code: def _get_predictor_input(self):
      input_config = self._get_input_config()
      batch_size = input_config["batch_size"]
      num_symbols = input_config["num_symbols"]
      max_target_length = input_config["max_target_length"]
  
      input = torch.randint(
          0, num_symbols, (batch_size, max_target_length)
      ).to(device=self.device, dtype=torch.int32)
      lengths = torch.full((batch_size,), max_target_length).to(
          device=self.device, dtype=torch.int32
      )
      return input, lengths
  
file_path: audio/test/torchaudio_unittest/prototype/rnnt_test_impl.py
imports: import torch
  from torchaudio.prototype.models import conformer_rnnt_model
  from torchaudio_unittest.common_utils import TestBaseMixin, torch_script
label_desc: Use image node_id 5 for calling the ConformerRNNTTestImpl obj's underlying member method code with example usage: obj._get_predictor_input() and returns: input,  lengths