code: def _load_multipart(
      paths,
      delimiter=",",
      encoding="utf-8",
      columns_to_keep=None,
      dtype=None,
      header=0,
      names=None,
      format=None,
      nrows=None,
      skiprows=None,
      usecols=None,
      low_memory=False,
      converters=None,
      filters=None,
      worker_count=None,
      multiprocessing_method="forkserver",
  ):
      cpu_count = multiprocessing.cpu_count()
      workers = int(round(cpu_count))
      if worker_count is not None:
          if worker_count <= workers:
              workers = worker_count
  
      logger.log(
          15,
          "Load multipart running pool with "
          + str(workers)
          + " workers...",
      )
  
      full_chunks = [
          [
              path,
              delimiter,
              encoding,
              columns_to_keep,
              dtype,
              header,
              names,
              format,
              nrows,
              skiprows,
              usecols,
              low_memory,
              converters,
              filters,
          ]
          for path in paths
      ]
  
      df_list = multiprocessing_utils.execute_multiprocessing(
          workers_count=workers,
          transformer=_load_multipart_child,
          chunks=full_chunks,
          multiprocessing_method=multiprocessing_method,
      )
  
      df_combined = pd.concat(df_list, axis=0, ignore_index=True)
  
      column_count = len(list(df_combined.columns.values))
      row_count = df_combined.shape[0]
  
      logger.log(
          20,
          "Loaded data from multipart file | Columns = "
          + str(column_count)
          + " | Rows = "
          + str(row_count),
      )
      return df_combined
  
file_path: autogluon/common/src/autogluon/common/loaders/load_pd.py
imports: import logging
  import multiprocessing
  from os import listdir
  from os.path import isfile, join
  import pandas
  from pandas import DataFrame
  from ..savers import save_pointer
  from ..utils import multiprocessing_utils, s3_utils
  from .None import load_pointer
  from .load_s3 import list_bucket_prefix_suffix_contains_s3
label_desc: Use image node_id 3 for calling a global function with example usage: _load_multipart(paths, delimiter, encoding, columns_to_keep, dtype, header, names, format, nrows, skiprows, usecols, low_memory, converters, filters, worker_count, multiprocessing_method) and returns: df_combined