code: def test_collate_with_new_dimension():
      class MyData(Data):
          def __cat_dim__(self, key, value, *args, **kwargs):
              if key == "foo":
                  return None
              else:
                  return super().__cat_dim__(
                      key, value, *args, **kwargs
                  )
  
      x = torch.tensor([1, 2, 3], dtype=torch.float)
      foo = torch.randn(4)
      y = torch.tensor(1)
  
      data = MyData(x=x, foo=foo, y=y)
  
      dataset = MyTestDataset([data, data])
      assert str(dataset) == "MyTestDataset(2)"
      assert len(dataset) == 2
  
      data1 = dataset[0]
      assert len(data1) == 3
      assert data1.x.tolist() == x.tolist()
      assert data1.foo.tolist() == foo.tolist()
      assert data1.y.tolist() == [1]
  
      data2 = dataset[0]
      assert len(data2) == 3
      assert data2.x.tolist() == x.tolist()
      assert data2.foo.tolist() == foo.tolist()
      assert data2.y.tolist() == [1]
  
imports: import copy
  import pytest
  import torch
  from torch_geometric import EdgeIndex
  from torch_geometric.data import Data, HeteroData, InMemoryDataset
  from torch_geometric.datasets import KarateClub
  from torch_geometric.testing import withPackage
  from torch_geometric.transforms import BaseTransform
  from torch_geometric.typing import SparseTensor
label_desc: Use image node_id 9 for calling a global function with example usage: test_collate_with_new_dimension() and returns: None, super