code: def parse_arguments():
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "--local_rank",
          type=int,
          default=-1,
          help="local_rank for distributed training on GPUs",
      )
      args, unknownargs = parser.parse_known_args()
      logging.info(f"Got unknown arguments: {unknownargs}")
      return args
  
file_path: FARM/examples/train_from_scratch_with_sagemaker.py
imports: import json
  import logging
  from pathlib import Path
  from transformers.tokenization_bert import BertTokenizer
  from farm.data_handler.data_silo import StreamingDataSilo, DataSilo
  from farm.data_handler.processor import BertStyleLMProcessor
  from farm.modeling.adaptive_model import AdaptiveModel
  from farm.modeling.language_model import LanguageModel
  from farm.modeling.optimization import initialize_optimizer
  from farm.modeling.prediction_head import BertLMHead, NextSentenceHead
  from farm.data_handler.utils import split_file
  from farm.train import Trainer
  from farm.utils import set_all_seeds, StdoutLogger, initialize_device_settings
  import argparse
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: parse_arguments() and returns: args