code: def __init__(
      self,
      input_feature_config: AudioInputFeatureConfig,
      encoder_obj=None,
      **kwargs,
  ):
      super().__init__(
          input_feature_config, encoder_obj=encoder_obj, **kwargs
      )
  
      if not getattr(self.encoder_obj.config, "embedding_size", None):
          raise ValueError(
              "embedding_size has to be defined - "
              'check "update_config_with_metadata()"'
          )
      if not getattr(
          self.encoder_obj.config, "max_sequence_length", None
      ):
          raise ValueError(
              "max_sequence_length has to be defined - "
              'check "update_config_with_metadata()"'
          )
  
imports: import logging
  import os
  from typing import Dict, List, Optional, Tuple, Union
  import numpy
  import torch
  import torchaudio
  from packaging import version
  from ludwig.constants import AUDIO, AUDIO_FEATURE_KEYS, COLUMN, NAME, PREPROCESSING, PROC_COLUMN, SRC, TYPE
  from ludwig.features.base_feature import BaseFeatureMixin
  from ludwig.features.sequence_feature import SequenceInputFeature
  from ludwig.schema.features.audio_feature import AudioInputFeatureConfig
  from ludwig.types import FeatureMetadataDict, ModelConfigDict, PreprocessingConfigDict, TrainingSetMetadataDict
  from ludwig.utils.audio_utils import calculate_mean, calculate_var, get_default_audio, get_fbank, get_group_delay, get_length_in_samp, get_max_length_stft_based, get_non_symmetric_length, get_phase_stft_magnitude, get_stft_magnitude, is_torch_audio_tuple, read_audio_from_bytes_obj, read_audio_from_path
  from ludwig.utils.data_utils import get_abs_path
  from ludwig.utils.fs_utils import has_remote_protocol
  from ludwig.utils.misc_utils import set_default_value
  from ludwig.utils.types import TorchscriptPreprocessingInput
label_desc: Use image node_id 1 to create a new AudioInputFeature object from inherited base classes: AudioFeatureMixin, SequenceInputFeature with example: obj = AudioInputFeature(input_feature_config, encoder_obj)