code: def main():
      L.seed_everything(42)
  
      # Data
      dataset = WikiText2()
  
      # Split data in to train, val, test
      n = len(dataset)
      train_dataset, val_dataset, test_dataset = random_split(
          dataset, [n - 4000, 2000, 2000]
      )
      train_dataloader = DataLoader(
          train_dataset, batch_size=20, shuffle=True
      )
      val_dataloader = DataLoader(
          val_dataset, batch_size=20, shuffle=False
      )
      test_dataloader = DataLoader(
          test_dataset, batch_size=20, shuffle=False
      )
  
      # Model
      model = LanguageModel(vocab_size=dataset.vocab_size)
  
      # Trainer
      trainer = L.Trainer(gradient_clip_val=0.25, max_epochs=20)
      trainer.fit(model, train_dataloader, val_dataloader)
      trainer.test(model, test_dataloader)
  
file_path: pytorch-lightning/examples/pytorch/basics/transformer.py
imports: import lightning
  import torch
  import torch.nn.functional
  from lightning.pytorch.demos import Transformer, WikiText2
  from torch.utils.data import DataLoader, random_split
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types