code: def test_empty_output(self):
      miner = DistanceWeightedMiner(0.1, 0.5)
      batch_size = 32
      for dtype in TEST_DTYPES:
          embeddings = (
              torch.randn(batch_size, 64).type(dtype).to(TEST_DEVICE)
          )
          labels = torch.arange(batch_size)
          a, p, n = miner(embeddings, labels)
          self.assertTrue(len(a) == 0)
          self.assertTrue(len(p) == 0)
          self.assertTrue(len(n) == 0)
  
file_path: pytorch-metric-learning/tests/miners/test_distance_weighted_miner.py
imports: import unittest
  import torch
  from pytorch_metric_learning.miners import DistanceWeightedMiner
  from pytorch_metric_learning.utils import loss_and_miner_utils
  from ..None import TEST_DEVICE, TEST_DTYPES
  from ..zzz_testing_utils.testing_utils import angle_to_coord
label_desc: Use image node_id 3 for calling the TestDistanceWeightedMiner obj's underlying member method code with example usage: obj.test_empty_output() without return types