old_contents: import theano.tensor as T
  
  from . import layers
  
  
  def l2(layer, include_biases=False):
      if include_biases:
          all_params = layers.get_all_params(layer)
      else:
          all_params = layers.get_all_non_bias_params(layer)
  
      return sum(T.sum(p**2) for p in all_params)
  
  
  # TODO: sparsity regularization
  
new_contents: import theano.tensor as T
  
  from . import layers
  
  
  def l2(layer, include_biases=False):
      if include_biases:
          all_params = layers.get_all_params(layer)
      else:
          all_params = layers.get_all_non_bias_params(layer)
  
      return sum(T.sum(p**2) for p in all_params)
  
  def l1(layer, include_biases=False):
      if include_biases:
          all_params = nn.layers.get_all_params(layer)
      else:
          all_params = nn.layers.get_all_non_bias_params(layer)
  
      return sum(T.sum(abs(p)) for p in all_params)
  
  # TODO: sparsity regularization
  
subject: Add l1 regularization.