code: def test_two_means_with_grad(self, device: str):
      seed_embeddings1 = torch.eye(2, device=device)
      seed_embeddings2 = 1 - torch.eye(2, device=device)
      seed_embeddings1 = seed_embeddings1.requires_grad_()
      seed_embeddings2 = seed_embeddings2.requires_grad_()
      assert seed_embeddings1.grad is None
      assert seed_embeddings2.grad is None
  
      two_means = TwoMeansBiasDirection(requires_grad=True)
      test_bias_direction = two_means(
          seed_embeddings1, seed_embeddings2
      )
      test_bias_direction.sum().backward()
      assert seed_embeddings1.grad is not None
      assert seed_embeddings2.grad is not None
  
imports: import torch
  from torch import allclose
  import pytest
  import math
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase, multi_device
  from allennlp.fairness.bias_direction import PCABiasDirection, PairedPCABiasDirection, TwoMeansBiasDirection, ClassificationNormalBiasDirection
label_desc: Use image node_id 3 for calling the TwoMeansBiasDirectionTest obj's underlying member method code with example usage: obj.test_two_means_with_grad(device) without return types