parameters: (scale_l1=1.0, scale_l2=1.0, scope=None)
return_statement: return sum_regularizer([l1_regularizer(scale_l1),
                            l2_regularizer(scale_l2)],
                           scope=scope)
docstring: Returns a function that can be used to apply L1 L2 regularizations.
  
    Args:
      scale_l1: A scalar multiplier `Tensor` for L1 regularization.
      scale_l2: A scalar multiplier `Tensor` for L2 regularization.
      scope: An optional scope name.
  
    Returns:
      A function with signature `l1_l2(weights)` that applies a weighted sum of
      L1 L2  regularization.
  
    Raises:
      ValueError: If scale is negative or if scale is not a float.
docstring_summary: Returns a function that can be used to apply L1 L2 regularizations.
docstring_tokens: Returns a function that can be used to apply L1 L2 regularizations .
function: def l1_l2_regularizer(scale_l1=1.0, scale_l2=1.0, scope=None):
    """Returns a function that can be used to apply L1 L2 regularizations.
  
    Args:
      scale_l1: A scalar multiplier `Tensor` for L1 regularization.
      scale_l2: A scalar multiplier `Tensor` for L2 regularization.
      scope: An optional scope name.
  
    Returns:
      A function with signature `l1_l2(weights)` that applies a weighted sum of
      L1 L2  regularization.
  
    Raises:
      ValueError: If scale is negative or if scale is not a float.
    """
    scope = scope or 'l1_l2_regularizer'
    return sum_regularizer([l1_regularizer(scale_l1),
                            l2_regularizer(scale_l2)],
                           scope=scope)
function_tokens: def l1_l2_regularizer ( scale_l1 = 1.0 , scale_l2 = 1.0 , scope = None ) : scope = scope or 'l1_l2_regularizer' return sum_regularizer ( [ l1_regularizer ( scale_l1 ) , l2_regularizer ( scale_l2 ) ] , scope = scope )