class_docstr: Test the TensorFlowLingvoASR estimator.
code: def test_loss_gradient_batch_mode(
      self, art_warning, batch_mode, audio_data
  ):
      try:
          test_input = audio_data
          test_target = np.array(["This", "is", "a dummy", "a dummy"])
  
          lingvo = TensorFlowLingvoASR()
  
          if batch_mode:
              gradients = lingvo._loss_gradient_per_batch(
                  test_input, test_target
              )
          else:
              gradients = lingvo._loss_gradient_per_sequence(
                  test_input, test_target
              )
          gradients_abs_sum = np.array(
              [np.abs(g).sum() for g in gradients], dtype=object
          )
  
          # test shape, equal inputs have equal gradients, non-zero inputs have non-zero gradient sums
          assert [x.shape for x in test_input] == [
              g.shape for g in gradients
          ]
          assert_allclose(
              np.abs(gradients[2]).sum(),
              np.abs(gradients[3]).sum(),
              rtol=1e-01,
          )
          assert_array_equal(
              gradients_abs_sum > 0, [False, True, True, True]
          )
      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 10 for calling the TestTensorFlowLingvoASR obj's underlying member method code with example usage: obj.test_loss_gradient_batch_mode(art_warning, batch_mode, audio_data) without return types