code: def test_error_calculator_transducer(
      report_opts, decoder_class, decoder_opts
  ):
      token_list = ["<blank>", "a", "b", "c", "<space>"]
      vocab_size = len(token_list)
  
      encoder_size = 4
  
      decoder = decoder_class(vocab_size, embed_size=4, **decoder_opts)
      joint_net = JointNetwork(
          vocab_size, encoder_size, 4, joint_space_size=2
      )
  
      error_calc = ErrorCalculator(
          decoder,
          joint_net,
          token_list,
          "<space>",
          "<blank>",
          **report_opts,
      )
  
      enc_out = torch.randn(4, 30, encoder_size)
      enc_out_lens = torch.tensor([30, 29, 28, 27])
      target = torch.randint(0, vocab_size, [4, 20], dtype=torch.int32)
  
      with torch.no_grad():
          _, _ = error_calc(enc_out, target, enc_out_lens)
  
imports: import pytest
  import torch
  from espnet2.asr_transducer.decoder.rnn_decoder import RNNDecoder
  from espnet2.asr_transducer.decoder.stateless_decoder import StatelessDecoder
  from espnet2.asr_transducer.error_calculator import ErrorCalculator
  from espnet2.asr_transducer.joint_network import JointNetwork
label_desc: Use image node_id 1 for calling a global function with example usage: test_error_calculator_transducer(report_opts, decoder_class, decoder_opts) without return types