code: def convert_files(args, ifiles, output):
      nnp = _import_file(args, ifiles)
      if nnp is not None:
          network_name = nnp.protobuf.executor[0].network_name
          if args.export_format == "ONNX":
              if args.config:
                  support_set = (
                      func_set_onnx_support()
                      & func_set_import_onnx_config(args.config)
                  )
              else:
                  support_set = func_set_onnx_support()
          elif args.export_format == "NNB":
              if args.config:
                  support_set = func_set_import_config(args.config)
              else:
                  support_set = func_set_nnabla_support()
          else:
              if args.config:
                  support_set = func_set_import_config(args.config)
              else:
                  if args.nnp_version is not None:
                      version_spec = (nnp, args.nnp_version)
                  else:
                      version_spec = None
                  support_set = func_set_nnabla_support(version_spec)
          if _need_split(nnp, args, support_set):
              for _net in nnp.protobuf.network[:]:
                  if _net.name != network_name:
                      nnp.protobuf.network.remove(_net)
              ranges = _get_split_ranges(nnp, args, support_set)
              nnb_info = collections.OrderedDict()
              for pos_start, pos_end in ranges:
                  print(
                      "   Shrink {} to {}.".format(pos_start, pos_end)
                  )
                  n, e = os.path.splitext(output)
                  new_output = (
                      n + "_{}_{}".format(pos_start, pos_end) + e
                  )
                  print("    Output to [{}]".format(new_output))
                  _nnp = _shrink_nnp(nnp, pos_start, pos_end)
                  nnb_info[new_output] = collections.OrderedDict()
                  nnb_info[new_output]["input"] = []
                  nnb_info[new_output]["output"] = []
                  i_var = []
                  o_var = []
                  for var in _nnp.protobuf.executor[0].data_variable:
                      i_var.append(var.variable_name)
                  for var in _nnp.protobuf.executor[0].output_variable:
                      o_var.append(var.variable_name)
                  for var in _nnp.protobuf.network[0].variable:
                      if var.name in i_var:
                          _info = collections.OrderedDict()
                          _info["name"] = var.name
                          _info["shape"] = "({})".format(
                              ", ".join(str(i) for i in var.shape.dim)
                          )
                          nnb_info[new_output]["input"].append(_info)
                      if var.name in o_var:
                          _info = collections.OrderedDict()
                          _info["name"] = var.name
                          _info["shape"] = "({})".format(
                              ", ".join(str(i) for i in var.shape.dim)
                          )
                          nnb_info[new_output]["output"].append(_info)
                  _export_from_nnp(args, _nnp, new_output)
              import yaml
  
              print(yaml.dump(nnb_info, default_flow_style=False))
          else:
              return _export_from_nnp(args, nnp, output)
      else:
          print("Import from {} failed.".format(ifiles))
          return False
  
file_path: nnabla/python/src/nnabla/utils/converter/commands.py
imports: import collections
  import os
  import sys
  from .nnabla import NnpImporter, NnpExporter
  from .nnablart import NnbExporter, CsrcExporter
  from .utils import func_set_import_nnp, func_set_import_onnx_config, func_set_import_config, func_set_nnabla_support, func_set_onnx_support, func_set_nnabla_version_decorate
  from nnabla.logger import logger
label_desc: Use image node_id 6 for calling a global function with example usage: convert_files(args, ifiles, output) and returns: False, _export_from_nnp