code: def test_to_and_from_nested_tensor_autograd():
      x = torch.randn(5, 4, 3, requires_grad=True)
      grad = torch.randn_like(x)
  
      out = to_nested_tensor(x, batch=torch.tensor([0, 0, 1, 1, 1]))
      out = from_nested_tensor(out)
      out.backward(grad)
      assert torch.equal(x.grad, grad)
  
imports: import pytest
  import torch
  from torch_geometric.testing import withPackage
  from torch_geometric.utils import from_nested_tensor, to_nested_tensor
label_desc: Use image node_id 3 for calling a global function with example usage: test_to_and_from_nested_tensor_autograd() without return types