code: def test_constructor(self, hybrid_asr_model):
      hybrid_asr_model.train()
      # TODO: make proper config and assert correct number of weights
      # Check to/from config_dict:
      confdict = hybrid_asr_model.to_config_dict()
      instance2 = EncDecHybridRNNTCTCModel.from_config_dict(confdict)
      assert isinstance(instance2, EncDecHybridRNNTCTCModel)
  
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 1 for calling the TestEncDecHybridRNNTCTCModel obj's underlying member method code with example usage: obj.test_constructor(hybrid_asr_model) without return types