code: def construct_length_prediction_module(
      cls,
      config: Config,
  ):
      return create_module(
          config.length_prediction_model,
          config.encoder_decoder.encoder.encoder_config.encoder_embed_dim,
      )
  
imports: from typing import Dict, List, Optional, Tuple, Union
  import torch
  from pytext.common.constants import Stage
  from pytext.data.masked_tensorizer import MaskedTokenTensorizer
  from pytext.data.tensorizers import GazetteerTensorizer, Tensorizer, TokenTensorizer
  from pytext.data.utils import Vocabulary
  from pytext.models.embeddings.scriptable_embedding_list import ScriptableEmbeddingList
  from pytext.models.model import Model
  from pytext.models.module import create_module
  from .conv_model import CNNModel, DecoupledCNNModel
  from .mask_generator import MaskedSequenceGenerator
  from .nar_length import ConvLengthPredictionModule, MaskedLengthPredictionModule
  from .nar_output_layer import NARSeq2SeqOutputLayer
  from .seq2seq_model import Seq2SeqModel
label_desc: Use image node_id 10 for calling the NARSeq2SeqModel obj's underlying member method code with example usage: obj.construct_length_prediction_module(cls, config) and returns: create_module