code: def get_decoder(vocab_size, params):
      if "is_rwkv" in params:
          del params["is_rwkv"]
  
          decoder = RWKVDecoder(vocab_size, **params)
      elif "rnn_type" in params:
          decoder = RNNDecoder(vocab_size, **params)
      elif "block_size" in params:
          decoder = MEGADecoder(vocab_size, **params)
      else:
          decoder = StatelessDecoder(vocab_size, **params)
  
      return decoder
  
imports: from pathlib import Path
  import numpy
  import pytest
  import torch
  from espnet2.asr.specaug.specaug import SpecAug
  from espnet2.asr_transducer.decoder.mega_decoder import MEGADecoder
  from espnet2.asr_transducer.decoder.rnn_decoder import RNNDecoder
  from espnet2.asr_transducer.decoder.rwkv_decoder import RWKVDecoder
  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
  from espnet2.layers.global_mvn import GlobalMVN
  from espnet2.layers.utterance_mvn import UtteranceMVN
label_desc: Use image node_id 3 for calling a global function with example usage: get_decoder(vocab_size, params) and returns: decoder