code: def __init__(
      self,
      dataset: TimeSeriesDataset,
      batch_size=32,
      valid_batch_size=1024,
      num_workers=0,
      drop_last=False,
  ):
      super().__init__()
      self.dataset = dataset
      self.batch_size = batch_size
      self.valid_batch_size = valid_batch_size
      self.num_workers = num_workers
      self.drop_last = drop_last
  
imports: import warnings
  from collections.abc import Mapping
  import numpy
  import pandas
  import pytorch_lightning
  import torch
  import utilsforecast.processing
  from torch.utils.data import Dataset, DataLoader
  from utilsforecast.compat import DataFrame, pl_Series
label_desc: Use image node_id 1 to create a new TimeSeriesDataModule object from inherited base classes: pl with example: obj = TimeSeriesDataModule(dataset, batch_size, valid_batch_size, num_workers, drop_last)