code: def test_pca_without_grad(self, device: str):
      seed_embeddings = torch.eye(2, device=device)
      pca = PCABiasDirection()
  
      const = 1 / math.sqrt(2)
      expected_bias_direction = torch.tensor(
          [const, -const], device=device
      )
      test_bias_direction = pca(seed_embeddings)
      k = expected_bias_direction / test_bias_direction
      assert k[0].item() == pytest.approx(k[1].item())
      assert seed_embeddings.grad is 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 2 for calling the PCABiasDirectionTest obj's underlying member method code with example usage: obj.test_pca_without_grad(device) without return types