code: def __init__(
      self,
      manifest_filepath: str,
      parser: Union[str, Callable],
      max_duration: Optional[float] = None,
      min_duration: Optional[float] = None,
      max_utts: int = 0,
      bos_id: Optional[int] = None,
      eos_id: Optional[int] = None,
      pad_id: int = 0,
      index_by_file_id: bool = False,
  ):
      self.parser = parser
      self.collection = collections.ASRFeatureText(
          manifests_files=manifest_filepath,
          parser=parser,
          min_duration=min_duration,
          max_duration=max_duration,
          max_number=max_utts,
          index_by_file_id=index_by_file_id,
      )
  
      self.eos_id = eos_id
      self.bos_id = bos_id
      self.pad_id = pad_id
  
imports: from typing import Callable, Dict, List, Optional, Tuple, Union
  import torch
  from nemo.collections.asr.data.feature_to_label import _audio_feature_collate_fn
  from nemo.collections.asr.parts.preprocessing.feature_loader import ExternalFeatureLoader
  from nemo.collections.asr.parts.preprocessing.features import normalize_batch
  from nemo.collections.asr.parts.utils.audio_utils import ChannelSelectorType
  from nemo.collections.asr.parts.utils.vad_utils import load_speech_segments_from_rttm
  from nemo.collections.common import tokenizers
  from nemo.collections.common.parts.preprocessing import collections, parsers
  from nemo.core.classes import Dataset
  from nemo.core.neural_types import AcousticEncodedRepresentation, LabelsType, LengthsType, NeuralType
label_desc: Use image node_id 1 to create a new ASRFeatureManifestProcessor object  with example: obj = ASRFeatureManifestProcessor(manifest_filepath, parser, max_duration, min_duration, max_utts, bos_id, eos_id, pad_id, index_by_file_id)