class_docstr: tf.signal feat unittest
class_docstr_tok: ["tf.signal","feat","unittest"]
docstr: test extract feature 
docstr_tok: ["test","extract","feature"]
code: def test_extract_feature(self):
      """test extract feature"""
      with self.cached_session(use_gpu=False, force_gpu=False):
          wavfile = tf.constant(self.wavpath)
  
          audio = tffeat.read_wav(wavfile, self.params)
  
          # slice and tile to batch
          audio = tf.stack([audio[:1000]] * 32)
  
          feature = tffeat.extract_feature(audio, self.params)
  
          self.assertEqual(audio.eval().shape, (32, 1000))
          self.assertAllEqual(audio.eval()[0], self.audio_true[:1000])
          self.assertEqual(feature.eval().shape, (32, 13, 40, 3))
  
file_path: delta/delta/data/feat/tf_speech_feature_test.py
imports: import os
  from pathlib import Path
  import delta.compat
  from absl import logging
  from delta.data.feat.speech_feature import load_wav
  from delta.data.feat import tf_speech_feature
  from delta import PACKAGE_ROOT_DIR
label_desc: Use image node_id 2 for calling the SpeechFeatTest obj's underlying member method code with example usage: obj.test_extract_feature() without return types