10335f61775faabe5e931f30b0ecf91f0719b727,tutorials/mnist_dpsgd_tutorial.py,,main,#Any#,180

Before Change

def main(unused_argv):
  tf.logging.set_verbosity(tf.logging.INFO)
  if FLAGS.dpsgd and FLAGS.batch_size % FLAGS.microbatches != 0:
    raise ValueError("Number of microbatches should divide evenly batch_size")

  // Load training and test data.

After Change

    // Compute the privacy budget expended.
    if FLAGS.dpsgd:
      if FLAGS.noise_multiplier > 0.0:
        eps, _ = compute_dp_sgd_privacy_lib.compute_dp_sgd_privacy(
            60000, FLAGS.batch_size, FLAGS.noise_multiplier, epoch, 1e-5)
        print("For delta=1e-5, the current epsilon is: %.2f" % eps)
      else:
        print("Trained with DP-SGD but with zero noise.")
    else:
      print("Trained with vanilla non-private SGD optimizer")

Instances