code: def get_char_dataset(
      config: dict, augmentor: Optional["FeatureAugmentor"] = None
  ) -> FeatureToCharDataset:
      """
      Instantiates a Character Encoding based FeatureToCharDataset.
  
      Args:
          config: Config of the FeatureToCharDataset.
          augmentor: Optional AudioAugmentor object for augmentations on audio data.
  
      Returns:
          An instance of FeatureToCharDataset.
      """
      if "labels" not in config:
          logging.warning(
              f"dataset does not have explicitly defined labels"
          )
  
      dataset = FeatureToCharDataset(
          manifest_filepath=config["manifest_filepath"],
          labels=config.get("labels", None),
          normalize=config.get("normalize", "post_norm"),
          normalize_type=config.get("normalize_type", "per_feature"),
          use_rttm=config.get("use_rttm", False),
          rttm_mode=config.get("rttm_mode", "mask"),
          feat_min_len=config.get("feat_min_len", 4),
          feat_mask_val=config.get("feat_mask_val", None),
          frame_unit_time_secs=config.get("frame_unit_time_secs", 0.01),
          sample_rate=config.get("sample_rate", 16000),
          augmentor=augmentor,
          max_duration=config.get("max_duration", None),
          min_duration=config.get("min_duration", None),
          max_utts=config.get("max_utts", 0),
          blank_index=config.get("blank_index", -1),
          unk_index=config.get("unk_index", -1),
          trim=config.get("trim_silence", False),
          parser=config.get("parser", "en"),
          return_sample_id=config.get("return_sample_id", False),
          channel_selector=config.get("channel_selector", None),
      )
      return dataset
  
imports: from typing import Optional
  from nemo.collections.asr.data.feature_to_text import FeatureToBPEDataset, FeatureToCharDataset
  from nemo.utils import logging
label_desc: Use image node_id 1 for calling a global function with example usage: get_char_dataset(config, augmentor) and returns: dataset