code: def main_debug():
      parser = argparse.ArgumentParser(description="Debug snippets")
      parser.add_argument(
          "mode",
          choices=["training", "inference"],
          help="'training' to debug training and 'inference to "
          "debug inference'",
      )
      parser.add_argument(
          "path", help="Path to the dataset or trained assistant"
      )
      parser.add_argument(
          "--config-path", help="Path to the assistant configuration"
      )
      args = vars(parser.parse_args())
      mode = args.pop("mode")
      if mode == "training":
          debug_training(*list(args.values()))
      elif mode == "inference":
          args.pop("config_path")
          debug_inference(*list(args.values()))
      else:
          raise ValueError("Invalid mode %s" % mode)
  
file_path: snips-nlu/debug/debug.py
imports: from __future__ import unicode_literals, print_function
  import argparse
  import json
  from builtins import input, bytes
  from pathlib import Path
  from snips_nlu import SnipsNLUEngine
  from snips_nlu.pipeline.configs.nlu_engine import NLUEngineConfig
label_desc: Use image node_id 3 for calling a global function with example usage: main_debug() without return types