code: def test_activation(act_type, act_params):
      batch_size = 2
      input_size = 10
  
      token_list = ["<blank>", "a", "b", "c", "<space>"]
      vocab_size = len(token_list)
  
      encoder = Encoder(
          input_size,
          [
              {
                  "block_type": "conformer",
                  "hidden_size": 8,
                  "linear_size": 4,
                  "conv_mod_kernel_size": 3,
              }
          ],
          main_conf=act_params,
      )
      decoder = StatelessDecoder(vocab_size, embed_size=4)
  
      joint_network = JointNetwork(
          vocab_size,
          encoder.output_size,
          decoder.output_size,
          joint_activation_type=act_type,
          **act_params,
      )
  
      model = ESPnetASRTransducerModel(
          vocab_size,
          token_list,
          frontend=None,
          specaug=None,
          normalize=None,
          encoder=encoder,
          decoder=decoder,
          joint_network=joint_network,
      )
  
      feats, labels, feat_len, label_len = prepare(
          model, input_size, vocab_size, batch_size
      )
  
      _ = model(feats, feat_len, labels, label_len)
  
imports: import pytest
  import torch
  from espnet2.asr_transducer.decoder.stateless_decoder import StatelessDecoder
  from espnet2.asr_transducer.encoder.encoder import Encoder
  from espnet2.asr_transducer.espnet_transducer_model import ESPnetASRTransducerModel
  from espnet2.asr_transducer.joint_network import JointNetwork
label_desc: Use image node_id 2 for calling a global function with example usage: test_activation(act_type, act_params) without return types