code: def _get_random_criteo_data(rows):
      dtypes = {col: float for col in [f"I{x}" for x in range(1, 14)]}
      dtypes.update(
          {col: int for col in [f"C{x}" for x in range(1, 27)]}
      )
      dtypes["label"] = bool
      ret = cudf.datasets.randomdata(rows, dtypes=dtypes)
      # binarize the labels
      ret.label = ret.label.astype(int)
      return ret
  
file_path: Merlin/tests/unit/examples/test_scaling_criteo_optimize_notebook.py
imports: import itertools
  import json
  import os
  import subprocess
  import sys
  from distutils.spawn import find_executable
  from os.path import dirname, realpath
  import pytest
  import cudf
  from tests.conftest import get_cuda_cluster
label_desc: Use image node_id 3 for calling a global function with example usage: _get_random_criteo_data(rows) and returns: ret