code: def test_check_concat_combiner_requirements():
      config = yaml.safe_load(
          """
  input_features:
    - name: description
      type: text
      encoder:
        type: embed
        reduce_output: null
      column: description
    - name: required_experience
      type: category
      column: required_experience
  output_features:
    - name: title
      type: category
  combiner:
      type: concat
  trainer:
    train_steps: 2
  model_type: ecd
  """
      )
  
      with pytest.raises(ConfigValidationError):
          ModelConfig.from_dict(config)
  
      # Confirms that the choice of the combiner type is the only reason for the ConfigValidationError.
      config[COMBINER][TYPE] = "sequence_concat"
      ModelConfig.from_dict(config)
  
imports: import contextlib
  from typing import Any, Dict, List, Optional
  import pytest
  import yaml
  from ludwig.constants import COMBINER, TYPE
  from ludwig.error import ConfigValidationError
  from ludwig.schema.model_types.base import ModelConfig
  from tests.integration_tests.utils import binary_feature, text_feature
label_desc: Use image node_id 11 for calling a global function with example usage: test_check_concat_combiner_requirements() without return types