code: def gen_int_or_float_in_numpy_file(
      dir, data_field, rows, start=0, force=False
  ):
      file_name = f"{data_field}.npy"
      file = f"{dir}/{file_name}"
      if not os.path.exists(file) or force:
          # non vector columns
          data = []
          # arr = np.array([])
          if rows > 0:
              if data_field == DataField.float_field:
                  data = [
                      np.float32(random.random()) for _ in range(rows)
                  ]
              elif data_field == DataField.double_field:
                  data = [
                      np.float64(random.random()) for _ in range(rows)
                  ]
              elif data_field == DataField.pk_field:
                  data = [i for i in range(start, start + rows)]
              elif data_field == DataField.int_field:
                  data = [
                      random.randint(-999999, 9999999)
                      for _ in range(rows)
                  ]
              arr = np.array(data)
              log.info(
                  f"file_name: {file_name} data type: {arr.dtype} data shape: {arr.shape}"
              )
              np.save(file, arr)
      return file_name
  
imports: import copy
  import json
  import os
  import time
  import numpy
  import pandas
  import random
  from faker import Faker
  from sklearn import preprocessing
  from common.common_func import gen_unique_str
  from common.minio_comm import copy_files_to_minio
  from utils.util_log import test_log
label_desc: Use image node_id 13 for calling a global function with example usage: gen_int_or_float_in_numpy_file(dir, data_field, rows, start, force) and returns: file_name