a97304d53e873ce5949b486c8fcbf5d4fcab7a3b,adversarial_text/adversarial_losses.py,,_scale_l2,#Any#Any#,174

Before Change

def _scale_l2(x, norm_length):
  // shape(x) = (batch, num_timesteps, d)
  x /= (1e-12 + tf.reduce_max(tf.abs(x), 2, keep_dims=True))
  x_2 = tf.reduce_sum(tf.pow(x, 2), 2, keep_dims=True)
  x /= tf.sqrt(1e-6 + x_2)

  return norm_length * x

After Change

  // 2norm(x) = a * 2norm(x/a)
  // Scale over the full sequence, dims (1, 2)
  alpha = tf.reduce_max(tf.abs(x), (1, 2), keep_dims=True) + 1e-12
  l2_norm = alpha * tf.sqrt(tf.reduce_sum(tf.pow(x / alpha, 2), (1, 2),
                                          keep_dims=True) + 1e-6)
  x_unit = x / l2_norm
  return norm_length * x_unit

Instances