class_docstr: Allow per-line lazy access to multiple csv files using numpy memmap.
  Returns a dictionary with multiple fields.
docstr: Args:
      dataset_paths: list of csv file paths to read data from
      newline_int: ASCII code to use to interpret newlines in file.
      header_lines: number of header lines in csv files.
      workers: number of workers to use for creating index files.
      tokenizer: tokenizer to use to convert text to tokens.
      sort_dataset_paths: whether to sort datasets by paths.
      data_sep: data separator.
      data_fields:  dict of field names and their corresponding column indices
      index_mapping_dir: directory to save the index mapping to.
          If None, will write to the same folder as the dataset.
code: def __init__(
      self,
      dataset_paths,
      newline_int=10,
      header_lines=1,
      workers=None,
      tokenizer=None,
      sort_dataset_paths=True,
      data_sep=",",
      data_fields={"data": 0},
      index_mapping_dir: Optional[str] = None,
  ):
      """
      Args:
          dataset_paths: list of csv file paths to read data from
          newline_int: ASCII code to use to interpret newlines in file.
          header_lines: number of header lines in csv files.
          workers: number of workers to use for creating index files.
          tokenizer: tokenizer to use to convert text to tokens.
          sort_dataset_paths: whether to sort datasets by paths.
          data_sep: data separator.
          data_fields:  dict of field names and their corresponding column indices
          index_mapping_dir: directory to save the index mapping to.
              If None, will write to the same folder as the dataset.
      """
      super().__init__(
          dataset_paths=dataset_paths,
          newline_int=newline_int,
          header_lines=header_lines,
          workers=workers,
          tokenizer=tokenizer,
          sort_dataset_paths=sort_dataset_paths,
          index_mapping_dir=index_mapping_dir,
      )
  
      self._data_fields = data_fields
      self._data_sep = data_sep
  
imports: import datetime
  import json
  import multiprocessing
  import os
  import pickle
  import time
  from functools import partial
  from typing import Callable, List, Optional, Type
  import numpy
  import torch
  from nemo.core import Dataset
  from nemo.utils import AppState, logging
label_desc: Use image node_id 1 to create a new CSVFieldsMemmapDataset object from inherited base classes: TextMemMapDataset with example: obj = CSVFieldsMemmapDataset(dataset_paths, newline_int, header_lines, workers, tokenizer, sort_dataset_paths, data_sep, data_fields, index_mapping_dir)