class_docstr: A base module for training models with PyTorch Lightning.
  
  .. seealso::
      :class:`pykeen.training.training_loop.TrainingLoop`
class_docstr_tok: ["A","base","module","for","training","models","with","PyTorch","Lightning",".","..","seealso",":",":",":","class",":","`","pykeen.training.training_loop.TrainingLoop","`"]
docstr: Create the training data loader.
docstr_tok: ["Create","the","training","data","loader","."]
code: def train_dataloader(self) -> torch.utils.data.DataLoader:
      """Create the training data loader."""
      return self._dataloader(
          triples_factory=self.dataset.training, shuffle=True
      )
  
imports: from abc import abstractmethod
  from typing import Optional
  import click
  import pytorch_lightning
  import torch
  import torch.utils.data
  from class_resolver import ClassResolver, HintOrType, OptionalKwargs
  from pykeen.datasets import dataset_resolver, get_dataset
  from pykeen.datasets.base import Dataset
  from pykeen.losses import Loss, loss_resolver
  from pykeen.models import Model, model_resolver
  from pykeen.models.cli import options
  from pykeen.optimizers import optimizer_resolver
  from pykeen.sampling import NegativeSampler
  from pykeen.training import LCWATrainingLoop, SLCWATrainingLoop
  from pykeen.triples.triples_factory import CoreTriplesFactory
  from pykeen.typing import InductiveMode, OneOrSequence
label_desc: Use image node_id 7 for calling the LitModule obj's underlying member method code with example usage: obj.train_dataloader() and returns: self