code: def get_dataset(dataset):
      "we wrapped a set of datasets as example"
      prepare_dataset(dataset)
      if dataset == "babi":
          raise NotImplementedError
      elif dataset == "copy" or dataset == "sort":
          return TranslationDataset(
              "data/{}".format(dataset),
              ("in", "out"),
              train="train",
              valid="valid",
              test="test",
          )
      elif dataset == "multi30k":
          return TranslationDataset(
              "data/multi30k",
              ("en.atok", "de.atok"),
              train="train",
              valid="val",
              test="test2016",
              replace_oov="<unk>",
          )
      elif dataset == "wmt14":
          return TranslationDataset(
              "data/wmt14",
              ("en", "de"),
              train="train.tok.clean.bpe.32000",
              valid="newstest2013.tok.bpe.32000",
              test="newstest2014.tok.bpe.32000.ende",
              vocab="vocab.bpe.32000",
          )
      else:
          raise KeyError()
  
file_path: dgl/examples/pytorch/transformer/dataset/__init__.py
imports: import os
  import random
  from .fields import *
  from .graph import *
  from .utils import prepare_dataset
label_desc: Use image node_id 1 for calling a global function with example usage: get_dataset(dataset) and returns: TranslationDataset, TranslationDataset, TranslationDataset