code: def test_initializer_recursion():
      config = {
          "input_features": [
              {
                  "name": "category_B9834",
                  "type": "category",
                  "encoder": {
                      "type": "dense",
                      "vocab_size": 2,
                      "embedding_size": 5,
                  },
                  "reduce_input": "sum",
                  "column": "category_B9834",
                  "proc_column": "category_B9834_mZFLky",
              },
              {
                  "name": "number_0F633",
                  "type": "number",
                  "encoder": {
                      "type": "dense",
                      "norm": "batch",
                      "norm_params": {"momentum": 0.2},
                  },
              },
          ],
          "output_features": [
              {
                  "name": "binary_52912",
                  "type": "binary",
                  "column": "binary_52912",
                  "proc_column": "binary_52912_mZFLky",
              }
          ],
          "combiner": {
              "type": "concat",
              "weights_initializer": {"type": "normal", "stddev": 0},
          },
      }
  
      config_obj = ModelConfig.from_dict(config)
  
      assert isinstance(config_obj.combiner.weights_initializer, dict)
  
imports: import os
  from tempfile import TemporaryDirectory
  from typing import Any, Dict, Optional, Union
  import pytest
  import yaml
  from ludwig.constants import ACTIVE, BASE_MODEL, CLIP, COLUMN, COMBINER, DECODER, DEFAULT_VALIDATION_METRIC, DEFAULTS, DEPENDENCIES, ENCODER, HYPEROPT, INPUT_FEATURES, INPUT_SIZE, LOSS, MODEL_ECD, MODEL_GBM, MODEL_LLM, MODEL_TYPE, NAME, NUM_CLASSES, OPTIMIZER, OUTPUT_FEATURES, PREPROCESSING, PROC_COLUMN, REDUCE_DEPENDENCIES, REDUCE_INPUT, TIED, TRAINER, TYPE
  from ludwig.error import ConfigValidationError
  from ludwig.schema.decoders.base import ClassifierConfig
  from ludwig.schema.encoders.text_encoders import BERTConfig
  from ludwig.schema.features.augmentation.image import RandomBlurConfig, RandomRotateConfig
  from ludwig.schema.features.image_feature import AUGMENTATION_DEFAULT_OPERATIONS
  from ludwig.schema.features.number_feature import NumberOutputFeatureConfig
  from ludwig.schema.features.text_feature import TextOutputFeatureConfig
  from ludwig.schema.llms.quantization import QuantizationConfig
  from ludwig.schema.model_config import ModelConfig
  from ludwig.schema.utils import BaseMarshmallowConfig, convert_submodules
label_desc: Use image node_id 18 for calling a global function with example usage: test_initializer_recursion() without return types