code: def membership_test(model, pois_x, pois_y):
      """Membership inference - detect poisoning."""
      probs = model.predict(
          np.concatenate([pois_x, np.zeros_like(pois_x)])
      )
      return np.multiply(probs[0, :] - probs[1, :], pois_y).sum()
  
file_path: privacy/research/audit_2020/fmnist_audit.py
imports: import numpy
  import tensorflow.compat.v1
  from tensorflow_privacy.privacy.analysis.rdp_accountant import compute_rdp
  from tensorflow_privacy.privacy.analysis.rdp_accountant import get_privacy_spent
  from tensorflow_privacy.privacy.optimizers import dp_optimizer_vectorized
  from absl import app
  from absl import flags
  import audit
label_desc: Use image node_id 4 for calling a global function with example usage: membership_test(model, pois_x, pois_y) and returns: np