code: def test_greedy_multi_decoding(self, greedy_class):
      token_list = [" ", "a", "b", "c"]
      vocab_size = len(token_list)
  
      encoder_output_size = 4
      decoder_output_size = 4
      joint_output_shape = 4
  
      prednet_cfg = {
          "pred_hidden": decoder_output_size,
          "pred_rnn_layers": 1,
      }
      jointnet_cfg = {
          "encoder_hidden": encoder_output_size,
          "pred_hidden": decoder_output_size,
          "joint_hidden": joint_output_shape,
          "activation": "relu",
      }
  
      decoder = RNNTDecoder(prednet_cfg, vocab_size)
      joint_net = RNNTJoint(
          jointnet_cfg, vocab_size, vocabulary=token_list
      )
  
      greedy = greedy_class(
          decoder,
          joint_net,
          blank_index=len(token_list) - 1,
          max_symbols_per_step=5,
      )
  
      # (B, D, T)
      enc_out = torch.randn(1, encoder_output_size, 30)
      enc_len = torch.tensor([30], dtype=torch.int32)
  
      with torch.no_grad():
          (partial_hyp) = greedy(
              encoder_output=enc_out, encoded_lengths=enc_len
          )
          partial_hyp = partial_hyp[0]
          _ = greedy(
              encoder_output=enc_out,
              encoded_lengths=enc_len,
              partial_hypotheses=partial_hyp,
          )
  
imports: import copy
  import pytest
  import torch
  from omegaconf import DictConfig, ListConfig
  from nemo.collections.asr.models import EncDecHybridRNNTCTCModel
  from nemo.collections.asr.modules import RNNTDecoder, RNNTJoint, SampledRNNTJoint, StatelessTransducerDecoder
  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.ctc_decoding import CTCDecoding, CTCDecodingConfig
  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__
  from nemo.utils.config_utils import assert_dataclass_signature_match
label_desc: Use image node_id 10 for calling the TestEncDecHybridRNNTCTCModel obj's underlying member method code with example usage: obj.test_greedy_multi_decoding(greedy_class) without return types