code: def __init__(self, num_steps, cuda=True):
      super(OriginalImplementationHistogramLoss, self).__init__()
      self.step = 2 / (num_steps - 1)
      self.eps = 1 / num_steps
      self.cuda = cuda
      self.t = torch.arange(-1, 1 + self.step, self.step).view(-1, 1)
      self.tsize = self.t.size()[0]
      if self.cuda:
          self.t = self.t.cuda()
  
file_path: pytorch-metric-learning/tests/losses/test_histogram_loss.py
imports: import unittest
  import torch
  from numpy.testing import assert_almost_equal
  from pytorch_metric_learning.losses import HistogramLoss
  from pytorch_metric_learning.utils import common_functions
  from ..None import TEST_DEVICE, TEST_DTYPES
label_desc: Use image node_id 1 to create a new OriginalImplementationHistogramLoss object from inherited base classes: torch.nn with example: obj = OriginalImplementationHistogramLoss(num_steps, cuda)