code: def read_single_udf(
      pickleSer, infile, eval_type, runner_conf, udf_index
  ):
      num_arg = read_int(infile)
  
      if eval_type in (
          PythonEvalType.SQL_BATCHED_UDF,
          PythonEvalType.SQL_ARROW_BATCHED_UDF,
          PythonEvalType.SQL_SCALAR_PANDAS_UDF,
          PythonEvalType.SQL_GROUPED_AGG_PANDAS_UDF,
          PythonEvalType.SQL_WINDOW_AGG_PANDAS_UDF,
          # The below doesn't support named argument, but shares the same protocol.
          PythonEvalType.SQL_SCALAR_PANDAS_ITER_UDF,
      ):
          args_offsets = []
          kwargs_offsets = {}
          for _ in range(num_arg):
              offset = read_int(infile)
              if read_bool(infile):
                  name = utf8_deserializer.loads(infile)
                  kwargs_offsets[name] = offset
              else:
                  args_offsets.append(offset)
      else:
          args_offsets = [read_int(infile) for i in range(num_arg)]
          kwargs_offsets = {}
  
      chained_func = None
      for i in range(read_int(infile)):
          f, return_type = read_command(pickleSer, infile)
          if chained_func is None:
              chained_func = f
          else:
              chained_func = chain(chained_func, f)
  
      if eval_type in (
          PythonEvalType.SQL_SCALAR_PANDAS_ITER_UDF,
          PythonEvalType.SQL_ARROW_BATCHED_UDF,
      ):
          func = chained_func
      else:
          # make sure StopIteration's raised in the user code are not ignored
          # when they are processed in a for loop, raise them as RuntimeError's instead
          func = fail_on_stopiteration(chained_func)
  
      # the last returnType will be the return type of UDF
      if eval_type == PythonEvalType.SQL_SCALAR_PANDAS_UDF:
          return wrap_scalar_pandas_udf(
              func, args_offsets, kwargs_offsets, return_type
          )
      elif eval_type == PythonEvalType.SQL_ARROW_BATCHED_UDF:
          return wrap_arrow_batch_udf(
              func, args_offsets, kwargs_offsets, return_type
          )
      elif eval_type == PythonEvalType.SQL_SCALAR_PANDAS_ITER_UDF:
          return args_offsets, wrap_pandas_batch_iter_udf(
              func, return_type
          )
      elif eval_type == PythonEvalType.SQL_MAP_PANDAS_ITER_UDF:
          return args_offsets, wrap_pandas_batch_iter_udf(
              func, return_type
          )
      elif eval_type == PythonEvalType.SQL_MAP_ARROW_ITER_UDF:
          return args_offsets, wrap_arrow_batch_iter_udf(
              func, return_type
          )
      elif eval_type == PythonEvalType.SQL_GROUPED_MAP_PANDAS_UDF:
          argspec = inspect.getfullargspec(
              chained_func
          )  # signature was lost when wrapping it
          return args_offsets, wrap_grouped_map_pandas_udf(
              func, return_type, argspec, runner_conf
          )
      elif eval_type == PythonEvalType.SQL_GROUPED_MAP_ARROW_UDF:
          argspec = inspect.getfullargspec(
              chained_func
          )  # signature was lost when wrapping it
          return args_offsets, wrap_grouped_map_arrow_udf(
              func, return_type, argspec, runner_conf
          )
      elif (
          eval_type
          == PythonEvalType.SQL_GROUPED_MAP_PANDAS_UDF_WITH_STATE
      ):
          return args_offsets, wrap_grouped_map_pandas_udf_with_state(
              func, return_type
          )
      elif eval_type == PythonEvalType.SQL_COGROUPED_MAP_PANDAS_UDF:
          argspec = inspect.getfullargspec(
              chained_func
          )  # signature was lost when wrapping it
          return args_offsets, wrap_cogrouped_map_pandas_udf(
              func, return_type, argspec, runner_conf
          )
      elif eval_type == PythonEvalType.SQL_COGROUPED_MAP_ARROW_UDF:
          argspec = inspect.getfullargspec(
              chained_func
          )  # signature was lost when wrapping it
          return args_offsets, wrap_cogrouped_map_arrow_udf(
              func, return_type, argspec, runner_conf
          )
      elif eval_type == PythonEvalType.SQL_GROUPED_AGG_PANDAS_UDF:
          return wrap_grouped_agg_pandas_udf(
              func, args_offsets, kwargs_offsets, return_type
          )
      elif eval_type == PythonEvalType.SQL_WINDOW_AGG_PANDAS_UDF:
          return wrap_window_agg_pandas_udf(
              func,
              args_offsets,
              kwargs_offsets,
              return_type,
              runner_conf,
              udf_index,
          )
      elif eval_type == PythonEvalType.SQL_BATCHED_UDF:
          return wrap_udf(
              func, args_offsets, kwargs_offsets, return_type
          )
      else:
          raise ValueError("Unknown eval type: {}".format(eval_type))
  
imports: import os
  import sys
  import dataclasses
  import time
  import inspect
  import json
  from typing import Any, Callable, Iterable, Iterator, Optional
  import faulthandler
  from pyspark.accumulators import _accumulatorRegistry
  from pyspark.java_gateway import local_connect_and_auth
  from pyspark.taskcontext import BarrierTaskContext, TaskContext
  from pyspark.resource import ResourceInformation
  from pyspark.rdd import PythonEvalType
  from pyspark.serializers import write_int, read_long, read_bool, write_long, read_int, SpecialLengths, UTF8Deserializer, CPickleSerializer, BatchedSerializer
  from pyspark.sql.functions import SkipRestOfInputTableException
  from pyspark.sql.pandas.serializers import ArrowStreamPandasUDFSerializer, ArrowStreamPandasUDTFSerializer, CogroupArrowUDFSerializer, CogroupPandasUDFSerializer, ArrowStreamUDFSerializer, ArrowStreamGroupUDFSerializer, ApplyInPandasWithStateSerializer
  from pyspark.sql.pandas.types import to_arrow_type
  from pyspark.sql.types import ArrayType, BinaryType, DataType, MapType, Row, StringType, StructType, _create_row, _parse_datatype_json_string
  from pyspark.util import fail_on_stopiteration, handle_worker_exception
  from pyspark import shuffle
  from pyspark.errors import PySparkRuntimeError, PySparkTypeError
  from pyspark.worker_util import check_python_version, read_command, pickleSer, send_accumulator_updates, setup_broadcasts, setup_memory_limits, setup_spark_files, utf8_deserializer
label_desc: Use image node_id 20 for calling a global function with example usage: read_single_udf(pickleSer, infile, eval_type, runner_conf, udf_index) and returns: wrap_scalar_pandas_udf, wrap_arrow_batch_udf, args_offsets,  wrap_pandas_batch_iter_udf, args_offsets,  wrap_pandas_batch_iter_udf, args_offsets,  wrap_arrow_batch_iter_udf, args_offsets,  wrap_grouped_map_pandas_udf, args_offsets,  wrap_grouped_map_arrow_udf, args_offsets,  wrap_grouped_map_pandas_udf_with_state, args_offsets,  wrap_cogrouped_map_pandas_udf, args_offsets,  wrap_cogrouped_map_arrow_udf, wrap_grouped_agg_pandas_udf, wrap_window_agg_pandas_udf, wrap_udf