code: def _get_inference_inputs(self, n_batch: int, max_text_length: int):
      text = torch.randint(
          0,
          148,
          (n_batch, max_text_length),
          dtype=torch.int32,
          device=self.device,
      )
      text_lengths = max_text_length * torch.ones(
          (n_batch,), dtype=torch.int32, device=self.device
      )
      return text, text_lengths
  
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 5 for calling the Tacotron2Tests obj's underlying member method code with example usage: obj._get_inference_inputs(n_batch, max_text_length) and returns: text,  text_lengths