code: def mul_plain(a: EV, b: V, pk: PK, coder: Coder, output_dtype=None):
      if output_dtype is None:
          output_dtype = b.dtype
      encoded = coder.encode_tensor(b, dtype=output_dtype)
      return a.mul(pk.pk, encoded)
  
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 10 for calling the evaluator obj's underlying member method code with example usage: obj.mul_plain(a, b, pk, coder, output_dtype) and returns: a