code: def get_rnnt_decoder(vocab_size, decoder_output_size=4):
      prednet_cfg = {
          "pred_hidden": decoder_output_size,
          "pred_rnn_layers": 1,
      }
      torch.manual_seed(0)
      decoder = RNNTDecoder(prednet=prednet_cfg, vocab_size=vocab_size)
      decoder.freeze()
      return decoder
  
imports: import os
  from functools import lru_cache
  import pytest
  import torch
  from omegaconf import DictConfig
  from nemo.collections.asr.models import ASRModel
  from nemo.collections.asr.modules import RNNTDecoder, RNNTJoint
  from nemo.collections.asr.parts.mixins import mixins
  from nemo.collections.asr.parts.submodules import rnnt_beam_decoding
  from nemo.collections.asr.parts.submodules import rnnt_greedy_decoding
  from nemo.collections.asr.parts.submodules.rnnt_decoding import RNNTBPEDecoding, RNNTDecoding, RNNTDecodingConfig
  from nemo.collections.asr.parts.utils import rnnt_utils
  from nemo.core.utils import numba_utils
  from nemo.core.utils.numba_utils import __NUMBA_MINIMUM_VERSION__
label_desc: Use image node_id 3 for calling a global function with example usage: get_rnnt_decoder(vocab_size, decoder_output_size) and returns: decoder