code: def test_classification(
      classification_data,
      continuous_cols,
      categorical_cols,
      continuous_feature_transform,
      normalize_continuous_features,
      num_gaussian,
  ):
      (train, test, target) = classification_data
      data_config = DataConfig(
          target=target,
          continuous_cols=continuous_cols,
          categorical_cols=categorical_cols,
          continuous_feature_transform=continuous_feature_transform,
          normalize_continuous_features=normalize_continuous_features,
      )
      model_config_params = {"task": "classification"}
      mdn_config = {"num_gaussian": num_gaussian}
      model_config_params["head_config"] = mdn_config
      model_config_params[
          "backbone_config_class"
      ] = "CategoryEmbeddingMDNConfig"
      model_config_params["backbone_config_params"] = {
          "task": "backbone"
      }
  
      model_config = MDNConfig(**model_config_params)
      trainer_config = TrainerConfig(
          max_epochs=3,
          checkpoints=None,
          early_stopping=None,
          accelerator="cpu",
          fast_dev_run=True,
      )
      optimizer_config = OptimizerConfig()
      with pytest.raises(AssertionError):
          tabular_model = TabularModel(
              data_config=data_config,
              model_config=model_config,
              optimizer_config=optimizer_config,
              trainer_config=trainer_config,
          )
          tabular_model.fit(train=train)
  
imports: import pytest
  from pytorch_tabular import TabularModel
  from pytorch_tabular.config import DataConfig, OptimizerConfig, TrainerConfig
  from pytorch_tabular.models import MDNConfig
label_desc: Use image node_id 2 for calling a global function with example usage: test_classification(classification_data, continuous_cols, categorical_cols, continuous_feature_transform, normalize_continuous_features, num_gaussian) without return types