docstr: Verify that scripting RNNTBeamSearch does not change the behavior of method `forward`.
code: def test_torchscript_consistency_forward(self):
      r"""Verify that scripting RNNTBeamSearch does not change the behavior of method `forward`."""
  
      input_config = self._get_input_config()
      batch_size = input_config["batch_size"]
      max_input_length = input_config["max_input_length"]
      right_context_length = input_config["right_context_length"]
      input_dim = input_config["input_dim"]
      num_symbols = input_config["num_symbols"]
      blank_idx = num_symbols - 1
      beam_width = 5
  
      input = torch.rand(
          batch_size, max_input_length + right_context_length, input_dim
      ).to(device=self.device, dtype=self.dtype)
      lengths = torch.randint(
          1, max_input_length + 1, (batch_size,)
      ).to(device=self.device, dtype=torch.int32)
  
      model = self._get_model()
      beam_search = RNNTBeamSearch(model, blank_idx)
      scripted = torch_script(beam_search)
  
      res = beam_search(input, lengths, beam_width)
      scripted_res = scripted(input, lengths, beam_width)
  
      self.assertEqual(res, scripted_res)
  
file_path: audio/test/torchaudio_unittest/models/rnnt_decoder/rnnt_decoder_test_impl.py
imports: import torch
  from torchaudio.models import emformer_rnnt_model, RNNTBeamSearch
  from torchaudio_unittest.common_utils import TestBaseMixin, torch_script
label_desc: Use image node_id 4 for calling the RNNTBeamSearchTestImpl obj's underlying member method code with example usage: obj.test_torchscript_consistency_forward() without return types