code: def test_negatives_that_have_no_positives(self):
      loss_func = PNPLoss()
      labels = torch.tensor([1, 1, 2], device=TEST_DEVICE)
      for dtype in TEST_DTYPES:
          embeddings = torch.randn(
              3, 32, dtype=dtype, device=TEST_DEVICE
          )
          loss = loss_func(embeddings, labels)
          self.assertTrue(not torch.isnan(loss))
  
file_path: pytorch-metric-learning/tests/losses/test_pnp_loss.py
imports: import unittest
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.nn.functional
  from pytorch_metric_learning.losses import PNPLoss
  from ..None import TEST_DEVICE, TEST_DTYPES
label_desc: Use image node_id 2 for calling the TestPNPLoss obj's underlying member method code with example usage: obj.test_negatives_that_have_no_positives() without return types