code: def _check_hls_config(config, hls_config):
      """
      Check hls_config for to set appropriate parameters for config.
      """
  
      if "LayerName" in hls_config:
          config["HLSConfig"]["LayerName"] = hls_config["LayerName"]
  
      if "LayerType" in hls_config:
          config["HLSConfig"]["LayerType"] = hls_config["LayerType"]
  
      if "Flows" in hls_config:
          config["HLSConfig"]["Flows"] = hls_config["Flows"]
  
      if "Optimizers" in hls_config:
          config["HLSConfig"]["Optimizers"] = hls_config["Optimizers"]
  
      if "SkipOptimizers" in hls_config:
          config["HLSConfig"]["SkipOptimizers"] = hls_config[
              "SkipOptimizers"
          ]
  
      return
  
imports: import importlib
  import os
  import warnings
  import yaml
  from hls4ml.converters.keras_to_hls import KerasFileReader
  from hls4ml.converters.keras_to_hls import KerasModelReader
  from hls4ml.converters.keras_to_hls import KerasReader
  from hls4ml.converters.keras_to_hls import get_supported_keras_layers
  from hls4ml.converters.keras_to_hls import parse_keras_model
  from hls4ml.converters.keras_to_hls import keras_to_hls, register_keras_layer_handler
  from hls4ml.model import ModelGraph
  from hls4ml.utils.config import create_config
  from hls4ml.utils.symbolic_utils import LUTFunction
label_desc: Use image node_id 3 for calling a global function with example usage: _check_hls_config(config, hls_config) without return types