code: def test_backward(self):
      loss_funcA = NPairsLoss()
      loss_funcB = NPairsLoss(embedding_regularizer=LpRegularizer())
  
      for dtype in TEST_DTYPES:
          for loss_func in [loss_funcA, loss_funcB]:
              embedding_angles = list(range(0, 180, 20))[:7]
              embeddings = torch.tensor(
                  [angle_to_coord(a) for a in embedding_angles],
                  requires_grad=True,
                  dtype=dtype,
              ).to(
                  TEST_DEVICE
              )  # 2D embeddings
              labels = torch.LongTensor([0, 0, 1, 1, 1, 2, 3])
  
              loss = loss_func(embeddings, labels)
              loss.backward()
  
file_path: pytorch-metric-learning/tests/losses/test_npairs_loss.py
imports: import unittest
  import torch
  from pytorch_metric_learning.losses import NPairsLoss
  from pytorch_metric_learning.regularizers import LpRegularizer
  from ..None import TEST_DEVICE, TEST_DTYPES
  from ..zzz_testing_utils.testing_utils import angle_to_coord
label_desc: Use image node_id 3 for calling the TestNPairsLoss obj's underlying member method code with example usage: obj.test_backward() without return types