code: def main():
      parser = HfArgumentParser((ModelArguments,))
      (model_args,) = parser.parse_args_into_dataclasses()
  
      # Load pretrained model and tokenizer
  
      # Use explicit specified encoder config
      if model_args.encoder_config_name:
          encoder_config = AutoConfig.from_pretrained(
              model_args.encoder_config_name
          )
      # Use pretrained encoder model's config
      else:
          encoder_config = AutoConfig.from_pretrained(
              model_args.encoder_model_name_or_path
          )
  
      # Use explicit specified decoder config
      if model_args.decoder_config_name:
          decoder_config = AutoConfig.from_pretrained(
              model_args.decoder_config_name
          )
      # Use pretrained decoder model's config
      else:
          decoder_config = AutoConfig.from_pretrained(
              model_args.decoder_model_name_or_path
          )
  
      # necessary for `from_encoder_decoder_pretrained` when `decoder_config` is passed
      decoder_config.is_decoder = True
      decoder_config.add_cross_attention = True
  
      model = FlaxVisionEncoderDecoderModel.from_encoder_decoder_pretrained(
          encoder_pretrained_model_name_or_path=model_args.encoder_model_name_or_path,
          decoder_pretrained_model_name_or_path=model_args.decoder_model_name_or_path,
          encoder_config=encoder_config,
          decoder_config=decoder_config,
      )
  
      # GPT2 only has bos/eos tokens but not decoder_start/pad tokens
      decoder_start_token_id = decoder_config.decoder_start_token_id
      pad_token_id = decoder_config.pad_token_id
      if decoder_start_token_id is None:
          decoder_start_token_id = decoder_config.bos_token_id
      if pad_token_id is None:
          pad_token_id = decoder_config.eos_token_id
  
      # This is necessary to make Flax's generate() work
      model.config.eos_token_id = decoder_config.eos_token_id
      model.config.decoder_start_token_id = decoder_start_token_id
      model.config.pad_token_id = pad_token_id
  
      image_processor = AutoImageProcessor.from_pretrained(
          model_args.encoder_model_name_or_path
      )
  
      tokenizer = AutoTokenizer.from_pretrained(
          model_args.decoder_model_name_or_path
      )
      tokenizer.pad_token = tokenizer.convert_ids_to_tokens(
          model.config.pad_token_id
      )
  
      model.save_pretrained(model_args.output_dir)
      image_processor.save_pretrained(model_args.output_dir)
      tokenizer.save_pretrained(model_args.output_dir)
  
imports: from dataclasses import dataclass, field
  from typing import Optional
  from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types