docstr: Validate the torchscript consistency of Tacotron2 inference function.
code: def test_tacotron2_inference_torchscript_consistency(self, n_batch):
      r"""Validate the torchscript consistency of Tacotron2 inference function."""
      n_mels = 40
      max_text_length = 100
      decoder_max_step = 200  # make inference more efficient
      gate_threshold = (
          0.51  # if set to 0.5, the model will only run one step
      )
  
      model = (
          _get_tacotron2_model(
              n_mels,
              decoder_max_step=decoder_max_step,
              gate_threshold=gate_threshold,
          )
          .to(self.device)
          .eval()
      )
      inputs = self._get_inference_inputs(n_batch, max_text_length)
  
      model_wrapper = Tacotron2InferenceWrapper(model)
  
      self._assert_torchscript_consistency(model_wrapper, inputs)
  
imports: from typing import Tuple
  import torch
  from parameterized import parameterized
  from torch import Tensor
  from torchaudio.models import Tacotron2
  from torchaudio.models.tacotron2 import _Decoder, _Encoder
  from torchaudio_unittest.common_utils import skipIfPy310, TestBaseMixin, torch_script
label_desc: Use image node_id 6 for calling the Tacotron2Tests obj's underlying member method code with example usage: obj.test_tacotron2_inference_torchscript_consistency(n_batch) without return types