code: def convert_FastSpeech2ConformerWithHifiGan_checkpoint(
      checkpoint_path,
      yaml_config_path,
      pytorch_dump_folder_path,
      repo_id=None,
  ):
      # Prepare the model
      model_params, *_ = remap_model_yaml_config(yaml_config_path)
      model_config = FastSpeech2ConformerConfig(**model_params)
  
      model = FastSpeech2ConformerModel(model_config)
  
      espnet_checkpoint = torch.load(checkpoint_path)
      hf_compatible_state_dict = convert_espnet_state_dict_to_hf(
          espnet_checkpoint
      )
      model.load_state_dict(hf_compatible_state_dict)
  
      # Prepare the vocoder
      config_kwargs = remap_hifigan_yaml_config(yaml_config_path)
      vocoder_config = FastSpeech2ConformerHifiGanConfig(
          **config_kwargs
      )
  
      vocoder = FastSpeech2ConformerHifiGan(vocoder_config)
      load_weights(espnet_checkpoint, vocoder, vocoder_config)
  
      # Prepare the model + vocoder
      config = (
          FastSpeech2ConformerWithHifiGanConfig.from_sub_model_configs(
              model_config, vocoder_config
          )
      )
      with_hifigan_model = FastSpeech2ConformerWithHifiGan(config)
      with_hifigan_model.model = model
      with_hifigan_model.vocoder = vocoder
  
      with_hifigan_model.save_pretrained(pytorch_dump_folder_path)
  
      if repo_id:
          print("Pushing to the hub...")
          with_hifigan_model.push_to_hub(repo_id)
  
imports: import argparse
  import torch
  from transformers import FastSpeech2ConformerConfig, FastSpeech2ConformerHifiGan, FastSpeech2ConformerHifiGanConfig, FastSpeech2ConformerModel, FastSpeech2ConformerWithHifiGan, FastSpeech2ConformerWithHifiGanConfig, logging
  from .convert_fastspeech2_conformer_original_pytorch_checkpoint_to_pytorch import convert_espnet_state_dict_to_hf, remap_model_yaml_config
  from .convert_hifigan import load_weights, remap_hifigan_yaml_config
label_desc: Use image node_id 1 for calling a global function with example usage: convert_FastSpeech2ConformerWithHifiGan_checkpoint(checkpoint_path, yaml_config_path, pytorch_dump_folder_path, repo_id) without return types