code: def prepare_feat_extract_dict(self):
      return {
          "spectrogram_length": self.spectrogram_length,
          "feature_size": self.feature_size,
          "num_audio_channels": self.num_audio_channels,
          "hop_length": self.hop_length,
          "chunk_length": self.chunk_length,
          "sampling_rate": self.sampling_rate,
      }
  
imports: import itertools
  import random
  import unittest
  import numpy
  from transformers import TvltFeatureExtractor, is_datasets_available
  from transformers.testing_utils import require_torch, require_torchaudio
  from transformers.utils.import_utils import is_torch_available
  from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
label_desc: Use image node_id 2 for calling the TvltFeatureExtractionTester obj's underlying member method code with example usage: obj.prepare_feat_extract_dict() and returns: dict