code: def test_espnet_model_transducer(
      encoder_arch, decoder_arch, multi_blank_durations
  ):
      # Multi-Blank Transducer only supports GPU
      if (
          len(multi_blank_durations) > 0
          and not torch.cuda.is_available()
      ):
          return
      device = "cuda" if len(multi_blank_durations) > 0 else "cpu"
      device = torch.device(device)
  
      vocab_size = 5
      enc_out = 4
      encoder = encoder_arch(
          20, output_size=enc_out, linear_units=4, num_blocks=2
      )
      decoder = TransducerDecoder(vocab_size, hidden_size=4)
      joint_network = JointNetwork(
          vocab_size, encoder_size=enc_out, decoder_size=4
      )
      ctc = CTC(odim=vocab_size, encoder_output_size=enc_out)
  
      model = ESPnetASRModel(
          vocab_size,
          token_list=["<blank>", "<unk>", "a", "i", "<eos>"],
          frontend=None,
          specaug=None,
          normalize=None,
          preencoder=None,
          encoder=encoder,
          postencoder=None,
          decoder=decoder,
          ctc=ctc,
          joint_network=joint_network,
          aux_ctc=None,
          transducer_multi_blank_durations=multi_blank_durations,
      ).to(device)
  
      inputs = dict(
          speech=torch.randn(2, 10, 20, requires_grad=True).to(device),
          speech_lengths=torch.tensor([10, 8], dtype=torch.long).to(
              device
          ),
          text=torch.randint(2, 4, [2, 4], dtype=torch.long).to(device),
          text_lengths=torch.tensor([4, 3], dtype=torch.long).to(
              device
          ),
      )
      loss, *_ = model(**inputs)
      loss.backward()
  
file_path: espnet/test/espnet2/asr/test_espnet_model.py
imports: import pytest
  import torch
  from espnet2.asr.ctc import CTC
  from espnet2.asr.decoder.transducer_decoder import TransducerDecoder
  from espnet2.asr.decoder.transformer_decoder import TransformerDecoder
  from espnet2.asr.encoder.conformer_encoder import ConformerEncoder
  from espnet2.asr.encoder.transformer_encoder import TransformerEncoder
  from espnet2.asr.espnet_model import ESPnetASRModel
  from espnet2.asr_transducer.joint_network import JointNetwork
label_desc: Use image node_id 2 for calling a global function with example usage: test_espnet_model_transducer(encoder_arch, decoder_arch, multi_blank_durations) without return types