def unit_ball_L_inf ( shape , precondition = True ) : x = tf . Variable ( tf . zeros ( shape ) ) if precondition : return constrain_L_inf_precondition ( x ) else : return constrain_L_inf ( x )
add early stopping in tensorflow 2 layers in python
A tensorflow variable tranfomed to be constrained in a L_inf unit ball .
def unit_ball_L_inf(shape, precondition=True):
  """A tensorflow variable tranfomed to be constrained in a L_inf unit ball.

  Note that this code also preconditions the gradient to go in the L_inf
  direction of steepest descent.

  EXPERIMENTAL: Do not use for adverserial examples if you need to be confident
  they are strong attacks. We are not yet confident in this code.
  """
  x = tf.Variable(tf.zeros(shape))
  if precondition:
    return constrain_L_inf_precondition(x)
  else:
    return constrain_L_inf(x)