code: def test_dynamic_soft_margin_loss_with_labels(self):
      torch.manual_seed(21)
      for dtype in TEST_DTYPES:
          if dtype == torch.float16:
              continue
          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])
  
          self.helper(
              embeddings, labels, dtype, min_val=-3.0, num_bins=10
          )
          self.helper(
              embeddings, labels, dtype, min_val=-3.0, num_bins=20
          )
          self.helper(
              embeddings, labels, dtype, min_val=-3.0, num_bins=30
          )
          self.helper(
              embeddings, labels, dtype, min_val=-2.0, num_bins=10
          )
          self.helper(
              embeddings, labels, dtype, min_val=-2.0, num_bins=20
          )
          self.helper(
              embeddings, labels, dtype, min_val=-2.0, num_bins=30
          )
          self.helper(
              embeddings, labels, dtype, min_val=-1.0, num_bins=10
          )
          self.helper(
              embeddings, labels, dtype, min_val=-1.0, num_bins=20
          )
          self.helper(
              embeddings, labels, dtype, min_val=-1.0, num_bins=30
          )
  
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 2 for calling the TestDynamicSoftMarginLoss obj's underlying member method code with example usage: obj.test_dynamic_soft_margin_loss_with_labels() without return types