code: def gpu_load_names(**kwargs):
      """Loads names used for renaming the banks
  
      Returns
      -------
      GPU DataFrame
      """
      chronometer = Chronometer.makeStarted()
  
      cols = ["seller_name", "new_seller_name"]
  
      dtypes = OrderedDict(
          [
              ("seller_name", "category"),
              ("new_seller_name", "category"),
          ]
      )
  
      names_table = pyblazing.create_table(
          table_name="names",
          type=get_type_schema(col_names_path),
          path=col_names_path,
          delimiter="|",
          names=cols,
          dtypes=get_dtype_values(dtypes),
          skip_rows=1,
      )
      Chronometer.show(chronometer, "Read Names CSV")
      return names_table
  
imports: import time
  from collections import OrderedDict
  import numpy
  import pandas
  import pyblazing
  from pyblazing import DriverType, FileSystemType, SchemaFrom, get_dtype_values
  from sklearn.model_selection import train_test_split
  import xgboost
  from Configuration import Settings
  from DemoTest.chronometer import Chronometer
  from Utils import Execution
label_desc: Use image node_id 10 for calling a global function with example usage: gpu_load_names() and returns: names_table