code: def test_constructor(self, speech_classification_model):
      asr_model = speech_classification_model.train()
  
      conv_cnt = (64 * 32 * 1 + 32) + (
          64 * 1 * 1 + 32
      )  # separable kernel + bias + pointwise kernel + bias
      bn_cnt = (4 * 32) * 2  # 2 * moving averages
      dec_cnt = 32 * 30 + 30  # fc + bias
  
      param_count = conv_cnt + bn_cnt + dec_cnt
      assert asr_model.num_weights == param_count
  
      # Check to/from config_dict:
      confdict = asr_model.to_config_dict()
      instance2 = EncDecClassificationModel.from_config_dict(confdict)
  
      assert isinstance(instance2, EncDecClassificationModel)
  
imports: import copy
  import os
  import pytest
  import torch
  from omegaconf import DictConfig, ListConfig
  from nemo.collections.asr.data import audio_to_label
  from nemo.collections.asr.models import EncDecClassificationModel, EncDecFrameClassificationModel, configs
  from nemo.utils.config_utils import assert_dataclass_signature_match
label_desc: Use image node_id 1 for calling the TestEncDecClassificationModel obj's underlying member method code with example usage: obj.test_constructor(speech_classification_model) without return types