code: def dSoftBinning(D, mid, Delta):
      side1 = (D > (mid - Delta)).type(D.dtype)
      side2 = (D <= mid).type(D.dtype)
      ind1 = side1 * side2  # .type(torch.uint8)
  
      side1 = (D > mid).type(D.dtype)
      side2 = (D <= (mid + Delta)).type(D.dtype)
      ind2 = side1 * side2  # .type(torch.uint8)
  
      return (ind1 - ind2) / Delta
  
file_path: pytorch-metric-learning/tests/losses/test_fastap_loss.py
imports: import torch
  from torch.autograd import Variable
  import unittest
  from pytorch_metric_learning.losses import FastAPLoss
  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 a global function with example usage: dSoftBinning(D, mid, Delta) and returns: unknown