code: def prepare_feat_extract_dict(self):
      return {
          "feature_size": self.feature_size,
          "hop_length": self.hop_length,
          "chunk_length": self.chunk_length,
          "padding_value": self.padding_value,
          "sampling_rate": self.sampling_rate,
          "return_attention_mask": self.return_attention_mask,
      }
  
imports: import gc
  import itertools
  import os
  import random
  import tempfile
  import unittest
  import numpy
  from datasets import Audio, load_dataset
  from transformers import ClvpFeatureExtractor
  from transformers.testing_utils import check_json_file_has_correct_format, require_torch, slow
  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 ClvpFeatureExtractionTester obj's underlying member method code with example usage: obj.prepare_feat_extract_dict() and returns: dict