code: def RAPPOR_loss(alpha):
      def rappor_loss(logits, targets):
          p = logits.sigmoid()
          r = alpha * p + (1 - alpha) * (1 - p)
          return torch.nn.functional.binary_cross_entropy(r, targets)
  
      return rappor_loss
  
imports: import copy
  import itertools
  import logging
  import crypten
  import torch
  from crypten.common.tensor_types import is_float_tensor
  from crypten.config import cfg
  from crypten.nn.privacy import DPSplitModel, SkippedLoss
  from test.multiprocess_test_case import get_random_test_tensor, MultiProcessTestCase
label_desc: Use image node_id 1 for calling a global function with example usage: RAPPOR_loss(alpha) and returns: rappor_loss, torch