code: def build_color_dict(names: list[str]) -> dict[str, np.ndarray]:
      norm = colors.Normalize(vmin=0, vmax=1)
      m = cm.ScalarMappable(norm, cm.tab20)
      color_dict = m.to_rgba(np.linspace(0, 1, len(names)))
      color_dict = dict(zip(names, color_dict))
  
      return color_dict
  
file_path: optuna/benchmarks/run_bayesmark.py
imports: from __future__ import annotations
  import argparse
  import json
  import os
  import subprocess
  from matplotlib import cm
  from matplotlib import colors
  from matplotlib.axes import Axes
  import matplotlib.pyplot
  import numpy
  import pandas
  from xarray import Dataset
label_desc: Use image node_id 4 for calling a global function with example usage: build_color_dict(names) and returns: color_dict