code: def test_backward(self):
      loss_funcA = ContrastiveLoss()
      loss_funcB = ContrastiveLoss(distance=CosineSimilarity())
      for dtype in TEST_DTYPES:
          for loss_func in [loss_funcA, loss_funcB]:
              embedding_angles = [0]
              embeddings = torch.tensor(
                  [
                      testing_utils.angle_to_coord(a)
                      for a in embedding_angles
                  ],
                  requires_grad=True,
                  dtype=dtype,
              ).to(
                  TEST_DEVICE
              )  # 2D embeddings
              labels = torch.LongTensor([0])
              loss = loss_func(embeddings, labels)
              loss.backward()
  
file_path: pytorch-metric-learning/tests/losses/test_contrastive_loss.py
imports: import unittest
  import torch
  from pytorch_metric_learning.distances import CosineSimilarity, LpDistance
  from pytorch_metric_learning.losses import ContrastiveLoss
  from pytorch_metric_learning.reducers import MeanReducer
  from ..None import TEST_DEVICE, TEST_DTYPES, WITH_COLLECT_STATS
  from ..zzz_testing_utils import testing_utils
label_desc: Use image node_id 3 for calling the TestContrastiveLoss obj's underlying member method code with example usage: obj.test_backward() without return types