code: def run_pearson(ctx: "Context"):
      from fate.ml.statistics.pearson_correlation import (
          PearsonCorrelation,
      )
      from fate.arch import dataframe
  
      ctx.mpc.init()
      args, _ = HfArgumentParser(
          PearsonArguments
      ).parse_args_into_dataclasses(return_remaining_strings=True)
      inst = PearsonCorrelation()
      if ctx.is_on_guest:
          kwargs = {
              "sample_id_name": None,
              "match_id_name": "id",
              "delimiter": ",",
              "label_name": "y",
              "label_type": "float32",
              "dtype": "float32",
          }
          input_data = dataframe.CSVReader(**kwargs).to_frame(
              ctx, args.guest_data
          )
      else:
          kwargs = {
              "sample_id_name": None,
              "match_id_name": "id",
              "delimiter": ",",
              "dtype": "float32",
          }
          input_data = dataframe.CSVReader(**kwargs).to_frame(
              ctx, args.host_data
          )
      inst.fit(ctx, input_data=input_data)
      print(f"role: {ctx.local.role};\n vif: {inst.vif}")
  
imports: import logging
  import typing
  from dataclasses import dataclass, field
  from fate.arch.launchers.argparser import HfArgumentParser
  from fate.arch.launchers.multiprocess_launcher import launch
label_desc: Use image node_id 1 for calling a global function with example usage: run_pearson(ctx) without return types