code: def add_plain_scalar(a: EV, b, pk: PK, coder: Coder, output_dtype):
      encoded = coder.encode(b, dtype=output_dtype)
      encrypted = pk.encrypt_encoded_scalar(encoded, obfuscate=False)
      return a.add_scalar(pk.pk, encrypted)
  
imports: from typing import List, Optional, Tuple
  import torch
  from fate_utils.ou import CiphertextVector, PlaintextVector
  from fate_utils.ou import Coder
  from fate_utils.ou import Evaluator
  from fate_utils.ou import PK
  from fate_utils.ou import SK
  from fate_utils.ou import keygen
  from .type import TensorEvaluator
label_desc: Use image node_id 3 for calling the evaluator obj's underlying member method code with example usage: obj.add_plain_scalar(a, b, pk, coder, output_dtype) and returns: a