code: def test_backward(self):
      torch.manual_seed(21)
      for dtype in TEST_DTYPES:
          if dtype == torch.float16:
              continue
          loss_func = DynamicSoftMarginLoss()
          embedding_angles = [0, 20, 40, 60, 80]
          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, 2])
  
          loss = loss_func(embeddings, labels)
          loss.backward()
  
imports: import torch
  import torch.nn
  from pytorch_metric_learning.utils import common_functions
  from pytorch_metric_learning.utils import loss_and_miner_utils
  import unittest
  from pytorch_metric_learning.losses import DynamicSoftMarginLoss
  from ..None import TEST_DEVICE, TEST_DTYPES
  from ..zzz_testing_utils.testing_utils import angle_to_coord
label_desc: Use image node_id 5 for calling the TestDynamicSoftMarginLoss obj's underlying member method code with example usage: obj.test_backward() without return types