code: def _compute_stats(self, pos_dist, neg_dist):
      hist_val = pos_dist - neg_dist
      if self._stats_initialized:
          self._compute_histogram(hist_val, self._momentum)
      else:
          self._compute_histogram(hist_val, 1.0)
          self._stats_initialized = True
  
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 OriginalImplementationDynamicSoftMarginLoss obj's underlying member method code with example usage: obj._compute_stats(pos_dist, neg_dist) without return types