code: def _nested_to_flatten_node_data_list(nested):
      """Makes nested node data to flatten node data list."""
      if _is_serialized_node_data(nested):
          return [nested]
  
      if isinstance(nested, list):
          return sum(map(_nested_to_flatten_node_data_list, nested), [])
  
      if isinstance(nested, dict):
          return sum(
              map(_nested_to_flatten_node_data_list, nested.values()),
              [],
          )
  
      raise ValueError(
          "{} is not a supported nested node data.".format(nested)
      )
  
imports: import warnings
  import tensorflow
  from tensorflow_model_optimization.python.core.keras import metrics
  from tensorflow_model_optimization.python.core.quantization.keras import quantize_annotate
  from tensorflow_model_optimization.python.core.quantization.keras import quantize_aware_activation
  from tensorflow_model_optimization.python.core.quantization.keras import quantize_config
  from tensorflow_model_optimization.python.core.quantization.keras import quantize_layer
  from tensorflow_model_optimization.python.core.quantization.keras import quantize_wrapper
  from tensorflow_model_optimization.python.core.quantization.keras import quantizers
  from tensorflow_model_optimization.python.core.quantization.keras import utils
  from tensorflow_model_optimization.python.core.quantization.keras.default_8bit import default_8bit_quantize_registry
  from tensorflow_model_optimization.python.core.quantization.keras.default_8bit import default_8bit_quantize_scheme
  from tensorflow_model_optimization.python.core.quantization.keras.experimental.default_n_bit import default_n_bit_quantize_registry
label_desc: Use image node_id 9 for calling a global function with example usage: _nested_to_flatten_node_data_list(nested) and returns: list, sum, sum