code: def test_margin_loss(self):
      for dtype in TEST_DTYPES:
          embeddings = torch.randn(
              5, 32, requires_grad=True, dtype=dtype
          ).to(TEST_DEVICE)
          embeddings = torch.nn.functional.normalize(embeddings)
          labels = torch.LongTensor([0, 0, 1, 1, 2])
  
          triplets = [
              (0, 1, 2),
              (0, 1, 3),
              (0, 1, 4),
              (1, 0, 2),
              (1, 0, 3),
              (1, 0, 4),
              (2, 3, 0),
              (2, 3, 1),
              (2, 3, 4),
              (3, 2, 0),
              (3, 2, 1),
              (3, 2, 4),
          ]
  
          self.helper(embeddings, labels, triplets, dtype)
  
file_path: pytorch-metric-learning/tests/losses/test_margin_loss.py
imports: import unittest
  import torch
  from pytorch_metric_learning.losses import MarginLoss
  from ..None import TEST_DEVICE, TEST_DTYPES
  from ..zzz_testing_utils.testing_utils import angle_to_coord
  from .utils import get_triplet_embeddings_with_ref
label_desc: Use image node_id 2 for calling the TestMarginLoss obj's underlying member method code with example usage: obj.test_margin_loss() without return types