code: def hydra_main(
      cfg: InferConfig,
  ) -> Union[float, Tuple[float, Optional[float]]]:
      container = OmegaConf.to_container(
          cfg, resolve=True, enum_to_str=True
      )
      cfg = OmegaConf.create(container)
      OmegaConf.set_struct(cfg, True)
  
      if cfg.common.reset_logging:
          reset_logging()
  
      utils.import_user_module(cfg.common)
  
      # logger.info("Config:\n%s", OmegaConf.to_yaml(cfg))
      wer = float("inf")
  
      try:
          if cfg.common.profile:
              with torch.cuda.profiler.profile():
                  with torch.autograd.profiler.emit_nvtx():
                      distributed_utils.call_main(cfg, main)
          else:
              distributed_utils.call_main(cfg, main)
  
          wer = parse_wer(get_wer_file(cfg))
      except BaseException as e:  # pylint: disable=broad-except
          if not cfg.common.suppress_crashes:
              raise
          else:
              logger.error("Crashed! %s", str(e))
  
      logger.info("Word error rate: %.4f", wer)
      if cfg.is_ax:
          return wer, None
  
      return wer
  
imports: import ast
  import hashlib
  import logging
  import os
  import shutil
  import sys
  import re
  from dataclasses import dataclass, field, is_dataclass
  from pathlib import Path
  from typing import Any, Dict, List, Optional, Tuple, Union
  import editdistance
  import torch
  import torch.distributed
  from examples.speech_recognition.new.decoders.decoder_config import DecoderConfig, FlashlightDecoderConfig
  from examples.speech_recognition.new.decoders.decoder import Decoder
  from fairseq import checkpoint_utils, distributed_utils, progress_bar, tasks, utils
  from fairseq.data.data_utils import post_process
  from fairseq.dataclass.configs import CheckpointConfig, CommonConfig, CommonEvalConfig, DatasetConfig, DistributedTrainingConfig, FairseqDataclass
  from fairseq.logging.meters import StopwatchMeter, TimeMeter
  from fairseq.logging.progress_bar import BaseProgressBar
  from fairseq.models.fairseq_model import FairseqModel
  from omegaconf import OmegaConf
  import hydra
  from hydra.core.config_store import ConfigStore
label_desc: Use image node_id 5 for calling a global function with example usage: hydra_main(cfg) and returns: wer, wer,  None