class_docstr: A module that builds on top of model.
  
  Args:
      name (str): Module name, also the variable scope.
docstr: Get all network weight variables in the current scope.
  
  Returns:
      List[tf.Variable]: A list of network weight variables in the
          current variable scope.
docstr_tok: ["Get","all","network","weight","variables","in","the","current","scope",".","Returns",":","List","[","tf.Variable","]",":","A","list","of","network","weight","variables","in","the","current","variable","scope","."]
code: def get_regularizable_vars(self):
      """Get all network weight variables in the current scope.
  
      Returns:
          List[tf.Variable]: A list of network weight variables in the
              current variable scope.
  
      """
      trainable = self._variable_scope.global_variables()
      return [
          var
          for var in trainable
          if "hidden" in var.name and "kernel" in var.name
      ]
  
imports: import abc
  import tensorflow
  from garage.np import flatten_tensors, unflatten_tensors
label_desc: Use image node_id 9 for calling the Module obj's underlying member method code with example usage: obj.get_regularizable_vars() and returns: unknown