code: def _get_feature_dim(
      preprocessing_parameters: PreprocessingConfigDict,
      sampling_rate_in_hz,
  ):
      feature_type = preprocessing_parameters[TYPE]
  
      if feature_type == "raw":
          feature_dim = 1
      elif feature_type == "stft_phase":
          feature_dim_symmetric = get_length_in_samp(
              preprocessing_parameters["window_length_in_s"],
              sampling_rate_in_hz,
          )
          feature_dim = 2 * get_non_symmetric_length(
              feature_dim_symmetric
          )
      elif feature_type in ["stft", "group_delay"]:
          feature_dim_symmetric = get_length_in_samp(
              preprocessing_parameters["window_length_in_s"],
              sampling_rate_in_hz,
          )
          feature_dim = get_non_symmetric_length(feature_dim_symmetric)
      elif feature_type == "fbank":
          feature_dim = preprocessing_parameters["num_filter_bands"]
      else:
          raise ValueError(f"{feature_type} is not recognized.")
  
      return feature_dim
  
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 4 for calling the AudioFeatureMixin obj's underlying member method code with example usage: obj._get_feature_dim(preprocessing_parameters, sampling_rate_in_hz) and returns: feature_dim