code: def _import_file(args, ifiles):
      if args.import_format == "NNP":
          # Input file that has unsupported extension store into output nnp
          # archive or directory.
          return NnpImporter(
              *ifiles,
              expand_network=not args.nnp_no_expand_network,
              executor_index=args.nnp_import_executor_index,
          ).execute()
  
      elif args.import_format == "ONNX":
          from .onnx import OnnxImporter
  
          return OnnxImporter(*ifiles).execute()
  
      elif (
          args.import_format == "TF_PB"
          or args.import_format == "TF_CKPT_V1"
          or args.import_format == "TF_CKPT_V2"
          or args.import_format == "SAVED_MODEL"
      ):
          from .tensorflow import TensorflowImporter
  
          return TensorflowImporter(
              *ifiles,
              tf_format=args.import_format,
              outputs=args.outputs,
              inputs=args.inputs,
          ).execute()
      elif args.import_format == "TFLITE":
          from .tflite import TFLiteImporter
  
          return TFLiteImporter(*ifiles).execute()
      return None
  
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 1 for calling a global function with example usage: _import_file(args, ifiles) and returns: None, NnpImporter, OnnxImporter, TensorflowImporter, TFLiteImporter