code: def _check_if_input_columns_exist(
      background_df: pd.DataFrame,
      foreground_df: pd.DataFrame,
      input_column_names: List[str],
  ) -> None:
      if not len(
          set(background_df.columns).intersection(input_column_names)
      ) == len(input_column_names) or not len(
          set(foreground_df.columns).intersection(input_column_names)
      ) == len(
          input_column_names
      ):
          raise ValueError(
              "Input column names not found in either the background or the foreground data."
          )
  
imports: from abc import abstractmethod
  from typing import List, Optional
  import numpy
  import pandas
  from sklearn.linear_model._base import LinearModel
  from sklearn.utils.validation import check_is_fitted
  from dowhy.gcm.ml.prediction_model import PredictionModel
  from dowhy.gcm.ml.regression import SklearnRegressionModel
  from dowhy.gcm.shapley import ShapleyConfig, estimate_shapley_values
label_desc: Use image node_id 6 for calling a global function with example usage: _check_if_input_columns_exist(background_df, foreground_df, input_column_names) without return types