class_docstr: Main life2vec data processing pipeline. The data is generated based on a corpus
  and a task. The generated data is stored in /processed/<corpus>/<task>, with
  subfolders corresponding to each data split. The remaining parameters are given
  to :class:`torch.utils.data.DataLoader`.
  
  :param corpus: The corpus to generate data from.
  :param vocabulary: Vocabulary to use.
  :param task: Task to generate data for.
  
  :param batch_size: Batch size
  :param num_workers: Number of data loading workers
  :param persisten_worksers: Whether to persist workers
  :param pin_memory: Whether to pin memory
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docstr: Since we dont want to include the data loading parameters, when validating
  the saved datasets with the current parameters, we instead supply the arguments
  of the corpus and task from here.
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code: def _arguments(self) -> Dict[str, Any]:
      """Since we dont want to include the data loading parameters, when validating
      the saved datasets with the current parameters, we instead supply the arguments
      of the corpus and task from here."""
  
      return {
          "corpus": _jsonify(self.corpus),
          "vocabulary": _jsonify(self.vocabulary),
          "task": _jsonify(self.task),
      }
  
imports: import enum
  import logging
  import pickle
  from dataclasses import dataclass, replace
  from pathlib import Path
  from typing import Any, Dict, List, Optional
  from typing_extensions import dataclass_transform
  import dask
  import dask.dataframe
  import pandas
  import numpy
  import pytorch_lightning
  import torch
  from pandas.tseries.offsets import MonthEnd
  from torch.utils.data import DataLoader, Dataset, WeightedRandomSampler
  from ..tasks.base import Task, collate_encoded_documents
  from .sampler import FixedSampler
  from .dataset import DocumentDataset, ShardedDocumentDataset
  from .decorators import save_parquet, save_pickle
  from .ops import concat_columns_dask, concat_sorted
  from .populations.base import Population
  from .serialize import DATA_ROOT, ValidationError, _jsonify
  from .sources.base import Field, TokenSource
  from .vocabulary import Vocabulary
label_desc: Use image node_id 4 for calling the L2VDataModule obj's underlying member method code with example usage: obj._arguments() and returns: dict