import_faiss
label_desc: Use image node_id 2 for calling the FAISSNeighborsRegressor obj's underlying member method code with example usage: obj.fit(X, y) and returns: self