code: def sum_regularizer(regularizer_list, scope=None):
      """Returns a function that applies the sum of multiple regularizers.
  
      Args:
        regularizer_list: A list of regularizers to apply.
        scope: An optional scope name
  
      Returns:
        A function with signature `sum_reg(weights)` that applies the
        sum of all the input regularizers.
      """
      regularizer_list = [
          reg for reg in regularizer_list if reg is not None
      ]
      if not regularizer_list:
          return None
  
      def sum_reg(weights):
          """Applies the sum of all the input regularizers."""
          with ops.name_scope(
              scope, "sum_regularizer", [weights]
          ) as name:
              regularizer_tensors = []
              for reg in regularizer_list:
                  tensor = reg(weights)
                  if tensor is not None:
                      regularizer_tensors.append(tensor)
              return (
                  math_ops.add_n(regularizer_tensors, name=name)
                  if regularizer_tensors
                  else None
              )
  
      return sum_reg
  
file_path: tensornets/tensornets/contrib_layers/regularizers.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numbers
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn
  from tensorflow.python.ops import standard_ops
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 4 for calling a global function with example usage: sum_regularizer(regularizer_list, scope) and returns: sum_reg, None, unknown