code: def test_triplet_margin_loss(self):
      for dtype in TEST_DTYPES:
          embeddings = torch.randn(
              5,
              32,
              requires_grad=True,
              dtype=dtype,
          ).to(
              TEST_DEVICE
          )  # 2D embeddings
          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_triplet_margin_loss.py
imports: import unittest
  import torch
  from pytorch_metric_learning.distances import CosineSimilarity
  from pytorch_metric_learning.losses import TripletMarginLoss
  from pytorch_metric_learning.reducers import MeanReducer
  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 1 for calling the TestTripletMarginLoss obj's underlying member method code with example usage: obj.test_triplet_margin_loss() without return types