code: def gpu_load_acquisition_csv(acquisition_path, **kwargs):
      """Loads acquisition data
  
      Returns
      -------
      GPU DataFrame
      """
      chronometer = Chronometer.makeStarted()
  
      cols = [
          "loan_id",
          "orig_channel",
          "seller_name",
          "orig_interest_rate",
          "orig_upb",
          "orig_loan_term",
          "orig_date",
          "first_pay_date",
          "orig_ltv",
          "orig_cltv",
          "num_borrowers",
          "dti",
          "borrower_credit_score",
          "first_home_buyer",
          "loan_purpose",
          "property_type",
          "num_units",
          "occupancy_status",
          "property_state",
          "zip",
          "mortgage_insurance_percent",
          "product_type",
          "coborrow_credit_score",
          "mortgage_insurance_type",
          "relocation_mortgage_indicator",
      ]
  
      dtypes = OrderedDict(
          [
              ("loan_id", "int64"),
              ("orig_channel", "category"),
              ("seller_name", "category"),
              ("orig_interest_rate", "float64"),
              ("orig_upb", "int64"),
              ("orig_loan_term", "int64"),
              ("orig_date", "date"),
              ("first_pay_date", "date"),
              ("orig_ltv", "float64"),
              ("orig_cltv", "float64"),
              ("num_borrowers", "float64"),
              ("dti", "float64"),
              ("borrower_credit_score", "float64"),
              ("first_home_buyer", "category"),
              ("loan_purpose", "category"),
              ("property_type", "category"),
              ("num_units", "int64"),
              ("occupancy_status", "category"),
              ("property_state", "category"),
              ("zip", "int64"),
              ("mortgage_insurance_percent", "float64"),
              ("product_type", "category"),
              ("coborrow_credit_score", "float64"),
              ("mortgage_insurance_type", "float64"),
              ("relocation_mortgage_indicator", "category"),
          ]
      )
  
      print(acquisition_path)
  
      acquisition_table = pyblazing.create_table(
          table_name="acq",
          type=get_type_schema(acquisition_path),
          path=acquisition_path,
          delimiter="|",
          names=cols,
          dtypes=dtypes,  # TODO: dtypes=get_dtype_values(dtypes)
          skip_rows=1,
      )
      Chronometer.show(chronometer, "Read Acquisition CSV")
      return acquisition_table
  
imports: import os
  import re
  import tempfile
  from collections import OrderedDict
  from os import listdir
  from os.path import isdir
  import glob
  from enum import IntEnum, unique
  import cudf
  import dask_cudf
  import numpy
  import pandas
  import pyblazing
  from blazingsql import DataType
  from pyhive import hive
  from Configuration import Settings
  from DemoTest.chronometer import Chronometer
label_desc: Use image node_id 26 for calling a global function with example usage: gpu_load_acquisition_csv(acquisition_path) and returns: acquisition_table