code: def _print_network_spec_parameter_info_style(
      mlmodel_spec, interface_only=False
  ):
      """Print the network information summary.
      Args:
      mlmodel_spec : the mlmodel spec
      interface_only : Shows only the input and output of the network
      """
      inputs, outputs, layers_info = _summarize_neural_network_spec(
          mlmodel_spec
      )
  
      print("Inputs:")
      for i in inputs:
          name, description = i
          print("  {} {}".format(name, description))
  
      print("Outputs:")
      for o in outputs:
          name, description = o
          print("  {} {}".format(name, description))
  
      if layers_info is None:
          print(
              "\n(This MLModel is not a neural network model or does not contain any layers)"
          )
  
      if layers_info and not interface_only:
          print("\nLayers:")
          for idx, l in enumerate(layers_info):
              layer_type, name, in_blobs, out_blobs, params_info = l
              print("[{}] ({}) {}".format(idx, layer_type, name))
              print("  Input blobs: {}".format(in_blobs))
              print("  Output blobs: {}".format(out_blobs))
              if len(params_info) > 0:
                  print("  Parameters: ")
              for param in params_info:
                  print("    {} = {}".format(param[0], param[1]))
  
      print("\n")
  
imports: from .spec_inspection_utils import _get_feature_description_summary, _summarize_neural_network_spec_code_style, _summarize_neural_network_spec
label_desc: Use image node_id 1 for calling a global function with example usage: _print_network_spec_parameter_info_style(mlmodel_spec, interface_only) without return types