code: def criteo_first_row():
      return {
          "label": 0,
          "int00": 1,
          "int01": 1,
          "int02": 5,
          "int03": 0,
          "int04": 1382,
          "int05": 4,
          "int06": 15,
          "int07": 2,
          "int08": 181,
          "int09": 1,
          "int10": 2,
          "int11": None,
          "int12": 2,
          "cat00": "68fd1e64",
          "cat01": "80e26c9b",
          "cat02": "fb936136",
          "cat03": "7b4723c4",
          "cat04": "25c83c98",
          "cat05": "7e0ccccf",
          "cat06": "de7995b8",
          "cat07": "1f89b562",
          "cat08": "a73ee510",
          "cat09": "a8cd5504",
          "cat10": "b2cb9c98",
          "cat11": "37c9c164",
          "cat12": "2824a5f6",
          "cat13": "1adce6ef",
          "cat14": "8ba8b39a",
          "cat15": "891b62e7",
          "cat16": "e5ba7672",
          "cat17": "f54016b9",
          "cat18": "21ddcdc9",
          "cat19": "b1252a9d",
          "cat20": "07b5194c",
          "cat21": None,
          "cat22": "3a171ecb",
          "cat23": "c5c50484",
          "cat24": "e8b83407",
          "cat25": "9727dd16",
      }
  
imports: import calendar
  import datetime
  import os
  from pathlib import Path
  from tempfile import TemporaryDirectory
  import numpy
  import pandas
  import pytest
  from sklearn.model_selection import train_test_split
  from recommenders.utils.constants import DEFAULT_USER_COL, DEFAULT_ITEM_COL, DEFAULT_RATING_COL, DEFAULT_TIMESTAMP_COL
  from recommenders.datasets.python_splitters import numpy_stratified_split
  from recommenders.datasets.python_splitters import python_chrono_split
  from recommenders.utils.spark_utils import start_or_get_spark
label_desc: Use image node_id 13 for calling a global function with example usage: criteo_first_row() and returns: dict