class_docstr: Test the TensorFlowLingvoASR estimator.
code: def test_predict_batch(self, art_warning, audio_batch_padded):
      try:
          test_input, test_mask_frequency = audio_batch_padded
          test_target_dummy = np.array(["DUMMY"] * test_input.shape[0])
  
          lingvo = TensorFlowLingvoASR()
          feed_dict = {
              lingvo._x_padded: test_input,
              lingvo._y_target: test_target_dummy,
              lingvo._mask_frequency: test_mask_frequency,
          }
          predictions = lingvo._sess.run(
              lingvo._predict_batch_op, feed_dict
          )
          assert set(predictions.keys()).issuperset(
              {
                  "target_ids",
                  "target_labels",
                  "target_weights",
                  "target_paddings",
                  "transcripts",
                  "topk_decoded",
                  "topk_ids",
                  "topk_lens",
                  "topk_scores",
                  "norm_wer_errors",
                  "norm_wer_words",
                  "utt_id",
              }
          )
      except ARTTestException as e:
          art_warning(e)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_equal
  from scipy.io.wavfile import read
  from art.estimators.speech_recognition.speech_recognizer import SpeechRecognizerMixin
  from art.estimators.speech_recognition.tensorflow_lingvo import TensorFlowLingvoASR
  from art.estimators.tensorflow import TensorFlowV2Estimator
  from art.utils import get_file
  from tests.utils import ARTTestException
label_desc: Use image node_id 7 for calling the TestTensorFlowLingvoASR obj's underlying member method code with example usage: obj.test_predict_batch(art_warning, audio_batch_padded) without return types