code: def to_dict(self) -> Dict[str, Any]:
      return {
          "tf_version": tf.__version__,  # type: ignore
          "kashgari_version": kashgari.__version__,
          "__class_name__": self.__class__.__name__,
          "__module__": self.__class__.__module__,
          "config": {
              "encoder_seq_length": self.encoder_seq_length,  # type: ignore
              "decoder_seq_length": self.decoder_seq_length,  # type: ignore
              "hidden_size": self.hidden_size,
          },
          "encoder_embedding": self.encoder_embedding.to_dict(),  # type: ignore
          "decoder_embedding": self.decoder_embedding.to_dict(),
          "encoder_processor": self.encoder_processor.to_dict(),
          "decoder_processor": self.decoder_processor.to_dict(),
      }
  
imports: import json
  import os
  import pathlib
  from typing import Any, Tuple, List, Dict
  import numpy
  import tensorflow
  import tqdm
  import kashgari
  from kashgari.embeddings import BareEmbedding
  from kashgari.embeddings.abc_embedding import ABCEmbedding
  from kashgari.generators import CorpusGenerator, Seq2SeqDataSet
  from kashgari.logger import logger
  from kashgari.processors import SequenceProcessor
  from kashgari.tasks.seq2seq.decoder import AttGRUDecoder
  from kashgari.tasks.seq2seq.encoder import GRUEncoder
  from kashgari.types import TextSamplesVar
label_desc: Use image node_id 1 for calling the Seq2Seq obj's underlying member method code with example usage: obj.to_dict() and returns: dict