code: def _get_2D_feature(
      audio: torch.Tensor,
      feature_type: str,
      audio_feature_dict: Dict[str, Union[float, int, str]],
      sampling_rate_in_hz: int,
  ) -> torch.Tensor:
      window_length_in_s = audio_feature_dict["window_length_in_s"]
      window_shift_in_s = audio_feature_dict["window_shift_in_s"]
      assert torch.jit.isinstance(window_length_in_s, float)
      assert torch.jit.isinstance(window_shift_in_s, float)
  
      window_length_in_samp = get_length_in_samp(
          window_length_in_s, sampling_rate_in_hz
      )
  
      if "num_fft_points" in audio_feature_dict:
          num_fft_points = audio_feature_dict["num_fft_points"]
          assert torch.jit.isinstance(num_fft_points, int)
  
          if num_fft_points < window_length_in_samp:
              raise ValueError(
                  "num_fft_points: {} < window length in "
                  "samples: {} (corresponds to window length"
                  " in s: {}".format(
                      num_fft_points,
                      window_length_in_s,
                      window_length_in_samp,
                  )
              )
      else:
          num_fft_points = window_length_in_samp
  
      if "window_type" in audio_feature_dict:
          window_type = audio_feature_dict["window_type"]
          assert torch.jit.isinstance(window_type, str)
      else:
          window_type = "hamming"
  
      if feature_type == "stft_phase":
          return get_phase_stft_magnitude(
              audio,
              sampling_rate_in_hz,
              window_length_in_s,
              window_shift_in_s,
              num_fft_points,
              window_type,
          )
      elif feature_type == "stft":
          return get_stft_magnitude(
              audio,
              sampling_rate_in_hz,
              window_length_in_s,
              window_shift_in_s,
              num_fft_points,
              window_type,
          )
      elif feature_type == "group_delay":
          return get_group_delay(
              audio,
              sampling_rate_in_hz,
              window_length_in_s,
              window_shift_in_s,
              num_fft_points,
              window_type,
          )
      elif feature_type == "fbank":
          num_filter_bands = audio_feature_dict["num_filter_bands"]
          assert torch.jit.isinstance(num_filter_bands, int)
  
          return get_fbank(
              audio,
              sampling_rate_in_hz,
              window_length_in_s,
              window_shift_in_s,
              num_fft_points,
              window_type,
              num_filter_bands,
          )
      else:
          raise ValueError(
              f'feature_type "{feature_type}" is not recognized.'
          )
  
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 9 for calling the AudioFeatureMixin obj's underlying member method code with example usage: obj._get_2D_feature(audio, feature_type, audio_feature_dict, sampling_rate_in_hz) and returns: get_phase_stft_magnitude, get_stft_magnitude, get_group_delay, get_fbank