code: def setup_method(self):
      super().setup_method()
  
      # embedding data from VERB demo
      emb_filename = str(
          self.FIXTURES_ROOT / "fairness" / "bias_embeddings.json"
      )
      with open(emb_filename) as emb_file:
          emb_data = json.load(emb_file)
  
      self.bias_direction1 = torch.Tensor(emb_data["oscar_bias1"])
      self.bias_direction2 = torch.Tensor(emb_data["oscar_bias2"])
  
      evaluation_embeddings = []
      expected_bias_mitigated_embeddings = []
      for word in ["programmer", "grandpa", "grandma"]:
          evaluation_embeddings.append(
              torch.Tensor(emb_data[word]).reshape(1, -1)
          )
          expected_bias_mitigated_embeddings.append(
              torch.Tensor(emb_data["oscar_" + word]).reshape(1, -1)
          )
      self.evaluation_embeddings = torch.cat(evaluation_embeddings)
      self.expected_bias_mitigated_embeddings = torch.cat(
          expected_bias_mitigated_embeddings
      )
  
imports: import torch
  from torch import allclose
  import pytest
  import json
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase, multi_device
  from allennlp.fairness.bias_mitigators import LinearBiasMitigator, HardBiasMitigator, INLPBiasMitigator, OSCaRBiasMitigator
  from allennlp.fairness.bias_direction import TwoMeansBiasDirection
label_desc: Use image node_id 1 for calling the OSCaRBiasMitigatorTest obj's underlying member method code with example usage: obj.setup_method() without return types