code: def _get_audio_features(self, mel: Tensor):
      if self.options.fp16:
          mel = mel.half()
  
      if mel.shape[-2:] == (
          self.model.dims.n_audio_ctx,
          self.model.dims.n_audio_state,
      ):
          # encoded audio features are given; skip audio encoding
          audio_features = mel
      else:
          audio_features = self.model.encoder(mel)
  
      if audio_features.dtype != (
          torch.float16 if self.options.fp16 else torch.float32
      ):
          return TypeError(
              f"audio_features has an incorrect dtype: {audio_features.dtype}"
          )
  
      return audio_features
  
imports: from dataclasses import dataclass, field, replace
  from typing import TYPE_CHECKING, Dict, Iterable, List, Optional, Sequence, Tuple, Union
  import numpy
  import torch
  import torch.nn.functional
  from torch import Tensor
  from torch.distributions import Categorical
  from .audio import CHUNK_LENGTH
  from .tokenizer import Tokenizer, get_tokenizer
  from .utils import compression_ratio
label_desc: Use image node_id 5 for calling the DecodingTask obj's underlying member method code with example usage: obj._get_audio_features(mel) and returns: audio_features, TypeError