code: def test_meta_dataloader_task_loader():
      dataset = Sinusoid(10, num_tasks=1000, noise_std=None)
      meta_dataloader = MetaDataLoader(dataset, batch_size=4)
      batch = next(iter(meta_dataloader))
  
      dataloader = DataLoader(batch[0], batch_size=5)
      inputs, targets = next(iter(dataloader))
  
      assert len(dataloader) == 2  # 10 / 5
      # PyTorch dataloaders convert numpy array to tensors
      assert isinstance(inputs, torch.Tensor)
      assert isinstance(targets, torch.Tensor)
      assert inputs.shape == (5, 1)
      assert targets.shape == (5, 1)
  
file_path: pytorch-meta/torchmeta/tests/utils/test_dataloaders.py
imports: import pytest
  import os
  import torch
  from torch.utils.data import DataLoader
  from torchmeta.datasets import helpers
  from torchmeta.toy import Sinusoid
  from torchmeta.transforms import ClassSplitter
  from torchmeta.utils.data import Task, MetaDataLoader, BatchMetaDataLoader
label_desc: Use image node_id 2 for calling a global function with example usage: test_meta_dataloader_task_loader() without return types