code: def build_drift_plot(score):
      """Build traffic light drift plot."""
      bar_traces, x_axis, y_axis = drift_score_bar_traces(score)
      x_axis["title"] = "Drift score"
      drift_plot = go.Figure(
          layout=dict(
              title="Drift Score - Multivariable",
              xaxis=x_axis,
              yaxis=y_axis,
              height=200,
          )
      )
  
      drift_plot.add_traces(bar_traces)
      return drift_plot
  
imports: import warnings
  from typing import Container, List, Tuple
  import pandas
  import plotly.graph_objects
  from sklearn.ensemble import HistGradientBoostingClassifier
  from sklearn.metrics import roc_auc_score
  from sklearn.model_selection import train_test_split
  from sklearn.preprocessing import OrdinalEncoder
  from deepchecks.tabular import Dataset
  from deepchecks.tabular.utils.feature_importance import N_TOP_MESSAGE, calculate_feature_importance_or_none
  from deepchecks.tabular.utils.task_type import TaskType
  from deepchecks.utils.dataframes import floatify_dataframe
  from deepchecks.utils.distribution.drift import get_drift_plot_sidenote
  from deepchecks.utils.distribution.plot import drift_score_bar_traces, feature_distribution_traces
  from deepchecks.utils.distribution.rare_category_encoder import RareCategoryEncoder
  from deepchecks.utils.plot import DEFAULT_DATASET_NAMES
  from deepchecks.utils.strings import format_percent
  from deepchecks.utils.typing import Hashable
label_desc: Use image node_id 3 for calling a global function with example usage: build_drift_plot(score) and returns: drift_plot