code: def set_predefined_weights(self, X, y):
      if self.sample_weight not in [
          AUTO_WEIGHT,
          BALANCE_WEIGHT,
      ] or self.problem_type not in [BINARY, MULTICLASS]:
          return X
      if self.sample_weight in X.columns:
          raise ValueError(
              f"Column name '{self.sample_weight}' cannot appear in your dataset with predefined weighting strategy. Please change it and try again."
          )
      if self.sample_weight == BALANCE_WEIGHT:
          if self.class_weights is None:
              class_counts = y.value_counts()
              n = len(y)
              k = len(class_counts)
              self.class_weights = {
                  c: n / (class_counts[c] * k)
                  for c in class_counts.index
              }
              logger.log(
                  20,
                  "Assigning sample weights to balance differences in frequency of classes.",
              )
              logger.log(
                  15,
                  f"Balancing classes via the following weights: {self.class_weights}",
              )
          w = y.map(self.class_weights)
      elif (
          self.sample_weight == AUTO_WEIGHT
      ):  # TODO: support more sophisticated auto_weight strategy
          raise NotImplementedError(
              f"{AUTO_WEIGHT} strategy not yet supported."
          )
      X[
          self.sample_weight
      ] = w  # TODO: consider not bundling sample weights inside X
      return X
  
imports: import copy
  import logging
  import math
  import time
  import numpy
  import pandas
  from pandas import DataFrame
  from autogluon.common.utils.log_utils import convert_time_in_s_to_log_friendly
  from autogluon.common.utils.system_info import get_ag_system_info
  from autogluon.core.constants import AUTO_WEIGHT, BALANCE_WEIGHT, BINARY, MULTICLASS, QUANTILE, REGRESSION
  from autogluon.core.data import LabelCleaner
  from autogluon.core.data.cleaner import Cleaner
  from autogluon.core.utils.time import sample_df_for_time_func, time_func
  from autogluon.core.utils.utils import augment_rare_classes, extract_column
  from ..trainer import AutoTrainer
  from .abstract_learner import AbstractTabularLearner
label_desc: Use image node_id 6 for calling the DefaultLearner obj's underlying member method code with example usage: obj.set_predefined_weights(X, y) and returns: X, X