code: def mse_functional(model: SklearnModel, sample: Model, X, y):
      predictions_transformed = sample.predict(X)
      predictions = model.data.y.unnormalize_y(predictions_transformed)
      return mean_squared_error(predictions, y)
  
imports: import argparse
  import itertools
  import os
  from functools import partial
  import numpy
  import pandas
  import matplotlib.pyplot
  from matplotlib import cm
  from tqdm import tqdm
  from sklearn import model_selection, datasets
  from sklearn.metrics import mean_squared_error
  from imodels import get_clean_dataset
  from imodels.experimental.bartpy.model import Model
  from imodels.experimental.bartpy.tree import Tree
  from ..sklearnmodel import BART, SklearnModel
label_desc: Use image node_id 2 for calling a global function with example usage: mse_functional(model, sample, X, y) and returns: mean_squared_error