class_docstr: An `Estimator` type with utilities for creating PyTorch-Lightning-based
  models.
  
  To extend this class, one needs to implement three methods:
  `create_transformation`, `create_training_network`, `create_predictor`,
  `create_training_data_loader`, and `create_validation_data_loader`.
class_docstr_tok: ["An","`","Estimator","`","type","with","utilities","for","creating","PyTorch-Lightning-based","models",".","To","extend","this","class",",","one","needs","to","implement","three","methods",":","`","create_transformation","`",",","`","create_training_network","`",",","`","create_predictor","`",",","`","create_training_data_loader","`",",","and","`","create_validation_data_loader","`","."]
docstr: Create a data loader for training purposes.
  
  Parameters
  ----------
  data
      Dataset from which to create the data loader.
  module
      The `pl.LightningModule` object that will receive the batches from
      the data loader.
  
  Returns
  -------
  Iterable
      The data loader, i.e. and iterable over batches of data.
docstr_tok: ["Create","a","data","loader","for","training","purposes",".","Parameters","--","--","--","--","--","data","Dataset","from","which","to","create","the","data","loader",".","module","The","`","pl.LightningModule","`","object","that","will","receive","the","batches","from","the","data","loader",".","Returns","--","--","--","-","Iterable","The","data","loader",",","i.e",".","and","iterable","over","batches","of","data","."]
code: def create_training_data_loader(
      self, data: Dataset, module, **kwargs
  ) -> Iterable:
      """
      Create a data loader for training purposes.
  
      Parameters
      ----------
      data
          Dataset from which to create the data loader.
      module
          The `pl.LightningModule` object that will receive the batches from
          the data loader.
  
      Returns
      -------
      Iterable
          The data loader, i.e. and iterable over batches of data.
      """
      raise NotImplementedError
  
imports: from typing import NamedTuple, Optional, Iterable, Dict, Any
  import logging
  import numpy
  import lightning.pytorch
  import torch.nn
  from gluonts.core.component import validated
  from gluonts.dataset.common import Dataset
  from gluonts.env import env
  from gluonts.itertools import Cached
  from gluonts.model import Estimator, Predictor
  from gluonts.torch.model.predictor import PyTorchPredictor
  from gluonts.transform import Transformation
label_desc: Use image node_id 5 for calling the PyTorchLightningEstimator obj's underlying member method code with example usage: obj.create_training_data_loader(data, module) without return types