parameters: (cls, op, X, W)
return_statement: return tensor_list
docstring: hanlde the special operators
          Args:
              op: a given operator
          Args:
              op_t: the tensor of the operator
          Returns: 
              onnx tensor list
docstring_summary: hanlde the special operators
          Args:
              op: a given operator
          Args:
              op_t: the tensor of the operator
          Returns: 
              onnx tensor list
docstring_tokens: hanlde the special operators Args : op : a given operator Args : op_t : the tensor of the operator Returns : onnx tensor list
function: def _special_handle_clip(cls, op, X, W):
          """
          hanlde the special operators
          Args:
              op: a given operator
          Args:
              op_t: the tensor of the operator
          Returns: 
              onnx tensor list
          """
          tensor_list = []
          # clip add min and max
          append_inputs = {"min": op.min, "max": op.max}
          for tmp_name, append_input in append_inputs.items():
              node_name = op.name + ":" + tmp_name
              tensor_list.append(
                  helper.make_tensor(node_name, TensorProto.FLOAT, [],
                                     [append_input]))
          return tensor_list
function_tokens: def _special_handle_clip ( cls , op , X , W ) : tensor_list = [ ] # clip add min and max append_inputs = { "min" : op . min , "max" : op . max } for tmp_name , append_input in append_inputs . items ( ) : node_name = op . name + ":" + tmp_name tensor_list . append ( helper . make_tensor ( node_name , TensorProto . FLOAT , [ ] , [ append_input ] ) ) return tensor_list