code: def test_loading_with_sampler(self):
      reader = MultiTaskDatasetReader(
          readers={"a": FakeDatasetReaderA(), "b": FakeDatasetReaderB()}
      )
      data_path = {"a": "ignored", "b": "ignored"}
      scheduler = RoundRobinScheduler(batch_size=4)
      sampler = WeightedSampler({"a": 1, "b": 2})
      loader = MultiTaskDataLoader(
          reader=reader,
          data_path=data_path,
          scheduler=scheduler,
          sampler=sampler,
          instances_per_epoch=9,
      )
      vocab = Vocabulary()
      vocab.add_tokens_to_namespace(["A", "B"], "labels")
      loader.index_with(vocab)
      iterator = iter(loader)
      batch = next(iterator)
      assert torch.all(batch["label"] == torch.IntTensor([0, 1, 0, 1]))
      batch = next(iterator)
      assert torch.all(batch["label"] == torch.IntTensor([0, 1, 1, 1]))
      batch = next(iterator)
      assert torch.all(batch["label"] == torch.IntTensor([1]))
      with pytest.raises(StopIteration):
          next(iterator)
  
file_path: allennlp/tests/data/data_loaders/multitask_data_loader_test.py
imports: import itertools
  import pytest
  import torch
  from allennlp.common.util import cycle_iterator_function
  from allennlp.data import DatasetReader, Instance, Vocabulary
  from allennlp.data.fields import LabelField
  from allennlp.data.dataset_readers import MultiTaskDatasetReader
  from allennlp.data.data_loaders.multitask_data_loader import MultiTaskDataLoader
  from allennlp.data.data_loaders.multitask_scheduler import RoundRobinScheduler
  from allennlp.data.data_loaders.multitask_epoch_sampler import UniformSampler, WeightedSampler
label_desc: Use image node_id 2 for calling the MultiTaskDataLoaderTest obj's underlying member method code with example usage: obj.test_loading_with_sampler() without return types